Spectral analysis of a two-species competition model: Determining the effects of extreme conditions on the color of noise generated from simulated time series

NASA Astrophysics Data System (ADS)

Golinski, M. R.

2006-07-01

Ecologists have observed that environmental noise affects population variance in the logistic equation for one-species growth. Interactions between deterministic and stochastic dynamics in a one-dimensional system result in increased variance in species population density over time. Since natural populations do not live in isolation, the present paper simulates a discrete-time two-species competition model with environmental noise to determine the type of colored population noise generated by extreme conditions in the long-term population dynamics of competing populations. Discrete Fourier analysis is applied to the simulation results and the calculated Hurst exponent ( H) is used to determine how the color of population noise for the two species corresponds to extreme conditions in population dynamics. To interpret the biological meaning of the color of noise generated by the two-species model, the paper determines the color of noise generated by three reference models: (1) A two-dimensional discrete-time white noise model (0⩽ H<1/2); (2) A two-dimensional fractional Brownian motion model (H=1/2); and (3) A two-dimensional discrete-time model with noise for unbounded growth of two uncoupled species (1/2< H⩽1).

FITPOP, a heuristic simulation model of population dynamics and genetics with special reference to fisheries

USGS Publications Warehouse

McKenna, James E.

2000-01-01

Although, perceiving genetic differences and their effects on fish population dynamics is difficult, simulation models offer a means to explore and illustrate these effects. I partitioned the intrinsic rate of increase parameter of a simple logistic-competition model into three components, allowing specification of effects of relative differences in fitness and mortality, as well as finite rate of increase. This model was placed into an interactive, stochastic environment to allow easy manipulation of model parameters (FITPOP). Simulation results illustrated the effects of subtle differences in genetic and population parameters on total population size, overall fitness, and sensitivity of the system to variability. Several consequences of mixing genetically distinct populations were illustrated. For example, behaviors such as depression of population size after initial introgression and extirpation of native stocks due to continuous stocking of genetically inferior fish were reproduced. It also was shown that carrying capacity relative to the amount of stocking had an important influence on population dynamics. Uncertainty associated with parameter estimates reduced confidence in model projections. The FITPOP model provided a simple tool to explore population dynamics, which may assist in formulating management strategies and identifying research needs.

The E-MOSAICS project: simulating the formation and co-evolution of galaxies and their star cluster populations

NASA Astrophysics Data System (ADS)

Pfeffer, Joel; Kruijssen, J. M. Diederik; Crain, Robert A.; Bastian, Nate

2018-04-01

We introduce the MOdelling Star cluster population Assembly In Cosmological Simulations within EAGLE (E-MOSAICS) project. E-MOSAICS incorporates models describing the formation, evolution, and disruption of star clusters into the EAGLE galaxy formation simulations, enabling the examination of the co-evolution of star clusters and their host galaxies in a fully cosmological context. A fraction of the star formation rate of dense gas is assumed to yield a cluster population; this fraction and the population's initial properties are governed by the physical properties of the natal gas. The subsequent evolution and disruption of the entire cluster population are followed accounting for two-body relaxation, stellar evolution, and gravitational shocks induced by the local tidal field. This introductory paper presents a detailed description of the model and initial results from a suite of 10 simulations of ˜L⋆ galaxies with disc-like morphologies at z = 0. The simulations broadly reproduce key observed characteristics of young star clusters and globular clusters (GCs), without invoking separate formation mechanisms for each population. The simulated GCs are the surviving population of massive clusters formed at early epochs (z ≳ 1-2), when the characteristic pressures and surface densities of star-forming gas were significantly higher than observed in local galaxies. We examine the influence of the star formation and assembly histories of galaxies on their cluster populations, finding that (at similar present-day mass) earlier-forming galaxies foster a more massive and disruption-resilient cluster population, while galaxies with late mergers are capable of forming massive clusters even at late cosmic epochs. We find that the phenomenological treatment of interstellar gas in EAGLE precludes the accurate modelling of cluster disruption in low-density environments, but infer that simulations incorporating an explicitly modelled cold interstellar gas phase will overcome this shortcoming.

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)

IBSEM: An Individual-Based Atlantic Salmon Population Model.

PubMed

Castellani, Marco; Heino, Mikko; Gilbey, John; Araki, Hitoshi; Svåsand, Terje; Glover, Kevin A

2015-01-01

Ecology and genetics can influence the fate of individuals and populations in multiple ways. However, to date, few studies consider them when modelling the evolutionary trajectory of populations faced with admixture with non-local populations. For the Atlantic salmon, a model incorporating these elements is urgently needed because many populations are challenged with gene-flow from non-local and domesticated conspecifics. We developed an Individual-Based Salmon Eco-genetic Model (IBSEM) to simulate the demographic and population genetic change of an Atlantic salmon population through its entire life-cycle. Processes such as growth, mortality, and maturation are simulated through stochastic procedures, which take into account environmental variables as well as the genotype of the individuals. IBSEM is based upon detailed empirical data from salmon biology, and parameterized to reproduce the environmental conditions and the characteristics of a wild population inhabiting a Norwegian river. Simulations demonstrated that the model consistently and reliably reproduces the characteristics of the population. Moreover, in absence of farmed escapees, the modelled populations reach an evolutionary equilibrium that is similar to our definition of a 'wild' genotype. We assessed the sensitivity of the model in the face of assumptions made on the fitness differences between farm and wild salmon, and evaluated the role of straying as a buffering mechanism against the intrusion of farm genes into wild populations. These results demonstrate that IBSEM is able to capture the evolutionary forces shaping the life history of wild salmon and is therefore able to model the response of populations under environmental and genetic stressors.

Incorporating parametric uncertainty into population viability analysis models

USGS Publications Warehouse

McGowan, Conor P.; Runge, Michael C.; Larson, Michael A.

2011-01-01

Uncertainty in parameter estimates from sampling variation or expert judgment can introduce substantial uncertainty into ecological predictions based on those estimates. However, in standard population viability analyses, one of the most widely used tools for managing plant, fish and wildlife populations, parametric uncertainty is often ignored in or discarded from model projections. We present a method for explicitly incorporating this source of uncertainty into population models to fully account for risk in management and decision contexts. Our method involves a two-step simulation process where parametric uncertainty is incorporated into the replication loop of the model and temporal variance is incorporated into the loop for time steps in the model. Using the piping plover, a federally threatened shorebird in the USA and Canada, as an example, we compare abundance projections and extinction probabilities from simulations that exclude and include parametric uncertainty. Although final abundance was very low for all sets of simulations, estimated extinction risk was much greater for the simulation that incorporated parametric uncertainty in the replication loop. Decisions about species conservation (e.g., listing, delisting, and jeopardy) might differ greatly depending on the treatment of parametric uncertainty in population models.

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 %).

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.

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.

Mussel dynamics model: A hydroinformatics tool for analyzing the effects of different stressors on the dynamics of freshwater mussel communities

USGS Publications Warehouse

Morales, Y.; Weber, L.J.; Mynett, A.E.; Newton, T.J.

2006-01-01

A model for simulating freshwater mussel population dynamics is presented. The model is a hydroinformatics tool that integrates principles from ecology, river hydraulics, fluid mechanics and sediment transport, and applies the individual-based modelling approach for simulating population dynamics. The general model layout, data requirements, and steps of the simulation process are discussed. As an illustration, simulation results from an application in a 10 km reach of the Upper Mississippi River are presented. The model was used to investigate the spatial distribution of mussels and the effects of food competition in native unionid mussel communities, and communities infested by Dreissena polymorpha, the zebra mussel. Simulation results were found to be realistic and coincided with data obtained from the literature. These results indicate that the model can be a useful tool for assessing the potential effects of different stressors on long-term population dynamics, and consequently, may improve the current understanding of cause and effect relationships in freshwater mussel communities. ?? 2006 Elsevier B.V. All rights reserved.

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.

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.

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.

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

IBSEM: An Individual-Based Atlantic Salmon Population Model

PubMed Central

Castellani, Marco; Heino, Mikko; Gilbey, John; Araki, Hitoshi; Svåsand, Terje; Glover, Kevin A.

2015-01-01

Ecology and genetics can influence the fate of individuals and populations in multiple ways. However, to date, few studies consider them when modelling the evolutionary trajectory of populations faced with admixture with non-local populations. For the Atlantic salmon, a model incorporating these elements is urgently needed because many populations are challenged with gene-flow from non-local and domesticated conspecifics. We developed an Individual-Based Salmon Eco-genetic Model (IBSEM) to simulate the demographic and population genetic change of an Atlantic salmon population through its entire life-cycle. Processes such as growth, mortality, and maturation are simulated through stochastic procedures, which take into account environmental variables as well as the genotype of the individuals. IBSEM is based upon detailed empirical data from salmon biology, and parameterized to reproduce the environmental conditions and the characteristics of a wild population inhabiting a Norwegian river. Simulations demonstrated that the model consistently and reliably reproduces the characteristics of the population. Moreover, in absence of farmed escapees, the modelled populations reach an evolutionary equilibrium that is similar to our definition of a ‘wild’ genotype. We assessed the sensitivity of the model in the face of assumptions made on the fitness differences between farm and wild salmon, and evaluated the role of straying as a buffering mechanism against the intrusion of farm genes into wild populations. These results demonstrate that IBSEM is able to capture the evolutionary forces shaping the life history of wild salmon and is therefore able to model the response of populations under environmental and genetic stressors. PMID:26383256

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.

Using dynamic population simulations to extend resource selection analyses and prioritize habitats for conservation

USGS Publications Warehouse

Heinrichs, Julie; Aldridge, Cameron L.; O'Donnell, Michael; Schumaker, Nathan

2017-01-01

Prioritizing habitats for conservation is a challenging task, particularly for species with fluctuating populations and seasonally dynamic habitat needs. Although the use of resource selection models to identify and prioritize habitat for conservation is increasingly common, their ability to characterize important long-term habitats for dynamic populations are variable. To examine how habitats might be prioritized differently if resource selection was directly and dynamically linked with population fluctuations and movement limitations among seasonal habitats, we constructed a spatially explicit individual-based model for a dramatically fluctuating population requiring temporally varying resources. Using greater sage-grouse (Centrocercus urophasianus) in Wyoming as a case study, we used resource selection function maps to guide seasonal movement and habitat selection, but emergent population dynamics and simulated movement limitations modified long-term habitat occupancy. We compared priority habitats in RSF maps to long-term simulated habitat use. We examined the circumstances under which the explicit consideration of movement limitations, in combination with population fluctuations and trends, are likely to alter predictions of important habitats. In doing so, we assessed the future occupancy of protected areas under alternative population and habitat conditions. Habitat prioritizations based on resource selection models alone predicted high use in isolated parcels of habitat and in areas with low connectivity among seasonal habitats. In contrast, results based on more biologically-informed simulations emphasized central and connected areas near high-density populations, sometimes predicted to be low selection value. Dynamic models of habitat use can provide additional biological realism that can extend, and in some cases, contradict habitat use predictions generated from short-term or static resource selection analyses. The explicit inclusion of population dynamics and movement propensities via spatial simulation modeling frameworks may provide an informative means of predicting long-term habitat use, particularly for fluctuating populations with complex seasonal habitat needs. Importantly, our results indicate the possible need to consider habitat selection models as a starting point rather than the common end point for refining and prioritizing habitats for protection for cyclic and highly variable populations.

A network-based approach for resistance transmission in bacterial populations.

PubMed

Gehring, Ronette; Schumm, Phillip; Youssef, Mina; Scoglio, Caterina

2010-01-07

Horizontal transfer of mobile genetic elements (conjugation) is an important mechanism whereby resistance is spread through bacterial populations. The aim of our work is to develop a mathematical model that quantitatively describes this process, and to use this model to optimize antimicrobial dosage regimens to minimize resistance development. The bacterial population is conceptualized as a compartmental mathematical model to describe changes in susceptible, resistant, and transconjugant bacteria over time. This model is combined with a compartmental pharmacokinetic model to explore the effect of different plasma drug concentration profiles. An agent-based simulation tool is used to account for resistance transfer occurring when two bacteria are adjacent or in close proximity. In addition, a non-linear programming optimal control problem is introduced to minimize bacterial populations as well as the drug dose. Simulation and optimization results suggest that the rapid death of susceptible individuals in the population is pivotal in minimizing the number of transconjugants in a population. This supports the use of potent antimicrobials that rapidly kill susceptible individuals and development of dosage regimens that maintain effective antimicrobial drug concentrations for as long as needed to kill off the susceptible population. Suggestions are made for experiments to test the hypotheses generated by these simulations.

Coupling population dynamics with earth system models: the POPEM model.

PubMed

Navarro, Andrés; Moreno, Raúl; Jiménez-Alcázar, Alfonso; Tapiador, Francisco J

2017-09-16

Precise modeling of CO 2 emissions is important for environmental research. This paper presents a new model of human population dynamics that can be embedded into ESMs (Earth System Models) to improve climate modeling. Through a system dynamics approach, we develop a cohort-component model that successfully simulates historical population dynamics with fine spatial resolution (about 1°×1°). The population projections are used to improve the estimates of CO 2 emissions, thus transcending the bulk approach of existing models and allowing more realistic non-linear effects to feature in the simulations. The module, dubbed POPEM (from Population Parameterization for Earth Models), is compared with current emission inventories and validated against UN aggregated data. Finally, it is shown that the module can be used to advance toward fully coupling the social and natural components of the Earth system, an emerging research path for environmental science and pollution research.

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...

Sensitivity analyses for simulating pesticide impacts on honey bee colonies

EPA Science Inventory

We employ Monte Carlo simulation and sensitivity analysis techniques to describe the population dynamics of pesticide exposure to a honey bee colony using the VarroaPop + Pesticide model. Simulations are performed of hive population trajectories with and without pesti...

A modified Wright-Fisher model that incorporates Ne: A variant of the standard model with increased biological realism and reduced computational complexity.

PubMed

Zhao, Lei; Gossmann, Toni I; Waxman, David

2016-03-21

The Wright-Fisher model is an important model in evolutionary biology and population genetics. It has been applied in numerous analyses of finite populations with discrete generations. It is recognised that real populations can behave, in some key aspects, as though their size that is not the census size, N, but rather a smaller size, namely the effective population size, Ne. However, in the Wright-Fisher model, there is no distinction between the effective and census population sizes. Equivalently, we can say that in this model, Ne coincides with N. The Wright-Fisher model therefore lacks an important aspect of biological realism. Here, we present a method that allows Ne to be directly incorporated into the Wright-Fisher model. The modified model involves matrices whose size is determined by Ne. Thus apart from increased biological realism, the modified model also has reduced computational complexity, particularly so when Ne⪡N. For complex problems, it may be hard or impossible to numerically analyse the most commonly-used approximation of the Wright-Fisher model that incorporates Ne, namely the diffusion approximation. An alternative approach is simulation. However, the simulations need to be sufficiently detailed that they yield an effective size that is different to the census size. Simulations may also be time consuming and have attendant statistical errors. The method presented in this work may then be the only alternative to simulations, when Ne differs from N. We illustrate the straightforward application of the method to some problems involving allele fixation and the determination of the equilibrium site frequency spectrum. We then apply the method to the problem of fixation when three alleles are segregating in a population. This latter problem is significantly more complex than a two allele problem and since the diffusion equation cannot be numerically solved, the only other way Ne can be incorporated into the analysis is by simulation. We have achieved good accuracy in all cases considered. In summary, the present work extends the realism and tractability of an important model of evolutionary biology and population genetics. Copyright © 2016 Elsevier Ltd. All rights reserved.

Building Better Planet Populations for EXOSIMS

NASA Astrophysics Data System (ADS)

Garrett, Daniel; Savransky, Dmitry

2018-01-01

The Exoplanet Open-Source Imaging Mission Simulator (EXOSIMS) software package simulates ensembles of space-based direct imaging surveys to provide a variety of science and engineering yield distributions for proposed mission designs. These mission simulations rely heavily on assumed distributions of planetary population parameters including semi-major axis, planetary radius, eccentricity, albedo, and orbital orientation to provide heuristics for target selection and to simulate planetary systems for detection and characterization. The distributions are encoded in PlanetPopulation modules within EXOSIMS which are selected by the user in the input JSON script when a simulation is run. The earliest written PlanetPopulation modules available in EXOSIMS are based on planet population models where the planetary parameters are considered to be independent from one another. While independent parameters allow for quick computation of heuristics and sampling for simulated planetary systems, results from planet-finding surveys have shown that many parameters (e.g., semi-major axis/orbital period and planetary radius) are not independent. We present new PlanetPopulation modules for EXOSIMS which are built on models based on planet-finding survey results where semi-major axis and planetary radius are not independent and provide methods for sampling their joint distribution. These new modules enhance the ability of EXOSIMS to simulate realistic planetary systems and give more realistic science yield distributions.

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.

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.

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.

A Computer Simulation Study of Vntr Population Genetics: Constrained Recombination Rules Out the Infinite Alleles Model

PubMed Central

Harding, R. M.; Boyce, A. J.; Martinson, J. J.; Flint, J.; Clegg, J. B.

1993-01-01

Extensive allelic diversity in variable numbers of tandem repeats (VNTRs) has been discovered in the human genome. For population genetic studies of VNTRs, such as forensic applications, it is important to know whether a neutral mutation-drift balance of VNTR polymorphism can be represented by the infinite alleles model. The assumption of the infinite alleles model that each new mutant is unique is very likely to be violated by unequal sister chromatid exchange (USCE), the primary process believed to generate VNTR mutants. We show that increasing both mutation rates and misalignment constraint for intrachromosomal recombination in a computer simulation model reduces simulated VNTR diversity below the expectations of the infinite alleles model. Maximal constraint, represented as slippage of single repeats, reduces simulated VNTR diversity to levels expected from the stepwise mutation model. Although misalignment rule is the more important variable, mutation rate also has an effect. At moderate rates of USCE, simulated VNTR diversity fluctuates around infinite alleles expectation. However, if rates of USCE are high, as for hypervariable VNTRs, simulated VNTR diversity is consistently lower than predicted by the infinite alleles model. This has been observed for many VNTRs and accounted for by technical problems in distinguishing alleles of neighboring size classes. We use sampling theory to confirm the intrinsically poor fit to the infinite alleles model of both simulated VNTR diversity and observed VNTR polymorphisms sampled from two Papua New Guinean populations. PMID:8293988

A computer simulation study of VNTR population genetics: constrained recombination rules out the infinite alleles model.

PubMed

Harding, R M; Boyce, A J; Martinson, J J; Flint, J; Clegg, J B

1993-11-01

Extensive allelic diversity in variable numbers of tandem repeats (VNTRs) has been discovered in the human genome. For population genetic studies of VNTRs, such as forensic applications, it is important to know whether a neutral mutation-drift balance of VNTR polymorphism can be represented by the infinite alleles model. The assumption of the infinite alleles model that each new mutant is unique is very likely to be violated by unequal sister chromatid exchange (USCE), the primary process believed to generate VNTR mutants. We show that increasing both mutation rates and misalignment constraint for intrachromosomal recombination in a computer simulation model reduces simulated VNTR diversity below the expectations of the infinite alleles model. Maximal constraint, represented as slippage of single repeats, reduces simulated VNTR diversity to levels expected from the stepwise mutation model. Although misalignment rule is the more important variable, mutation rate also has an effect. At moderate rates of USCE, simulated VNTR diversity fluctuates around infinite alleles expectation. However, if rates of USCE are high, as for hypervariable VNTRs, simulated VNTR diversity is consistently lower than predicted by the infinite alleles model. This has been observed for many VNTRs and accounted for by technical problems in distinguishing alleles of neighboring size classes. We use sampling theory to confirm the intrinsically poor fit to the infinite alleles model of both simulated VNTR diversity and observed VNTR polymorphisms sampled from two Papua New Guinean populations.

Sensitivity analyses for simulating pesticide impacts on honey bee colonies

USDA-ARS?s Scientific Manuscript database

We employ Monte Carlo simulation and sensitivity analysis techniques to describe the population dynamics of pesticide exposure to a honey bee colony using the VarroaPop+Pesticide model. Simulations are performed of hive population trajectories with and without pesticide exposure to determine the eff...

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

Temporally structured replay of neural activity in a model of entorhinal cortex, hippocampus and postsubiculum

PubMed Central

Hasselmo, Michael E.

2008-01-01

The spiking activity of hippocampal neurons during REM sleep exhibits temporally structured replay of spiking occurring during previously experienced trajectories (Louie and Wilson, 2001). Here, temporally structured replay of place cell activity during REM sleep is modeled in a large-scale network simulation of grid cells, place cells and head direction cells. During simulated waking behavior, the movement of the simulated rat drives activity of a population of head direction cells that updates the activity of a population of entorhinal grid cells. The population of grid cells drives the activity of place cells coding individual locations. Associations between location and movement direction are encoded by modification of excitatory synaptic connections from place cells to speed modulated head direction cells. During simulated REM sleep, the population of place cells coding an experienced location activates the head direction cells coding the associated movement direction. Spiking of head direction cells then causes frequency shifts within the population of entorhinal grid cells to update a phase representation of location. Spiking grid cells then activate new place cells that drive new head direction activity. In contrast to models that perform temporally compressed sequence retrieval similar to sharp wave activity, this model can simulate data on temporally structured replay of hippocampal place cell activity during REM sleep at time scales similar to those observed during waking. These mechanisms could be important for episodic memory of trajectories. PMID:18973557

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.

A computer simulation study of VNTR population genetics: Constrained recombination rules out the infinite alleles model

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

Harding, R.M.; Martinson, J.J.; Flint, J.

1993-11-01

Extensive allelic diversity in variable numbers of tandem repeats (VNTRs) has been discovered in the human genome. For population genetic studies of VNTRs, such as forensic applications, it is important to know whether a neutral mutation-drift balance of VNTR polymorphism can be represented by the infinite alleles model. The assumption of the infinite alleles model that each new mutant is unique is very likely to be violated by unequal sister chromatid exchange (USCE), the primary process believed to generate VNTR mutants. The authors show that increasing both mutation rates and misalignment constraint for intrachromosomal recombination in a computer simulation modelmore » reduces simulated VNTR diversity below the expectations of the infinite alleles model. Maximal constraint, represented as slippage of single repeats, reduces simulated VNTR diversity to levels expected from the stepwise mutation model. Although misalignment rule is the more important variable, mutation rate also has an effect. At moderate rates of USCE, simulated VNTR diversity fluctuates around infinite alleles expectation. However, if rates of USCE are high, as for hypervariable VNTRs, simulated VNTR diversity is consistently lower than predicted by the infinite alleles model. This has been observed for many VNTRs and accounted for by technical problems in distinguishing alleles of neighboring size classes. The authors use sampling theory to confirm the intrinsically poor fit to the infinite model of both simulated VNTR diversity and observed VNTR polymorphisms sampled from two Papua New Guinean populations. 25 refs., 20 figs., 4 tabs.« less

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.

Population pharmacokinetics of rifampin in the treatment of Mycobacterium tuberculosis in Asian elephants.

PubMed

Egelund, E F; Isaza, R; Brock, A P; Alsultan, A; An, G; Peloquin, C A

2015-04-01

The objective of this study was to develop a population pharmacokinetic model for rifampin in elephants. Rifampin concentration data from three sources were pooled to provide a total of 233 oral concentrations from 37 Asian elephants. The population pharmacokinetic models were created using Monolix (version 4.2). Simulations were conducted using ModelRisk. We examined the influence of age, food, sex, and weight as model covariates. We further optimized the dosing of rifampin based upon simulations using the population pharmacokinetic model. Rifampin pharmacokinetics were best described by a one-compartment open model including first-order absorption with a lag time and first-order elimination. Body weight was a significant covariate for volume of distribution, and food intake was a significant covariate for lag time. The median Cmax of 6.07 μg/mL was below the target range of 8-24 μg/mL. Monte Carlo simulations predicted the highest treatable MIC of 0.25 μg/mL with the current initial dosing recommendation of 10 mg/kg, based upon a previously published target AUC0-24/MIC > 271 (fAUC > 41). Simulations from the population model indicate that the current dose of 10 mg/kg may be adequate for MICs up to 0.25 μg/mL. While the targeted AUC/MIC may be adequate for most MICs, the median Cmax for all elephants is below the human and elephant targeted ranges. © 2014 John Wiley & Sons Ltd.

CDPOP: A spatially explicit cost distance population genetics program

Treesearch

Erin L. Landguth; S. A. Cushman

2010-01-01

Spatially explicit simulation of gene flow in complex landscapes is essential to explain observed population responses and provide a foundation for landscape genetics. To address this need, we wrote a spatially explicit, individual-based population genetics model (CDPOP). The model implements individual-based population modelling with Mendelian inheritance and k-allele...

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.

Estimation of mussel population response to hydrologic alteration in a southeastern U.S. stream

USGS Publications Warehouse

Peterson, J.T.; Wisniewski, J.M.; Shea, C.P.; Rhett, Jackson C.

2011-01-01

The southeastern United States has experienced severe, recurrent drought, rapid human population growth, and increasing agricultural irrigation during recent decades, resulting in greater demand for the water resources. During the same time period, freshwater mussels (Unioniformes) in the region have experienced substantial population declines. Consequently, there is growing interest in determining how mussel population declines are related to activities associated with water resource development. Determining the causes of mussel population declines requires, in part, an understanding of the factors influencing mussel population dynamics. We developed Pradel reverse-time, tag-recapture models to estimate survival, recruitment, and population growth rates for three federally endangered mussel species in the Apalachicola- Chattahoochee-Flint River Basin, Georgia. The models were parameterized using mussel tag-recapture data collected over five consecutive years from Sawhatchee Creek, located in southwestern Georgia. Model estimates indicated that mussel survival was strongly and negatively related to high flows during the summer, whereas recruitment was strongly and positively related to flows during the spring and summer. Using these models, we simulated mussel population dynamics under historic (1940-1969) and current (1980-2008) flow regimes and under increasing levels of water use to evaluate the relative effectiveness of alternative minimum flow regulations. The simulations indicated that the probability of simulated mussel population extinction was at least 8 times greater under current hydrologic regimes. In addition, simulations of mussel extinction under varying levels of water use indicated that the relative risk of extinction increased with increased water use across a range of minimum flow regulations. The simulation results also indicated that our estimates of the effects of water use on mussel extinction were influenced by the assumptions about the dynamics of the system, highlighting the need for further study of mussel population dynamics. ?? 2011 Springer Science+Business Media, LLC (outside the USA).

A computer simulation model of Wolbachia invasion for disease vector population modification.

PubMed

Guevara-Souza, Mauricio; Vallejo, Edgar E

2015-10-05

Wolbachia invasion has been proved to be a promising alternative for controlling vector-borne diseases, particularly Dengue fever. Creating computer models that can provide insight into how vector population modification can be achieved under different conditions would be most valuable for assessing the efficacy of control strategies for this disease. In this paper, we present a computer model that simulates the behavior of native mosquito populations after the introduction of mosquitoes infected with the Wolbachia bacteria. We studied how different factors such as fecundity, fitness cost of infection, migration rates, number of populations, population size, and number of introduced infected mosquitoes affect the spread of the Wolbachia bacteria among native mosquito populations. Two main scenarios of the island model are presented in this paper, with infected mosquitoes introduced into the largest source population and peripheral populations. Overall, the results are promising; Wolbachia infection spreads among native populations and the computer model is capable of reproducing the results obtained by mathematical models and field experiments. Computer models can be very useful for gaining insight into how Wolbachia invasion works and are a promising alternative for complementing experimental and mathematical approaches for vector-borne disease control.

Development of a paediatric population-based model of the pharmacokinetics of rivaroxaban.

PubMed

Willmann, Stefan; Becker, Corina; Burghaus, Rolf; Coboeken, Katrin; Edginton, Andrea; Lippert, Jörg; Siegmund, Hans-Ulrich; Thelen, Kirstin; Mück, Wolfgang

2014-01-01

Venous thromboembolism has been increasingly recognised as a clinical problem in the paediatric population. Guideline recommendations for antithrombotic therapy in paediatric patients are based mainly on extrapolation from adult clinical trial data, owing to the limited number of clinical trials in paediatric populations. The oral, direct Factor Xa inhibitor rivaroxaban has been approved in adult patients for several thromboembolic disorders, and its well-defined pharmacokinetic and pharmacodynamic characteristics and efficacy and safety profiles in adults warrant further investigation of this agent in the paediatric population. The objective of this study was to develop and qualify a physiologically based pharmacokinetic (PBPK) model for rivaroxaban doses of 10 and 20 mg in adults and to scale this model to the paediatric population (0-18 years) to inform the dosing regimen for a clinical study of rivaroxaban in paediatric patients. Experimental data sets from phase I studies supported the development and qualification of an adult PBPK model. This adult PBPK model was then scaled to the paediatric population by including anthropometric and physiological information, age-dependent clearance and age-dependent protein binding. The pharmacokinetic properties of rivaroxaban in virtual populations of children were simulated for two body weight-related dosing regimens equivalent to 10 and 20 mg once daily in adults. The quality of the model was judged by means of a visual predictive check. Subsequently, paediatric simulations of the area under the plasma concentration-time curve (AUC), maximum (peak) plasma drug concentration (C max) and concentration in plasma after 24 h (C 24h) were compared with the adult reference simulations. Simulations for AUC, C max and C 24h throughout the investigated age range largely overlapped with values obtained for the corresponding dose in the adult reference simulation for both body weight-related dosing regimens. However, pharmacokinetic values in infants and preschool children (body weight <40 kg) were lower than the 90 % confidence interval threshold of the adult reference model and, therefore, indicated that doses in these groups may need to be increased to achieve the same plasma levels as in adults. For children with body weight between 40 and 70 kg, simulated plasma pharmacokinetic parameters (C max, C 24h and AUC) overlapped with the values obtained in the corresponding adult reference simulation, indicating that body weight-related exposure was similar between these children and adults. In adolescents of >70 kg body weight, the simulated 90 % prediction interval values of AUC and C 24h were much higher than the 90 % confidence interval of the adult reference population, owing to the weight-based simulation approach, but for these patients rivaroxaban would be administered at adult fixed doses of 10 and 20 mg. The paediatric PBPK model developed here allowed an exploratory analysis of the pharmacokinetics of rivaroxaban in children to inform the dosing regimen for a clinical study in paediatric patients.

Efficient simulation and likelihood methods for non-neutral multi-allele models.

PubMed

Joyce, Paul; Genz, Alan; Buzbas, Erkan Ozge

2012-06-01

Throughout the 1980s, Simon Tavaré made numerous significant contributions to population genetics theory. As genetic data, in particular DNA sequence, became more readily available, a need to connect population-genetic models to data became the central issue. The seminal work of Griffiths and Tavaré (1994a , 1994b , 1994c) was among the first to develop a likelihood method to estimate the population-genetic parameters using full DNA sequences. Now, we are in the genomics era where methods need to scale-up to handle massive data sets, and Tavaré has led the way to new approaches. However, performing statistical inference under non-neutral models has proved elusive. In tribute to Simon Tavaré, we present an article in spirit of his work that provides a computationally tractable method for simulating and analyzing data under a class of non-neutral population-genetic models. Computational methods for approximating likelihood functions and generating samples under a class of allele-frequency based non-neutral parent-independent mutation models were proposed by Donnelly, Nordborg, and Joyce (DNJ) (Donnelly et al., 2001). DNJ (2001) simulated samples of allele frequencies from non-neutral models using neutral models as auxiliary distribution in a rejection algorithm. However, patterns of allele frequencies produced by neutral models are dissimilar to patterns of allele frequencies produced by non-neutral models, making the rejection method inefficient. For example, in some cases the methods in DNJ (2001) require 10(9) rejections before a sample from the non-neutral model is accepted. Our method simulates samples directly from the distribution of non-neutral models, making simulation methods a practical tool to study the behavior of the likelihood and to perform inference on the strength of selection.

LEGEND, a LEO-to-GEO Environment Debris Model

NASA Technical Reports Server (NTRS)

Liou, Jer Chyi; Hall, Doyle T.

2013-01-01

LEGEND (LEO-to-GEO Environment Debris model) is a three-dimensional orbital debris evolutionary model that is capable of simulating the historical and future debris populations in the near-Earth environment. The historical component in LEGEND adopts a deterministic approach to mimic the known historical populations. Launched rocket bodies, spacecraft, and mission-related debris (rings, bolts, etc.) are added to the simulated environment. Known historical breakup events are reproduced, and fragments down to 1 mm in size are created. The LEGEND future projection component adopts a Monte Carlo approach and uses an innovative pair-wise collision probability evaluation algorithm to simulate the future breakups and the growth of the debris populations. This algorithm is based on a new "random sampling in time" approach that preserves characteristics of the traditional approach and captures the rapidly changing nature of the orbital debris environment. LEGEND is a Fortran 90-based numerical simulation program. It operates in a UNIX/Linux environment.

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 models and simulation methods: The case of the Spearman rank correlation.

PubMed

Astivia, Oscar L Olvera; Zumbo, Bruno D

2017-11-01

The purpose of this paper is to highlight the importance of a population model in guiding the design and interpretation of simulation studies used to investigate the Spearman rank correlation. The Spearman rank correlation has been known for over a hundred years to applied researchers and methodologists alike and is one of the most widely used non-parametric statistics. Still, certain misconceptions can be found, either explicitly or implicitly, in the published literature because a population definition for this statistic is rarely discussed within the social and behavioural sciences. By relying on copula distribution theory, a population model is presented for the Spearman rank correlation, and its properties are explored both theoretically and in a simulation study. Through the use of the Iman-Conover algorithm (which allows the user to specify the rank correlation as a population parameter), simulation studies from previously published articles are explored, and it is found that many of the conclusions purported in them regarding the nature of the Spearman correlation would change if the data-generation mechanism better matched the simulation design. More specifically, issues such as small sample bias and lack of power of the t-test and r-to-z Fisher transformation disappear when the rank correlation is calculated from data sampled where the rank correlation is the population parameter. A proof for the consistency of the sample estimate of the rank correlation is shown as well as the flexibility of the copula model to encompass results previously published in the mathematical literature. © 2017 The British Psychological Society.

EPA's SHEDS-multimedia model: children's cumulative pyrethroid exposure estimates and evaluation against NHANES biomarker data.

PubMed

Xue, Jianping; Zartarian, Valerie; Tornero-Velez, Rogelio; Tulve, Nicolle S

2014-12-01

The U.S. EPA's SHEDS-Multimedia model was applied to enhance the understanding of children's exposures and doses to multiple pyrethroid pesticides, including major contributing chemicals and pathways. This paper presents combined dietary and residential exposure estimates and cumulative doses for seven commonly used pyrethroids, and comparisons of model evaluation results with NHANES biomarker data for 3-PBA and DCCA metabolites. Model input distributions were fit to publicly available pesticide usage survey data, NHANES, and other studies, then SHEDS-Multimedia was applied to estimate total pyrethroid exposures and doses for 3-5 year olds for one year variability simulations. For dose estimations we used a pharmacokinetic model and two approaches for simulating dermal absorption. SHEDS-Multimedia predictions compared well to NHANES biomarker data: ratios of 3-PBA observed data to SHEDS-Multimedia modeled results were 0.88, 0.51, 0.54 and 1.02 for mean, median, 95th, and 99th percentiles, respectively; for DCCA, the ratios were 0.82, 0.53, 0.56, and 0.94. Modeled time-averaged cumulative absorbed dose of the seven pyrethroids was 3.1 nmol/day (versus 8.4 nmol/day for adults) in the general population (residential pyrethroid use and non-use homes) and 6.7 nmol/day (versus 10.5 nmol/day for adults) in the simulated residential pyrethroid use population. For the general population, contributions to modeled cumulative dose by chemical were permethrin (60%), cypermethrin (22%), and cyfluthrin (16%); for residential use homes, contributions were cypermethrin (49%), permethrin (29%), and cyfluthrin (17%). The primary exposure route for 3-5 year olds in the simulated residential use population was non-dietary ingestion exposure; whereas for the simulated general population, dietary exposure was the primary exposure route. Below the 95th percentile, the major exposure pathway was dietary for the general population; non-dietary ingestion was the major pathway starting below the 70th percentile for the residential use population. The new dermal absorption methodology considering surface loading had some impact, but did not change the order of key pathways. Published by Elsevier Ltd.

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.

Synthetic Survey of the Kepler Field

NASA Astrophysics Data System (ADS)

Wells, Mark; Prša, Andrej

2018-01-01

In the era of large scale surveys, including LSST and Gaia, binary population studies will flourish due to the large influx of data. In addition to probing binary populations as a function of galactic latitude, under-sampled groups such as low mass binaries will be observed at an unprecedented rate. To prepare for these missions, binary population simulations need to be carried out at high fidelity. These simulations will enable the creation of simulated data and, through comparison with real data, will allow the underlying binary parameter distributions to be explored. In order for the simulations to be considered robust, they should reproduce observed distributions accurately. To this end we have developed a simulator which takes input models and creates a synthetic population of eclipsing binaries. Starting from a galactic single star model, implemented using Galaxia, a code by Sharma et al. (2011), and applying observed multiplicity, mass-ratio, period, and eccentricity distributions, as reported by Raghavan et al. (2010), Duchêne & Kraus (2013), and Moe & Di Stefano (2017), we are able to generate synthetic binary surveys that correspond to any survey cadences. In order to calibrate our input models we compare the results of our synthesized eclipsing binary survey to the Kepler Eclipsing Binary catalog.

A dynamic life table model of Psorophora columbiae in the southern Louisiana rice agroecosystem with supporting hydrologic submodel. Part 1. Analysis of literature and model development.

PubMed

Focks, D A; McLaughlin, R E; Smith, B M

1988-09-01

During the past decade, the rice agroecosystem and its associated mosquitoes have been the subject of an extensive research effort directed toward the development and implementation of integrated pest management (IPM) strategies. The objective of this work was to synthesize the literature and unpublished data on the rice agroecosystem into a comprehensive simulation model of the key elements of the system known to influence the population dynamics of Psorophora columbiae. Subsequent companion papers will present a validation of these models, provide an in-depth analysis of the population dynamics of Ps. columbiae, and evaluate current and proposed IPM strategies for this mosquito. This paper describes the development of 2 models: WaterMod: Because spatial and temporal distributions of surface water and soil moisture play a decisive role in the dynamics of Ps. columbiae, an essentially hydrological simulator was developed. Its purpose is to provide environmental inputs for a second model (PcSim) which simulates the population dynamics of Ps. columbiae. WaterMod utilizes data on weather, agricultural practices, and soil characteristics for a particular region to generate a data set containing daily estimates of soil moisture and depth of water table for 12 representative areas comprising the rice agroecosystem. This model could be used to provide hydrologic inputs for additional simulation models of other riceland mosquito species. PcSim: This model simulates the population dynamics of Ps. columbiae by using the computer to maintain a daily accounting of the absolute number of mosquitoes within each daily age class for each life stage. The model creates estimates of the number of eggs, larvae, pupae, and adults for a representative l-ha area of a rice agroecosystem.

Estimating risks of heat strain by age and sex: a population-level simulation model.

PubMed

Glass, Kathryn; Tait, Peter W; Hanna, Elizabeth G; Dear, Keith

2015-05-18

Individuals living in hot climates face health risks from hyperthermia due to excessive heat. Heat strain is influenced by weather exposure and by individual characteristics such as age, sex, body size, and occupation. To explore the population-level drivers of heat strain, we developed a simulation model that scales up individual risks of heat storage (estimated using Myrup and Morgan's man model "MANMO") to a large population. Using Australian weather data, we identify high-risk weather conditions together with individual characteristics that increase the risk of heat stress under these conditions. The model identifies elevated risks in children and the elderly, with females aged 75 and older those most likely to experience heat strain. Risk of heat strain in males does not increase as rapidly with age, but is greatest on hot days with high solar radiation. Although cloudy days are less dangerous for the wider population, older women still have an elevated risk of heat strain on hot cloudy days or when indoors during high temperatures. Simulation models provide a valuable method for exploring population level risks of heat strain, and a tool for evaluating public health and other government policy interventions.

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.

Assessing recovery feasibility for piping plovers using optimization and simulation

USGS Publications Warehouse

Larson, M.A.; Ryan, M.R.; Murphy, R.K.

2003-01-01

Optimization and simulation modeling can be used to account for demographic and economic factors simultaneously in a comprehensive analysis of endangered-species population recovery. This is a powerful approach that is broadly applicable but underutilized in conservation biology. We applied the approach to a population recovery analysis of threatened and endangered piping plovers (Charadrius melodus) in the Great Plains of North America. Predator exclusion increases the reproductive success of piping plovers, but the most cost-efficient strategy of applying predator exclusion and the number of protected breeding pairs necessary to prevent further population declines were unknown. We developed a linear programming model to define strategies that would either maximize fledging rates or minimize financial costs by allocating plover pairs to 1 of 6 types of protection. We evaluated the optimal strategies using a stochastic population simulation model. The minimum cost to achieve a 20% chance of stabilizing simulated populations was approximately $1-11 million over 50 years. Increasing reproductive success to 1.24 fledglings/pair at minimal cost in any given area required fencing 85% of pairs at managed sites but cost 23% less than the current approach. Maximum fledging rates resulted in >20% of simulated populations reaching recovery goals in 30-50 years at cumulative costs of <$16 million. Protecting plover pairs within 50 km of natural resource agency field offices was sufficient to increase simulated populations to established recovery goals. A range-wide management plan needs to be developed and implemented to foster the involvement and cooperation among managers that will be necessary for recovery efforts to be successful. We also discuss how our approach can be applied to a variety of wildlife management issues.

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.

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.

Simulating free-roaming cat population management options in open demographic environments.

PubMed

Miller, Philip S; Boone, John D; Briggs, Joyce R; Lawler, Dennis F; Levy, Julie K; Nutter, Felicia B; Slater, Margaret; Zawistowski, Stephen

2014-01-01

Large populations of free-roaming cats (FRCs) generate ongoing concerns for welfare of both individual animals and populations, for human public health, for viability of native wildlife populations, and for local ecological damage. Managing FRC populations is a complex task, without universal agreement on best practices. Previous analyses that use simulation modeling tools to evaluate alternative management methods have focused on relative efficacy of removal (or trap-return, TR), typically involving euthanasia, and sterilization (or trap-neuter-return, TNR) in demographically isolated populations. We used a stochastic demographic simulation approach to evaluate removal, permanent sterilization, and two postulated methods of temporary contraception for FRC population management. Our models include demographic connectivity to neighboring untreated cat populations through natural dispersal in a metapopulation context across urban and rural landscapes, and also feature abandonment of owned animals. Within population type, a given implementation rate of the TR strategy results in the most rapid rate of population decline and (when populations are isolated) the highest probability of population elimination, followed in order of decreasing efficacy by equivalent rates of implementation of TNR and temporary contraception. Even low levels of demographic connectivity significantly reduce the effectiveness of any management intervention, and continued abandonment is similarly problematic. This is the first demographic simulation analysis to consider the use of temporary contraception and account for the realities of FRC dispersal and owned cat abandonment.

Computer simulation models as tools for identifying research needs: A black duck population model

USGS Publications Warehouse

Ringelman, J.K.; Longcore, J.R.

1980-01-01

Existing data on the mortality and production rates of the black duck (Anas rubripes) were used to construct a WATFIV computer simulation model. The yearly cycle was divided into 8 phases: hunting, wintering, reproductive, molt, post-molt, and juvenile dispersal mortality, and production from original and renesting attempts. The program computes population changes for sex and age classes during each phase. After completion of a standard simulation run with all variable default values in effect, a sensitivity analysis was conducted by changing each of 50 input variables, 1 at a time, to assess the responsiveness of the model to changes in each variable. Thirteen variables resulted in a substantial change in population level. Adult mortality factors were important during hunting and wintering phases. All production and mortality associated with original nesting attempts were sensitive, as was juvenile dispersal mortality. By identifying those factors which invoke the greatest population change, and providing an indication of the accuracy required in estimating these factors, the model helps to identify those variables which would be most profitable topics for future research.

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

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

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.

In Vitro Model Simulating Gastro-Intestinal Digestion in the Pediatric Population (Neonates and Young Infants).

PubMed

Kamstrup, Danna; Berthelsen, Ragna; Sassene, Philip Jonas; Selen, Arzu; Müllertz, Anette

2017-02-01

The focus on drug delivery for the pediatric population has been steadily increasing in the last decades. In terms of developing in vitro models simulating characteristics of the targeted pediatric population, with the purpose of predicting drug product performance after oral administration, it is important to simulate the gastro-intestinal conditions and processes the drug will encounter upon oral administration. When a drug is administered in the fed state, which is commonly the case for neonates, as they are typically fed every 3 h, the digestion of the milk will affect the composition of the fluid available for drug dissolution/solubilization. Therefore, in order to predict the solubilized amount of drug available for absorption, an in vitro model simulating digestion in the gastro-intestinal tract should be utilized. In order to simulate the digestion process and the drug solubilization taking place in vivo, the following aspects should be considered; physiologically relevant media, media volume, use of physiological enzymes in proper amounts, as well as correct pH and addition of relevant co-factors, e.g., bile salts and co-enzymes. Furthermore, physiological transit times and appropriate mixing should be considered and mimicked as close as possible. This paper presents a literature review on physiological factors relevant for digestion and drug solubilization in neonates. Based on the available literature data, a novel in vitro digestion model simulating digestion and drug solubilization in the neonate and young infant pediatric population (2 months old and younger) was designed.

Population viability of Pediocactus bradyi (Cactaceae) in a changing climate.

PubMed

Shryock, Daniel F; Esque, Todd C; Hughes, Lee

2014-11-01

A key question concerns the vulnerability of desert species adapted to harsh, variable climates to future climate change. Evaluating this requires coupling long-term demographic models with information on past and projected future climates. We investigated climatic drivers of population growth using a 22-yr demographic model for Pediocactus bradyi, an endangered cactus in northern Arizona. We used a matrix model to calculate stochastic population growth rates (λs) and the relative influences of life-cycle transitions on population growth. Regression models linked population growth with climatic variability, while stochastic simulations were used to (1) understand how predicted increases in drought frequency and extreme precipitation would affect λs, and (2) quantify variability in λs based on temporal replication of data. Overall λs was below unity (0.961). Population growth was equally influenced by fecundity and survival and significantly correlated with increased annual precipitation and higher winter temperatures. Stochastic simulations increasing the probability of drought and extreme precipitation reduced λs, but less than simulations increasing the probability of drought alone. Simulations varying the temporal replication of data suggested 14 yr were required for accurate λs estimates. Pediocactus bradyi may be vulnerable to increases in the frequency and intensity of extreme climatic events, particularly drought. Biotic interactions resulting in low survival during drought years outweighed increased seedling establishment following heavy precipitation. Climatic extremes beyond historical ranges of variability may threaten rare desert species with low population growth rates and therefore high susceptibility to stochastic events. © 2014 Botanical Society of America, Inc.

A Simulation To Model Exponential Growth.

ERIC Educational Resources Information Center

Appelbaum, Elizabeth Berman

2000-01-01

Describes a simulation using dice-tossing students in a population cluster to model the growth of cancer cells. This growth is recorded in a scatterplot and compared to an exponential function graph. (KHR)

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.

A POPULATION EXPOSURE MODEL FOR PARTICULATE MATTER: CASE STUDY RESULTS FOR PM 2.5 IN PHILADELPHIA, PA

EPA Science Inventory

A population exposure model for particulate matter (PM), called the Stochastic Human Exposure and Dose Simulation (SHEDS-PM) model, has been developed and applied in a case study of daily PM2.5 exposures for the population living in Philadelphia, PA. SHEDS-PM is a probabilisti...

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.

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.

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.

Modeling individual movement decisions of brown hare (Lepus europaeus) as a key concept for realistic spatial behavior and exposure: A population model for landscape-level risk assessment.

PubMed

Kleinmann, Joachim U; Wang, Magnus

2017-09-01

Spatial behavior is of crucial importance for the risk assessment of pesticides and for the assessment of effects of agricultural practice or multiple stressors, because it determines field use, exposition, and recovery. Recently, population models have increasingly been used to understand the mechanisms driving risk and recovery or to conduct landscape-level risk assessments. To include spatial behavior appropriately in population models for use in risk assessments, a new method, "probabilistic walk," was developed, which simulates the detailed daily movement of individuals by taking into account food resources, vegetation cover, and the presence of conspecifics. At each movement step, animals decide where to move next based on probabilities being determined from this information. The model was parameterized to simulate populations of brown hares (Lepus europaeus). A detailed validation of the model demonstrated that it can realistically reproduce various natural patterns of brown hare ecology and behavior. Simulated proportions of time animals spent in fields (PT values) were also comparable to field observations. It is shown that these important parameters for the risk assessment may, however, vary in different landscapes. The results demonstrate the value of using population models to reduce uncertainties in risk assessment and to better understand which factors determine risk in a landscape context. Environ Toxicol Chem 2017;36:2299-2307. © 2017 SETAC. © 2017 SETAC.

MoSeS: Modelling and Simulation for e-Social Science.

PubMed

Townend, Paul; Xu, Jie; Birkin, Mark; Turner, Andy; Wu, Belinda

2009-07-13

MoSeS (Modelling and Simulation for e-Social Science) is a research node of the National Centre for e-Social Science. MoSeS uses e-Science techniques to execute an events-driven model that simulates discrete demographic processes; this allows us to project the UK population 25 years into the future. This paper describes the architecture, simulation methodology and latest results obtained by MoSeS.

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.

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.

Modeling snail breeding in a bioregenerative life support system

NASA Astrophysics Data System (ADS)

Kovalev, V. S.; Manukovsky, N. S.; Tikhomirov, A. A.; Kolmakova, A. A.

2015-07-01

The discrete-time model of snail breeding consists of two sequentially linked submodels: "Stoichiometry" and "Population". In both submodels, a snail population is split up into twelve age groups within one year of age. The first submodel is used to simulate the metabolism of a single snail in each age group via the stoichiometric equation; the second submodel is used to optimize the age structure and the size of the snail population. Daily intake of snail meat by crewmen is a guideline which specifies the population productivity. The mass exchange of the snail unit inhabited by land snails of Achatina fulica is given as an outcome of step-by-step modeling. All simulations are performed using Solver Add-In of Excel 2007.

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.

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

ERIC Educational Resources Information Center

Friedland, James

Presented are instructions for the use of "TAG," a model for estimating animal population in a given area. The computer program asks the student to estimate the number of bass in a simulated farm pond using the technique of tagging and recovery. The objective of the simulation is to teach principles for estimating animal populations when they…

Analysis of Road Network Pattern Considering Population Distribution and Central Business District

PubMed Central

Zhao, Fangxia; Sun, Huijun; Wu, Jianjun; Gao, Ziyou; Liu, Ronghui

2016-01-01

This paper proposes a road network growing model with the consideration of population distribution and central business district (CBD) attraction. In the model, the relative neighborhood graph (RNG) is introduced as the connection mechanism to capture the characteristics of road network topology. The simulation experiment is set up to illustrate the effects of population distribution and CBD attraction on the characteristics of road network. Moreover, several topological attributes of road network is evaluated by using coverage, circuitness, treeness and total length in the experiment. Finally, the suggested model is verified in the simulation of China and Beijing Highway networks. PMID:26981857

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

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.

App Usage Factor: A Simple Metric to Compare the Population Impact of Mobile Medical Apps.

PubMed

Lewis, Thomas Lorchan; Wyatt, Jeremy C

2015-08-19

One factor when assessing the quality of mobile apps is quantifying the impact of a given app on a population. There is currently no metric which can be used to compare the population impact of a mobile app across different health care disciplines. The objective of this study is to create a novel metric to characterize the impact of a mobile app on a population. We developed the simple novel metric, app usage factor (AUF), defined as the logarithm of the product of the number of active users of a mobile app with the median number of daily uses of the app. The behavior of this metric was modeled using simulated modeling in Python, a general-purpose programming language. Three simulations were conducted to explore the temporal and numerical stability of our metric and a simulated app ecosystem model using a simulated dataset of 20,000 apps. Simulations confirmed the metric was stable between predicted usage limits and remained stable at extremes of these limits. Analysis of a simulated dataset of 20,000 apps calculated an average value for the app usage factor of 4.90 (SD 0.78). A temporal simulation showed that the metric remained stable over time and suitable limits for its use were identified. A key component when assessing app risk and potential harm is understanding the potential population impact of each mobile app. Our metric has many potential uses for a wide range of stakeholders in the app ecosystem, including users, regulators, developers, and health care professionals. Furthermore, this metric forms part of the overall estimate of risk and potential for harm or benefit posed by a mobile medical app. We identify the merits and limitations of this metric, as well as potential avenues for future validation and research.

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.

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...

Developing Cognitive Models for Social Simulation from Survey Data

NASA Astrophysics Data System (ADS)

Alt, Jonathan K.; Lieberman, Stephen

The representation of human behavior and cognition continues to challenge the modeling and simulation community. The use of survey and polling instruments to inform belief states, issue stances and action choice models provides a compelling means of developing models and simulations with empirical data. Using these types of data to population social simulations can greatly enhance the feasibility of validation efforts, the reusability of social and behavioral modeling frameworks, and the testable reliability of simulations. We provide a case study demonstrating these effects, document the use of survey data to develop cognitive models, and suggest future paths forward for social and behavioral modeling.

Factors affecting GEBV accuracy with single-step Bayesian models.

PubMed

Zhou, Lei; Mrode, Raphael; Zhang, Shengli; Zhang, Qin; Li, Bugao; Liu, Jian-Feng

2018-01-01

A single-step approach to obtain genomic prediction was first proposed in 2009. Many studies have investigated the components of GEBV accuracy in genomic selection. However, it is still unclear how the population structure and the relationships between training and validation populations influence GEBV accuracy in terms of single-step analysis. Here, we explored the components of GEBV accuracy in single-step Bayesian analysis with a simulation study. Three scenarios with various numbers of QTL (5, 50, and 500) were simulated. Three models were implemented to analyze the simulated data: single-step genomic best linear unbiased prediction (GBLUP; SSGBLUP), single-step BayesA (SS-BayesA), and single-step BayesB (SS-BayesB). According to our results, GEBV accuracy was influenced by the relationships between the training and validation populations more significantly for ungenotyped animals than for genotyped animals. SS-BayesA/BayesB showed an obvious advantage over SSGBLUP with the scenarios of 5 and 50 QTL. SS-BayesB model obtained the lowest accuracy with the 500 QTL in the simulation. SS-BayesA model was the most efficient and robust considering all QTL scenarios. Generally, both the relationships between training and validation populations and LD between markers and QTL contributed to GEBV accuracy in the single-step analysis, and the advantages of single-step Bayesian models were more apparent when the trait is controlled by fewer QTL.

Predator-prey models with component Allee effect for predator reproduction.

PubMed

Terry, Alan J

2015-12-01

We present four predator-prey models with component Allee effect for predator reproduction. Using numerical simulation results for our models, we describe how the customary definitions of component and demographic Allee effects, which work well for single species models, can be extended to predators in predator-prey models by assuming that the prey population is held fixed. We also find that when the prey population is not held fixed, then these customary definitions may lead to conceptual problems. After this discussion of definitions, we explore our four models, analytically and numerically. Each of our models has a fixed point that represents predator extinction, which is always locally stable. We prove that the predator will always die out either if the initial predator population is sufficiently small or if the initial prey population is sufficiently small. Through numerical simulations, we explore co-existence fixed points. In addition, we demonstrate, by simulation, the existence of a stable limit cycle in one of our models. Finally, we derive analytical conditions for a co-existence trapping region in three of our models, and show that the fourth model cannot possess a particular kind of co-existence trapping region. We punctuate our results with comments on their real-world implications; in particular, we mention the possibility of prey resurgence from mortality events, and the possibility of failure in a biological pest control program.

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

PubMed

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

2013-09-01

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

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

PubMed Central

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

2014-01-01

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

Design of a digital phantom population for myocardial perfusion SPECT imaging research.

PubMed

Ghaly, Michael; Du, Yong; Fung, George S K; Tsui, Benjamin M W; Links, Jonathan M; Frey, Eric

2014-06-21

Digital phantoms and Monte Carlo (MC) simulations have become important tools for optimizing and evaluating instrumentation, acquisition and processing methods for myocardial perfusion SPECT (MPS). In this work, we designed a new adult digital phantom population and generated corresponding Tc-99m and Tl-201 projections for use in MPS research. The population is based on the three-dimensional XCAT phantom with organ parameters sampled from the Emory PET Torso Model Database. Phantoms included three variations each in body size, heart size, and subcutaneous adipose tissue level, for a total of 27 phantoms of each gender. The SimSET MC code and angular response functions were used to model interactions in the body and the collimator-detector system, respectively. We divided each phantom into seven organs, each simulated separately, allowing use of post-simulation summing to efficiently model uptake variations. Also, we adapted and used a criterion based on the relative Poisson effective count level to determine the required number of simulated photons for each simulated organ. This technique provided a quantitative estimate of the true noise in the simulated projection data, including residual MC simulation noise. Projections were generated in 1 keV wide energy windows from 48-184 keV assuming perfect energy resolution to permit study of the effects of window width, energy resolution, and crosstalk in the context of dual isotope MPS. We have developed a comprehensive method for efficiently simulating realistic projections for a realistic population of phantoms in the context of MPS imaging. The new phantom population and realistic database of simulated projections will be useful in performing mathematical and human observer studies to evaluate various acquisition and processing methods such as optimizing the energy window width, investigating the effect of energy resolution on image quality and evaluating compensation methods for degrading factors such as crosstalk in the context of single and dual isotope MPS.

Design of a digital phantom population for myocardial perfusion SPECT imaging research

NASA Astrophysics Data System (ADS)

Ghaly, Michael; Du, Yong; Fung, George S. K.; Tsui, Benjamin M. W.; Links, Jonathan M.; Frey, Eric

2014-06-01

Digital phantoms and Monte Carlo (MC) simulations have become important tools for optimizing and evaluating instrumentation, acquisition and processing methods for myocardial perfusion SPECT (MPS). In this work, we designed a new adult digital phantom population and generated corresponding Tc-99m and Tl-201 projections for use in MPS research. The population is based on the three-dimensional XCAT phantom with organ parameters sampled from the Emory PET Torso Model Database. Phantoms included three variations each in body size, heart size, and subcutaneous adipose tissue level, for a total of 27 phantoms of each gender. The SimSET MC code and angular response functions were used to model interactions in the body and the collimator-detector system, respectively. We divided each phantom into seven organs, each simulated separately, allowing use of post-simulation summing to efficiently model uptake variations. Also, we adapted and used a criterion based on the relative Poisson effective count level to determine the required number of simulated photons for each simulated organ. This technique provided a quantitative estimate of the true noise in the simulated projection data, including residual MC simulation noise. Projections were generated in 1 keV wide energy windows from 48-184 keV assuming perfect energy resolution to permit study of the effects of window width, energy resolution, and crosstalk in the context of dual isotope MPS. We have developed a comprehensive method for efficiently simulating realistic projections for a realistic population of phantoms in the context of MPS imaging. The new phantom population and realistic database of simulated projections will be useful in performing mathematical and human observer studies to evaluate various acquisition and processing methods such as optimizing the energy window width, investigating the effect of energy resolution on image quality and evaluating compensation methods for degrading factors such as crosstalk in the context of single and dual isotope MPS.

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

EPA Science Inventory

The Stochastic Human Exposure and Dose Simulation (SHEDS) models being developed by the US EPA/NERL use a probabilistic approach to predict population exposures to pollutants. The SHEDS model for particulate matter (SHEDS-PM) estimates the population distribution of PM exposure...

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.

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.

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.

A POPULATION EXPOSURE MODEL FOR PARTICULATE MATTER: SHEDS-PM

EPA Science Inventory

The US EPA National Exposure Research Laboratory (NERL) has developed a population exposure and dose model for particulate matter (PM) that will be publicly available in Fall 2002. The Stochastic Human Exposure and Dose Simulation (SHEDS-PM) model uses a probabilistic approach ...

A modelling approach to vaccination and contraception programmes for rabies control in fox populations.

PubMed Central

Suppo, C; Naulin, J M; Langlais, M; Artois, M

2000-01-01

In a previous study, three of the authors designed a one-dimensional model to simulate the propagation of rabies within a growing fox population; the influence of various parameters on the epidemic model was studied, including oral-vaccination programmes. In this work, a two-dimensional model of a fox population having either an exponential or a logistic growth pattern was considered. Using numerical simulations, the efficiencies of two prophylactic methods (fox contraception and vaccination against rabies) were assessed, used either separately or jointly. It was concluded that far lower rates of administration are necessary to eradicate rabies, and that the undesirable side-effects of each programme disappear, when both are used together. PMID:11007334

Genetic demographic networks: Mathematical model and applications.

PubMed

Kimmel, Marek; Wojdyła, Tomasz

2016-10-01

Recent improvement in the quality of genetic data obtained from extinct human populations and their ancestors encourages searching for answers to basic questions regarding human population history. The most common and successful are model-based approaches, in which genetic data are compared to the data obtained from the assumed demography model. Using such approach, it is possible to either validate or adjust assumed demography. Model fit to data can be obtained based on reverse-time coalescent simulations or forward-time simulations. In this paper we introduce a computational method based on mathematical equation that allows obtaining joint distributions of pairs of individuals under a specified demography model, each of them characterized by a genetic variant at a chosen locus. The two individuals are randomly sampled from either the same or two different populations. The model assumes three types of demographic events (split, merge and migration). Populations evolve according to the time-continuous Moran model with drift and Markov-process mutation. This latter process is described by the Lyapunov-type equation introduced by O'Brien and generalized in our previous works. Application of this equation constitutes an original contribution. In the result section of the paper we present sample applications of our model to both simulated and literature-based demographies. Among other we include a study of the Slavs-Balts-Finns genetic relationship, in which we model split and migrations between the Balts and Slavs. We also include another example that involves the migration rates between farmers and hunters-gatherers, based on modern and ancient DNA samples. This latter process was previously studied using coalescent simulations. Our results are in general agreement with the previous method, which provides validation of our approach. Although our model is not an alternative to simulation methods in the practical sense, it provides an algorithm to compute pairwise distributions of alleles, in the case of haploid non-recombining loci such as mitochondrial and Y-chromosome loci in humans. Copyright © 2016 Elsevier Inc. All rights reserved.

The Stochastic Human Exposure and Dose Simulation Model for Multimedia, Multipathway Chemicals: Dietary Module Version 1: Technical Manual

EPA Pesticide Factsheets

SHEDS - Multimedia is EPA's premier physically-based, probabilistic model, that can simulate cumulative or aggregate exposures for a population across a variety of multimedia, multipathway environmental chemicals.

Influence of erroneous patient records on population pharmacokinetic modeling and individual bayesian estimation.

PubMed

van der Meer, Aize Franciscus; Touw, Daniël J; Marcus, Marco A E; Neef, Cornelis; Proost, Johannes H

2012-10-01

Observational data sets can be used for population pharmacokinetic (PK) modeling. However, these data sets are generally less precisely recorded than experimental data sets. This article aims to investigate the influence of erroneous records on population PK modeling and individual maximum a posteriori Bayesian (MAPB) estimation. A total of 1123 patient records of neonates who were administered vancomycin were used for population PK modeling by iterative 2-stage Bayesian (ITSB) analysis. Cut-off values for weighted residuals were tested for exclusion of records from the analysis. A simulation study was performed to assess the influence of erroneous records on population modeling and individual MAPB estimation. Also the cut-off values for weighted residuals were tested in the simulation study. Errors in registration have limited the influence on outcomes of population PK modeling but can have detrimental effects on individual MAPB estimation. A population PK model created from a data set with many registration errors has little influence on subsequent MAPB estimates for precisely recorded data. A weighted residual value of 2 for concentration measurements has good discriminative power for identification of erroneous records. ITSB analysis and its individual estimates are hardly affected by most registration errors. Large registration errors can be detected by weighted residuals of concentration.

Graph-based analysis of connectivity in spatially-explicit population models: HexSim and the Connectivity Analysis Toolkit

EPA Science Inventory

Background / Question / Methods Planning for the recovery of threatened species is increasingly informed by spatially-explicit population models. However, using simulation model results to guide land management decisions can be difficult due to the volume and complexity of model...

Policy evaluation in diabetes prevention and treatment using a population-based macro simulation model: the MICADO model.

PubMed

van der Heijden, A A W A; Feenstra, T L; Hoogenveen, R T; Niessen, L W; de Bruijne, M C; Dekker, J M; Baan, C A; Nijpels, G

2015-12-01

To test a simulation model, the MICADO model, for estimating the long-term effects of interventions in people with and without diabetes. The MICADO model includes micro- and macrovascular diseases in relation to their risk factors. The strengths of this model are its population scope and the possibility to assess parameter uncertainty using probabilistic sensitivity analyses. Outcomes include incidence and prevalence of complications, quality of life, costs and cost-effectiveness. We externally validated MICADO's estimates of micro- and macrovascular complications in a Dutch cohort with diabetes (n = 498,400) by comparing these estimates with national and international empirical data. For the annual number of people undergoing amputations, MICADO's estimate was 592 (95% interquantile range 291-842), which compared well with the registered number of people with diabetes-related amputations in the Netherlands (728). The incidence of end-stage renal disease estimated using the MICADO model was 247 people (95% interquartile range 120-363), which was also similar to the registered incidence in the Netherlands (277 people). MICADO performed well in the validation of macrovascular outcomes of population-based cohorts, while it had more difficulty in reflecting a highly selected trial population. Validation by comparison with independent empirical data showed that the MICADO model simulates the natural course of diabetes and its micro- and macrovascular complications well. As a population-based model, MICADO can be applied for projections as well as scenario analyses to evaluate the long-term (cost-)effectiveness of population-level interventions targeting diabetes and its complications in the Netherlands or similar countries. © 2015 The Authors. Diabetic Medicine © 2015 Diabetes UK.

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.

Hybrid-Lambda: simulation of multiple merger and Kingman gene genealogies in species networks and species trees.

PubMed

Zhu, Sha; Degnan, James H; Goldstien, Sharyn J; Eldon, Bjarki

2015-09-15

There has been increasing interest in coalescent models which admit multiple mergers of ancestral lineages; and to model hybridization and coalescence simultaneously. Hybrid-Lambda is a software package that simulates gene genealogies under multiple merger and Kingman's coalescent processes within species networks or species trees. Hybrid-Lambda allows different coalescent processes to be specified for different populations, and allows for time to be converted between generations and coalescent units, by specifying a population size for each population. In addition, Hybrid-Lambda can generate simulated datasets, assuming the infinitely many sites mutation model, and compute the F ST statistic. As an illustration, we apply Hybrid-Lambda to infer the time of subdivision of certain marine invertebrates under different coalescent processes. Hybrid-Lambda makes it possible to investigate biogeographic concordance among high fecundity species exhibiting skewed offspring distribution.

Reconstructing a Large-Scale Population for Social Simulation

NASA Astrophysics Data System (ADS)

Fan, Zongchen; Meng, Rongqing; Ge, Yuanzheng; Qiu, Xiaogang

The advent of social simulation has provided an opportunity to research on social systems. More and more researchers tend to describe the components of social systems in a more detailed level. Any simulation needs the support of population data to initialize and implement the simulation systems. However, it's impossible to get the data which provide full information about individuals and households. We propose a two-step method to reconstruct a large-scale population for a Chinese city according to Chinese culture. Firstly, a baseline population is generated through gathering individuals into households one by one; secondly, social relationships such as friendship are assigned to the baseline population. Through a case study, a population of 3,112,559 individuals gathered in 1,133,835 households is reconstructed for Urumqi city, and the results show that the generated data can respect the real data quite well. The generated data can be applied to support modeling of some social phenomenon.

Modelling the effects of stranding on the Atlantic salmon population in the Dale River, Norway.

PubMed

Sauterleute, Julian F; Hedger, Richard D; Hauer, Christoph; Pulg, Ulrich; Skoglund, Helge; Sundt-Hansen, Line E; Bakken, Tor Haakon; Ugedal, Ola

2016-12-15

Rapid dewatering in rivers as a consequence of hydropower operations may cause stranding of juvenile fish and have a negative impact on fish populations. We implemented stranding into an Atlantic salmon population model in order to evaluate long-term effects on the population in the Dale River, Western Norway. Furthermore, we assessed the sensitivity of the stranding model to dewatered area in comparison to biological parameters, and compared different methods for calculating wetted area, the main abiotic input parameter to the population model. Five scenarios were simulated dependent on fish life-stage, season and light level. Our simulation results showed largest negative effect on the population abundance for hydropeaking during winter daylight. Salmon smolt production had highest sensitivity to the stranding mortality of older juvenile fish, suggesting that stranding of fish at these life-stages is likely to have greater population impacts than that of earlier life-stages. Downstream retention effects on the ramping velocity were found to be negligible in the stranding model, but are suggested to be important in the context of mitigation measure design. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

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...

An application of forward-backward difference approximation method on the optimal control problem in the transmission of tuberculosis model

NASA Astrophysics Data System (ADS)

Rahmah, Z.; Subartini, B.; Djauhari, E.; Anggriani, N.; Supriatna, A. K.

2017-03-01

Tuberculosis (TB) is a disease that is infected by the bacteria Mycobacterium tuberculosis. The World Health Organization (WHO) recommends to implement the Baccilus Calmete Guerin (BCG) vaccine in toddler aged two to three months to be protected from the infection. This research explores the numerical simulation of forward-backward difference approximation method on the model of TB transmission considering this vaccination program. The model considers five compartments of sub-populations, i.e. susceptible, vaccinated, exposed, infected, and recovered human sub-populations. We consider here the vaccination as a control variable. The results of the simulation showed that vaccination can indeed reduce the number of infected human population.

Simulation modeling of population viability for the leopard darter (Percidae: Percina pantherina)

USGS Publications Warehouse

Williams, L.R.; Echelle, A.A.; Toepfer, C.S.; Williams, M.G.; Fisher, W.L.

1999-01-01

We used the computer program RAMAS to perform a population viability analysis for the leopard darter, Percina pantherina. This percid fish is a threatened species confined to five isolated rivers in the Ouachita Mountains of Oklahoma and Arkansas. A base model created from life history data indicated a 6% probability that the leopard darter would go extinct in 50 years. We performed sensitivity analyses to determine the effects of initial population size, variation in age structure, variation in severity and probability of catastrophe, and migration rate. Catastrophe (modeled as the probability and severity of drought) and migration had the greatest effects on persistence. Results of these simulations have implications for management of this species.

From individual to population level effects of toxicants in the tubicifid Branchiura sowerbyi using threshold effect models in a Bayesian framework.

PubMed

Ducrot, Virginie; Billoir, Elise; Péry, Alexandre R R; Garric, Jeanne; Charles, Sandrine

2010-05-01

Effects of zinc were studied in the freshwater worm Branchiura sowerbyi using partial and full life-cycle tests. Only newborn and juveniles were sensitive to zinc, displaying effects on survival, growth, and age at first brood at environmentally relevant concentrations. Threshold effect models were proposed to assess toxic effects on individuals. They were fitted to life-cycle test data using Bayesian inference and adequately described life-history trait data in exposed organisms. The daily asymptotic growth rate of theoretical populations was then simulated with a matrix population model, based upon individual-level outputs. Population-level outputs were in accordance with existing literature for controls. Working in a Bayesian framework allowed incorporating parameter uncertainty in the simulation of the population-level response to zinc exposure, thus increasing the relevance of test results in the context of ecological risk assessment.

Simulation of Range Safety for the NASA Space Shuttle

NASA Technical Reports Server (NTRS)

Rabelo, Luis; Sepulveda, Jose; Compton, Jeppie; Turner, Robert

2005-01-01

This paper describes a simulation environment that seamlessly combines a number of safety and environmental models for the launch phase of a NASA Space Shuttle mission. The components of this simulation environment represent the different systems that must interact in order to determine the Expectation of casualties (E(sub c)) resulting from the toxic effects of the gas dispersion that occurs after a disaster affecting a Space Shuttle within 120 seconds of lift-off. The utilization of the Space Shuttle reliability models, trajectory models, weather dissemination systems, population models, amount and type of toxicants, gas dispersion models, human response functions to toxicants, and a geographical information system are all integrated to create this environment. This simulation environment can help safety managers estimate the population at risk in order to plan evacuation, make sheltering decisions, determine the resources required to provide aid and comfort, and mitigate damages in case of a disaster. This simulation environment may also be modified and used for the landing phase of a space vehicle but will not be discussed in this paper.

The Stochastic Human Exposure and Dose Simulation Model for Multimedia, Multipathway Chemicals: Residential Module Version 4: User Guide, June 2012

EPA Pesticide Factsheets

SHEDS - Multimedia is EPA's premier physically-based, probabilistic model, that can simulate cumulative or aggregate exposures for a population across a variety of multimedia, multipathway environmental chemicals.

The Stochastic Human Exposure and Dose Simulation Model for Multimedia, Multipathway Chemicals: Residential Module Version 4: Technical Manual, May 2012

EPA Pesticide Factsheets

SHEDS - Multimedia is EPA's premier physically-based, probabilistic model, that can simulate cumulative or aggregate exposures for a population across a variety of multimedia, multipathway environmental chemicals.

The Stochastic Human Exposure and Dose Simulation Model for Multimedia, Multipathway Chemicals: Dietary Module Version 1: User Guide, June 2012

EPA Pesticide Factsheets

SHEDS - Multimedia is EPA's premier physically-based, probabilistic model, that can simulate cumulative or aggregate exposures for a population across a variety of multimedia, multipathway environmental chemicals.

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

An open Markov chain scheme model for a credit consumption portfolio fed by ARIMA and SARMA processes

NASA Astrophysics Data System (ADS)

Esquível, Manuel L.; Fernandes, José Moniz; Guerreiro, Gracinda R.

2016-06-01

We introduce a schematic formalism for the time evolution of a random population entering some set of classes and such that each member of the population evolves among these classes according to a scheme based on a Markov chain model. We consider that the flow of incoming members is modeled by a time series and we detail the time series structure of the elements in each of the classes. We present a practical application to data from a credit portfolio of a Cape Verdian bank; after modeling the entering population in two different ways - namely as an ARIMA process and as a deterministic sigmoid type trend plus a SARMA process for the residues - we simulate the behavior of the population and compare the results. We get that the second method is more accurate in describing the behavior of the populations when compared to the observed values in a direct simulation of the Markov chain.

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

NASA Technical Reports Server (NTRS)

Holms, A. G.

1974-01-01

Monte Carlo studies using population models intended to represent response surface applications are reported. Simulated experiments were generated by adding pseudo random normally distributed errors to population values to generate observations. Model equations were fitted to the observations and the decision procedure was used to delete terms. Comparison of values predicted by the reduced models with the true population values enabled the identification of deletion strategies that are approximately optimal for minimizing prediction errors.

The structure of the distant Kuiper belt in a Nice model scenario

NASA Astrophysics Data System (ADS)

Pike, Rosemary E.; Lawler, Samantha; Brasser, Ramon; Shankman, Cory; Alexandersen, Mike; Kavelaars, J. J.

2016-10-01

By utilizing a well-sampled migration model and characterized survey detections, we demonstrate that the Nice-model scenario results in consistent populations of scattering trans-Neptunian objects (TNOs) and several resonant TNO populations, but fails to reproduce the large population of 5:1 resonators discovered in surveys. We examine in detail the TNO populations implanted by the Nice model simulation from Brasser and Morbidelli (2013, B&M). This analysis focuses on the region from 25-155 AU, probing the classical, scattering, detached, and major resonant populations. Additional integrations were necessary to classify the test particles and determine population sizes and characteristics. The classified simulation objects are compared to the real TNOs from the Canada-France Ecliptic Plane Survey (CFEPS), CFEPS high latitude fields, and the Alexandersen (2016) survey. These surveys all include a detailed characterization of survey depth, pointing, and tracking efficiency, which allows detailed testing of this independently produced model of TNO populations. In the B&M model, the regions of the outer Solar System populated via capture of scattering objects are consistent with survey constraints. The scattering TNOs and most n:1 resonant populations have consistent orbital distributions and population sizes with the real detections, as well as a starting disk mass consistent with expectations. The B&M 5:1 resonators have a consistent orbital distribution with the real detections and previous models. However, the B&M 5:1 Neptune resonance is underpopulated by a factor of ~100 and would require a starting proto-planetesimal disk with a mass of ~100 Earth masses. The large population in the 5:1 Neptune resonance is unexplained by scattering capture in a Nice-model scenario, however this model accurately produces the TNO subpopulations that result from scattering object capture and provides additional insight into sub-population orbital distributions.

Simulating the Performance of Ground-Based Optical Asteroid Surveys

NASA Astrophysics Data System (ADS)

Christensen, Eric J.; Shelly, Frank C.; Gibbs, Alex R.; Grauer, Albert D.; Hill, Richard E.; Johnson, Jess A.; Kowalski, Richard A.; Larson, Stephen M.

2014-11-01

We are developing a set of asteroid survey simulation tools in order to estimate the capability of existing and planned ground-based optical surveys, and to test a variety of possible survey cadences and strategies. The survey simulator is composed of several layers, including a model population of solar system objects and an orbital integrator, a site-specific atmospheric model (including inputs for seeing, haze and seasonal cloud cover), a model telescope (with a complete optical path to estimate throughput), a model camera (including FOV, pixel scale, and focal plane fill factor) and model source extraction and moving object detection layers with tunable detection requirements. We have also developed a flexible survey cadence planning tool to automatically generate nightly survey plans. Inputs to the cadence planner include camera properties (FOV, readout time), telescope limits (horizon, declination, hour angle, lunar and zenithal avoidance), preferred and restricted survey regions in RA/Dec, ecliptic, and Galactic coordinate systems, and recent coverage by other asteroid surveys. Simulated surveys are created for a subset of current and previous NEO surveys (LINEAR, Pan-STARRS and the three Catalina Sky Survey telescopes), and compared against the actual performance of these surveys in order to validate the model’s performance. The simulator tracks objects within the FOV of any pointing that were not discovered (e.g. too few observations, too trailed, focal plane array gaps, too fast or slow), thus dividing the population into “discoverable” and “discovered” subsets, to inform possible survey design changes. Ongoing and future work includes generating a realistic “known” subset of the model NEO population, running multiple independent simulated surveys in coordinated and uncoordinated modes, and testing various cadences to find optimal strategies for detecting NEO sub-populations. These tools can also assist in quantifying the efficiency of novel yet unverified survey cadences (e.g. the baseline LSST cadence) that sparsely spread the observations required for detection over several days or weeks.

Evaluating and improving count-based population inference: A case study from 31 years of monitoring Sandhill Cranes

USGS Publications Warehouse

Gerber, Brian D.; Kendall, William L.

2017-01-01

Monitoring animal populations can be difficult. Limited resources often force monitoring programs to rely on unadjusted or smoothed counts as an index of abundance. Smoothing counts is commonly done using a moving-average estimator to dampen sampling variation. These indices are commonly used to inform management decisions, although their reliability is often unknown. We outline a process to evaluate the biological plausibility of annual changes in population counts and indices from a typical monitoring scenario and compare results with a hierarchical Bayesian time series (HBTS) model. We evaluated spring and fall counts, fall indices, and model-based predictions for the Rocky Mountain population (RMP) of Sandhill Cranes (Antigone canadensis) by integrating juvenile recruitment, harvest, and survival into a stochastic stage-based population model. We used simulation to evaluate population indices from the HBTS model and the commonly used 3-yr moving average estimator. We found counts of the RMP to exhibit biologically unrealistic annual change, while the fall population index was largely biologically realistic. HBTS model predictions suggested that the RMP changed little over 31 yr of monitoring, but the pattern depended on assumptions about the observational process. The HBTS model fall population predictions were biologically plausible if observed crane harvest mortality was compensatory up to natural mortality, as empirical evidence suggests. Simulations indicated that the predicted mean of the HBTS model was generally a more reliable estimate of the true population than population indices derived using a moving 3-yr average estimator. Practitioners could gain considerable advantages from modeling population counts using a hierarchical Bayesian autoregressive approach. Advantages would include: (1) obtaining measures of uncertainty; (2) incorporating direct knowledge of the observational and population processes; (3) accommodating missing years of data; and (4) forecasting population size.

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...

Use of population pharmacokinetic modeling and Monte Carlo simulation to capture individual animal variability in the prediction of flunixin withdrawal times in cattle.

PubMed

Wu, H; Baynes, R E; Leavens, T; Tell, L A; Riviere, J E

2013-06-01

The objective of this study was to develop a population pharmacokinetic (PK) model and predict tissue residues and the withdrawal interval (WDI) of flunixin in cattle. Data were pooled from published PK studies in which flunixin was administered through various dosage regimens to diverse populations of cattle. A set of liver data used to establish the regulatory label withdrawal time (WDT) also were used in this study. Compartmental models with first-order absorption and elimination were fitted to plasma and liver concentrations by a population PK modeling approach. Monte Carlo simulations were performed with the population mean and variabilities of PK parameters to predict liver concentrations of flunixin. The PK of flunixin was described best by a 3-compartment model with an extra liver compartment. The WDI estimated in this study with liver data only was the same as the label WDT. However, a longer WDI was estimated when both plasma and liver data were included in the population PK model. This study questions the use of small groups of healthy animals to determine WDTs for drugs intended for administration to large diverse populations. This may warrant a reevaluation of the current procedure for establishing WDT to prevent violative residues of flunixin. © 2012 Blackwell Publishing Ltd.

POPULATION EXPOSURE AND DOSE MODEL FOR AIR TOXICS: A BENZENE CASE STUDY

EPA Science Inventory

The EPA's National Exposure Research Laboratory (NERL) is developing a human exposure and dose model called the Stochastic Human Exposure and Dose Simulation model for Air Toxics (SHEDS-AirToxics) to characterize population exposure to air toxics in support of the National Air ...

New parsimonious simulation methods and tools to assess future food and environmental security of farm populations

PubMed Central

Antle, John M.; Stoorvogel, Jetse J.; Valdivia, Roberto O.

2014-01-01

This article presents conceptual and empirical foundations for new parsimonious simulation models that are being used to assess future food and environmental security of farm populations. The conceptual framework integrates key features of the biophysical and economic processes on which the farming systems are based. The approach represents a methodological advance by coupling important behavioural processes, for example, self-selection in adaptive responses to technological and environmental change, with aggregate processes, such as changes in market supply and demand conditions or environmental conditions as climate. Suitable biophysical and economic data are a critical limiting factor in modelling these complex systems, particularly for the characterization of out-of-sample counterfactuals in ex ante analyses. Parsimonious, population-based simulation methods are described that exploit available observational, experimental, modelled and expert data. The analysis makes use of a new scenario design concept called representative agricultural pathways. A case study illustrates how these methods can be used to assess food and environmental security. The concluding section addresses generalizations of parametric forms and linkages of regional models to global models. PMID:24535388

New parsimonious simulation methods and tools to assess future food and environmental security of farm populations.

PubMed

Antle, John M; Stoorvogel, Jetse J; Valdivia, Roberto O

2014-04-05

This article presents conceptual and empirical foundations for new parsimonious simulation models that are being used to assess future food and environmental security of farm populations. The conceptual framework integrates key features of the biophysical and economic processes on which the farming systems are based. The approach represents a methodological advance by coupling important behavioural processes, for example, self-selection in adaptive responses to technological and environmental change, with aggregate processes, such as changes in market supply and demand conditions or environmental conditions as climate. Suitable biophysical and economic data are a critical limiting factor in modelling these complex systems, particularly for the characterization of out-of-sample counterfactuals in ex ante analyses. Parsimonious, population-based simulation methods are described that exploit available observational, experimental, modelled and expert data. The analysis makes use of a new scenario design concept called representative agricultural pathways. A case study illustrates how these methods can be used to assess food and environmental security. The concluding section addresses generalizations of parametric forms and linkages of regional models to global models.

Agent-Based Deterministic Modeling of the Bone Marrow Homeostasis.

PubMed

Kurhekar, Manish; Deshpande, Umesh

2016-01-01

Modeling of stem cells not only describes but also predicts how a stem cell's environment can control its fate. The first stem cell populations discovered were hematopoietic stem cells (HSCs). In this paper, we present a deterministic model of bone marrow (that hosts HSCs) that is consistent with several of the qualitative biological observations. This model incorporates stem cell death (apoptosis) after a certain number of cell divisions and also demonstrates that a single HSC can potentially populate the entire bone marrow. It also demonstrates that there is a production of sufficient number of differentiated cells (RBCs, WBCs, etc.). We prove that our model of bone marrow is biologically consistent and it overcomes the biological feasibility limitations of previously reported models. The major contribution of our model is the flexibility it allows in choosing model parameters which permits several different simulations to be carried out in silico without affecting the homeostatic properties of the model. We have also performed agent-based simulation of the model of bone marrow system proposed in this paper. We have also included parameter details and the results obtained from the simulation. The program of the agent-based simulation of the proposed model is made available on a publicly accessible website.

The accuracy of climate models' simulated season lengths and the effectiveness of grid scale correction factors

DOE PAGES

Winterhalter, Wade E.

2011-09-01

Global climate change is expected to impact biological populations through a variety of mechanisms including increases in the length of their growing season. Climate models are useful tools for predicting how season length might change in the future. However, the accuracy of these models tends to be rather low at regional geographic scales. Here, I determined the ability of several atmosphere and ocean general circulating models (AOGCMs) to accurately simulate historical season lengths for a temperate ectotherm across the continental United States. I also evaluated the effectiveness of regional-scale correction factors to improve the accuracy of these models. I foundmore » that both the accuracy of simulated season lengths and the effectiveness of the correction factors to improve the model's accuracy varied geographically and across models. These results suggest that regional specific correction factors do not always adequately remove potential discrepancies between simulated and historically observed environmental parameters. As such, an explicit evaluation of the correction factors' effectiveness should be included in future studies of global climate change's impact on biological populations.« less

The Stochastic Human Exposure and Dose Simulation Model for Multimedia, Multipathway Chemicals: Dietary Module Version 1: Quick Start Guide, May 2012

EPA Pesticide Factsheets

SHEDS - Multimedia is EPA's premier physically-based, probabilistic model, that can simulate cumulative or aggregate exposures for a population across a variety of multimedia, multipathway environmental chemicals.

The Stochastic Human Exposure and Dose Simulation Model for Multimedia, Multipathway Chemicals: Residential Module Version 4: Quick Start Guide, April 2012

EPA Pesticide Factsheets

SHEDS - Multimedia is EPA's premier physically-based, probabilistic model, that can simulate cumulative or aggregate exposures for a population across a variety of multimedia, multipathway environmental chemicals.

Using HexSim to link demography and genetics in animal and plant simulations

EPA Science Inventory

Simulation models are essential for understanding the effects of land management practices and environmental drivers, including landscape change, shape population genetic structure and persistence probabilities. The emerging field of eco-evolutionary modeling is beginning to dev...

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...

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.

Sampling ARG of multiple populations under complex configurations of subdivision and admixture.

PubMed

Carrieri, Anna Paola; Utro, Filippo; Parida, Laxmi

2016-04-01

Simulating complex evolution scenarios of multiple populations is an important task for answering many basic questions relating to population genomics. Apart from the population samples, the underlying Ancestral Recombinations Graph (ARG) is an additional important means in hypothesis checking and reconstruction studies. Furthermore, complex simulations require a plethora of interdependent parameters making even the scenario-specification highly non-trivial. We present an algorithm SimRA that simulates generic multiple population evolution model with admixture. It is based on random graphs that improve dramatically in time and space requirements of the classical algorithm of single populations.Using the underlying random graphs model, we also derive closed forms of expected values of the ARG characteristics i.e., height of the graph, number of recombinations, number of mutations and population diversity in terms of its defining parameters. This is crucial in aiding the user to specify meaningful parameters for the complex scenario simulations, not through trial-and-error based on raw compute power but intelligent parameter estimation. To the best of our knowledge this is the first time closed form expressions have been computed for the ARG properties. We show that the expected values closely match the empirical values through simulations.Finally, we demonstrate that SimRA produces the ARG in compact forms without compromising any accuracy. We demonstrate the compactness and accuracy through extensive experiments. SimRA (Simulation based on Random graph Algorithms) source, executable, user manual and sample input-output sets are available for downloading at: https://github.com/ComputationalGenomics/SimRA CONTACT: : parida@us.ibm.com Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Impact of correlation of predictors on discrimination of risk models in development and external populations.

PubMed

Kundu, Suman; Mazumdar, Madhu; Ferket, Bart

2017-04-19

The area under the ROC curve (AUC) of risk models is known to be influenced by differences in case-mix and effect size of predictors. The impact of heterogeneity in correlation among predictors has however been under investigated. We sought to evaluate how correlation among predictors affects the AUC in development and external populations. We simulated hypothetical populations using two different methods based on means, standard deviations, and correlation of two continuous predictors. In the first approach, the distribution and correlation of predictors were assumed for the total population. In the second approach, these parameters were modeled conditional on disease status. In both approaches, multivariable logistic regression models were fitted to predict disease risk in individuals. Each risk model developed in a population was validated in the remaining populations to investigate external validity. For both approaches, we observed that the magnitude of the AUC in the development and external populations depends on the correlation among predictors. Lower AUCs were estimated in scenarios of both strong positive and negative correlation, depending on the direction of predictor effects and the simulation method. However, when adjusted effect sizes of predictors were specified in the opposite directions, increasingly negative correlation consistently improved the AUC. AUCs in external validation populations were higher or lower than in the derivation cohort, even in the presence of similar predictor effects. Discrimination of risk prediction models should be assessed in various external populations with different correlation structures to make better inferences about model generalizability.

75 FR 74073 - Endangered and Threatened Wildlife and Plants; Draft Revised Recovery Plan for the Northern...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-11-30

... population program HexSim. Though still at preliminary draft stage, population response simulations from this portion of the modeling process are available for public review by request from our office. These simulations do not estimate what will occur in the future, but provide comparative information on potential...

From innervation density to tactile acuity: 1. Spatial representation.

PubMed

Brown, Paul B; Koerber, H Richard; Millecchia, Ronald

2004-06-11

We tested the hypothesis that the population receptive field representation (a superposition of the excitatory receptive field areas of cells responding to a tactile stimulus) provides spatial information sufficient to mediate one measure of static tactile acuity. In psychophysical tests, two-point discrimination thresholds on the hindlimbs of adult cats varied as a function of stimulus location and orientation, as they do in humans. A statistical model of the excitatory low threshold mechanoreceptive fields of spinocervical, postsynaptic dorsal column and spinothalamic tract neurons was used to simulate the population receptive field representations in this neural population of the one- and two-point stimuli used in the psychophysical experiments. The simulated and observed thresholds were highly correlated. Simulated and observed thresholds' relations to physiological and anatomical variables such as stimulus location and orientation, receptive field size and shape, map scale, and innervation density were strikingly similar. Simulated and observed threshold variations with receptive field size and map scale obeyed simple relationships predicted by the signal detection model, and were statistically indistinguishable from each other. The population receptive field representation therefore contains information sufficient for this discrimination.

Exploring Population Admixture Dynamics via Empirical and Simulated Genome-wide Distribution of Ancestral Chromosomal Segments

PubMed Central

Jin, Wenfei; Wang, Sijia; Wang, Haifeng; Jin, Li; Xu, Shuhua

2012-01-01

The processes of genetic admixture determine the haplotype structure and linkage disequilibrium patterns of the admixed population, which is important for medical and evolutionary studies. However, most previous studies do not consider the inherent complexity of admixture processes. Here we proposed two approaches to explore population admixture dynamics, and we demonstrated, by analyzing genome-wide empirical and simulated data, that the approach based on the distribution of chromosomal segments of distinct ancestry (CSDAs) was more powerful than that based on the distribution of individual ancestry proportions. Analysis of 1,890 African Americans showed that a continuous gene flow model, in which the African American population continuously received gene flow from European populations over about 14 generations, best explained the admixture dynamics of African Americans among several putative models. Interestingly, we observed that some African Americans had much more European ancestry than the simulated samples, indicating substructures of local ancestries in African Americans that could have been caused by individuals from some particular lineages having repeatedly admixed with people of European ancestry. In contrast, the admixture dynamics of Mexicans could be explained by a gradual admixture model in which the Mexican population continuously received gene flow from both European and Amerindian populations over about 24 generations. Our results also indicated that recent gene flows from Sub-Saharan Africans have contributed to the gene pool of Middle Eastern populations such as Mozabite, Bedouin, and Palestinian. In summary, this study not only provides approaches to explore population admixture dynamics, but also advances our understanding on population history of African Americans, Mexicans, and Middle Eastern populations. PMID:23103229

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

Population and Activity of On-road Vehicles in MOVES2014 ...

EPA Pesticide Factsheets

This report describes the sources and derivation for on-road vehicle population and activity information and associated adjustments as stored in the MOVES2014 default databases. Motor Vehicle Emission Simulator, the MOVES2014 model, is a set of modeling tools for estimating emissions produced by on-road (cars, trucks, motorcycles, etc.) and nonroad (backhoes, lawnmowers, etc.) mobile sources. The national default activity information in MOVES2014 provides a reasonable basis for estimating national emissions. However, the uncertainties and variability in the default data contribute to the uncertainty in the resulting emission estimates. Properly characterizing emissions from the on-road vehicle subset requires a detailed understanding of the cars and trucks that make up the vehicle fleet and their patterns of operation. The MOVES model calculates emission inventories by multiplying emission rates by the appropriate emission-related activity, applying correction (adjustment) factors as needed to simulate specific situations, and then adding up the emissions from all sources (populations) and regions. This report describes the sources and derivation for on-road vehicle population and activity information and associated adjustments as stored in the MOVES2014 default databases. Motor Vehicle Emission Simulator, the MOVES2014 model, is a set of modeling tools for estimating emissions produced by on-road (cars, trucks, motorcycles, etc.) and nonroad (backhoes, law

Love Kills:. Simulations in Penna Ageing Model

NASA Astrophysics Data System (ADS)

Stauffer, Dietrich; Cebrat, Stanisław; Penna, T. J. P.; Sousa, A. O.

The standard Penna ageing model with sexual reproduction is enlarged by adding additional bit-strings for love: Marriage happens only if the male love strings are sufficiently different from the female ones. We simulate at what level of required difference the population dies out.

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...

Efficient coarse simulation of a growing avascular tumor

PubMed Central

Kavousanakis, Michail E.; Liu, Ping; Boudouvis, Andreas G.; Lowengrub, John; Kevrekidis, Ioannis G.

2013-01-01

The subject of this work is the development and implementation of algorithms which accelerate the simulation of early stage tumor growth models. Among the different computational approaches used for the simulation of tumor progression, discrete stochastic models (e.g., cellular automata) have been widely used to describe processes occurring at the cell and subcell scales (e.g., cell-cell interactions and signaling processes). To describe macroscopic characteristics (e.g., morphology) of growing tumors, large numbers of interacting cells must be simulated. However, the high computational demands of stochastic models make the simulation of large-scale systems impractical. Alternatively, continuum models, which can describe behavior at the tumor scale, often rely on phenomenological assumptions in place of rigorous upscaling of microscopic models. This limits their predictive power. In this work, we circumvent the derivation of closed macroscopic equations for the growing cancer cell populations; instead, we construct, based on the so-called “equation-free” framework, a computational superstructure, which wraps around the individual-based cell-level simulator and accelerates the computations required for the study of the long-time behavior of systems involving many interacting cells. The microscopic model, e.g., a cellular automaton, which simulates the evolution of cancer cell populations, is executed for relatively short time intervals, at the end of which coarse-scale information is obtained. These coarse variables evolve on slower time scales than each individual cell in the population, enabling the application of forward projection schemes, which extrapolate their values at later times. This technique is referred to as coarse projective integration. Increasing the ratio of projection times to microscopic simulator execution times enhances the computational savings. Crucial accuracy issues arising for growing tumors with radial symmetry are addressed by applying the coarse projective integration scheme in a cotraveling (cogrowing) frame. As a proof of principle, we demonstrate that the application of this scheme yields highly accurate solutions, while preserving the computational savings of coarse projective integration. PMID:22587128

Modeling Chagas Disease at Population Level to Explain Venezuela's Real Data

PubMed Central

González-Parra, Gilberto; Chen-Charpentier, Benito M.; Bermúdez, Moises

2015-01-01

Objectives In this paper we present an age-structured epidemiological model for Chagas disease. This model includes the interactions between human and vector populations that transmit Chagas disease. Methods The human population is divided into age groups since the proportion of infected individuals in this population changes with age as shown by real prevalence data. Moreover, the age-structured model allows more accurate information regarding the prevalence, which can help to design more specific control programs. We apply this proposed model to data from the country of Venezuela for two periods, 1961–1971, and 1961–1991 taking into account real demographic data for these periods. Results Numerical computer simulations are presented to show the suitability of the age-structured model to explain the real data regarding prevalence of Chagas disease in each of the age groups. In addition, a numerical simulation varying the death rate of the vector is done to illustrate prevention and control strategies against Chagas disease. Conclusion The proposed model can be used to determine the effect of control strategies in different age groups. PMID:26929912

Linear time algorithms to construct populations fitting multiple constraint distributions at genomic scales.

PubMed

Siragusa, Enrico; Haiminen, Niina; Utro, Filippo; Parida, Laxmi

2017-10-09

Computer simulations can be used to study population genetic methods, models and parameters, as well as to predict potential outcomes. For example, in plant populations, predicting the outcome of breeding operations can be studied using simulations. In-silico construction of populations with pre-specified characteristics is an important task in breeding optimization and other population genetic studies. We present two linear time Simulation using Best-fit Algorithms (SimBA) for two classes of problems where each co-fits two distributions: SimBA-LD fits linkage disequilibrium and minimum allele frequency distributions, while SimBA-hap fits founder-haplotype and polyploid allele dosage distributions. An incremental gap-filling version of previously introduced SimBA-LD is here demonstrated to accurately fit the target distributions, allowing efficient large scale simulations. SimBA-hap accuracy and efficiency is demonstrated by simulating tetraploid populations with varying numbers of founder haplotypes, we evaluate both a linear time greedy algoritm and an optimal solution based on mixed-integer programming. SimBA is available on http://researcher.watson.ibm.com/project/5669.

PopGen Fishbowl: A Free Online Simulation Model of Microevolutionary Processes

ERIC Educational Resources Information Center

Jones, Thomas C.; Laughlin, Thomas F.

2010-01-01

Natural selection and other components of evolutionary theory are known to be particularly challenging concepts for students to understand. To help illustrate these concepts, we developed a simulation model of microevolutionary processes. The model features all the components of Hardy-Weinberg theory, with population size, selection, gene flow,…

Development and Evaluation of a New Air Exchange Rate Algorithm for the Stochastic Human Exposure and Dose Simulation Model

EPA Science Inventory

between-home and between-city variability in residential pollutant infiltration. This is likely a result of differences in home ventilation, or air exchange rates (AER). The Stochastic Human Exposure and Dose Simulation (SHEDS) model is a population exposure model that uses a pro...

PM2.5 Population Exposure in New Delhi Using a Probabilistic Simulation Framework.

PubMed

Saraswat, Arvind; Kandlikar, Milind; Brauer, Michael; Srivastava, Arun

2016-03-15

This paper presents a Geographical Information System (GIS) based probabilistic simulation framework to estimate PM2.5 population exposure in New Delhi, India. The framework integrates PM2.5 output from spatiotemporal LUR models and trip distribution data using a Gravity model based on zonal data for population, employment and enrollment in educational institutions. Time-activity patterns were derived from a survey of randomly sampled individuals (n = 1012) and in-vehicle exposure was estimated using microenvironmental monitoring data based on field measurements. We simulated population exposure for three different scenarios to capture stay-at-home populations (Scenario 1), working population exposed to near-road concentrations during commutes (Scenario 2), and the working population exposed to on-road concentrations during commutes (Scenario 3). Simulated annual average levels of PM2.5 exposure across the entire city were very high, and particularly severe in the winter months: ∼200 μg m(-3) in November, roughly four times higher compared to the lower levels in the monsoon season. Mean annual exposures ranged from 109 μg m(-3) (IQR: 97-120 μg m(-3)) for Scenario 1, to 121 μg m(-3) (IQR: 110-131 μg m(-3)), and 125 μg m(-3) (IQR: 114-136 μ gm(-3)) for Scenarios 2 and 3 respectively. Ignoring the effects of mobility causes the average annual PM2.5 population exposure to be underestimated by only 11%.

Impact of different policies on unhealthy dietary behaviors in an urban adult population: an agent-based simulation model.

PubMed

Zhang, Donglan; Giabbanelli, Philippe J; Arah, Onyebuchi A; Zimmerman, Frederick J

2014-07-01

Unhealthy eating is a complex-system problem. We used agent-based modeling to examine the effects of different policies on unhealthy eating behaviors. We developed an agent-based simulation model to represent a synthetic population of adults in Pasadena, CA, and how they make dietary decisions. Data from the 2007 Food Attitudes and Behaviors Survey and other empirical studies were used to calibrate the parameters of the model. Simulations were performed to contrast the potential effects of various policies on the evolution of dietary decisions. Our model showed that a 20% increase in taxes on fast foods would lower the probability of fast-food consumption by 3 percentage points, whereas improving the visibility of positive social norms by 10%, either through community-based or mass-media campaigns, could improve the consumption of fruits and vegetables by 7 percentage points and lower fast-food consumption by 6 percentage points. Zoning policies had no significant impact. Interventions emphasizing healthy eating norms may be more effective than directly targeting food prices or regulating local food outlets. Agent-based modeling may be a useful tool for testing the population-level effects of various policies within complex systems.

[The history of development of evolutionary methods in St. Petersburg school of computer simulation in biology].

PubMed

Menshutkin, V V; Kazanskiĭ, A B; Levchenko, V F

2010-01-01

The history of rise and development of evolutionary methods in Saint Petersburg school of biological modelling is traced and analyzed. Some pioneering works in simulation of ecological and evolutionary processes, performed in St.-Petersburg school became an exemplary ones for many followers in Russia and abroad. The individual-based approach became the crucial point in the history of the school as an adequate instrument for construction of models of biological evolution. This approach is natural for simulation of the evolution of life-history parameters and adaptive processes in populations and communities. In some cases simulated evolutionary process was used for solving a reverse problem, i. e., for estimation of uncertain life-history parameters of population. Evolutionary computations is one more aspect of this approach application in great many fields. The problems and vistas of ecological and evolutionary modelling in general are discussed.

App Usage Factor: A Simple Metric to Compare the Population Impact of Mobile Medical Apps

PubMed Central

Wyatt, Jeremy C

2015-01-01

Background One factor when assessing the quality of mobile apps is quantifying the impact of a given app on a population. There is currently no metric which can be used to compare the population impact of a mobile app across different health care disciplines. Objective The objective of this study is to create a novel metric to characterize the impact of a mobile app on a population. Methods We developed the simple novel metric, app usage factor (AUF), defined as the logarithm of the product of the number of active users of a mobile app with the median number of daily uses of the app. The behavior of this metric was modeled using simulated modeling in Python, a general-purpose programming language. Three simulations were conducted to explore the temporal and numerical stability of our metric and a simulated app ecosystem model using a simulated dataset of 20,000 apps. Results Simulations confirmed the metric was stable between predicted usage limits and remained stable at extremes of these limits. Analysis of a simulated dataset of 20,000 apps calculated an average value for the app usage factor of 4.90 (SD 0.78). A temporal simulation showed that the metric remained stable over time and suitable limits for its use were identified. Conclusions A key component when assessing app risk and potential harm is understanding the potential population impact of each mobile app. Our metric has many potential uses for a wide range of stakeholders in the app ecosystem, including users, regulators, developers, and health care professionals. Furthermore, this metric forms part of the overall estimate of risk and potential for harm or benefit posed by a mobile medical app. We identify the merits and limitations of this metric, as well as potential avenues for future validation and research. PMID:26290093

AMBIENT PARTICULATE MATTER EXPOSURES: A COMPARISON OF SHEDS-PM EXPOSURE MODEL PREDICTIONS AND ESTIMATES DERIVED FROM MEASUREMENTS COLLECTED DURING NERL'S RTP PM PANEL STUDY

EPA Science Inventory

The US EPA National Exposure Research Laboratory (NERL) is currently refining and evaluating a population exposure model for particulate matter (PM), called the Stochastic Human Exposure and Dose Simulation (SHEDS-PM) model. The SHEDS-PM model estimates the population distribu...

Kinetic Model of Growth of Arthropoda Populations

NASA Astrophysics Data System (ADS)

Ershov, Yu. A.; Kuznetsov, M. A.

2018-05-01

Kinetic equations were derived for calculating the growth of crustacean populations ( Crustacea) based on the biological growth model suggested earlier using shrimp ( Caridea) populations as an example. The development cycle of successive stages for populations can be represented in the form of quasi-chemical equations. The kinetic equations that describe the development cycle of crustaceans allow quantitative prediction of the development of populations depending on conditions. In contrast to extrapolation-simulation models, in the developed kinetic model of biological growth the kinetic parameters are the experimental characteristics of population growth. Verification and parametric identification of the developed model on the basis of the experimental data showed agreement with experiment within the error of the measurement technique.

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

Agent-based modeling of malaria vectors: the importance of spatial simulation.

PubMed

Bomblies, Arne

2014-07-03

The modeling of malaria vector mosquito populations yields great insight into drivers of malaria transmission at the village scale. Simulation of individual mosquitoes as "agents" in a distributed, dynamic model domain may be greatly beneficial for simulation of spatial relationships of vectors and hosts. In this study, an agent-based model is used to simulate the life cycle and movement of individual malaria vector mosquitoes in a Niger Sahel village, with individual simulated mosquitoes interacting with their physical environment as well as humans. Various processes that are known to be epidemiologically important, such as the dependence of parity on flight distance between developmental habitat and blood meal hosts and therefore spatial relationships of pools and houses, are readily simulated using this modeling paradigm. Impacts of perturbations can be evaluated on the basis of vectorial capacity, because the interactions between individuals that make up the population- scale metric vectorial capacity can be easily tracked for simulated mosquitoes and human blood meal hosts, without the need to estimate vectorial capacity parameters. As expected, model results show pronounced impacts of pool source reduction from larvicide application and draining, but with varying degrees of impact depending on the spatial relationship between pools and human habitation. Results highlight the importance of spatially-explicit simulation that can model individuals such as in an agent-based model. The impacts of perturbations on village scale malaria transmission depend on spatial locations of individual mosquitoes, as well as the tracking of relevant life cycle events and characteristics of individual mosquitoes. This study demonstrates advantages of using an agent-based approach for village-scale mosquito simulation to address questions in which spatial relationships are known to be important.

Programming strategy for efficient modeling of dynamics in a population of heterogeneous cells.

PubMed

Hald, Bjørn Olav; Garkier Hendriksen, Morten; Sørensen, Preben Graae

2013-05-15

Heterogeneity is a ubiquitous property of biological systems. Even in a genetically identical population of a single cell type, cell-to-cell differences are observed. Although the functional behavior of a given population is generally robust, the consequences of heterogeneity are fairly unpredictable. In heterogeneous populations, synchronization of events becomes a cardinal problem-particularly for phase coherence in oscillating systems. The present article presents a novel strategy for construction of large-scale simulation programs of heterogeneous biological entities. The strategy is designed to be tractable, to handle heterogeneity and to handle computational cost issues simultaneously, primarily by writing a generator of the 'model to be simulated'. We apply the strategy to model glycolytic oscillations among thousands of yeast cells coupled through the extracellular medium. The usefulness is illustrated through (i) benchmarking, showing an almost linear relationship between model size and run time, and (ii) analysis of the resulting simulations, showing that contrary to the experimental situation, synchronous oscillations are surprisingly hard to achieve, underpinning the need for tools to study heterogeneity. Thus, we present an efficient strategy to model the biological heterogeneity, neglected by ordinary mean-field models. This tool is well posed to facilitate the elucidation of the physiologically vital problem of synchronization. The complete python code is available as Supplementary Information. bjornhald@gmail.com or pgs@kiku.dk Supplementary data are available at Bioinformatics online.

A new model for the multiple stellar populations within Terzan 5

NASA Astrophysics Data System (ADS)

McKenzie, M.; Bekki, K.

2018-06-01

Recent observational studies have demonstrated that the complex stellar system Terzan 5 (Ter 5) harbours multiple populations of stars. Several models have attempted to interpret the large age difference of several Gyrs between the dominant populations, but none have been universally accepted. We propose a new scenario whereby a collision between a metal-poor Ter 5 and a giant molecular cloud (GMC) serves as a catalyst for the generation of a super-solar population of stars. Using numerical simulations of this new "GC-GMC" collision scenario we demonstrate that, within a time frame of several Gyrs, our synthetic Ter 5 was capable of interacting with a metal-rich GMC in the central region of the Galaxy. As a consequence of this, our simulated globular cluster (GC) is able to capture enough gas from the colliding GMC to form a new population of metal-rich stars. Furthermore, the younger population created from the high-density regions of the captured gas is shown to have a stronger central mass concentration than the older metal-poor one, which is consistent with observations. A chemical link between Ter 5 and the bulge population of the Milky Way has long been observed and these simulations finally provide evidence for their similarities. Our model rationalises the 5 Gyrs of quiescence observed between the two dominant populations of Ter 5 and justifies the existence of the young generation. We discuss the advantages and disadvantages of the new scenario in the context of the observed physical properties of Ter 5.

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.

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.

Estimation of population size using open capture-recapture models

USGS Publications Warehouse

McDonald, T.L.; Amstrup, Steven C.

2001-01-01

One of the most important needs for wildlife managers is an accurate estimate of population size. Yet, for many species, including most marine species and large mammals, accurate and precise estimation of numbers is one of the most difficult of all research challenges. Open-population capture-recapture models have proven useful in many situations to estimate survival probabilities but typically have not been used to estimate population size. We show that open-population models can be used to estimate population size by developing a Horvitz-Thompson-type estimate of population size and an estimator of its variance. Our population size estimate keys on the probability of capture at each trap occasion and therefore is quite general and can be made a function of external covariates measured during the study. Here we define the estimator and investigate its bias, variance, and variance estimator via computer simulation. Computer simulations make extensive use of real data taken from a study of polar bears (Ursus maritimus) in the Beaufort Sea. The population size estimator is shown to be useful because it was negligibly biased in all situations studied. The variance estimator is shown to be useful in all situations, but caution is warranted in cases of extreme capture heterogeneity.

Stochastic Human Exposure and Dose Simulation for Air Toxics

EPA Science Inventory

The Stochastic Human Exposure and Dose Simulation model for Air Toxics (SHEDS-AirToxics) is a multimedia, multipathway population-based exposure and dose model for air toxics developed by the US EPA's National Exposure Research Laboratory (NERL). SHEDS-AirToxics uses a probabili...

SHEDS-PM: A POPULATION EXPOSURE MODEL FOR PREDICTING DISTRIBUTIONS OF PM EXPOSURE AND DOSE FROM BOTH OUTDOOR AND INDOOR SOURCES

EPA Science Inventory

The US EPA National Exposure Research Laboratory (NERL) has developed a population exposure and dose model for particulate matter (PM), called the Stochastic Human Exposure and Dose Simulation (SHEDS) model. SHEDS-PM uses a probabilistic approach that incorporates both variabi...

IMPLICATIONS OF SELECTING ALTERNATIVE EXPOSURE METRICS IN ANALYZING THE RELATIONSHIPS BETWEEN PM AND ACUTE MORTALITY AND MORBIDITY IN PHILADELPHIA

EPA Science Inventory

The US EPA National Exposure Research Laboratory (NERL) has developed a population exposure model for particulate matter (PM), called the Stochastic Human Exposure and Dose Simulation (SHEDS-PM) model. The SHEDS-PM model estimates the population distribution of PM exposures by...

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.

Modelling the competition of planktonic and sessile aerobic heterotrophs for complementary nutrients in biofilm reactor.

PubMed

Lu, T; Saikaly, P E; Oerther, D B

2007-01-01

A comprehensive, simplified microbial biofilm model was developed to evaluate the impact of bioreactor operating parameters on changes in microbial population abundance. Biofilm simulations were conducted using three special cases: fully penetrated, internal mass transfer resistance and external mass transfer resistance. The results of model simulations showed that for certain operating conditions, competition for growth limiting nutrients generated oscillations in the abundance of planktonic and sessile microbial populations. These oscillations resulted in the violation of the competitive exclusion principle where the number of microbial populations was greater than the number of growth limiting nutrients. However, the operating conditions which impacted microbial community diversity were different for the three special cases. Comparing the results of model simulations for dispersed-growth, biofilms and bioflocs showed that oscillations and microbial community diversity were a function of competition as well as other key features of the ecosystem. The significance of the current study is that it is the first to examine competition as a mechanism for controlling microbial community diversity in biofilm reactors.

Mathematical models for predicting human mobility in the context of infectious disease spread: introducing the impedance model.

PubMed

Sallah, Kankoé; Giorgi, Roch; Bengtsson, Linus; Lu, Xin; Wetter, Erik; Adrien, Paul; Rebaudet, Stanislas; Piarroux, Renaud; Gaudart, Jean

2017-11-22

Mathematical models of human mobility have demonstrated a great potential for infectious disease epidemiology in contexts of data scarcity. While the commonly used gravity model involves parameter tuning and is thus difficult to implement without reference data, the more recent radiation model based on population densities is parameter-free, but biased. In this study we introduce the new impedance model, by analogy with electricity. Previous research has compared models on the basis of a few specific available spatial patterns. In this study, we use a systematic simulation-based approach to assess the performances. Five hundred spatial patterns were generated using various area sizes and location coordinates. Model performances were evaluated based on these patterns. For simulated data, comparison measures were average root mean square error (aRMSE) and bias criteria. Modeling of the 2010 Haiti cholera epidemic with a basic susceptible-infected-recovered (SIR) framework allowed an empirical evaluation through assessing the goodness-of-fit of the observed epidemic curve. The new, parameter-free impedance model outperformed previous models on simulated data according to average aRMSE and bias criteria. The impedance model achieved better performances with heterogeneous population densities and small destination populations. As a proof of concept, the basic compartmental SIR framework was used to confirm the results obtained with the impedance model in predicting the spread of cholera in Haiti in 2010. The proposed new impedance model provides accurate estimations of human mobility, especially when the population distribution is highly heterogeneous. This model can therefore help to achieve more accurate predictions of disease spread in the context of an epidemic.

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...

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.

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 and Activity of On-road Vehicles in MOVES2014

EPA Science Inventory

This report describes the sources and derivation for on-road vehicle population and activity information and associated adjustments as stored in the MOVES2014 default databases. Motor Vehicle Emission Simulator, the MOVES2014 model, is a set of modeling tools for estimating emiss...

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;...

A generalised individual-based algorithm for modelling the evolution of quantitative herbicide resistance in arable weed populations.

PubMed

Liu, Chun; Bridges, Melissa E; Kaundun, Shiv S; Glasgow, Les; Owen, Micheal Dk; Neve, Paul

2017-02-01

Simulation models are useful tools for predicting and comparing the risk of herbicide resistance in weed populations under different management strategies. Most existing models assume a monogenic mechanism governing herbicide resistance evolution. However, growing evidence suggests that herbicide resistance is often inherited in a polygenic or quantitative fashion. Therefore, we constructed a generalised modelling framework to simulate the evolution of quantitative herbicide resistance in summer annual weeds. Real-field management parameters based on Amaranthus tuberculatus (Moq.) Sauer (syn. rudis) control with glyphosate and mesotrione in Midwestern US maize-soybean agroecosystems demonstrated that the model can represent evolved herbicide resistance in realistic timescales. Sensitivity analyses showed that genetic and management parameters were impactful on the rate of quantitative herbicide resistance evolution, whilst biological parameters such as emergence and seed bank mortality were less important. The simulation model provides a robust and widely applicable framework for predicting the evolution of quantitative herbicide resistance in summer annual weed populations. The sensitivity analyses identified weed characteristics that would favour herbicide resistance evolution, including high annual fecundity, large resistance phenotypic variance and pre-existing herbicide resistance. Implications for herbicide resistance management and potential use of the model are discussed. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

The impact of individual-level heterogeneity on estimated infectious disease burden: a simulation study.

PubMed

McDonald, Scott A; Devleesschauwer, Brecht; Wallinga, Jacco

2016-12-08

Disease burden is not evenly distributed within a population; this uneven distribution can be due to individual heterogeneity in progression rates between disease stages. Composite measures of disease burden that are based on disease progression models, such as the disability-adjusted life year (DALY), are widely used to quantify the current and future burden of infectious diseases. Our goal was to investigate to what extent ignoring the presence of heterogeneity could bias DALY computation. Simulations using individual-based models for hypothetical infectious diseases with short and long natural histories were run assuming either "population-averaged" progression probabilities between disease stages, or progression probabilities that were influenced by an a priori defined individual-level frailty (i.e., heterogeneity in disease risk) distribution, and DALYs were calculated. Under the assumption of heterogeneity in transition rates and increasing frailty with age, the short natural history disease model predicted 14% fewer DALYs compared with the homogenous population assumption. Simulations of a long natural history disease indicated that assuming homogeneity in transition rates when heterogeneity was present could overestimate total DALYs, in the present case by 4% (95% quantile interval: 1-8%). The consequences of ignoring population heterogeneity should be considered when defining transition parameters for natural history models and when interpreting the resulting disease burden estimates.

In silico evaluation of gadofosveset pharmacokinetics in different population groups using the Simcyp® simulator platform.

PubMed

Spanakis, Marios; Marias, Kostas

2014-12-01

Gadofosveset is a Gd-based contrast agent used for magnetic resonance imaging (MRI). Gadolinium kinetic distribution models are implemented in T1-weighted dynamic contrast-enhanced perfusion MRI for characterization of lesion sites in the body. Physiology changes in a disease state potentially can influence the pharmacokinetics of drugs and to this respect modify the distribution properties of contrast agents. This work focuses on the in silico modelling of pharmacokinetic properties of gadofosveset in different population groups through the application of physiologically-based pharmacokinetic models (PBPK) embedded in Simcyp® population pharmacokinetics platform. Physicochemical and pharmacokinetic properties of gadofosveset were introduced into Simcyp® simulator platform and a min-PBPK model was applied. In silico clinical trials were generated simulating the administration of the recommended dose for the contrast agent (i.v., 30 mg/kg) in population cohorts of healthy volunteers, obese, renal and liver impairment, and in a generated virtual oncology population. Results were evaluated regarding basic pharmacokinetic parameters of Cmax, AUC and systemic CL and differences were assessed through ANOVA and estimation of ratio of geometric mean between healthy volunteers and the other population groups. Simcyp® predicted a mean Cmax = 551.60 mg/l, a mean AUC = 4079.12 mg/L*h and a mean systemic CL = 0.56 L/h for the virtual population of healthy volunteers. Obese population showed a modulation in Cmax and CL, attributed to increased administered dose. In renal and liver impairment cohorts a significant modulation in Cmax, AUC and CL of gadofosveset is predicted. Oncology population exhibited statistical significant differences regarding AUC when compared with healthy volunteers. This work employed Simcyp® population pharmacokinetics platform in order to compute gadofosveset's pharmacokinetic profiles through PBPK models and in silico clinical trials and evaluate possible differences between population groups. The approach showed promising results that could provide new insights regarding administration of contrast agents in special population cohorts. In silico pharmacokinetics could further be used for evaluating of possible toxicity, interpretation of MRI PK image maps and development of novel contrast agents.

The threshold of a stochastic avian-human influenza epidemic model with psychological effect

NASA Astrophysics Data System (ADS)

Zhang, Fengrong; Zhang, Xinhong

2018-02-01

In this paper, a stochastic avian-human influenza epidemic model with psychological effect in human population and saturation effect within avian population is investigated. This model describes the transmission of avian influenza among avian population and human population in random environments. For stochastic avian-only system, persistence in the mean and extinction of the infected avian population are studied. For the avian-human influenza epidemic system, sufficient conditions for the existence of an ergodic stationary distribution are obtained. Furthermore, a threshold of this stochastic model which determines the outcome of the disease is obtained. Finally, numerical simulations are given to support the theoretical results.

Range Systems Simulation for the NASA Shuttle: Emphasis on Disaster and Prevention Management During Lift-Off

NASA Technical Reports Server (NTRS)

Rabelo, Lisa; Sepulveda, Jose; Moraga, Reinaldo; Compton, Jeppie; Turner, Robert

2005-01-01

This article describes a decision-making system composed of a number of safety and environmental models for the launch phase of a NASA Space Shuttle mission. The components of this distributed simulation environment represent the different systems that must collaborate to establish the Expectation of Casualties (E(sub c)) caused by a failed Space Shuttle launch and subsequent explosion (accidental or instructed) of the spacecraft shortly after liftoff. This decision-making tool employs Space Shuttle reliability models, trajectory models, a blast model, weather dissemination systems, population models, amount and type of toxicants, gas dispersion models, human response functions to toxicants, and a geographical information system. Since one of the important features of this proposed simulation environment is to measure blast, toxic, and debris effects, the clear benefits is that it can help safety managers not only estimate the population at risk, but also to help plan evacuations, make sheltering decisions, establish the resources required to provide aid and comfort, and mitigate damages in case of a disaster.

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,…

Developing a rich definition of the person/residence to support person-oriented models of consumer product usage

EPA Science Inventory

Person Oriented Models (POMs) provide a basis for simulating aggregate chemical exposures in a population over time (Price and Chaisson, 2005). POMs assign characteristics to simulated individuals that are used to determine the individual’s probability of interacting with e...

A Comparison of Normal and Elliptical Estimation Methods in Structural Equation Models.

ERIC Educational Resources Information Center

Schumacker, Randall E.; Cheevatanarak, Suchittra

Monte Carlo simulation compared chi-square statistics, parameter estimates, and root mean square error of approximation values using normal and elliptical estimation methods. Three research conditions were imposed on the simulated data: sample size, population contamination percent, and kurtosis. A Bentler-Weeks structural model established the…

A NEO population generation and observation simulation software tool

NASA Astrophysics Data System (ADS)

Müller, Sven; Gelhaus, Johannes; Hahn, Gerhard; Franco, Raffaella

One of the main targets of ESA's Space Situational Awareness (SSA) program is to build a wide knowledge base about objects that can potentially harm Earth (Near-Earth Objects, NEOs). An important part of this effort is to create the Small Bodies Data Centre (SBDC) which is going to aggregate measurement data from a fully-integrated NEO observation sensor network. Until this network is developed, artificial NEO measurement data is needed in order to validate SBDC algorithms. Moreover, to establish a functioning NEO observation sensor network, it has to be determined where to place sensors, what technical requirements have to be met in order to be able to detect NEOs and which observation strategies work the best. Because of this, a sensor simulation software was needed. This paper presents a software tool which allows users to create and analyse NEO populations and to simulate and analyse population observations. It is a console program written in Fortran and comes with a Graphical User Interface (GUI) written in Java and C. The tool can be distinguished into the components ``Population Generator'' and ``Observation Simulator''. The Population Generator component is responsible for generating and analysing a NEO population. Users can choose between creating fictitious (random) and synthetic populations. The latter are based on one of two models describing the orbital and size distribution of observed NEOs: The existing socalled ``Bottke Model'' (Bottke et al. 2000, 2002) and the new ``Granvik Model'' (Granvik et al. 2014, in preparation) which has been developed in parallel to the tool. Generated populations can be analysed by defining 2D, 3D and scatter plots using various NEO attributes. As a result, the tool creates the appropiate files for the plotting tool ``gnuplot''. The tool's Observation Simulator component yields the Observation Simulation and Observation Analysis functions. Users can define sensor systems using ground- or space-based locations as well as optical or radar sensors and simulate observation campaigns. The tool outputs field-of-view crossings and actual detections of the selected NEO population objects. Using the Observation Analysis users are able to process and plot the results of the Observation Simulation. In order to enable end-users to handle the tool in a user-intuitive and comfortable way, a GUI has been created based on the modular Eclipse Rich Client Platform (RCP) technology. Through the GUI users can easily enter input data for the tool, execute it and view its output data in a clear way. Additionally, the GUI runs gnuplot to create plot pictures and presents them to the user. Furthermore, users can create projects to organise executions of the tool.

skelesim: an extensible, general framework for population genetic simulation in R.

PubMed

Parobek, Christian M; Archer, Frederick I; DePrenger-Levin, Michelle E; Hoban, Sean M; Liggins, Libby; Strand, Allan E

2017-01-01

Simulations are a key tool in molecular ecology for inference and forecasting, as well as for evaluating new methods. Due to growing computational power and a diversity of software with different capabilities, simulations are becoming increasingly powerful and useful. However, the widespread use of simulations by geneticists and ecologists is hindered by difficulties in understanding these softwares' complex capabilities, composing code and input files, a daunting bioinformatics barrier and a steep conceptual learning curve. skelesim (an R package) guides users in choosing appropriate simulations, setting parameters, calculating genetic summary statistics and organizing data output, in a reproducible pipeline within the R environment. skelesim is designed to be an extensible framework that can 'wrap' around any simulation software (inside or outside the R environment) and be extended to calculate and graph any genetic summary statistics. Currently, skelesim implements coalescent and forward-time models available in the fastsimcoal2 and rmetasim simulation engines to produce null distributions for multiple population genetic statistics and marker types, under a variety of demographic conditions. skelesim is intended to make simulations easier while still allowing full model complexity to ensure that simulations play a fundamental role in molecular ecology investigations. skelesim can also serve as a teaching tool: demonstrating the outcomes of stochastic population genetic processes; teaching general concepts of simulations; and providing an introduction to the R environment with a user-friendly graphical user interface (using shiny). © 2016 John Wiley & Sons Ltd.

skeleSim: an extensible, general framework for population genetic simulation in R

PubMed Central

Parobek, Christian M.; Archer, Frederick I.; DePrenger-Levin, Michelle E.; Hoban, Sean M.; Liggins, Libby; Strand, Allan E.

2016-01-01

Simulations are a key tool in molecular ecology for inference and forecasting, as well as for evaluating new methods. Due to growing computational power and a diversity of software with different capabilities, simulations are becoming increasingly powerful and useful. However, the widespread use of simulations by geneticists and ecologists is hindered by difficulties in understanding these softwares’ complex capabilities, composing code and input files, a daunting bioinformatics barrier, and a steep conceptual learning curve. skeleSim (an R package) guides users in choosing appropriate simulations, setting parameters, calculating genetic summary statistics, and organizing data output, in a reproducible pipeline within the R environment. skeleSim is designed to be an extensible framework that can ‘wrap’ around any simulation software (inside or outside the R environment) and be extended to calculate and graph any genetic summary statistics. Currently, skeleSim implements coalescent and forward-time models available in the fastsimcoal2 and rmetasim simulation engines to produce null distributions for multiple population genetic statistics and marker types, under a variety of demographic conditions. skeleSim is intended to make simulations easier while still allowing full model complexity to ensure that simulations play a fundamental role in molecular ecology investigations. skeleSim can also serve as a teaching tool: demonstrating the outcomes of stochastic population genetic processes; teaching general concepts of simulations; and providing an introduction to the R environment with a user-friendly graphical user interface (using shiny). PMID:27736016

Integrating data from multiple sources for insights into demographic processes: Simulation studies and proof of concept for hierarchical change-in-ratio models.

PubMed

Nilsen, Erlend B; Strand, Olav

2018-01-01

We developed a model for estimating demographic rates and population abundance based on multiple data sets revealing information about population age- and sex structure. Such models have previously been described in the literature as change-in-ratio models, but we extend the applicability of the models by i) using time series data allowing the full temporal dynamics to be modelled, by ii) casting the model in an explicit hierarchical modelling framework, and by iii) estimating parameters based on Bayesian inference. Based on sensitivity analyses we conclude that the approach developed here is able to obtain estimates of demographic rate with high precision whenever unbiased data of population structure are available. Our simulations revealed that this was true also when data on population abundance are not available or not included in the modelling framework. Nevertheless, when data on population structure are biased due to different observability of different age- and sex categories this will affect estimates of all demographic rates. Estimates of population size is particularly sensitive to such biases, whereas demographic rates can be relatively precisely estimated even with biased observation data as long as the bias is not severe. We then use the models to estimate demographic rates and population abundance for two Norwegian reindeer (Rangifer tarandus) populations where age-sex data were available for all harvested animals, and where population structure surveys were carried out in early summer (after calving) and late fall (after hunting season), and population size is counted in winter. We found that demographic rates were similar regardless whether we include population count data in the modelling, but that the estimated population size is affected by this decision. This suggest that monitoring programs that focus on population age- and sex structure will benefit from collecting additional data that allow estimation of observability for different age- and sex classes. In addition, our sensitivity analysis suggests that focusing monitoring towards changes in demographic rates might be more feasible than monitoring abundance in many situations where data on population age- and sex structure can be collected.

Development and validation of a generic finite element vehicle buck model for the analysis of driver rib fractures in real life nearside oblique frontal crashes.

PubMed

Iraeus, Johan; Lindquist, Mats

2016-10-01

Frontal crashes still account for approximately half of all fatalities in passenger cars, despite several decades of crash-related research. For serious injuries in this crash mode, several authors have listed the thorax as the most important. Computer simulation provides an effective tool to study crashes and evaluate injury mechanisms, and using stochastic input data, whole populations of crashes can be studied. The aim of this study was to develop a generic buck model and to validate this model on a population of real-life frontal crashes in terms of the risk of rib fracture. The study was conducted in four phases. In the first phase, real-life validation data were derived by analyzing NASS/CDS data to find the relationship between injury risk and crash parameters. In addition, available statistical distributions for the parameters were collected. In the second phase, a generic parameterized finite element (FE) model of a vehicle interior was developed based on laser scans from the A2MAC1 database. In the third phase, model parameters that could not be found in the literature were estimated using reverse engineering based on NCAP tests. Finally, in the fourth phase, the stochastic FE model was used to simulate a population of real-life crashes, and the result was compared to the validation data from phase one. The stochastic FE simulation model overestimates the risk of rib fracture, more for young occupants and less for senior occupants. However, if the effect of underestimation of rib fractures in the NASS/CDS material is accounted for using statistical simulations, the risk of rib fracture based on the stochastic FE model matches the risk based on the NASS/CDS data for senior occupants. The current version of the stochastic model can be used to evaluate new safety measures using a population of frontal crashes for senior occupants. Copyright © 2016 Elsevier Ltd. All rights reserved.

A dental public health approach based on computational mathematics: Monte Carlo simulation of childhood dental decay.

PubMed

Tennant, Marc; Kruger, Estie

2013-02-01

This study developed a Monte Carlo simulation approach to examining the prevalence and incidence of dental decay using Australian children as a test environment. Monte Carlo simulation has been used for a half a century in particle physics (and elsewhere); put simply, it is the probability for various population-level outcomes seeded randomly to drive the production of individual level data. A total of five runs of the simulation model for all 275,000 12-year-olds in Australia were completed based on 2005-2006 data. Measured on average decayed/missing/filled teeth (DMFT) and DMFT of highest 10% of sample (Sic10) the runs did not differ from each other by more than 2% and the outcome was within 5% of the reported sampled population data. The simulations rested on the population probabilities that are known to be strongly linked to dental decay, namely, socio-economic status and Indigenous heritage. Testing the simulated population found DMFT of all cases where DMFT<>0 was 2.3 (n = 128,609) and DMFT for Indigenous cases only was 1.9 (n = 13,749). In the simulation population the Sic25 was 3.3 (n = 68,750). Monte Carlo simulations were created in particle physics as a computational mathematical approach to unknown individual-level effects by resting a simulation on known population-level probabilities. In this study a Monte Carlo simulation approach to childhood dental decay was built, tested and validated. © 2013 FDI World Dental Federation.

Uncertainty in age-specific harvest estimates and consequences for white-tailed deer management

USGS Publications Warehouse

Collier, B.A.; Krementz, D.G.

2007-01-01

Age structure proportions (proportion of harvested individuals within each age class) are commonly used as support for regulatory restrictions and input for deer population models. Such use requires critical evaluation when harvest regulations force hunters to selectively harvest specific age classes, due to impact on the underlying population age structure. We used a stochastic population simulation model to evaluate the impact of using harvest proportions to evaluate changes in population age structure under a selective harvest management program at two scales. Using harvest proportions to parameterize the age-specific harvest segment of the model for the local scale showed that predictions of post-harvest age structure did not vary dependent upon whether selective harvest criteria were in use or not. At the county scale, yearling frequency in the post-harvest population increased, but model predictions indicated that post-harvest population size of 2.5 years old males would decline below levels found before implementation of the antler restriction, reducing the number of individuals recruited into older age classes. Across the range of age-specific harvest rates modeled, our simulation predicted that underestimation of age-specific harvest rates has considerable influence on predictions of post-harvest population age structure. We found that the consequence of uncertainty in harvest rates corresponds to uncertainty in predictions of residual population structure, and this correspondence is proportional to scale. Our simulations also indicate that regardless of use of harvest proportions or harvest rates, at either the local or county scale the modeled SHC had a high probability (>0.60 and >0.75, respectively) of eliminating recruitment into >2.5 years old age classes. Although frequently used to increase population age structure, our modeling indicated that selective harvest criteria can decrease or eliminate the number of white-tailed deer recruited into older age classes. Thus, we suggest that using harvest proportions for management planning and evaluation should be viewed with caution. In addition, we recommend that managers focus more attention on estimation of age-specific harvest rates, and modeling approaches which combine harvest rates with information from harvested individuals to further increase their ability to effectively manage deer populations under selective harvest programs. ?? 2006 Elsevier B.V. All rights reserved.

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)

APPLICATION OF ELASTICITY ANALYSES AND PERTURBATION SIMULATIONS IN DETERMINING STRESSOR IMPACTS ON POPULATION GROWTH RATE AND EXTINCTION RISK

EPA Science Inventory

Population structure and life history strategies are determinants of how populations respond to stressor-induced impairments in individual-level responses, but a consistent and holistic analysis has not been reported. Effects on population growth rate were modeled using five theo...

APPLICATION OF PERTURBATION SIMULATIONS IN POPULATION RISK ASSESSMENT FOR DIFFERENT LIFE HISTORY STRATEGIES AND ELASTICITY PATTERNS

EPA Science Inventory

Population structure and life history strategies are determinants of how populations respond to stressor-induced impairments in organism-level responses, but a consistent and holistic analysis has not been reported. Effects on population growth rate were modeled using seven theor...

Ancestral haplotype-based association mapping with generalized linear mixed models accounting for stratification.

PubMed

Zhang, Z; Guillaume, F; Sartelet, A; Charlier, C; Georges, M; Farnir, F; Druet, T

2012-10-01

In many situations, genome-wide association studies are performed in populations presenting stratification. Mixed models including a kinship matrix accounting for genetic relatedness among individuals have been shown to correct for population and/or family structure. Here we extend this methodology to generalized linear mixed models which properly model data under various distributions. In addition we perform association with ancestral haplotypes inferred using a hidden Markov model. The method was shown to properly account for stratification under various simulated scenari presenting population and/or family structure. Use of ancestral haplotypes resulted in higher power than SNPs on simulated datasets. Application to real data demonstrates the usefulness of the developed model. Full analysis of a dataset with 4600 individuals and 500 000 SNPs was performed in 2 h 36 min and required 2.28 Gb of RAM. The software GLASCOW can be freely downloaded from www.giga.ulg.ac.be/jcms/prod_381171/software. francois.guillaume@jouy.inra.fr Supplementary data are available at Bioinformatics online.

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).

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.

IMPACT: a generic tool for modelling and simulating public health policy.

PubMed

Ainsworth, J D; Carruthers, E; Couch, P; Green, N; O'Flaherty, M; Sperrin, M; Williams, R; Asghar, Z; Capewell, S; Buchan, I E

2011-01-01

Populations are under-served by local health policies and management of resources. This partly reflects a lack of realistically complex models to enable appraisal of a wide range of potential options. Rising computing power coupled with advances in machine learning and healthcare information now enables such models to be constructed and executed. However, such models are not generally accessible to public health practitioners who often lack the requisite technical knowledge or skills. To design and develop a system for creating, executing and analysing the results of simulated public health and healthcare policy interventions, in ways that are accessible and usable by modellers and policy-makers. The system requirements were captured and analysed in parallel with the statistical method development for the simulation engine. From the resulting software requirement specification the system architecture was designed, implemented and tested. A model for Coronary Heart Disease (CHD) was created and validated against empirical data. The system was successfully used to create and validate the CHD model. The initial validation results show concordance between the simulation results and the empirical data. We have demonstrated the ability to connect health policy-modellers and policy-makers in a unified system, thereby making population health models easier to share, maintain, reuse and deploy.

Automatic training and reliability estimation for 3D ASM applied to cardiac MRI segmentation

NASA Astrophysics Data System (ADS)

Tobon-Gomez, Catalina; Sukno, Federico M.; Butakoff, Constantine; Huguet, Marina; Frangi, Alejandro F.

2012-07-01

Training active shape models requires collecting manual ground-truth meshes in a large image database. While shape information can be reused across multiple imaging modalities, intensity information needs to be imaging modality and protocol specific. In this context, this study has two main purposes: (1) to test the potential of using intensity models learned from MRI simulated datasets and (2) to test the potential of including a measure of reliability during the matching process to increase robustness. We used a population of 400 virtual subjects (XCAT phantom), and two clinical populations of 40 and 45 subjects. Virtual subjects were used to generate simulated datasets (MRISIM simulator). Intensity models were trained both on simulated and real datasets. The trained models were used to segment the left ventricle (LV) and right ventricle (RV) from real datasets. Segmentations were also obtained with and without reliability information. Performance was evaluated with point-to-surface and volume errors. Simulated intensity models obtained average accuracy comparable to inter-observer variability for LV segmentation. The inclusion of reliability information reduced volume errors in hypertrophic patients (EF errors from 17 ± 57% to 10 ± 18% LV MASS errors from -27 ± 22 g to -14 ± 25 g), and in heart failure patients (EF errors from -8 ± 42% to -5 ± 14%). The RV model of the simulated images needs further improvement to better resemble image intensities around the myocardial edges. Both for real and simulated models, reliability information increased segmentation robustness without penalizing accuracy.

Automatic training and reliability estimation for 3D ASM applied to cardiac MRI segmentation.

PubMed

Tobon-Gomez, Catalina; Sukno, Federico M; Butakoff, Constantine; Huguet, Marina; Frangi, Alejandro F

2012-07-07

Training active shape models requires collecting manual ground-truth meshes in a large image database. While shape information can be reused across multiple imaging modalities, intensity information needs to be imaging modality and protocol specific. In this context, this study has two main purposes: (1) to test the potential of using intensity models learned from MRI simulated datasets and (2) to test the potential of including a measure of reliability during the matching process to increase robustness. We used a population of 400 virtual subjects (XCAT phantom), and two clinical populations of 40 and 45 subjects. Virtual subjects were used to generate simulated datasets (MRISIM simulator). Intensity models were trained both on simulated and real datasets. The trained models were used to segment the left ventricle (LV) and right ventricle (RV) from real datasets. Segmentations were also obtained with and without reliability information. Performance was evaluated with point-to-surface and volume errors. Simulated intensity models obtained average accuracy comparable to inter-observer variability for LV segmentation. The inclusion of reliability information reduced volume errors in hypertrophic patients (EF errors from 17 ± 57% to 10 ± 18%; LV MASS errors from -27 ± 22 g to -14 ± 25 g), and in heart failure patients (EF errors from -8 ± 42% to -5 ± 14%). The RV model of the simulated images needs further improvement to better resemble image intensities around the myocardial edges. Both for real and simulated models, reliability information increased segmentation robustness without penalizing accuracy.

How Obstacles Perturb Population Fronts and Alter Their Genetic Structure.

PubMed

Möbius, Wolfram; Murray, Andrew W; Nelson, David R

2015-12-01

As populations spread into new territory, environmental heterogeneities can shape the population front and genetic composition. We focus here on the effects of an important building block of heterogeneous environments, isolated obstacles. With a combination of experiments, theory, and simulation, we show how isolated obstacles both create long-lived distortions of the front shape and amplify the effect of genetic drift. A system of bacteriophage T7 spreading on a spatially heterogeneous Escherichia coli lawn serves as an experimental model system to study population expansions. Using an inkjet printer, we create well-defined replicates of the lawn and quantitatively study the population expansion of phage T7. The transient perturbations of the population front found in the experiments are well described by a model in which the front moves with constant speed. Independent of the precise details of the expansion, we show that obstacles create a kink in the front that persists over large distances and is insensitive to the details of the obstacle's shape. The small deviations between experimental findings and the predictions of the constant speed model can be understood with a more general reaction-diffusion model, which reduces to the constant speed model when the obstacle size is large compared to the front width. Using this framework, we demonstrate that frontier genotypes just grazing the side of an isolated obstacle increase in abundance, a phenomenon we call 'geometry-enhanced genetic drift', complementary to the founder effect associated with spatial bottlenecks. Bacterial range expansions around nutrient-poor barriers and stochastic simulations confirm this prediction. The effect of the obstacle on the genealogy of individuals at the front is characterized by simulations and rationalized using the constant speed model. Lastly, we consider the effect of two obstacles on front shape and genetic composition of the population illuminating the effects expected from complex environments with many obstacles.

How Obstacles Perturb Population Fronts and Alter Their Genetic Structure

PubMed Central

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

2015-01-01

As populations spread into new territory, environmental heterogeneities can shape the population front and genetic composition. We focus here on the effects of an important building block of heterogeneous environments, isolated obstacles. With a combination of experiments, theory, and simulation, we show how isolated obstacles both create long-lived distortions of the front shape and amplify the effect of genetic drift. A system of bacteriophage T7 spreading on a spatially heterogeneous Escherichia coli lawn serves as an experimental model system to study population expansions. Using an inkjet printer, we create well-defined replicates of the lawn and quantitatively study the population expansion of phage T7. The transient perturbations of the population front found in the experiments are well described by a model in which the front moves with constant speed. Independent of the precise details of the expansion, we show that obstacles create a kink in the front that persists over large distances and is insensitive to the details of the obstacle’s shape. The small deviations between experimental findings and the predictions of the constant speed model can be understood with a more general reaction-diffusion model, which reduces to the constant speed model when the obstacle size is large compared to the front width. Using this framework, we demonstrate that frontier genotypes just grazing the side of an isolated obstacle increase in abundance, a phenomenon we call ‘geometry-enhanced genetic drift’, complementary to the founder effect associated with spatial bottlenecks. Bacterial range expansions around nutrient-poor barriers and stochastic simulations confirm this prediction. The effect of the obstacle on the genealogy of individuals at the front is characterized by simulations and rationalized using the constant speed model. Lastly, we consider the effect of two obstacles on front shape and genetic composition of the population illuminating the effects expected from complex environments with many obstacles. PMID:26696601

Oak habitat recovery on California's largest islands: Scenarios for the role of corvid seed dispersal

USGS Publications Warehouse

Pesendorfer, Mario B.; Baker, Christopher M.; Stringer, Martin; McDonald-Madden, Eve; Bode, Michael; McEachern, A. Kathryn; Morrison, Scott A.; Sillett, T. Scott

2018-01-01

Seed dispersal by birds is central to the passive restoration of many tree communities. Reintroduction of extinct seed dispersers can therefore restore degraded forests and woodlands. To test this, we constructed a spatially explicit simulation model, parameterized with field data, to consider the effect of different seed dispersal scenarios on the extent of oak populations. We applied the model to two islands in California's Channel Islands National Park (USA), one of which has lost a key seed disperser.We used an ensemble modelling approach to simulate island scrub oak (Quercus pacifica) demography. The model was developed and trained to recreate known population changes over a 20-year period on 250-km2 Santa Cruz Island, and incorporated acorn dispersal by island scrub-jays (Aphelocoma insularis), deer mice (Peromyscus maniculatus) and gravity, as well as seed predation. We applied the trained model to 215-km2 Santa Rosa Island to examine how reintroducing island scrub-jays would affect the rate and pattern of oak population expansion. Oak habitat on Santa Rosa Island has been greatly reduced from its historical extent due to past grazing by introduced ungulates, the last of which were removed by 2011.Our simulation model predicts that a seed dispersal scenario including island scrub-jays would increase the extent of the island scrub oak population on Santa Rosa Island by 281% over 100 years, and by 544% over 200 years. Scenarios without jays would result in little expansion. Simulated long-distance seed dispersal by jays also facilitates establishment of discontinuous patches of oaks, and increases their elevational distribution.Synthesis and applications. Scenario planning provides powerful decision support for conservation managers. We used ensemble modelling of plant demographic and seed dispersal processes to investigate whether the reintroduction of seed dispersers could provide cost-effective means of achieving broader ecosystem restoration goals on California's second-largest island. The simulation model, extensively parameterized with field data, suggests that re-establishing the mutualism with seed-hoarding jays would accelerate the expansion of island scrub oak, which could benefit myriad species of conservation concern.

SU-E-T-565: RAdiation Resistance of Cancer CElls Using GEANT4 DNA: RACE

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

Perrot, Y; Payno, H; Delage, E

2014-06-01

Purpose: The objective of the RACE project is to develop a comparison between Monte Carlo simulation using the Geant4-DNA toolkit and measurements of radiation damage on 3D melanoma and chondrosarcoma culture cells coupled with gadolinium nanoparticles. We currently expose the status of the developments regarding simulations. Methods: Monte Carlo studies are driven using the Geant4 toolkit and the Geant4-DNA extension. In order to model the geometry of a cell population, the opensource CPOP++ program is being developed for the geometrical representation of 3D cell populations including a specific cell mesh coupled with a multi-agent system. Each cell includes cytoplasm andmore » nucleus. The correct modeling of the cell population has been validated with confocal microscopy images of spheroids. The Geant4 Livermore physics models are used to simulate the interactions of a 250 keV X-ray beam and the production of secondaries from gadolinium nanoparticles supposed to be fixed on the cell membranes. Geant4-DNA processes are used to simulate the interactions of charged particles with the cells. An atomistic description of the DNA molecule, from PDB (Protein Data Bank) files, is provided by the so-called PDB4DNA Geant4 user application we developed to score energy depositions in DNA base pairs and sugar-phosphate groups. Results: At the microscopic level, our simulations enable assessing microscopic energy distribution in each cell compartment of a realistic 3D cell population. Dose enhancement factors due to the presence of gadolinium nanoparticles can be estimated. At the nanometer scale, direct damages on nuclear DNA are also estimated. Conclusion: We successfully simulated the impact of direct radiations on a realistic 3D cell population model compatible with microdosimetry calculations using the Geant4-DNA toolkit. Upcoming validation and the future integration of the radiochemistry module of Geant4-DNA will propose to correlate clusters of ionizations with in vitro experiments. All those developments will be released publicly. This work was supported by grants from Plan Cancer 2009-2013 French national initiative managed by INSERM (Institut National de la Sante et de la Recherche Medicale)« less

Effects of uncertainty and variability on population declines and IUCN Red List classifications.

PubMed

Rueda-Cediel, Pamela; Anderson, Kurt E; Regan, Tracey J; Regan, Helen M

2018-01-22

The International Union for Conservation of Nature (IUCN) Red List Categories and Criteria is a quantitative framework for classifying species according to extinction risk. Population models may be used to estimate extinction risk or population declines. Uncertainty and variability arise in threat classifications through measurement and process error in empirical data and uncertainty in the models used to estimate extinction risk and population declines. Furthermore, species traits are known to affect extinction risk. We investigated the effects of measurement and process error, model type, population growth rate, and age at first reproduction on the reliability of risk classifications based on projected population declines on IUCN Red List classifications. We used an age-structured population model to simulate true population trajectories with different growth rates, reproductive ages and levels of variation, and subjected them to measurement error. We evaluated the ability of scalar and matrix models parameterized with these simulated time series to accurately capture the IUCN Red List classification generated with true population declines. Under all levels of measurement error tested and low process error, classifications were reasonably accurate; scalar and matrix models yielded roughly the same rate of misclassifications, but the distribution of errors differed; matrix models led to greater overestimation of extinction risk than underestimations; process error tended to contribute to misclassifications to a greater extent than measurement error; and more misclassifications occurred for fast, rather than slow, life histories. These results indicate that classifications of highly threatened taxa (i.e., taxa with low growth rates) under criterion A are more likely to be reliable than for less threatened taxa when assessed with population models. Greater scrutiny needs to be placed on data used to parameterize population models for species with high growth rates, particularly when available evidence indicates a potential transition to higher risk categories. © 2018 Society for Conservation Biology.

Psychological effect on single-species population models in a polluted environment.

PubMed

Wei, Fengying; Chen, Lihong

2017-08-01

We formulate and investigate the psychological effect of single-species population models in a polluted environment in this paper. For the deterministic single-species population model, the conditions that guarantee the local extinction and persistence in the mean are derived firstly. We then show that, around the pollution-free equilibrium, the stochastic single-species population is weakly persistent in the mean, and is stochastically permanent under some conditions. As a consequence, some numerical simulations demonstrate the efficiency of the main results. Copyright © 2017 Elsevier Inc. All rights reserved.

Impact of Different Policies on Unhealthy Dietary Behaviors in an Urban Adult Population: An Agent-Based Simulation Model

PubMed Central

Giabbanelli, Philippe J.; Arah, Onyebuchi A.; Zimmerman, Frederick J.

2014-01-01

Objectives. Unhealthy eating is a complex-system problem. We used agent-based modeling to examine the effects of different policies on unhealthy eating behaviors. Methods. We developed an agent-based simulation model to represent a synthetic population of adults in Pasadena, CA, and how they make dietary decisions. Data from the 2007 Food Attitudes and Behaviors Survey and other empirical studies were used to calibrate the parameters of the model. Simulations were performed to contrast the potential effects of various policies on the evolution of dietary decisions. Results. Our model showed that a 20% increase in taxes on fast foods would lower the probability of fast-food consumption by 3 percentage points, whereas improving the visibility of positive social norms by 10%, either through community-based or mass-media campaigns, could improve the consumption of fruits and vegetables by 7 percentage points and lower fast-food consumption by 6 percentage points. Zoning policies had no significant impact. Conclusions. Interventions emphasizing healthy eating norms may be more effective than directly targeting food prices or regulating local food outlets. Agent-based modeling may be a useful tool for testing the population-level effects of various policies within complex systems. PMID:24832414

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.

Dr. Tulp attends the soft machine: patient simulators, user involvement and intellectual disability.

PubMed

McClimens, Alex; Lewis, Robin; Brewster, Jacqui

2012-09-01

Simulation as a way to teach clinical skills attracts much critical attention. Its benefits, however, might be significantly reduced when the simulation model used relies exclusively on patient simulators. This is particularly true if the intended patient population for students taught is characterized by intellectual disability. Learning to care for people with intellectual disability might be better supplemented when the simulation model used incorporates input from 'real' people. If these people themselves have intellectual disabilities then the verisimilitude of the simulation will be higher and the outcomes for learners and potential patients will also be improved.

A Comparison of Grizzly Bear Demographic Parameters Estimated from Non-Spatial and Spatial Open Population Capture-Recapture Models.

PubMed

Whittington, Jesse; Sawaya, Michael A

2015-01-01

Capture-recapture studies are frequently used to monitor the status and trends of wildlife populations. Detection histories from individual animals are used to estimate probability of detection and abundance or density. The accuracy of abundance and density estimates depends on the ability to model factors affecting detection probability. Non-spatial capture-recapture models have recently evolved into spatial capture-recapture models that directly include the effect of distances between an animal's home range centre and trap locations on detection probability. Most studies comparing non-spatial and spatial capture-recapture biases focussed on single year models and no studies have compared the accuracy of demographic parameter estimates from open population models. We applied open population non-spatial and spatial capture-recapture models to three years of grizzly bear DNA-based data from Banff National Park and simulated data sets. The two models produced similar estimates of grizzly bear apparent survival, per capita recruitment, and population growth rates but the spatial capture-recapture models had better fit. Simulations showed that spatial capture-recapture models produced more accurate parameter estimates with better credible interval coverage than non-spatial capture-recapture models. Non-spatial capture-recapture models produced negatively biased estimates of apparent survival and positively biased estimates of per capita recruitment. The spatial capture-recapture grizzly bear population growth rates and 95% highest posterior density averaged across the three years were 0.925 (0.786-1.071) for females, 0.844 (0.703-0.975) for males, and 0.882 (0.779-0.981) for females and males combined. The non-spatial capture-recapture population growth rates were 0.894 (0.758-1.024) for females, 0.825 (0.700-0.948) for males, and 0.863 (0.771-0.957) for both sexes. The combination of low densities, low reproductive rates, and predominantly negative population growth rates suggest that Banff National Park's population of grizzly bears requires continued conservation-oriented management actions.

InterSpread Plus: a spatial and stochastic simulation model of disease in animal populations.

PubMed

Stevenson, M A; Sanson, R L; Stern, M W; O'Leary, B D; Sujau, M; Moles-Benfell, N; Morris, R S

2013-04-01

We describe the spatially explicit, stochastic simulation model of disease spread, InterSpread Plus, in terms of its epidemiological framework, operation, and mode of use. The input data required by the model, the method for simulating contact and infection spread, and methods for simulating disease control measures are described. Data and parameters that are essential for disease simulation modelling using InterSpread Plus are distinguished from those that are non-essential, and it is suggested that a rational approach to simulating disease epidemics using this tool is to start with core data and parameters, adding additional layers of complexity if and when the specific requirements of the simulation exercise require it. We recommend that simulation models of disease are best developed as part of epidemic contingency planning so decision makers are familiar with model outputs and assumptions and are well-positioned to evaluate their strengths and weaknesses to make informed decisions in times of crisis. Copyright © 2012 Elsevier B.V. All rights reserved.

Revisiting node-based SIR models in complex networks with degree correlations

NASA Astrophysics Data System (ADS)

Wang, Yi; Cao, Jinde; Alofi, Abdulaziz; AL-Mazrooei, Abdullah; Elaiw, Ahmed

2015-11-01

In this paper, we consider two growing networks which will lead to the degree-degree correlations between two nearest neighbors in the network. When the network grows to some certain size, we introduce an SIR-like disease such as pandemic influenza H1N1/09 to the population. Due to its rapid spread, the population size changes slowly, and thus the disease spreads on correlated networks with approximately fixed size. To predict the disease evolution on correlated networks, we first review two node-based SIR models incorporating degree correlations and an edge-based SIR model without considering degree correlation, and then compare the predictions of these models with stochastic SIR simulations, respectively. We find that the edge-based model, even without considering degree correlations, agrees much better than the node-based models incorporating degree correlations with stochastic SIR simulations in many respects. Moreover, simulation results show that for networks with positive correlation, the edge-based model provides a better upper bound of the cumulative incidence than the node-based SIR models, whereas for networks with negative correlation, it provides a lower bound of the cumulative incidence.

Forecasting and evaluating patterns of energy development in southwestern Wyoming

USGS Publications Warehouse

Garman, Steven L.

2015-01-01

The effects of future oil and natural gas development in southwestern Wyoming on wildlife populations are topical to conservation of the sagebrush steppe ecosystem. To aid in understanding these potential effects, the U.S. Geological Survey developed an Energy Footprint simulation model that forecasts the amount and pattern of energy development under different assumptions of development rates and well-drilling methods. The simulated disturbance patterns produced by the footprint model are used to assess the potential effects on wildlife habitat and populations. A goal of this modeling effort is to use measures of energy production (number of simulated wells), well-pad and road-surface disturbance, and potential effects on wildlife to identify build-out designs that minimize the physical and ecological footprint of energy development for different levels of energy production and development costs.

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.

Estimation of effectiveness of three methods of feral cat population control by use of a simulation model.

PubMed

McCarthy, Robert J; Levine, Stephen H; Reed, J Michael

2013-08-15

To predict effectiveness of 3 interventional methods of population control for feral cat colonies. Population model. Estimates of vital data for feral cats. Data were gathered from the literature regarding the demography and mating behavior of feral cats. An individual-based stochastic simulation model was developed to evaluate the effectiveness of trap-neuter-release (TNR), lethal control, and trap-vasectomy-hysterectomy-release (TVHR) in decreasing the size of feral cat populations. TVHR outperformed both TNR and lethal control at all annual capture probabilities between 10% and 90%. Unless > 57% of cats were captured and neutered annually by TNR or removed by lethal control, there was minimal effect on population size. In contrast, with an annual capture rate of ≥ 35%, TVHR caused population size to decrease. An annual capture rate of 57% eliminated the modeled population in 4,000 days by use of TVHR, whereas > 82% was required for both TNR and lethal control. When the effect of fraction of adult cats neutered on kitten and young juvenile survival rate was included in the analysis, TNR performed progressively worse and could be counterproductive, such that population size increased, compared with no intervention at all. TVHR should be preferred over TNR for management of feral cats if decrease in population size is the goal. This model allowed for many factors related to the trapping program and cats to be varied and should be useful for determining the financial and person-effort commitments required to have a desired effect on a given feral cat population.

Simulation of Micron-Sized Debris Populations in Low Earth Orbit

NASA Technical Reports Server (NTRS)

Xu, Y.-L.; Hyde, J. L.; Prior, T.; Matney, Mark

2010-01-01

The update of ORDEM2000, the NASA Orbital Debris Engineering Model, to its new version ORDEM2010, is nearly complete. As a part of the ORDEM upgrade, this paper addresses the simulation of micro-debris (greater than 10 m and smaller than 1 mm in size) populations in low Earth orbit. The principal data used in the modeling of the micron-sized debris populations are in-situ hypervelocity impact records, accumulated in post-flight damage surveys on the space-exposed surfaces of returned spacecrafts. The development of the micro-debris model populations follows the general approach to deriving other ORDEM2010-required input populations for various components and types of debris. This paper describes the key elements and major steps in the statistical inference of the ORDEM2010 micro-debris populations. A crucial step is the construction of a degradation/ejecta source model to provide prior information on the micron-sized objects (such as orbital and object-size distributions). Another critical step is to link model populations with data, which is rather involved. It demands detailed information on area-time/directionality for all the space-exposed elements of a shuttle orbiter and damage laws, which relate impact damage with the physical properties of a projectile and impact conditions such as impact angle and velocity. Also needed are model-predicted debris fluxes as a function of object size and impact velocity from all possible directions. In spite of the very limited quantity of the available shuttle impact data, the population-derivation process is satisfactorily stable. Final modeling results obtained from shuttle window and radiator impact data are reasonably convergent and consistent, especially for the debris populations with object-size thresholds at 10 and 100 m.

Simulation of Micron-Sized Debris Populations in Low Earth Orbit

NASA Technical Reports Server (NTRS)

Xu, Y.-L.; Matney, M.; Liou, J.-C.; Hyde, J. L.; Prior, T. G.

2010-01-01

The update of ORDEM2000, the NASA Orbital Debris Engineering Model, to its new version . ORDEM2010, is nearly complete. As a part of the ORDEM upgrade, this paper addresses the simulation of micro-debris (greater than 10 micron and smaller than 1 mm in size) populations in low Earth orbit. The principal data used in the modeling of the micron-sized debris populations are in-situ hypervelocity impact records, accumulated in post-flight damage surveys on the space-exposed surfaces of returned spacecrafts. The development of the micro-debris model populations follows the general approach to deriving other ORDEM2010-required input populations for various components and types of debris. This paper describes the key elements and major steps in the statistical inference of the ORDEM2010 micro-debris populations. A crucial step is the construction of a degradation/ejecta source model to provide prior information on the micron-sized objects (such as orbital and object-size distributions). Another critical step is to link model populations with data, which is rather involved. It demands detailed information on area-time/directionality for all the space-exposed elements of a shuttle orbiter and damage laws, which relate impact damage with the physical properties of a projectile and impact conditions such as impact angle and velocity. Also needed are model-predicted debris fluxes as a function of object size and impact velocity from all possible directions. In spite of the very limited quantity of the available shuttle impact data, the population-derivation process is satisfactorily stable. Final modeling results obtained from shuttle window and radiator impact data are reasonably convergent and consistent, especially for the debris populations with object-size thresholds at 10 and 100 micron.

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

Dynamics of climate-based malaria transmission model with age-structured human population

NASA Astrophysics Data System (ADS)

Addawe, Joel; Pajimola, Aprimelle Kris

2016-10-01

In this paper, we proposed to study the dynamics of malaria transmission with periodic birth rate of the vector and an age-structure for the human population. The human population is divided into two compartments: pre-school (0-5 years) and the rest of the human population. We showed the existence of a disease-free equilibrium point. Using published epidemiological parameters, we use numerical simulations to show potential effect of climate change in the dynamics of age-structured malaria transmission. Numerical simulations suggest that there exists an asymptotically attractive solution that is positive and periodic.

CFD-PBM coupled simulation of a nanobubble generator with honeycomb structure

NASA Astrophysics Data System (ADS)

Ren, F.; Noda, N. A.; Ueda, T.; Sano, Y.; Takase, Y.; Umekage, T.; Yonezawa, Y.; Tanaka, H.

2018-06-01

In recent years, nanobubble technologies have drawn great attention due to their wide applications in many fields of science and technology. The nitrogen nanobubble water circulation can be used to slow the progressions of oxidation and spoilage for the seafood long- term storage. From previous studies, a kind of honeycomb structure for high-efficiency nanobubble generation has been proposed. In this paper, the bubbly flow in the honeycomb structure was studied. The numerical simulations of honeycomb structure were performed by using a computational fluid dynamics–population balance model (CFD-PBM) coupled model. The numerical model was based on the Eulerian multiphase model and the population balance model (PBM) was used to calculate the gas bubble size distribution. The bubble coalescence and breakage were included. Considering the effect of bubble diameter on the fluid flow, the phase interactions were coupled with the PBM. The bubble size distributions in the honeycomb structure under different work conditions were predicted. The experimental results were compared with the simulation predictions.

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.

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.

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.

The Hydrology of Malaria: Model Development and Application to a Sahelian Village

NASA Astrophysics Data System (ADS)

Bomblies, A.; Duchemin, J.; Eltahir, E. A.

2008-12-01

We present a coupled hydrology and entomology model for the mechanistic simulation of local-scale response of malaria transmission to hydrological and climatological determinants in semi-arid, desert fringe environments. The model is applied to the Sahel village of Banizoumbou, Niger, to predict interannual variability in malaria vector mosquito populations which lead to variations in malaria transmission. Using a high-resolution, small-scale distributed hydrology model that incorporates remotely-sensed data for land cover and topography, we simulate the formation and persistence of the pools constituting the primary breeding habitat of Anopheles gambiae s.l. mosquitoes, the principal regional malaria vector mosquitoes. An agent-based mosquito population model is coupled to the distributed hydrology model, with aquatic stage and adult stage components. For each individual adult mosquito, the model tracks attributes relevant to population dynamics and malaria transmission, which are updated as mosquitoes interact with their environment, humans, and animals. Weekly field observations were made in 2005 and 2006. The model reproduces mosquito population variability at seasonal and interannual time scales, and highlights individual pool persistence as a dominant control. Future developments to the presented model can be used in the evaluation of impacts of climate change on malaria, as well as the a priori evaluation of environmental management-based interventions.

Holliday Junction Thermodynamics and Structure: Coarse-Grained Simulations and Experiments

NASA Astrophysics Data System (ADS)

Wang, Wujie; Nocka, Laura M.; Wiemann, Brianne Z.; Hinckley, Daniel M.; Mukerji, Ishita; Starr, Francis W.

2016-03-01

Holliday junctions play a central role in genetic recombination, DNA repair and other cellular processes. We combine simulations and experiments to evaluate the ability of the 3SPN.2 model, a coarse-grained representation designed to mimic B-DNA, to predict the properties of DNA Holliday junctions. The model reproduces many experimentally determined aspects of junction structure and stability, including the temperature dependence of melting on salt concentration, the bias between open and stacked conformations, the relative populations of conformers at high salt concentration, and the inter-duplex angle (IDA) between arms. We also obtain a close correspondence between the junction structure evaluated by all-atom and coarse-grained simulations. We predict that, for salt concentrations at physiological and higher levels, the populations of the stacked conformers are independent of salt concentration, and directly observe proposed tetrahedral intermediate sub-states implicated in conformational transitions. Our findings demonstrate that the 3SPN.2 model captures junction properties that are inaccessible to all-atom studies, opening the possibility to simulate complex aspects of junction behavior.

Ca-Pri a Cellular Automata Phenomenological Research Investigation: Simulation Results

NASA Astrophysics Data System (ADS)

Iannone, G.; Troisi, A.

2013-05-01

Following the introduction of a phenomenological cellular automata (CA) model capable to reproduce city growth and urban sprawl, we develop a toy model simulation considering a realistic framework. The main characteristic of our approach is an evolution algorithm based on inhabitants preferences. The control of grown cells is obtained by means of suitable functions which depend on the initial condition of the simulation. New born urban settlements are achieved by means of a logistic evolution of the urban pattern while urban sprawl is controlled by means of the population evolution function. In order to compare model results with a realistic urban framework we have considered, as the area of study, the island of Capri (Italy) in the Mediterranean Sea. Two different phases of the urban evolution on the island have been taken into account: a new born initial growth as induced by geographic suitability and the simulation of urban spread after 1943 induced by the population evolution after this date.

Computer simulation models of pre-diabetes populations: a systematic review protocol

PubMed Central

Khurshid, Waqar; Pagano, Eva; Feenstra, Talitha

2017-01-01

Introduction Diabetes is a major public health problem and prediabetes (intermediate hyperglycaemia) is associated with a high risk of developing diabetes. With evidence supporting the use of preventive interventions for prediabetes populations and the discovery of novel biomarkers stratifying the risk of progression, there is a need to evaluate their cost-effectiveness across jurisdictions. In diabetes and prediabetes, it is relevant to inform cost-effectiveness analysis using decision models due to their ability to forecast long-term health outcomes and costs beyond the time frame of clinical trials. To support good implementation and reimbursement decisions of interventions in these populations, models should be clinically credible, based on best available evidence, reproducible and validated against clinical data. Our aim is to identify recent studies on computer simulation models and model-based economic evaluations of populations of individuals with prediabetes, qualify them and discuss the knowledge gaps, challenges and opportunities that need to be addressed for future evaluations. Methods and analysis A systematic review will be conducted in MEDLINE, Embase, EconLit and National Health Service Economic Evaluation Database. We will extract peer-reviewed studies published between 2000 and 2016 that describe computer simulation models of the natural history of individuals with prediabetes and/or decision models to evaluate the impact of interventions, risk stratification and/or screening on these populations. Two reviewers will independently assess each study for inclusion. Data will be extracted using a predefined pro forma developed using best practice. Study quality will be assessed using a modelling checklist. A narrative synthesis of all studies will be presented, focussing on model structure, quality of models and input data, and validation status. Ethics and dissemination This systematic review is exempt from ethics approval because the work is carried out on published documents. The findings of the review will be disseminated in a related peer-reviewed journal and presented at conferences. Reviewregistration number CRD42016047228. PMID:28982807

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

Simultaneous population pharmacokinetic modelling of plasma and intracellular PBMC miltefosine concentrations in New World cutaneous leishmaniasis and exploration of exposure-response relationships.

PubMed

Kip, Anke E; Castro, María Del Mar; Gomez, Maria Adelaida; Cossio, Alexandra; Schellens, Jan H M; Beijnen, Jos H; Saravia, Nancy Gore; Dorlo, Thomas P C

2018-05-10

Leishmania parasites reside within macrophages and the direct target of antileishmanial drugs is therefore intracellular. We aimed to characterize the intracellular PBMC miltefosine kinetics by developing a population pharmacokinetic (PK) model simultaneously describing plasma and intracellular PBMC pharmacokinetics. Furthermore, we explored exposure-response relationships and simulated alternative dosing regimens. A population PK model was developed with NONMEM, based on 339 plasma and 194 PBMC miltefosine concentrations from Colombian cutaneous leishmaniasis patients [29 children (2-12 years old) and 22 adults] receiving 1.8-2.5 mg/kg/day miltefosine for 28 days. A three-compartment model with miltefosine distribution into an intracellular PBMC effect compartment best fitted the data. Intracellular PBMC distribution was described with an intracellular-to-plasma concentration ratio of 2.17 [relative standard error (RSE) 4.9%] and intracellular distribution rate constant of 1.23 day-1 (RSE 14%). In exploring exposure-response relationships, both plasma and intracellular model-based exposure estimates significantly influenced probability of cure. A proposed PK target for the area under the plasma concentration-time curve (day 0-28) of >535 mg·day/L corresponded to >95% probability of cure. In linear dosing simulations, 18.3% of children compared with 2.8% of adults failed to reach 535 mg·day/L. In children, this decreased to 1.8% after allometric dosing simulation. The developed population PK model described the rate and extent of miltefosine distribution from plasma into PBMCs. Miltefosine exposure was significantly related to probability of cure in this cutaneous leishmaniasis patient population. We propose an exploratory PK target, which should be validated in a larger cohort study.

Development and validation of a new population-based simulation model of osteoarthritis in New Zealand.

PubMed

Wilson, R; Abbott, J H

2018-04-01

To describe the construction and preliminary validation of a new population-based microsimulation model developed to analyse the health and economic burden and cost-effectiveness of treatments for knee osteoarthritis (OA) in New Zealand (NZ). We developed the New Zealand Management of Osteoarthritis (NZ-MOA) model, a discrete-time state-transition microsimulation model of the natural history of radiographic knee OA. In this article, we report on the model structure, derivation of input data, validation of baseline model parameters against external data sources, and validation of model outputs by comparison of the predicted population health loss with previous estimates. The NZ-MOA model simulates both the structural progression of radiographic knee OA and the stochastic development of multiple disease symptoms. Input parameters were sourced from NZ population-based data where possible, and from international sources where NZ-specific data were not available. The predicted distributions of structural OA severity and health utility detriments associated with OA were externally validated against other sources of evidence, and uncertainty resulting from key input parameters was quantified. The resulting lifetime and current population health-loss burden was consistent with estimates of previous studies. The new NZ-MOA model provides reliable estimates of the health loss associated with knee OA in the NZ population. The model structure is suitable for analysis of the effects of a range of potential treatments, and will be used in future work to evaluate the cost-effectiveness of recommended interventions within the NZ healthcare system. Copyright © 2018 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

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.

Integrating the simulation of domestic water demand behaviour to an urban water model using agent based modelling

NASA Astrophysics Data System (ADS)

Koutiva, Ifigeneia; Makropoulos, Christos

2015-04-01

The urban water system's sustainable evolution requires tools that can analyse and simulate the complete cycle including both physical and cultural environments. One of the main challenges, in this regard, is the design and development of tools that are able to simulate the society's water demand behaviour and the way policy measures affect it. The effects of these policy measures are a function of personal opinions that subsequently lead to the formation of people's attitudes. These attitudes will eventually form behaviours. This work presents the design of an ABM tool for addressing the social dimension of the urban water system. The created tool, called Urban Water Agents' Behaviour (UWAB) model, was implemented, using the NetLogo agent programming language. The main aim of the UWAB model is to capture the effects of policies and environmental pressures to water conservation behaviour of urban households. The model consists of agents representing urban households that are linked to each other creating a social network that influences the water conservation behaviour of its members. Household agents are influenced as well by policies and environmental pressures, such as drought. The UWAB model simulates behaviour resulting in the evolution of water conservation within an urban population. The final outcome of the model is the evolution of the distribution of different conservation levels (no, low, high) to the selected urban population. In addition, UWAB is implemented in combination with an existing urban water management simulation tool, the Urban Water Optioneering Tool (UWOT) in order to create a modelling platform aiming to facilitate an adaptive approach of water resources management. For the purposes of this proposed modelling platform, UWOT is used in a twofold manner: (1) to simulate domestic water demand evolution and (2) to simulate the response of the water system to the domestic water demand evolution. The main advantage of the UWAB - UWOT model integration is that it allows the investigation of the effects of different water demand management strategies to an urban population's water demand behaviour and ultimately the effects of these policies to the volume of domestic water demand and the water resources system. The proposed modelling platform is optimised to simulate the effects of water policies during the Athens drought period of 1988-1994. The calibrated modelling platform is then applied to evaluate scenarios of water supply, water demand and water demand management strategies.

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.

Simulation of C. elegans thermotactic behavior in a linear thermal gradient using a simple phenomenological motility model.

PubMed

Matsuoka, Tomohiro; Gomi, Sohei; Shingai, Ryuzo

2008-01-21

The nematode Caenorhabditis elegans has been reported to exhibit thermotaxis, a sophisticated behavioral response to temperature. However, there appears to be some inconsistency among previous reports. The results of population-level thermotaxis investigations suggest that C. elegans can navigate to the region of its cultivation temperature from nearby regions of higher or lower temperature. However, individual C. elegans nematodes appear to show only cryophilic tendencies above their cultivation temperature. A Monte-Carlo style simulation using a simple individual model of C. elegans provides insight into clarifying apparent inconsistencies among previous findings. The simulation using the thermotaxis model that includes the cryophilic tendencies, isothermal tracking and thermal adaptation was conducted. As a result of the random walk property of locomotion of C. elegans, only cryophilic tendencies above the cultivation temperature result in population-level thermophilic tendencies. Isothermal tracking, a period of active pursuit of an isotherm around regions of temperature near prior cultivation temperature, can strengthen the tendencies of these worms to gather around near-cultivation-temperature regions. A statistical index, the thermotaxis (TTX) L-skewness, was introduced and was useful in analyzing the population-level thermotaxis of model worms.

Bias correction factors for near-Earth asteroids

NASA Technical Reports Server (NTRS)

Benedix, Gretchen K.; Mcfadden, Lucy Ann; Morrow, Esther M.; Fomenkova, Marina N.

1992-01-01

Knowledge of the population size and physical characteristics (albedo, size, and rotation rate) of near-Earth asteroids (NEA's) is biased by observational selection effects which are functions of the population's intrinsic properties and the size of the telescope, detector sensitivity, and search strategy used. The NEA population is modeled in terms of orbital and physical elements: a, e, i, omega, Omega, M, albedo, and diameter, and an asteroid search program is simulated using actual telescope pointings of right ascension, declination, date, and time. The position of each object in the model population is calculated at the date and time of each telescope pointing. The program tests to see if that object is within the field of view (FOV = 8.75 degrees) of the telescope and above the limiting magnitude (V = +1.65) of the film. The effect of the starting population on the outcome of the simulation's discoveries is compared to the actual discoveries in order to define a most probable starting population.

An examination of problem-based teaching and learning in population genetics and evolution using EVOLVE, a computer simulation

NASA Astrophysics Data System (ADS)

Soderberg, Patti; Price, Frank

2003-01-01

This study describes a lesson in which students engaged in inquiry in evolutionary biology in order to develop a better understanding of the concepts and reasoning skills necessary to support knowledge claims about changes in the genetic structure of populations, also known as microevolution. This paper describes how a software simulation called EVOLVE can be used to foster discussions about the conceptual knowledge used by advanced secondary or introductory college students when investigating the effects of natural selection on hypothetical populations over time. An experienced professor's use and rationale of a problem-based lesson using the simulation is examined. Examples of student misconceptions and naïve (incomplete) conceptions are described and an analysis of the procedural knowledge for experimenting with the computer model is provided. The results of this case study provide a model of how EVOLVE can be used to engage students in a complex problem-solving experience that encourages student meta-cognitive reflection about their understanding of evolution at the population level. Implications for teaching are provided and ways to improve student learning and problem solving in population genetics are suggested.

A Universe of ultradiffuse galaxies: theoretical predictions from ΛCDM simulations

NASA Astrophysics Data System (ADS)

Rong, Yu; Guo, Qi; Gao, Liang; Liao, Shihong; Xie, Lizhi; Puzia, Thomas H.; Sun, Shuangpeng; Pan, Jun

2017-10-01

A particular population of galaxies have drawn much interest recently, which are as faint as typical dwarf galaxies but have the sizes as large as L* galaxies, the so called ultradiffuse galaxies (UDGs). The lack of tidal features of UDGs in dense environments suggests that their host haloes are perhaps as massive as that of the Milky Way. On the other hand, galaxy formation efficiency should be much higher in the haloes of such masses. Here, we use the model galaxy catalogue generated by populating two large simulations: the Millennium-II cosmological simulation and Phoenix simulations of nine big clusters with the semi-analytic galaxy formation model. This model reproduces remarkably well the observed properties of UDGs in the nearby clusters, including the abundance, profile, colour and morphology, etc. We search for UDG candidates using the public data and find two UDG candidates in our Local Group and 23 in our Local Volume, in excellent agreement with the model predictions. We demonstrate that UDGs are genuine dwarf galaxies, formed in the haloes of ˜1010 M⊙. It is the combination of the late formation time and high spins of the host haloes that results in the spatially extended feature of this particular population. The lack of tidal disruption features of UDGs in clusters can also be explained by their late infall-time.

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.

Transition to an aging Japan: public pension, savings, and capital taxation.

PubMed

Kato, R

1998-09-01

This study examined options for compensating for the shortages of money for public pensions due to population aging in Japan: increases in pension contributions, consumption pension taxes, interest income pension taxes, and inheritance pension taxes. The analysis relied on simulation in an expanded life cycle growth model. Data were obtained from 1992 estimations of population by the Institute of Population Problems of the Ministry of Health and Welfare. This study is unique in its use of real population data for the simulations and in its use of transition states. The analysis begins with a description of the altered Overlapping Generations Model by Auerback and Kotlikoff (1983). The model accounts for the inaccuracy of lifetime and liquidity constraints and ordinary budget constraints and reproduces the consumption-savings profiles of older people and incorporates wage income taxation and other forms of taxation. Income includes wage and interest income. The analysis includes a description of the method of simulation, assumptions, and evaluation of the effects of population aging. It is assumed that narrower government sector spending on general expenditures per worker will increase by 1% every year. It is concluded that national saving rates will probably decrease due to population aging. The lowest levels of capital stock and savings will result from higher pension contributions. The highest level of capital stock will result from higher consumption pension taxes during 1990-2015. Preferred policies should focus on increasing interest income rates.

Cancer heterogeneity and multilayer spatial evolutionary games.

PubMed

Świerniak, Andrzej; Krześlak, Michał

2016-10-13

Evolutionary game theory (EGT) has been widely used to simulate tumour processes. In almost all studies on EGT models analysis is limited to two or three phenotypes. Our model contains four main phenotypes. Moreover, in a standard approach only heterogeneity of populations is studied, while cancer cells remain homogeneous. A multilayer approach proposed in this paper enables to study heterogeneity of single cells. In the extended model presented in this paper we consider four strategies (phenotypes) that can arise by mutations. We propose multilayer spatial evolutionary games (MSEG) played on multiple 2D lattices corresponding to the possible phenotypes. It enables simulation and investigation of heterogeneity on the player-level in addition to the population-level. Moreover, it allows to model interactions between arbitrary many phenotypes resulting from the mixture of basic traits. Different equilibrium points and scenarios (monomorphic and polymorphic populations) have been achieved depending on model parameters and the type of played game. However, there is a possibility of stable quadromorphic population in MSEG games for the same set of parameters like for the mean-field game. The model assumes an existence of four possible phenotypes (strategies) in the population of cells that make up tumour. Various parameters and relations between cells lead to complex analysis of this model and give diverse results. One of them is a possibility of stable coexistence of different tumour cells within the population, representing almost arbitrary mixture of the basic phenotypes. This article was reviewed by Tomasz Lipniacki, Urszula Ledzewicz and Jacek Banasiak.

A brucellosis disease control strategy for the Kakheti region of the country of Georgia: an agent-based model.

PubMed

Havas, K A; Boone, R B; Hill, A E; Salman, M D

2014-06-01

Brucellosis has been reported in livestock and humans in the country of Georgia with Brucella melitensis as the most common species causing disease. Georgia lacked sufficient data to assess effectiveness of the various potential control measures utilizing a reliable population-based simulation model of animal-to-human transmission of this infection. Therefore, an agent-based model was built using data from previous studies to evaluate the effect of an animal-level infection control programme on human incidence and sheep flock and cattle herd prevalence of brucellosis in the Kakheti region of Georgia. This model simulated the patterns of interaction of human-animal workers, sheep flocks and cattle herds with various infection control measures and returned population-based data. The model simulates the use of control measures needed for herd and flock prevalence to fall below 2%. As per the model output, shepherds had the greatest disease reduction as a result of the infection control programme. Cattle had the greatest influence on the incidence of human disease. Control strategies should include all susceptible animal species, sheep and cattle, identify the species of brucellosis present in the cattle population and should be conducted at the municipality level. This approach can be considered as a model to other countries and regions when assessment of control strategies is needed but data are scattered. © 2013 Blackwell Verlag GmbH.

A Parallel Sliding Region Algorithm to Make Agent-Based Modeling Possible for a Large-Scale Simulation: Modeling Hepatitis C Epidemics in Canada.

PubMed

Wong, William W L; Feng, Zeny Z; Thein, Hla-Hla

2016-11-01

Agent-based models (ABMs) are computer simulation models that define interactions among agents and simulate emergent behaviors that arise from the ensemble of local decisions. ABMs have been increasingly used to examine trends in infectious disease epidemiology. However, the main limitation of ABMs is the high computational cost for a large-scale simulation. To improve the computational efficiency for large-scale ABM simulations, we built a parallelizable sliding region algorithm (SRA) for ABM and compared it to a nonparallelizable ABM. We developed a complex agent network and performed two simulations to model hepatitis C epidemics based on the real demographic data from Saskatchewan, Canada. The first simulation used the SRA that processed on each postal code subregion subsequently. The second simulation processed the entire population simultaneously. It was concluded that the parallelizable SRA showed computational time saving with comparable results in a province-wide simulation. Using the same method, SRA can be generalized for performing a country-wide simulation. Thus, this parallel algorithm enables the possibility of using ABM for large-scale simulation with limited computational resources.

The Dauer Mutation of the Caenorhabditis Elegans, Simulated with the Penna and the Stauffer Models

NASA Astrophysics Data System (ADS)

Colonius, Kerstin

Two aging models were analyzed on whether they can confirm the dauer mutation of the nematode helps to preserve the species. As a result the Penna model shows that populations with dauer larvae survive bad environmental conditions, whereas populations without it die out. In the Stauffer model, the advantage of the dauer mutation for the survival is only given under certain conditions.

Recombination enhances HIV-1 envelope diversity by facilitating the survival of latent genomic fragments in the plasma virus population

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

Immonen, Taina T.; Conway, Jessica M.; Romero-Severson, Ethan O.

HIV-1 is subject to immune pressure exerted by the host, giving variants that escape the immune response an advantage. Virus released from activated latent cells competes against variants that have continually evolved and adapted to host immune pressure. Nevertheless, there is increasing evidence that virus displaying a signal of latency survives in patient plasma despite having reduced fitness due to long-term immune memory. We investigated the survival of virus with latent envelope genomic fragments by simulating within-host HIV-1 sequence evolution and the cycling of viral lineages in and out of the latent reservoir. Our model incorporates a detailed mutation processmore » including nucleotide substitution, recombination, latent reservoir dynamics, diversifying selection pressure driven by the immune response, and purifying selection pressure asserted by deleterious mutations. We evaluated the ability of our model to capture sequence evolution in vivo by comparing our simulated sequences to HIV-1 envelope sequence data from 16 HIV-infected untreated patients. Empirical sequence divergence and diversity measures were qualitatively and quantitatively similar to those of our simulated HIV-1 populations, suggesting that our model invokes realistic trends of HIV-1 genetic evolution. Moreover, reconstructed phylogenies of simulated and patient HIV-1 populations showed similar topological structures. Our simulation results suggest that recombination is a key mechanism facilitating the persistence of virus with latent envelope genomic fragments in the productively infected cell population. Recombination increased the survival probability of latent virus forms approximately 13-fold. Prevalence of virus with latent fragments in productively infected cells was observed in only 2% of simulations when we ignored recombination, while the proportion increased to 27% of simulations when we allowed recombination. We also found that the selection pressures exerted by different fitness landscapes influenced the shape of phylogenies, diversity trends, and survival of virus with latent genomic fragments. Furthermore, our model predicts that the persistence of latent genomic fragments from multiple different ancestral origins increases sequence diversity in plasma for reasonable fitness landscapes.« less

Recombination enhances HIV-1 envelope diversity by facilitating the survival of latent genomic fragments in the plasma virus population

DOE PAGES

Immonen, Taina T.; Conway, Jessica M.; Romero-Severson, Ethan O.; ...

2015-12-22

HIV-1 is subject to immune pressure exerted by the host, giving variants that escape the immune response an advantage. Virus released from activated latent cells competes against variants that have continually evolved and adapted to host immune pressure. Nevertheless, there is increasing evidence that virus displaying a signal of latency survives in patient plasma despite having reduced fitness due to long-term immune memory. We investigated the survival of virus with latent envelope genomic fragments by simulating within-host HIV-1 sequence evolution and the cycling of viral lineages in and out of the latent reservoir. Our model incorporates a detailed mutation processmore » including nucleotide substitution, recombination, latent reservoir dynamics, diversifying selection pressure driven by the immune response, and purifying selection pressure asserted by deleterious mutations. We evaluated the ability of our model to capture sequence evolution in vivo by comparing our simulated sequences to HIV-1 envelope sequence data from 16 HIV-infected untreated patients. Empirical sequence divergence and diversity measures were qualitatively and quantitatively similar to those of our simulated HIV-1 populations, suggesting that our model invokes realistic trends of HIV-1 genetic evolution. Moreover, reconstructed phylogenies of simulated and patient HIV-1 populations showed similar topological structures. Our simulation results suggest that recombination is a key mechanism facilitating the persistence of virus with latent envelope genomic fragments in the productively infected cell population. Recombination increased the survival probability of latent virus forms approximately 13-fold. Prevalence of virus with latent fragments in productively infected cells was observed in only 2% of simulations when we ignored recombination, while the proportion increased to 27% of simulations when we allowed recombination. We also found that the selection pressures exerted by different fitness landscapes influenced the shape of phylogenies, diversity trends, and survival of virus with latent genomic fragments. Furthermore, our model predicts that the persistence of latent genomic fragments from multiple different ancestral origins increases sequence diversity in plasma for reasonable fitness landscapes.« less

A unified genetic association test robust to latent population structure for a count phenotype.

PubMed

Song, Minsun

2018-06-04

Confounding caused by latent population structure in genome-wide association studies has been a big concern despite the success of genome-wide association studies at identifying genetic variants associated with complex diseases. In particular, because of the growing interest in association mapping using count phenotype data, it would be interesting to develop a testing framework for genetic associations that is immune to population structure when phenotype data consist of count measurements. Here, I propose a solution for testing associations between single nucleotide polymorphisms and a count phenotype in the presence of an arbitrary population structure. I consider a classical range of models for count phenotype data. Under these models, a unified test for genetic associations that protects against confounding was derived. An algorithm was developed to efficiently estimate the parameters that are required to fit the proposed model. I illustrate the proposed approach using simulation studies and an empirical study. Both simulated and real-data examples suggest that the proposed method successfully corrects population structure. Copyright © 2018 John Wiley & Sons, Ltd.

[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.

A Variable-Instar Climate-Driven Individual Beetle-Based Phenology Model for the Invasive Asian Longhorned Beetle (Coleoptera: Cerambycidae).

PubMed

Trotter, R Talbot; Keena, Melody A

2016-12-01

Efforts to manage and eradicate invasive species can benefit from an improved understanding of the physiology, biology, and behavior of the target species, and ongoing efforts to eradicate the Asian longhorned beetle (Anoplophora glabripennis Motschulsky) highlight the roles this information may play. Here, we present a climate-driven phenology model for A. glabripennis that provides simulated life-tables for populations of individual beetles under variable climatic conditions that takes into account the variable number of instars beetles may undergo as larvae. Phenology parameters in the model are based on a synthesis of published data and studies of A. glabripennis, and the model output was evaluated using a laboratory-reared population maintained under varying temperatures mimicking those typical of Central Park in New York City. The model was stable under variations in population size, simulation length, and the Julian dates used to initiate individual beetles within the population. Comparison of model results with previously published field-based phenology studies in native and invasive populations indicates both this new phenology model, and the previously published heating-degree-day model show good agreement in the prediction of the beginning of the flight season for adults. However, the phenology model described here avoids underpredicting the cumulative emergence of adults through the season, in addition to providing tables of life stages and estimations of voltinism for local populations. This information can play a key role in evaluating risk by predicting the potential for population growth, and may facilitate the optimization of management and eradication efforts. Published by Oxford University Press on behalf of Entomological Society of America 2016. This work is written by US Government employees and is in the public domain in the US.

Comparison of an Agent-based Model of Disease Propagation with the Generalised SIR Epidemic Model

DTIC Science & Technology

2009-08-01

has become a practical method for conducting Epidemiological Modelling. In the agent- based approach the whole township can be modelled as a system of...SIR system was initially developed based on a very simplified model of social interaction. For instance an assumption of uniform population mixing was...simulating the progress of a disease within a host and of transmission between hosts is based upon Transportation Analysis and Simulation System

Computational Simulation and Analysis of Mutations: Nucleotide Fixation, Allelic Age and Rare Genetic Variations in Population

ERIC Educational Resources Information Center

Qiu, Shuhao

2015-01-01

In order to investigate the complexity of mutations, a computational approach named Genome Evolution by Matrix Algorithms ("GEMA") has been implemented. GEMA models genomic changes, taking into account hundreds of mutations within each individual in a population. By modeling of entire human chromosomes, GEMA precisely mimics real…

A Dasymetric-Based Monte Carlo Simulation Approach to the Probabilistic Analysis of Spatial Variables

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

Morton, April M; Piburn, Jesse O; McManamay, Ryan A

2017-01-01

Monte Carlo simulation is a popular numerical experimentation technique used in a range of scientific fields to obtain the statistics of unknown random output variables. Despite its widespread applicability, it can be difficult to infer required input probability distributions when they are related to population counts unknown at desired spatial resolutions. To overcome this challenge, we propose a framework that uses a dasymetric model to infer the probability distributions needed for a specific class of Monte Carlo simulations which depend on population counts.

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

SimBA: simulation algorithm to fit extant-population distributions.

PubMed

Parida, Laxmi; Haiminen, Niina

2015-03-14

Simulation of populations with specified characteristics such as allele frequencies, linkage disequilibrium etc., is an integral component of many studies, including in-silico breeding optimization. Since the accuracy and sensitivity of population simulation is critical to the quality of the output of the applications that use them, accurate algorithms are required to provide a strong foundation to the methods in these studies. In this paper we present SimBA (Simulation using Best-fit Algorithm) a non-generative approach, based on a combination of stochastic techniques and discrete methods. We optimize a hill climbing algorithm and extend the framework to include multiple subpopulation structures. Additionally, we show that SimBA is very sensitive to the input specifications, i.e., very similar but distinct input characteristics result in distinct outputs with high fidelity to the specified distributions. This property of the simulation is not explicitly modeled or studied by previous methods. We show that SimBA outperforms the existing population simulation methods, both in terms of accuracy as well as time-efficiency. Not only does it construct populations that meet the input specifications more stringently than other published methods, SimBA is also easy to use. It does not require explicit parameter adaptations or calibrations. Also, it can work with input specified as distributions, without an exemplar matrix or population as required by some methods. SimBA is available at http://researcher.ibm.com/project/5669 .

Monte Carlo computer simulations of Venus equilibrium and global resurfacing models

NASA Technical Reports Server (NTRS)

Dawson, D. D.; Strom, R. G.; Schaber, G. G.

1992-01-01

Two models have been proposed for the resurfacing history of Venus: (1) equilibrium resurfacing and (2) global resurfacing. The equilibrium model consists of two cases: in case 1, areas less than or equal to 0.03 percent of the planet are spatially randomly resurfaced at intervals of less than or greater than 150,000 yr to produce the observed spatially random distribution of impact craters and average surface age of about 500 m.y.; and in case 2, areas greater than or equal to 10 percent of the planet are resurfaced at intervals of greater than or equal to 50 m.y. The global resurfacing model proposes that the entire planet was resurfaced about 500 m.y. ago, destroying the preexisting crater population and followed by significantly reduced volcanism and tectonism. The present crater population has accumulated since then with only 4 percent of the observed craters having been embayed by more recent lavas. To test the equilibrium resurfacing model we have run several Monte Carlo computer simulations for the two proposed cases. It is shown that the equilibrium resurfacing model is not a valid model for an explanation of the observed crater population characteristics or Venus' resurfacing history. The global resurfacing model is the most likely explanation for the characteristics of Venus' cratering record. The amount of resurfacing since that event, some 500 m.y. ago, can be estimated by a different type of Monte Carolo simulation. To date, our initial simulation has only considered the easiest case to implement. In this case, the volcanic events are randomly distributed across the entire planet and, therefore, contrary to observation, the flooded craters are also randomly distributed across the planet.

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

Explaining the heterogeneity of functional connectivity findings in multiple sclerosis: An empirically informed modeling study.

PubMed

Tewarie, Prejaas; Steenwijk, Martijn D; Brookes, Matthew J; Uitdehaag, Bernard M J; Geurts, Jeroen J G; Stam, Cornelis J; Schoonheim, Menno M

2018-06-01

To understand the heterogeneity of functional connectivity results reported in the literature, we analyzed the separate effects of grey and white matter damage on functional connectivity and networks in multiple sclerosis. For this, we employed a biophysical thalamo-cortical model consisting of interconnected cortical and thalamic neuronal populations, informed and amended by empirical diffusion MRI tractography data, to simulate functional data that mimic neurophysiological signals. Grey matter degeneration was simulated by decreasing within population connections and white matter degeneration by lowering between population connections, based on lesion predilection sites in multiple sclerosis. For all simulations, functional connectivity and functional network organization are quantified by phase synchronization and network integration, respectively. Modeling results showed that both cortical and thalamic grey matter damage induced a global increase in functional connectivity, whereas white matter damage induced an initially increased connectivity followed by a global decrease. Both white and especially grey matter damage, however, induced a decrease in network integration. These empirically informed simulations show that specific topology and timing of structural damage are nontrivial aspects in explaining functional abnormalities in MS. Insufficient attention to these aspects likely explains contradictory findings in multiple sclerosis functional imaging studies so far. © 2018 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Population, internal migration, and economic growth: an empirical analysis.

PubMed

Moreland, R S

1982-01-01

The role of population growth in the development process has received increasing attention during the last 15 years, as manifested in the literature in 3 broad categories. In the 1st category, the effects of rapid population growth on the growth of income have been studied with the use of simulation models, which sometimes include endogenous population growth. The 2nd category of the literature is concerned with theoretical and empirical studies of the economic determinants of various demographic rates--most usually fertility. Internal migration and dualism is the 3rd population development category to recieve attention. An attempt is made to synthesize developments in these 3 categories by estimating from a consistent set of data a 2 sector economic demographic model in which the major demographic rates are endogenous. Due to the fact that the interactions between economic and demographic variables are nonlinear and complex, the indirect effects of changes in a particular variable may depend upon the balance of numerical coefficients. For this reason it was felt that the model should be empirically grounded. A brief overview of the model is provided, and the model is compared to some similar existing models. Estimation of the model's 9 behavior equations is discussed, followed by a "base run" simulation of a developing country "stereotype" and a report of a number of policy experiments. The relatively new field of economic determinants of demographic variables was drawn upon in estimating equations to endogenize demographic phenomena that are frequently left exogenous in simulation models. The fertility and labor force participation rate functions are fairly standard, but a step beyong existing literature was taken in the life expectancy and intersectorial migration equations. On the economic side, sectoral savings functions were estimated, and it was found that the marginal propensity to save is lower in agriculture than in nonagriculture. Testing to see the effect of a population's age structure on savings rather than assuming a particular direction as Coale-Hoover and Simon do in their models, it was found that a higher proportion of children compete with savings in agriculture but complement savings in industrial areas. This was consistent with the economic value of children in agricultural and nonagricultural regions of less developed countries. The estimated production functions showed that marginal products of labor were considerably higher in agriculture than in nonagriculture. As with other simulation models, the effect of reducing fertility was to accelerate income growth. Reductions in rural fertility were more equitable and raised the overall level of per capita income more than similar efforts directed to urban areas only.

Population pharmacokinetics and safety of eptifibatide in healthy Chinese volunteers and simulations on the dose regimens approved for a Western population.

PubMed

Wang, Xi-Pei; Zhou, Zhi-Ling; Yang, Min; Mai, Li-Ping; Zheng, Zhi-Jie; He, Guo-Dong; Wu, Yue-Heng; Lin, Qiu-Xiong; Shan, Zhi-Xin; Yu, Xi-Yong

2015-08-01

This study was designed to evaluate the pharmacokinetics (PK) and safety of eptifibatide in healthy Chinese volunteers and provide information for the further study in the Chinese population. 30 healthy volunteers (15 male) were enrolled in the study and divided into three dose groups (45 µg x kg⁻¹, 90 µg x kg⁻¹, and 180 µg x kg⁻¹). Plasma and urine samples were drawn after one single-bolus administration and measured by LC-MS/MS. The plasma and urine data were analyzed simultaneously by the population approach using the NONMEM software and evaluated by the visual predicted check (VPC) and bootstraping. The PK profiles of dose regimens approved for a Western population in the Chinese population were simulated. A two-compartment model adequately described the PK profiles of eptifibatide. The clearance (CL) and the distribution volume (V₁) of the central compartment were 0.128 L x h⁻¹ x kg⁻¹ and 0.175 L x kg⁻¹, respectively. The clearance (Q) and V₂of the peripheral compartment were 0.0988 L x h⁻¹ x kg⁻¹ and 0.147 L x kg⁻¹, respectively. The elimination fraction from plasma to urine (F₀) was 17.2%. No covariates were found to have a significant effect. Inter-individual variabilites were all within 33.9%. The VPC plots and bootstrap results indicated good precision and prediction of the model. The simulations of the approved regimens in the Chinese population showed much lower steady-state concentrations than the target concentration obtained from the Western clinical trials. No severe safety events were found in this study. The PK model of eptifibatide was established and could provide PK information for further studies in the Chinese population.

A statistical approach to quasi-extinction forecasting.

PubMed

Holmes, Elizabeth Eli; Sabo, John L; Viscido, Steven Vincent; Fagan, William Fredric

2007-12-01

Forecasting population decline to a certain critical threshold (the quasi-extinction risk) is one of the central objectives of population viability analysis (PVA), and such predictions figure prominently in the decisions of major conservation organizations. In this paper, we argue that accurate forecasting of a population's quasi-extinction risk does not necessarily require knowledge of the underlying biological mechanisms. Because of the stochastic and multiplicative nature of population growth, the ensemble behaviour of population trajectories converges to common statistical forms across a wide variety of stochastic population processes. This paper provides a theoretical basis for this argument. We show that the quasi-extinction surfaces of a variety of complex stochastic population processes (including age-structured, density-dependent and spatially structured populations) can be modelled by a simple stochastic approximation: the stochastic exponential growth process overlaid with Gaussian errors. Using simulated and real data, we show that this model can be estimated with 20-30 years of data and can provide relatively unbiased quasi-extinction risk with confidence intervals considerably smaller than (0,1). This was found to be true even for simulated data derived from some of the noisiest population processes (density-dependent feedback, species interactions and strong age-structure cycling). A key advantage of statistical models is that their parameters and the uncertainty of those parameters can be estimated from time series data using standard statistical methods. In contrast for most species of conservation concern, biologically realistic models must often be specified rather than estimated because of the limited data available for all the various parameters. Biologically realistic models will always have a prominent place in PVA for evaluating specific management options which affect a single segment of a population, a single demographic rate, or different geographic areas. However, for forecasting quasi-extinction risk, statistical models that are based on the convergent statistical properties of population processes offer many advantages over biologically realistic models.

A novel approach to simulate gene-environment interactions in complex diseases.

PubMed

Amato, Roberto; Pinelli, Michele; D'Andrea, Daniel; Miele, Gennaro; Nicodemi, Mario; Raiconi, Giancarlo; Cocozza, Sergio

2010-01-05

Complex diseases are multifactorial traits caused by both genetic and environmental factors. They represent the major part of human diseases and include those with largest prevalence and mortality (cancer, heart disease, obesity, etc.). Despite a large amount of information that has been collected about both genetic and environmental risk factors, there are few examples of studies on their interactions in epidemiological literature. One reason can be the incomplete knowledge of the power of statistical methods designed to search for risk factors and their interactions in these data sets. An improvement in this direction would lead to a better understanding and description of gene-environment interactions. To this aim, a possible strategy is to challenge the different statistical methods against data sets where the underlying phenomenon is completely known and fully controllable, for example simulated ones. We present a mathematical approach that models gene-environment interactions. By this method it is possible to generate simulated populations having gene-environment interactions of any form, involving any number of genetic and environmental factors and also allowing non-linear interactions as epistasis. In particular, we implemented a simple version of this model in a Gene-Environment iNteraction Simulator (GENS), a tool designed to simulate case-control data sets where a one gene-one environment interaction influences the disease risk. The main aim has been to allow the input of population characteristics by using standard epidemiological measures and to implement constraints to make the simulator behaviour biologically meaningful. By the multi-logistic model implemented in GENS it is possible to simulate case-control samples of complex disease where gene-environment interactions influence the disease risk. The user has full control of the main characteristics of the simulated population and a Monte Carlo process allows random variability. A knowledge-based approach reduces the complexity of the mathematical model by using reasonable biological constraints and makes the simulation more understandable in biological terms. Simulated data sets can be used for the assessment of novel statistical methods or for the evaluation of the statistical power when designing a study.

Modeling Newspaper Advertising

ERIC Educational Resources Information Center

Harper, Joseph; And Others

1978-01-01

Presents a mathematical model for simulating a newspaper financial system. Includes the effects of advertising and circulation for predicting advertising linage as a function of population, income, and advertising rate. (RL)

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.

Spatial genetic structure in continuous and fragmented populations of Pinus pinaster Aiton.

PubMed

De-Lucas, A I; González-Martínez, S C; Vendramin, G G; Hidalgo, E; Heuertz, M

2009-11-01

Habitat fragmentation, i.e., the reduction of populations into small isolated remnants, is expected to increase spatial genetic structure (SGS) in plant populations through nonrandom mating, lower population densities and potential aggregation of reproductive individuals. We investigated the effects of population size reduction and genetic isolation on SGS in maritime pine (Pinus pinaster Aiton) using a combined experimental and simulation approach. Maritime pine is a wind-pollinated conifer which has a scattered distribution in the Iberian Peninsula as a result of forest fires and habitat fragmentation. Five highly polymorphic nuclear microsatellites were genotyped in a total of 394 individuals from two population pairs from the Iberian Peninsula, formed by one continuous and one fragmented population each. In agreement with predictions, SGS was significant and stronger in fragments (Sp = 0.020 and Sp = 0.026) than in continuous populations, where significant SGS was detected for one population only (Sp = 0.010). Simulations suggested that under fat-tailed dispersal, small population size is a stronger determinant of SGS than genetic isolation, while under normal dispersal, genetic isolation has a stronger effect. SGS was always stronger in real populations than in simulations, except if unrealistically narrow dispersal and/or high variance of reproductive success were modelled (even when accounting for potential overestimation of SGS in real populations as a result of short-distance sampling). This suggests that factors such as nonrandom mating or selection not considered in the simulations were additionally operating on SGS in Iberian maritime pine 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.

INSTAR: simulating the biological cycle of a forest pest in Mediterranean pine stands

NASA Astrophysics Data System (ADS)

Suárez-Muñoz, María; Bonet García, Francisco J.; Hódar, José A.

2017-04-01

The pine processionary moth (Thaumetopoea pityocampa) is a typically Mediterranean forest pest feeding on pine needles during its larval stages. The outbreaks of this pest cause important landscape impacts and public health problems (i.e. larvae are very urticant). Larvae feed during winter months and cold temperature is the main limiting factor in their development. Therefore, rising temperatures are thought to benefit this species. Indeed, observations suggest that outbreaks are becoming more frequent and populations are shifting uphill. The objective of this work is to simulate the biological cycle of T. pityocampa to make predictions about where and when outbreaks will occur. Thus, we have created a model called INSTAR that will help to identify hotspots and foresee massive defoliation episodes. This will enhance the information available for the control of this pest. INSTAR is an Agent-Based Model, which allows the inclusion of important characteristics of the system: emergence, feedback (i.e. interaction between agents and their environment), adaptation (i.e. decision based on the mentioned interactions) and path dependence (i.e. possibilities at one time point are determined by past conditions). These characteristics arise from a set of functions simulating pine growth, processionary development, mortality and movement. These functions are easily extrapolable to other similar biological processes and therefore INSTAR aims at serving of example for other forest pest models. INSTAR is the first comprehensive approach to simulate the biological cycle of T pityocampa. It simulates the pest development in a given area, from which elevation and pine trees are considered. Moreover, it is also a good example of integrating environmental information into a population dynamic model: meteorological variables and soil moisture are obtained from a hydrological model (WiMMed, Herrero et al. 2009) executed for the area of interest. These variables are the inputs of the model, which feed the functions that simulate the processionary life cycle. Model's executions in two different areas and for relatively long time frames (1993-2014 and 2000-2014) yield relevant information about the biological cycle of the forest pest: the simulated peaks of larvae are followed by minimal values of pine biomass and pine infections are more abundant at the edge of the stands. Moreover, emerging patterns such as denso-dependency can be observed. To sum up, INSTAR is a promising tool for modeling T. pityocampa population dynamics. The obtained model will help to improve the decision making process regarding the control of the forest pest. Moreover, its simple structure of functions will facilitate the design of new models simulating other forest pests.

The Structure of the Distant Kuiper Belt in a Nice Model Scenario

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

Pike, R. E.; Shankman, C. J.; Kavelaars, J. J.

2017-03-01

This work explores the orbital distribution of minor bodies in the outer Solar System emplaced as a result of a Nice model migration from the simulations of Brasser and Morbidelli. This planetary migration scatters a planetesimal disk from between 29 and 34 au and emplaces a population of objects into the Kuiper Belt region. From the 2:1 Neptune resonance and outward, the test particles analyzed populate the outer resonances with orbital distributions consistent with trans-Neptunian object (TNO) detections in semimajor axis, inclination, and eccentricity, while capture into the closest resonances is too efficient. The relative populations of the simulated scatteringmore » objects and resonant objects in the 3:1 and 4:1 resonances are also consistent with observed populations based on debiased TNO surveys, but the 5:1 resonance is severely underpopulated compared to population estimates from survey results. Scattering emplacement results in the expected orbital distribution for the majority of the TNO populations; however, the origin of the large observed population in the 5:1 resonance remains unexplained.« less

[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.

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.

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.

Population modelling to compare chronic external radiotoxicity between individual and population endpoints in four taxonomic groups.

PubMed

Alonzo, Frédéric; Hertel-Aas, Turid; Real, Almudena; Lance, Emilie; Garcia-Sanchez, Laurent; Bradshaw, Clare; Vives I Batlle, Jordi; Oughton, Deborah H; Garnier-Laplace, Jacqueline

2016-02-01

In this study, we modelled population responses to chronic external gamma radiation in 12 laboratory species (including aquatic and soil invertebrates, fish and terrestrial mammals). Our aim was to compare radiosensitivity between individual and population endpoints and to examine how internationally proposed benchmarks for environmental radioprotection protected species against various risks at the population level. To do so, we used population matrix models, combining life history and chronic radiotoxicity data (derived from laboratory experiments and described in the literature and the FREDERICA database) to simulate changes in population endpoints (net reproductive rate R0, asymptotic population growth rate λ, equilibrium population size Neq) for a range of dose rates. Elasticity analyses of models showed that population responses differed depending on the affected individual endpoint (juvenile or adult survival, delay in maturity or reduction in fecundity), the considered population endpoint (R0, λ or Neq) and the life history of the studied species. Among population endpoints, net reproductive rate R0 showed the lowest EDR10 (effective dose rate inducing 10% effect) in all species, with values ranging from 26 μGy h(-1) in the mouse Mus musculus to 38,000 μGy h(-1) in the fish Oryzias latipes. For several species, EDR10 for population endpoints were lower than the lowest EDR10 for individual endpoints. Various population level risks, differing in severity for the population, were investigated. Population extinction (predicted when radiation effects caused population growth rate λ to decrease below 1, indicating that no population growth in the long term) was predicted for dose rates ranging from 2700 μGy h(-1) in fish to 12,000 μGy h(-1) in soil invertebrates. A milder risk, that population growth rate λ will be reduced by 10% of the reduction causing extinction, was predicted for dose rates ranging from 24 μGy h(-1) in mammals to 1800 μGy h(-1) in soil invertebrates. These predictions suggested that proposed reference benchmarks from the literature for different taxonomic groups protected all simulated species against population extinction. A generic reference benchmark of 10 μGy h(-1) protected all simulated species against 10% of the effect causing population extinction. Finally, a risk of pseudo-extinction was predicted from 2.0 μGy h(-1) in mammals to 970 μGy h(-1) in soil invertebrates, representing a slight but statistically significant population decline, the importance of which remains to be evaluated in natural settings. Copyright © 2015 Elsevier Ltd. All rights reserved.

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.

Detecting Directional Selection in the Presence of Recent Admixture in African-Americans

PubMed Central

Lohmueller, Kirk E.; Bustamante, Carlos D.; Clark, Andrew G.

2011-01-01

We investigate the performance of tests of neutrality in admixed populations using plausible demographic models for African-American history as well as resequencing data from African and African-American populations. The analysis of both simulated and human resequencing data suggests that recent admixture does not result in an excess of false-positive results for neutrality tests based on the frequency spectrum after accounting for the population growth in the parental African population. Furthermore, when simulating positive selection, Tajima's D, Fu and Li's D, and haplotype homozygosity have lower power to detect population-specific selection using individuals sampled from the admixed population than from the nonadmixed population. Fay and Wu's H test, however, has more power to detect selection using individuals from the admixed population than from the nonadmixed population, especially when the selective sweep ended long ago. Our results have implications for interpreting recent genome-wide scans for positive selection in human populations. PMID:21196524

Genetic and demographic implications of aquaculture in white sturgeon (Acipenser transmontanus)conservation

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

Jager, Yetta

2005-01-01

This study uses a genetic individual-based model of white sturgeon (Acipenser transmontanus) populations in a river to examine the genetic and demographic trade-offs associated with operating a conservation hatchery. Simulation experiments evaluated three management practices: (i) setting quotas to equalize family contributions in an effort to prevent genetic swamping, (ii) an adaptive management scheme that interrupts stocking when introgression exceeds a specified threshold, and (iii) alternative broodstock selection strategies that influence domestication. The first set of simulations, designed to evaluate equalizing the genetic contribution of families, did not show the genetic benefits expected. The second set of simulations showed thatmore » simulated adaptive management was not successful in controlling introgression over the long term, especially with uncertain feedback. The third set of simulations compared the effects of three alternative broodstock selection strategies on domestication for hypothetical traits controlling early density-dependent survival. Simulated aquaculture selected for a density-tolerant phenotype when broodstock were taken from a genetically connected population. Using broodstock from an isolated population (i.e., above an upstream barrier or in a different watershed) was more effective at preventing domestication than using wild broodstock from a connected population.« less

Levofloxacin Penetration into Epithelial Lining Fluid as Determined by Population Pharmacokinetic Modeling and Monte Carlo Simulation

PubMed Central

Drusano, G. L.; Preston, S. L.; Gotfried, M. H.; Danziger, L. H.; Rodvold, K. A.

2002-01-01

Levofloxacin was administered orally to steady state to volunteers randomly in doses of 500 and 750 mg. Plasma and epithelial lining fluid (ELF) samples were obtained at 4, 12, and 24 h after the final dose. All data were comodeled in a population pharmacokinetic analysis employing BigNPEM. Penetration was evaluated from the population mean parameter vector values and from the results of a 1,000-subject Monte Carlo simulation. Evaluation from the population mean values demonstrated a penetration ratio (ELF/plasma) of 1.16. The Monte Carlo simulation provided a measure of dispersion, demonstrating a mean ratio of 3.18, with a median of 1.43 and a 95% confidence interval of 0.14 to 19.1. Population analysis with Monte Carlo simulation provides the best and least-biased estimate of penetration. It also demonstrates clearly that we can expect differences in penetration between patients. This analysis did not deal with inflammation, as it was performed in volunteers. The influence of lung pathology on penetration needs to be examined. PMID:11796385

Population viability analysis for endangered Roanoke logperch

USGS Publications Warehouse

Roberts, James H.; Angermeier, Paul; Anderson, Gregory B.

2016-01-01

A common strategy for recovering endangered species is ensuring that populations exceed the minimum viable population size (MVP), a demographic benchmark that theoretically ensures low long-term extinction risk. One method of establishing MVP is population viability analysis, a modeling technique that simulates population trajectories and forecasts extinction risk based on a series of biological, environmental, and management assumptions. Such models also help identify key uncertainties that have a large influence on extinction risk. We used stochastic count-based simulation models to explore extinction risk, MVP, and the possible benefits of alternative management strategies in populations of Roanoke logperch Percina rex, an endangered stream fish. Estimates of extinction risk were sensitive to the assumed population growth rate and model type, carrying capacity, and catastrophe regime (frequency and severity of anthropogenic fish kills), whereas demographic augmentation did little to reduce extinction risk. Under density-dependent growth, the estimated MVP for Roanoke logperch ranged from 200 to 4200 individuals, depending on the assumed severity of catastrophes. Thus, depending on the MVP threshold, anywhere from two to all five of the logperch populations we assessed were projected to be viable. Despite this uncertainty, these results help identify populations with the greatest relative extinction risk, as well as management strategies that might reduce this risk the most, such as increasing carrying capacity and reducing fish kills. Better estimates of population growth parameters and catastrophe regimes would facilitate the refinement of MVP and extinction-risk estimates, and they should be a high priority for future research on Roanoke logperch and other imperiled stream-fish species.

The Apollo Structured Vocabulary: an OWL2 ontology of phenomena in infectious disease epidemiology and population biology for use in epidemic simulation.

PubMed

Hogan, William R; Wagner, Michael M; Brochhausen, Mathias; Levander, John; Brown, Shawn T; Millett, Nicholas; DePasse, Jay; Hanna, Josh

2016-08-18

We developed the Apollo Structured Vocabulary (Apollo-SV)-an OWL2 ontology of phenomena in infectious disease epidemiology and population biology-as part of a project whose goal is to increase the use of epidemic simulators in public health practice. Apollo-SV defines a terminology for use in simulator configuration. Apollo-SV is the product of an ontological analysis of the domain of infectious disease epidemiology, with particular attention to the inputs and outputs of nine simulators. Apollo-SV contains 802 classes for representing the inputs and outputs of simulators, of which approximately half are new and half are imported from existing ontologies. The most important Apollo-SV class for users of simulators is infectious disease scenario, which is a representation of an ecosystem at simulator time zero that has at least one infection process (a class) affecting at least one population (also a class). Other important classes represent ecosystem elements (e.g., households), ecosystem processes (e.g., infection acquisition and infectious disease), censuses of ecosystem elements (e.g., censuses of populations), and infectious disease control measures. In the larger project, which created an end-user application that can send the same infectious disease scenario to multiple simulators, Apollo-SV serves as the controlled terminology and strongly influences the design of the message syntax used to represent an infectious disease scenario. As we added simulators for different pathogens (e.g., malaria and dengue), the core classes of Apollo-SV have remained stable, suggesting that our conceptualization of the information required by simulators is sound. Despite adhering to the OBO Foundry principle of orthogonality, we could not reuse Infectious Disease Ontology classes as the basis for infectious disease scenarios. We thus defined new classes in Apollo-SV for host, pathogen, infection, infectious disease, colonization, and infection acquisition. Unlike IDO, our ontological analysis extended to existing mathematical models of key biological phenomena studied by infectious disease epidemiology and population biology. Our ontological analysis as expressed in Apollo-SV was instrumental in developing a simulator-independent representation of infectious disease scenarios that can be run on multiple epidemic simulators. Our experience suggests the importance of extending ontological analysis of a domain to include existing mathematical models of the phenomena studied by the domain. Apollo-SV is freely available at: http://purl.obolibrary.org/obo/apollo_sv.owl .

Land Use Change on Household Farms in the Ecuadorian Amazon: Design and Implementation of an Agent-Based Model.

PubMed

Mena, Carlos F; Walsh, Stephen J; Frizzelle, Brian G; Xiaozheng, Yao; Malanson, George P

2011-01-01

This paper describes the design and implementation of an Agent-Based Model (ABM) used to simulate land use change on household farms in the Northern Ecuadorian Amazon (NEA). The ABM simulates decision-making processes at the household level that is examined through a longitudinal, socio-economic and demographic survey that was conducted in 1990 and 1999. Geographic Information Systems (GIS) are used to establish spatial relationships between farms and their environment, while classified Landsat Thematic Mapper (TM) imagery is used to set initial land use/land cover conditions for the spatial simulation, assess from-to land use/land cover change patterns, and describe trajectories of land use change at the farm and landscape levels. Results from prior studies in the NEA provide insights into the key social and ecological variables, describe human behavioral functions, and examine population-environment interactions that are linked to deforestation and agricultural extensification, population migration, and demographic change. Within the architecture of the model, agents are classified as active or passive. The model comprises four modules, i.e., initialization, demography, agriculture, and migration that operate individually, but are linked through key household processes. The main outputs of the model include a spatially-explicit representation of the land use/land cover on survey and non-survey farms and at the landscape level for each annual time-step, as well as simulated socio-economic and demographic characteristics of households and communities. The work describes the design and implementation of the model and how population-environment interactions can be addressed in a frontier setting. The paper contributes to land change science by examining important pattern-process relations, advocating a spatial modeling approach that is capable of synthesizing fundamental relationships at the farm level, and links people and environment in complex ways.

How wild is your model fire? Constraining WRF-Chem wildfire smoke simulations with satellite observations

NASA Astrophysics Data System (ADS)

Fischer, E. V.; Ford, B.; Lassman, W.; Pierce, J. R.; Pfister, G.; Volckens, J.; Magzamen, S.; Gan, R.

2015-12-01

Exposure to high concentrations of particulate matter (PM) present during acute pollution events is associated with adverse health effects. While many anthropogenic pollution sources are regulated in the United States, emissions from wildfires are difficult to characterize and control. With wildfire frequency and intensity in the western U.S. projected to increase, it is important to more precisely determine the effect that wildfire emissions have on human health, and whether improved forecasts of these air pollution events can mitigate the health risks associated with wildfires. One of the challenges associated with determining health risks associated with wildfire emissions is that the low spatial resolution of surface monitors means that surface measurements may not be representative of a population's exposure, due to steep concentration gradients. To obtain better estimates of ambient exposure levels for health studies, a chemical transport model (CTM) can be used to simulate the evolution of a wildfire plume as it travels over populated regions downwind. Improving the performance of a CTM would allow the development of a new forecasting framework that could better help decision makers estimate and potentially mitigate future health impacts. We use the Weather Research and Forecasting model with online chemistry (WRF-Chem) to simulate wildfire plume evolution. By varying the model resolution, meteorology reanalysis initial conditions, and biomass burning inventories, we are able to explore the sensitivity of model simulations to these various parameters. Satellite observations are used first to evaluate model skill, and then to constrain the model results. These data are then used to estimate population-level exposure, with the aim of better characterizing the effects that wildfire emissions have on human health.

NUNOA: a computer simulator of individuals, families, and extended families of the high-altitude Quechua

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

Brandt, C.C.; Weinstein, D.A.; Shugart, H.H.

1980-10-01

The Quechua Indians of the Peruvian Andes are an example of a human population which has developed special cultural adaptations to deal with hypocaloric stress imposed by a harsh environment. A highly detailed human ecosystem model, NUNOA, which simulates the yearly energy balance of individuals, families, and extended families in a hypothetical farming and herding Quechua community of the high Andes was developed. Unlike most population models which use sets of differential equations in which individuals are aggregated into groups, this model considers the response of each individual to a stochastic environment. The model calculates the yearly energy demand formore » each family based on caloric requirements of its members. For each family, the model simulates the cultivation of seven different crops and the impact of precipitation, temperature, and disease on yield. Herding, slaughter, and market sales of three different animal species are also simulated. Any energy production in excess of the family's energy demand is placed into extended family storage for possible redistribution. A family failing to meet their annual energy demand may slaughter additional herd animals, temporarily migrate from the community, or borrow food from the extended family storage. The energy balance is used in determining births, deaths, marriages, and resource sharing in the Indian community. In addition, the model maintains a record of each individual's ancestry as well as seven genetic traits for use in tracing lineage and gene flow. The model user has the opportunity to investigate the effect of changes in marriage patterns, resource sharing patterns, or subsistence activities on the ability of the human population to survive in the harsh Andean environment. In addition, the user may investigate the impact of external technology on the Indian culture.« less

Theory and data for simulating fine-scale human movement in an urban environment

PubMed Central

Perkins, T. Alex; Garcia, Andres J.; Paz-Soldán, Valerie A.; Stoddard, Steven T.; Reiner, Robert C.; Vazquez-Prokopec, Gonzalo; Bisanzio, Donal; Morrison, Amy C.; Halsey, Eric S.; Kochel, Tadeusz J.; Smith, David L.; Kitron, Uriel; Scott, Thomas W.; Tatem, Andrew J.

2014-01-01

Individual-based models of infectious disease transmission depend on accurate quantification of fine-scale patterns of human movement. Existing models of movement either pertain to overly coarse scales, simulate some aspects of movement but not others, or were designed specifically for populations in developed countries. Here, we propose a generalizable framework for simulating the locations that an individual visits, time allocation across those locations, and population-level variation therein. As a case study, we fit alternative models for each of five aspects of movement (number, distance from home and types of locations visited; frequency and duration of visits) to interview data from 157 residents of the city of Iquitos, Peru. Comparison of alternative models showed that location type and distance from home were significant determinants of the locations that individuals visited and how much time they spent there. We also found that for most locations, residents of two neighbourhoods displayed indistinguishable preferences for visiting locations at various distances, despite differing distributions of locations around those neighbourhoods. Finally, simulated patterns of time allocation matched the interview data in a number of ways, suggesting that our framework constitutes a sound basis for simulating fine-scale movement and for investigating factors that influence it. PMID:25142528

Human judgment vs. quantitative models for the management of ecological resources.

PubMed

Holden, Matthew H; Ellner, Stephen P

2016-07-01

Despite major advances in quantitative approaches to natural resource management, there has been resistance to using these tools in the actual practice of managing ecological populations. Given a managed system and a set of assumptions, translated into a model, optimization methods can be used to solve for the most cost-effective management actions. However, when the underlying assumptions are not met, such methods can potentially lead to decisions that harm the environment and economy. Managers who develop decisions based on past experience and judgment, without the aid of mathematical models, can potentially learn about the system and develop flexible management strategies. However, these strategies are often based on subjective criteria and equally invalid and often unstated assumptions. Given the drawbacks of both methods, it is unclear whether simple quantitative models improve environmental decision making over expert opinion. In this study, we explore how well students, using their experience and judgment, manage simulated fishery populations in an online computer game and compare their management outcomes to the performance of model-based decisions. We consider harvest decisions generated using four different quantitative models: (1) the model used to produce the simulated population dynamics observed in the game, with the values of all parameters known (as a control), (2) the same model, but with unknown parameter values that must be estimated during the game from observed data, (3) models that are structurally different from those used to simulate the population dynamics, and (4) a model that ignores age structure. Humans on average performed much worse than the models in cases 1-3, but in a small minority of scenarios, models produced worse outcomes than those resulting from students making decisions based on experience and judgment. When the models ignored age structure, they generated poorly performing management decisions, but still outperformed students using experience and judgment 66% of the time. © 2016 by the Ecological Society of America.

Mathematical analysis of epidemiological models with heterogeneity

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

Van Ark, J.W.

1992-01-01

For many diseases in human populations the disease shows dissimilar characteristics in separate subgroups of the population; for example, the probability of disease transmission for gonorrhea or AIDS is much higher from male to female than from female to male. There is reason to construct and analyze epidemiological models which allow this heterogeneity of population, and to use these models to run computer simulations of the disease to predict the incidence and prevalence of the disease. In the models considered here the heterogeneous population is separated into subpopulations whose internal and external interactions are homogeneous in the sense that eachmore » person in the population can be assumed to have all average actions for the people of that subpopulation. The first model considered is an SIRS models; i.e., the Susceptible can become Infected, and if so he eventually Recovers with temporary immunity, and after a period of time becomes Susceptible again. Special cases allow for permanent immunity or other variations. This model is analyzed and threshold conditions are given which determine whether the disease dies out or persists. A deterministic model is presented; this model is constructed using difference equations, and it has been used in computer simulations for the AIDS epidemic in the homosexual population in San Francisco. The homogeneous version and the heterogeneous version of the differential-equations and difference-equations versions of the deterministic model are analyzed mathematically. In the analysis, equilibria are identified and threshold conditions are set forth for the disease to die out if the disease is below the threshold so that the disease-free equilibrium is globally asymptotically stable. Above the threshold the disease persists so that the disease-free equilibrium is unstable and there is a unique endemic equilibrium.« less

Economic consequences of population size, structure and growth.

PubMed

Lee, R

1983-01-01

There seems to be 4 major approaches to conceptualizing and modeling demographic influences on economic and social welfare. These approaches are combined in various ways to construct richer and more comprehensive models. The basic approaches are: demographic influences on household or family behavior; population growth and reproducible capital; population size and fixed factors; and population and advantages of scale. These 4 models emphasize the supply side effects of population. A few of the ways in which these theories have been combined are sketched. Neoclassical growth models often have been combined with age distributed populations of individuals (or households), assumed to pursue optimal life cycle consumption and saving. In some well known development models, neoclassical growth models for the modern sector are linked by labor markets and migration to fixed factor (land) models of the traditional (agricultural) sector. A whole series of macro simulation models for developed and developing countries was based on single sector neoclassical growth models with age distributed populations. Yet, typically the household level foundations of assumed age distribution effects were not worked out. Simon's (1977) simulation models are in a class by themselves, for they are the only models that attempt to incorporate all the kinds of effects discussed. The economic demography of the individual and family cycle, as it is affected by regimes of fertility, mortality, and nuptiality, taken as given, are considered. The examination touches on many of the purported consequences of aggregate population growth and age composition, since so many of these are based implicitly or explicitly on assertions about micro level behavior. Demographic influences on saving and consumption, on general labor supply and female labor supply, and on problems of youth and old age dependency frequently fall in this category. Finally, attention is focused specifically on macro economic issues in the consequences of population in both developed and developing countries. In general cross national studies have failed to provide rough and stylized depiction of the consequences of rapid population growth, unless the absence of significant results is itself the result.

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.

Vulnerability of Population and Transportation Infrastructure at the East Bank of Delaware Bay Due to Coastal Flooding in Sea-Level Rise Conditions

DTIC Science & Technology

2013-04-30

resulting impact on residents and transportation infrastructure. The three-dimensional coastal ocean model FVCOM coupled with a two-dimensional...shallow water model is used to simulate hydrodynamic flooding from coastal ocean water with fine-resolution meshes, and a topography-based hydrologic... ocean model FVCOM coupled with a two-dimensional shallow water model is used to simulate hydrodynamic flooding from coastal ocean water with fine

Development of a Novel Rabies Simulation Model for Application in a Non-endemic Environment

PubMed Central

Dürr, Salome; Ward, Michael P.

2015-01-01

Domestic dog rabies is an endemic disease in large parts of the developing world and also epidemic in previously free regions. For example, it continues to spread in eastern Indonesia and currently threatens adjacent rabies-free regions with high densities of free-roaming dogs, including remote northern Australia. Mathematical and simulation disease models are useful tools to provide insights on the most effective control strategies and to inform policy decisions. Existing rabies models typically focus on long-term control programs in endemic countries. However, simulation models describing the dog rabies incursion scenario in regions where rabies is still exotic are lacking. We here describe such a stochastic, spatially explicit rabies simulation model that is based on individual dog information collected in two remote regions in northern Australia. Illustrative simulations produced plausible results with epidemic characteristics expected for rabies outbreaks in disease free regions (mean R0 1.7, epidemic peak 97 days post-incursion, vaccination as the most effective response strategy). Systematic sensitivity analysis identified that model outcomes were most sensitive to seven of the 30 model parameters tested. This model is suitable for exploring rabies spread and control before an incursion in populations of largely free-roaming dogs that live close together with their owners. It can be used for ad-hoc contingency or response planning prior to and shortly after incursion of dog rabies in previously free regions. One challenge that remains is model parameterisation, particularly how dogs’ roaming and contacts and biting behaviours change following a rabies incursion in a previously rabies free population. PMID:26114762

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.

Relationships between migration rates and landscape resistance assessed using individual-based simulations

Treesearch

E. L. Landguth; S. A. Cushman; M. A. Murphy; G. Luikart

2010-01-01

Linking landscape effects on gene flow to processes such as dispersal and mating is essential to provide a conceptual foundation for landscape genetics. It is particularly important to determine how classical population genetic models relate to recent individual-based landscape genetic models when assessing individual movement and its influence on population genetic...

Biologically Informed Individual-Based Network Model for Rift Valley Fever in the US and Evaluation of Mitigation Strategies

PubMed Central

Scoglio, Caterina M.

2016-01-01

Rift Valley fever (RVF) is a zoonotic disease endemic in sub-Saharan Africa with periodic outbreaks in human and animal populations. Mosquitoes are the primary disease vectors; however, Rift Valley fever virus (RVFV) can also spread by direct contact with infected tissues. The transmission cycle is complex, involving humans, livestock, and multiple species of mosquitoes. The epidemiology of RVFV in endemic areas is strongly affected by climatic conditions and environmental variables. In this research, we adapt and use a network-based modeling framework to simulate the transmission of RVFV among hypothetical cattle operations in Kansas, US. Our model considers geo-located livestock populations at the individual level while incorporating the role of mosquito populations and the environment at a coarse resolution. Extensive simulations show the flexibility of our modeling framework when applied to specific scenarios to quantitatively evaluate the efficacy of mosquito control and livestock movement regulations in reducing the extent and intensity of RVF outbreaks in the United States. PMID:27662585

Biologically Informed Individual-Based Network Model for Rift Valley Fever in the US and Evaluation of Mitigation Strategies.

PubMed

Scoglio, Caterina M; Bosca, Claudio; Riad, Mahbubul H; Sahneh, Faryad D; Britch, Seth C; Cohnstaedt, Lee W; Linthicum, Kenneth J

Rift Valley fever (RVF) is a zoonotic disease endemic in sub-Saharan Africa with periodic outbreaks in human and animal populations. Mosquitoes are the primary disease vectors; however, Rift Valley fever virus (RVFV) can also spread by direct contact with infected tissues. The transmission cycle is complex, involving humans, livestock, and multiple species of mosquitoes. The epidemiology of RVFV in endemic areas is strongly affected by climatic conditions and environmental variables. In this research, we adapt and use a network-based modeling framework to simulate the transmission of RVFV among hypothetical cattle operations in Kansas, US. Our model considers geo-located livestock populations at the individual level while incorporating the role of mosquito populations and the environment at a coarse resolution. Extensive simulations show the flexibility of our modeling framework when applied to specific scenarios to quantitatively evaluate the efficacy of mosquito control and livestock movement regulations in reducing the extent and intensity of RVF outbreaks in the United States.

Simulating the Distribution of Individual Livestock Farms and Their Populations in the United States: An Example Using Domestic Swine (Sus scrofa domesticus) Farms

PubMed Central

Garza, Sarah J.; Miller, Ryan S.

2015-01-01

Livestock distribution in the United States (U.S.) can only be mapped at a county-level or worse resolution. We developed a spatial microsimulation model called the Farm Location and Agricultural Production Simulator (FLAPS) that simulated the distribution and populations of individual livestock farms throughout the conterminous U.S. Using domestic pigs (Sus scrofa domesticus) as an example species, we customized iterative proportional-fitting algorithms for the hierarchical structure of the U.S. Census of Agriculture and imputed unpublished state- or county-level livestock population totals that were redacted to ensure confidentiality. We used a weighted sampling design to collect data on the presence and absence of farms and used them to develop a national-scale distribution model that predicted the distribution of individual farms at a 100 m resolution. We implemented microsimulation algorithms that simulated the populations and locations of individual farms using output from our imputed Census of Agriculture dataset and distribution model. Approximately 19% of county-level pig population totals were unpublished in the 2012 Census of Agriculture and needed to be imputed. Using aerial photography, we confirmed the presence or absence of livestock farms at 10,238 locations and found livestock farms were correlated with open areas, cropland, and roads, and also areas with cooler temperatures and gentler topography. The distribution of swine farms was highly variable, but cross-validation of our distribution model produced an area under the receiver-operating characteristics curve value of 0.78, which indicated good predictive performance. Verification analyses showed FLAPS accurately imputed and simulated Census of Agriculture data based on absolute percent difference values of < 0.01% at the state-to-national scale, 3.26% for the county-to-state scale, and 0.03% for the individual farm-to-county scale. Our output data have many applications for risk management of agricultural systems including epidemiological studies, food safety, biosecurity issues, emergency-response planning, and conflicts between livestock and other natural resources. PMID:26571497

Simulating the Distribution of Individual Livestock Farms and Their Populations in the United States: An Example Using Domestic Swine (Sus scrofa domesticus) Farms.

PubMed

Burdett, Christopher L; Kraus, Brian R; Garza, Sarah J; Miller, Ryan S; Bjork, Kathe E

2015-01-01

Livestock distribution in the United States (U.S.) can only be mapped at a county-level or worse resolution. We developed a spatial microsimulation model called the Farm Location and Agricultural Production Simulator (FLAPS) that simulated the distribution and populations of individual livestock farms throughout the conterminous U.S. Using domestic pigs (Sus scrofa domesticus) as an example species, we customized iterative proportional-fitting algorithms for the hierarchical structure of the U.S. Census of Agriculture and imputed unpublished state- or county-level livestock population totals that were redacted to ensure confidentiality. We used a weighted sampling design to collect data on the presence and absence of farms and used them to develop a national-scale distribution model that predicted the distribution of individual farms at a 100 m resolution. We implemented microsimulation algorithms that simulated the populations and locations of individual farms using output from our imputed Census of Agriculture dataset and distribution model. Approximately 19% of county-level pig population totals were unpublished in the 2012 Census of Agriculture and needed to be imputed. Using aerial photography, we confirmed the presence or absence of livestock farms at 10,238 locations and found livestock farms were correlated with open areas, cropland, and roads, and also areas with cooler temperatures and gentler topography. The distribution of swine farms was highly variable, but cross-validation of our distribution model produced an area under the receiver-operating characteristics curve value of 0.78, which indicated good predictive performance. Verification analyses showed FLAPS accurately imputed and simulated Census of Agriculture data based on absolute percent difference values of < 0.01% at the state-to-national scale, 3.26% for the county-to-state scale, and 0.03% for the individual farm-to-county scale. Our output data have many applications for risk management of agricultural systems including epidemiological studies, food safety, biosecurity issues, emergency-response planning, and conflicts between livestock and other natural resources.

An Agent-Based Modeling Template for a Cohort of Veterans with Diabetic Retinopathy.

PubMed

Day, Theodore Eugene; Ravi, Nathan; Xian, Hong; Brugh, Ann

2013-01-01

Agent-based models are valuable for examining systems where large numbers of discrete individuals interact with each other, or with some environment. Diabetic Veterans seeking eye care at a Veterans Administration hospital represent one such cohort. The objective of this study was to develop an agent-based template to be used as a model for a patient with diabetic retinopathy (DR). This template may be replicated arbitrarily many times in order to generate a large cohort which is representative of a real-world population, upon which in-silico experimentation may be conducted. Agent-based template development was performed in java-based computer simulation suite AnyLogic Professional 6.6. The model was informed by medical data abstracted from 535 patient records representing a retrospective cohort of current patients of the VA St. Louis Healthcare System Eye clinic. Logistic regression was performed to determine the predictors associated with advancing stages of DR. Predicted probabilities obtained from logistic regression were used to generate the stage of DR in the simulated cohort. The simulated cohort of DR patients exhibited no significant deviation from the test population of real-world patients in proportion of stage of DR, duration of diabetes mellitus (DM), or the other abstracted predictors. Simulated patients after 10 years were significantly more likely to exhibit proliferative DR (P<0.001). Agent-based modeling is an emerging platform, capable of simulating large cohorts of individuals based on manageable data abstraction efforts. The modeling method described may be useful in simulating many different conditions where course of disease is described in categorical stages.

Bayesian Parameter Inference and Model Selection by Population Annealing in Systems Biology

PubMed Central

Murakami, Yohei

2014-01-01

Parameter inference and model selection are very important for mathematical modeling in systems biology. Bayesian statistics can be used to conduct both parameter inference and model selection. Especially, the framework named approximate Bayesian computation is often used for parameter inference and model selection in systems biology. However, Monte Carlo methods needs to be used to compute Bayesian posterior distributions. In addition, the posterior distributions of parameters are sometimes almost uniform or very similar to their prior distributions. In such cases, it is difficult to choose one specific value of parameter with high credibility as the representative value of the distribution. To overcome the problems, we introduced one of the population Monte Carlo algorithms, population annealing. Although population annealing is usually used in statistical mechanics, we showed that population annealing can be used to compute Bayesian posterior distributions in the approximate Bayesian computation framework. To deal with un-identifiability of the representative values of parameters, we proposed to run the simulations with the parameter ensemble sampled from the posterior distribution, named “posterior parameter ensemble”. We showed that population annealing is an efficient and convenient algorithm to generate posterior parameter ensemble. We also showed that the simulations with the posterior parameter ensemble can, not only reproduce the data used for parameter inference, but also capture and predict the data which was not used for parameter inference. Lastly, we introduced the marginal likelihood in the approximate Bayesian computation framework for Bayesian model selection. We showed that population annealing enables us to compute the marginal likelihood in the approximate Bayesian computation framework and conduct model selection depending on the Bayes factor. PMID:25089832

Population variability in animal health: Influence on dose-exposure-response relationships: Part II: Modelling and simulation.

PubMed

Martinez, Marilyn N; Gehring, Ronette; Mochel, Jonathan P; Pade, Devendra; Pelligand, Ludovic

2018-05-28

During the 2017 Biennial meeting, the American Academy of Veterinary Pharmacology and Therapeutics hosted a 1-day session on the influence of population variability on dose-exposure-response relationships. In Part I, we highlighted some of the sources of population variability. Part II provides a summary of discussions on modelling and simulation tools that utilize existing pharmacokinetic data, can integrate drug physicochemical characteristics with species physiological characteristics and dosing information or that combine observed with predicted and in vitro information to explore and describe sources of variability that may influence the safe and effective use of veterinary pharmaceuticals. © 2018 John Wiley & Sons Ltd. This article has been contributed to by US Government employees and their work is in the public domain in the USA.

Simulation of the Impact of Climate Variability on Malaria Transmission in the Sahel

NASA Astrophysics Data System (ADS)

Bomblies, A.; Eltahir, E.; Duchemin, J.

2007-12-01

A coupled hydrology and entomology model for simulation of malaria transmission and malaria transmitting mosquito population dynamics is presented. Model development and validation is done using field data and observations collected at Banizoumbou and Zindarou, Niger spanning three wet seasons, from 2005 through 2007. The primary model objective is the accurate determination of climate variability effects on village scale malaria transmission. Malaria transmission dependence on climate variables is highly nonlinear and complex. Temperature and humidity affect mosquito longevity, temperature controls parasite development rates in the mosquito as well as subadult mosquito development rates, and precipitation determines the formation and persistence of adequate breeding pools. Moreover, unsaturated zone hydrology influences overland flow, and climate controlled evapotranspiration rates and root zone uptake therefore also influence breeding pool formation. High resolution distributed hydrologic simulation allows representation of the small-scale ephemeral pools that constitute the primary habitat of Anopheles gambiae mosquitoes, the dominant malaria vectors in the Niger Sahel. Remotely sensed soil type, vegetation type, and microtopography rasters are used to assign the distributed parameter fields for simulation of the land surface hydrologic response to precipitation and runoff generation. Predicted runoff from each cell flows overland and into topographic depressions, with explicit representation of infiltration and evapotranspiration. The model's entomology component interacts with simulated pools. Subadult (aquatic stage) mosquito breeding is simulated in the pools, and water temperature dependent stage advancement rates regulate adult mosquito emergence into the model domain. Once emerged, adult mosquitoes are tracked as independent individual agents that interact with their immediate environment. Attributes relevant to malaria transmission such as gonotrophic state, infected and infectious states, age, and location relative to human population are tracked for each individual. The model operates at a resolution consistent with the characteristic scale of relevant ecological processes. Microhabitat exploitation and spatial structure of the mosquito population surrounding villages is reproduced in this manner. The resulting coupled model predicts not only malaria transmission's response to interannual climate variability, but can also evaluate land use change effects on malaria transmission. The late Professor Andrew Spielman of the Harvard School of Public Health provided medical entomology expertise and was a part of this effort.

A Comparison of Grizzly Bear Demographic Parameters Estimated from Non-Spatial and Spatial Open Population Capture-Recapture Models

PubMed Central

Whittington, Jesse; Sawaya, Michael A.

2015-01-01

Capture-recapture studies are frequently used to monitor the status and trends of wildlife populations. Detection histories from individual animals are used to estimate probability of detection and abundance or density. The accuracy of abundance and density estimates depends on the ability to model factors affecting detection probability. Non-spatial capture-recapture models have recently evolved into spatial capture-recapture models that directly include the effect of distances between an animal’s home range centre and trap locations on detection probability. Most studies comparing non-spatial and spatial capture-recapture biases focussed on single year models and no studies have compared the accuracy of demographic parameter estimates from open population models. We applied open population non-spatial and spatial capture-recapture models to three years of grizzly bear DNA-based data from Banff National Park and simulated data sets. The two models produced similar estimates of grizzly bear apparent survival, per capita recruitment, and population growth rates but the spatial capture-recapture models had better fit. Simulations showed that spatial capture-recapture models produced more accurate parameter estimates with better credible interval coverage than non-spatial capture-recapture models. Non-spatial capture-recapture models produced negatively biased estimates of apparent survival and positively biased estimates of per capita recruitment. The spatial capture-recapture grizzly bear population growth rates and 95% highest posterior density averaged across the three years were 0.925 (0.786–1.071) for females, 0.844 (0.703–0.975) for males, and 0.882 (0.779–0.981) for females and males combined. The non-spatial capture-recapture population growth rates were 0.894 (0.758–1.024) for females, 0.825 (0.700–0.948) for males, and 0.863 (0.771–0.957) for both sexes. The combination of low densities, low reproductive rates, and predominantly negative population growth rates suggest that Banff National Park’s population of grizzly bears requires continued conservation-oriented management actions. PMID:26230262

Effects of sample size on estimates of population growth rates calculated with matrix models.

PubMed

Fiske, Ian J; Bruna, Emilio M; Bolker, Benjamin M

2008-08-28

Matrix models are widely used to study the dynamics and demography of populations. An important but overlooked issue is how the number of individuals sampled influences estimates of the population growth rate (lambda) calculated with matrix models. Even unbiased estimates of vital rates do not ensure unbiased estimates of lambda-Jensen's Inequality implies that even when the estimates of the vital rates are accurate, small sample sizes lead to biased estimates of lambda due to increased sampling variance. We investigated if sampling variability and the distribution of sampling effort among size classes lead to biases in estimates of lambda. Using data from a long-term field study of plant demography, we simulated the effects of sampling variance by drawing vital rates and calculating lambda for increasingly larger populations drawn from a total population of 3842 plants. We then compared these estimates of lambda with those based on the entire population and calculated the resulting bias. Finally, we conducted a review of the literature to determine the sample sizes typically used when parameterizing matrix models used to study plant demography. We found significant bias at small sample sizes when survival was low (survival = 0.5), and that sampling with a more-realistic inverse J-shaped population structure exacerbated this bias. However our simulations also demonstrate that these biases rapidly become negligible with increasing sample sizes or as survival increases. For many of the sample sizes used in demographic studies, matrix models are probably robust to the biases resulting from sampling variance of vital rates. However, this conclusion may depend on the structure of populations or the distribution of sampling effort in ways that are unexplored. We suggest more intensive sampling of populations when individual survival is low and greater sampling of stages with high elasticities.

Novel probabilistic models of spatial genetic ancestry with applications to stratification correction in genome-wide association studies.

PubMed

Bhaskar, Anand; Javanmard, Adel; Courtade, Thomas A; Tse, David

2017-03-15

Genetic variation in human populations is influenced by geographic ancestry due to spatial locality in historical mating and migration patterns. Spatial population structure in genetic datasets has been traditionally analyzed using either model-free algorithms, such as principal components analysis (PCA) and multidimensional scaling, or using explicit spatial probabilistic models of allele frequency evolution. We develop a general probabilistic model and an associated inference algorithm that unify the model-based and data-driven approaches to visualizing and inferring population structure. Our spatial inference algorithm can also be effectively applied to the problem of population stratification in genome-wide association studies (GWAS), where hidden population structure can create fictitious associations when population ancestry is correlated with both the genotype and the trait. Our algorithm Geographic Ancestry Positioning (GAP) relates local genetic distances between samples to their spatial distances, and can be used for visually discerning population structure as well as accurately inferring the spatial origin of individuals on a two-dimensional continuum. On both simulated and several real datasets from diverse human populations, GAP exhibits substantially lower error in reconstructing spatial ancestry coordinates compared to PCA. We also develop an association test that uses the ancestry coordinates inferred by GAP to accurately account for ancestry-induced correlations in GWAS. Based on simulations and analysis of a dataset of 10 metabolic traits measured in a Northern Finland cohort, which is known to exhibit significant population structure, we find that our method has superior power to current approaches. Our software is available at https://github.com/anand-bhaskar/gap . abhaskar@stanford.edu or ajavanma@usc.edu. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

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

Cell population modelling of yeast glycolytic oscillations.

PubMed Central

Henson, Michael A; Müller, Dirk; Reuss, Matthias

2002-01-01

We investigated a cell-population modelling technique in which the population is constructed from an ensemble of individual cell models. The average value or the number distribution of any intracellular property captured by the individual cell model can be calculated by simulation of a sufficient number of individual cells. The proposed method is applied to a simple model of yeast glycolytic oscillations where synchronization of the cell population is mediated by the action of an excreted metabolite. We show that smooth one-dimensional distributions can be obtained with ensembles comprising 1000 individual cells. Random variations in the state and/or structure of individual cells are shown to produce complex dynamic behaviours which cannot be adequately captured by small ensembles. PMID:12206713

Minimum intravenous thrombolysis utilization rates in acute ischemic stroke to achieve population effects on disability: A discrete-event simulation model.

PubMed

Hoffmeister, Lorena; Lavados, Pablo M; Mar, Javier; Comas, Merce; Arrospide, Arantzazu; Castells, Xavier

2016-06-15

The only pharmacological treatment with proven cost-effectiveness in reducing acute ischemic stroke (AIS) associated disability is intravenous thrombolysis with recombinant tissue plasminogen activator but it's utilization rate is still low in most of the world. We estimated the minimum thrombolysis utilization rate needed to decrease the prevalence of stroke-related disability at a population level by using a discrete-event simulation model. The model included efficacy according to time to treatment up to 4.5h, and four scenarios for the utilization of intravenous thrombolysis in eligible patients with AIS: a) 2%; b) 12% c) 25% and d) 40%. We calculated the prevalence of AIS related disability in each scenario, using population based data. The simulation was performed from 2002 to 2017 using the ARENA software. A 2% utilization rate yielded a prevalence of disability of 359.1 per 100,000. Increasing thrombolysis to 12% avoided 779 disabled patients. If the utilization rate was increased to 25%, 1783 disabled patients would be avoided. The maximum scenario of 40% decreased disability to 335.7 per 100,000, avoiding 17% of AIS-related disability. The current utilization rate of intravenous thrombolysis of 2% has minimal population impact. Increasing the rate of utilization to more than 12% is the minimum to have a significant population effect on disability and should be a public policy aim. Copyright © 2016 Elsevier B.V. All rights reserved.

Stochastic multi-scale models of competition within heterogeneous cellular populations: Simulation methods and mean-field analysis.

PubMed

Cruz, Roberto de la; Guerrero, Pilar; Spill, Fabian; Alarcón, Tomás

2016-10-21

We propose a modelling framework to analyse the stochastic behaviour of heterogeneous, multi-scale cellular populations. We illustrate our methodology with a particular example in which we study a population with an oxygen-regulated proliferation rate. Our formulation is based on an age-dependent stochastic process. Cells within the population are characterised by their age (i.e. time elapsed since they were born). The age-dependent (oxygen-regulated) birth rate is given by a stochastic model of oxygen-dependent cell cycle progression. Once the birth rate is determined, we formulate an age-dependent birth-and-death process, which dictates the time evolution of the cell population. The population is under a feedback loop which controls its steady state size (carrying capacity): cells consume oxygen which in turn fuels cell proliferation. We show that our stochastic model of cell cycle progression allows for heterogeneity within the cell population induced by stochastic effects. Such heterogeneous behaviour is reflected in variations in the proliferation rate. Within this set-up, we have established three main results. First, we have shown that the age to the G1/S transition, which essentially determines the birth rate, exhibits a remarkably simple scaling behaviour. Besides the fact that this simple behaviour emerges from a rather complex model, this allows for a huge simplification of our numerical methodology. A further result is the observation that heterogeneous populations undergo an internal process of quasi-neutral competition. Finally, we investigated the effects of cell-cycle-phase dependent therapies (such as radiation therapy) on heterogeneous populations. In particular, we have studied the case in which the population contains a quiescent sub-population. Our mean-field analysis and numerical simulations confirm that, if the survival fraction of the therapy is too high, rescue of the quiescent population occurs. This gives rise to emergence of resistance to therapy since the rescued population is less sensitive to therapy. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Hybrid stochastic simulations of intracellular reaction-diffusion systems.

PubMed

Kalantzis, Georgios

2009-06-01

With the observation that stochasticity is important in biological systems, chemical kinetics have begun to receive wider interest. While the use of Monte Carlo discrete event simulations most accurately capture the variability of molecular species, they become computationally costly for complex reaction-diffusion systems with large populations of molecules. On the other hand, continuous time models are computationally efficient but they fail to capture any variability in the molecular species. In this study a hybrid stochastic approach is introduced for simulating reaction-diffusion systems. We developed an adaptive partitioning strategy in which processes with high frequency are simulated with deterministic rate-based equations, and those with low frequency using the exact stochastic algorithm of Gillespie. Therefore the stochastic behavior of cellular pathways is preserved while being able to apply it to large populations of molecules. We describe our method and demonstrate its accuracy and efficiency compared with the Gillespie algorithm for two different systems. First, a model of intracellular viral kinetics with two steady states and second, a compartmental model of the postsynaptic spine head for studying the dynamics of Ca+2 and NMDA receptors.

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...

Simulating fish assemblages in riverine networks

EPA Science Inventory

We describe a modeling approach for simulating assemblages of fish in riverine landscapes. The approach allows a user to determine the grain and extent of river networks within which fish populations reproduce, move, and survive in response to both environmental drivers and assem...

A full annual cycle modeling framework for American black ducks

USGS Publications Warehouse

Robinson, Orin J.; McGowan, Conor P.; Devers, Patrick K.; Brook, Rodney W.; Huang, Min; Jones, Malcom; McAuley, Daniel G.; Zimmerman, Guthrie S.

2016-01-01

American black ducks (Anas rubripes) are a harvested, international migratory waterfowl species in eastern North America. Despite an extended period of restrictive harvest regulations, the black duck population is still below the population goal identified in the North American Waterfowl Management Plan (NAWMP). It has been hypothesized that density-dependent factors restrict population growth in the black duck population and that habitat management (increases, improvements, etc.) may be a key component of growing black duck populations and reaching the prescribed NAWMP population goal. Using banding data from 1951 to 2011 and breeding population survey data from 1990 to 2014, we developed a full annual cycle population model for the American black duck. This model uses the seven management units as set by the Black Duck Joint Venture, allows movement into and out of each unit during each season, and models survival and fecundity for each region separately. We compare model population trajectories with observed population data and abundance estimates from the breeding season counts to show the accuracy of this full annual cycle model. With this model, we then show how to simulate the effects of habitat management on the continental black duck population.

Accounting for genotype uncertainty in the estimation of allele frequencies in autopolyploids.

PubMed

Blischak, Paul D; Kubatko, Laura S; Wolfe, Andrea D

2016-05-01

Despite the increasing opportunity to collect large-scale data sets for population genomic analyses, the use of high-throughput sequencing to study populations of polyploids has seen little application. This is due in large part to problems associated with determining allele copy number in the genotypes of polyploid individuals (allelic dosage uncertainty-ADU), which complicates the calculation of important quantities such as allele frequencies. Here, we describe a statistical model to estimate biallelic SNP frequencies in a population of autopolyploids using high-throughput sequencing data in the form of read counts. We bridge the gap from data collection (using restriction enzyme based techniques [e.g. GBS, RADseq]) to allele frequency estimation in a unified inferential framework using a hierarchical Bayesian model to sum over genotype uncertainty. Simulated data sets were generated under various conditions for tetraploid, hexaploid and octoploid populations to evaluate the model's performance and to help guide the collection of empirical data. We also provide an implementation of our model in the R package polyfreqs and demonstrate its use with two example analyses that investigate (i) levels of expected and observed heterozygosity and (ii) model adequacy. Our simulations show that the number of individuals sampled from a population has a greater impact on estimation error than sequencing coverage. The example analyses also show that our model and software can be used to make inferences beyond the estimation of allele frequencies for autopolyploids by providing assessments of model adequacy and estimates of heterozygosity. © 2015 John Wiley & Sons Ltd.

Computer simulation of population dynamics inside the urban environment

NASA Astrophysics Data System (ADS)

Andreev, A. S.; Inovenkov, I. N.; Echkina, E. Yu.; Nefedov, V. V.; Ponomarenko, L. S.; Tikhomirov, V. V.

2017-12-01

In this paper using a mathematical model of the so-called “space-dynamic” approach we investigate the problem of development and temporal dynamics of different urban population groups. For simplicity we consider an interaction of only two population groups inside a single urban area with axial symmetry. This problem can be described qualitatively by a system of two non-stationary nonlinear differential equations of the diffusion type with boundary conditions of the third type. The results of numerical simulations show that with a suitable choice of the diffusion coefficients and interaction functions between different population groups we can receive different scenarios of population dynamics: from complete displacement of one population group by another (originally more “aggressive”) to the “peaceful” situation of co-existence of them together.

Potential demographic and genetic effects of a sterilant applied to wild horse mares

USGS Publications Warehouse

Roelle, James E.; Oyler-McCance, Sara J.

2015-01-01

Wild horse populations on western ranges can increase rapidly, resulting in the need for the Bureau of Land Management (BLM) to remove animals in order to protect the habitat that horses share with numerous other species. As an alternative to removals, BLM has sought to develop a long-term, perhaps even permanent, contraceptive to aid in reducing population growth rates. With long-term (perhaps even permanent) efficacy of contraception, however, comes increased concern about the genetic health of populations and about the potential for local extirpation. We used simulation modeling to examine the potential demographic and genetic consequences of applying a mare sterilant to wild horse populations. Using the VORTEX software package, we modeled the potential effects of a sterilant on 70 simulated populations having different initial sizes (7 values), growth rates (5 values), and genetic diversity (2 values). For each population, we varied the treatment rate of mares from 0 to 100 percent in increments of 10 percent. For each combination of these treatment levels, we ran 100 stochastic simulations, and we present the results in the form of tables and graphs showing mean population size after 20 years, mean number of removals after 20 years, mean probability of extirpation after 50 years, and mean heterozygosity after 50 years. By choosing one or two combinations of initial population size, population growth rate, and genetic diversity that best represent a herd of interest, a manager can assess the likely effects of a contraceptive program by examining the output tables and graphs representing the selected conditions.

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

Developing approaches for linear mixed modeling in landscape genetics through landscape-directed dispersal simulations

USGS Publications Warehouse

Row, Jeffrey R.; Knick, Steven T.; Oyler-McCance, Sara J.; Lougheed, Stephen C.; Fedy, Bradley C.

2017-01-01

Dispersal can impact population dynamics and geographic variation, and thus, genetic approaches that can establish which landscape factors influence population connectivity have ecological and evolutionary importance. Mixed models that account for the error structure of pairwise datasets are increasingly used to compare models relating genetic differentiation to pairwise measures of landscape resistance. A model selection framework based on information criteria metrics or explained variance may help disentangle the ecological and landscape factors influencing genetic structure, yet there are currently no consensus for the best protocols. Here, we develop landscape-directed simulations and test a series of replicates that emulate independent empirical datasets of two species with different life history characteristics (greater sage-grouse; eastern foxsnake). We determined that in our simulated scenarios, AIC and BIC were the best model selection indices and that marginal R2 values were biased toward more complex models. The model coefficients for landscape variables generally reflected the underlying dispersal model with confidence intervals that did not overlap with zero across the entire model set. When we controlled for geographic distance, variables not in the underlying dispersal models (i.e., nontrue) typically overlapped zero. Our study helps establish methods for using linear mixed models to identify the features underlying patterns of dispersal across a variety of landscapes.

Population pharmacokinetics of recombinant coagulation factor VIII-SingleChain in patients with severe hemophilia A.

PubMed

Zhang, Y; Roberts, J; Tortorici, M; Veldman, A; St Ledger, K; Feussner, A; Sidhu, J

2017-06-01

Essentials rVIII-SingleChain is a unique recombinant factor VIII (FVIII) molecule. A population pharmacokinetic model was based on FVIII activity of severe hemophilia A patients. The model was used to simulate factor VIII activity-time profiles for various dosing scenarios. The model supports prolonged dosing of rVIII-SingleChain with intervals of up to twice per week. Background Single-chain recombinant coagulation factor VIII (rVIII-SingleChain) is a unique recombinant coagulation factor VIII molecule. Objectives To: (i) characterize the population pharmacokinetics (PK) of rVIII-SingleChain in patients with severe hemophilia A; (ii) identify correlates of variability in rVIII-SingleChain PK; and (iii) simulate various dosing scenarios of rVIII-SingleChain. Patients/Methods A population PK model was developed, based on FVIII activity levels of 130 patients with severe hemophilia A (n = 91 for ≥ 12-65 years; n = 39 for < 12 years) who had participated in a single-dose PK investigation with rVIII-SingleChain 50 IU kg -1 . PK sampling was performed for up to 96 h. Results A two-compartment population PK model with first-order elimination adequately described FVIII activity. Body weight and predose level of von Willebrand factor were significant covariates on clearance, and body weight was a significant covariate on the central distribution volume. Simulations using the model with various dosing scenarios estimated that > 85% and > 93% of patients were predicted to maintain FVIII activity level above 1 IU dL -1 , at all times with three-times-weekly dosing (given on days 0, 2, and 4.5) at the lowest (20 IU kg -1 ) and highest (50 IU kg -1 ) doses, respectively. For twice weekly dosing (days 0 and 3.5) of 50 IU kg -1 rVIII-SingleChain, 62-80% of patients across all ages were predicted to maintain a FVIII activity level above 1 IU dL -1 at day 7. Conclusions The population PK model adequately characterized rVIII-SingleChain PK, and the model can be utilized to simulate FVIII activity-time profiles for various dosing scenarios. © 2017 The Authors. Journal of Thrombosis and Haemostasis published by Wiley Periodicals, Inc. on behalf of International Society on Thrombosis and Haemostasis.

Evaluation of model predictions of the ecological effects of 4-nonylphenol -- before and after model refinement

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

Hanratty, M.P.; Liber, K.

1994-12-31

The Littoral Ecosystem Risk Assessment Model (LERAM) is a bioenergetic ecosystem effects model. It links single species toxicity data to a bioenergetic model of the trophic structure of an ecosystem in order to simulate community and ecosystem level effects of chemical stressors. LERAM was used in 1992 to simulate the ecological effects of diflubenzuron. When compared to the results from a littoral enclosure study, the model exaggerated the cascading of effects through the trophic levels of the littoral ecosystem. It was hypothesized that this could be corrected by making minor changes in the representation of the littoral food web. Twomore » refinements of the model were therefore performed: (1) the plankton and macroinvertebrate model populations [eg., predatory Copepoda, herbivorous Insecta, green phytoplankton, etc.] were changed to better represent the habitat and feeding preferences of the endemic taxa; and (2) the method for modeling the microbial degradation of detritus (and the resulting nutrient remineralization) was changed from simulating bacterial populations to simulating bacterial function. Model predictions of the ecological effects of 4-nonylphenol were made before and after these refinements. Both sets of predictions were then compared to the results from a littoral enclosure study of the ecological effects of 4-nonylphenol. The changes in the LERAM predictions were then used to determine the success of the refinements, to guide. future research, and to further define LERAM`s domain of application.« less

Modeling and simulation of count data.

PubMed

Plan, E L

2014-08-13

Count data, or number of events per time interval, are discrete data arising from repeated time to event observations. Their mean count, or piecewise constant event rate, can be evaluated by discrete probability distributions from the Poisson model family. Clinical trial data characterization often involves population count analysis. This tutorial presents the basics and diagnostics of count modeling and simulation in the context of pharmacometrics. Consideration is given to overdispersion, underdispersion, autocorrelation, and inhomogeneity.

Simulation models in population breast cancer screening: A systematic review.

PubMed

Koleva-Kolarova, Rositsa G; Zhan, Zhuozhao; Greuter, Marcel J W; Feenstra, Talitha L; De Bock, Geertruida H

2015-08-01

The aim of this review was to critically evaluate published simulation models for breast cancer screening of the general population and provide a direction for future modeling. A systematic literature search was performed to identify simulation models with more than one application. A framework for qualitative assessment which incorporated model type; input parameters; modeling approach, transparency of input data sources/assumptions, sensitivity analyses and risk of bias; validation, and outcomes was developed. Predicted mortality reduction (MR) and cost-effectiveness (CE) were compared to estimates from meta-analyses of randomized control trials (RCTs) and acceptability thresholds. Seven original simulation models were distinguished, all sharing common input parameters. The modeling approach was based on tumor progression (except one model) with internal and cross validation of the resulting models, but without any external validation. Differences in lead times for invasive or non-invasive tumors, and the option for cancers not to progress were not explicitly modeled. The models tended to overestimate the MR (11-24%) due to screening as compared to optimal RCTs 10% (95% CI - 2-21%) MR. Only recently, potential harms due to regular breast cancer screening were reported. Most scenarios resulted in acceptable cost-effectiveness estimates given current thresholds. The selected models have been repeatedly applied in various settings to inform decision making and the critical analysis revealed high risk of bias in their outcomes. Given the importance of the models, there is a need for externally validated models which use systematical evidence for input data to allow for more critical evaluation of breast cancer screening. Copyright © 2015 Elsevier Ltd. All rights reserved.

Testing spatial heterogeneity with stock assessment models

PubMed Central

Eero, Margit; Silva, Alexandra; Ulrich, Clara; Pawlowski, Lionel; Holmes, Steven J.; Ibaibarriaga, Leire; De Oliveira, José A. A.; Riveiro, Isabel; Alzorriz, Nekane; Citores, Leire; Scott, Finlay; Uriarte, Andres; Carrera, Pablo; Duhamel, Erwan; Mosqueira, Iago

2018-01-01

This paper describes a methodology that combines meta-population theory and stock assessment models to gain insights about spatial heterogeneity of the meta-population in an operational time frame. The methodology was tested with stochastic simulations for different degrees of connectivity between sub-populations and applied to two case studies, North Sea cod (Gadus morua) and Northeast Atlantic sardine (Sardina pilchardus). Considering that the biological components of a population can be partitioned into discrete spatial units, we extended this idea into a property of additivity of sub-population abundances. If the additivity results hold true for putative sub-populations, then assessment results based on sub-populations will provide information to develop and monitor the implementation of finer scale/local management. The simulation study confirmed that when sub-populations are independent and not too heterogeneous with regards to productivity, the sum of stock assessment model estimates of sub-populations’ SSB is similar to the SSB estimates of the meta-population. It also showed that a strong diffusion process can be detected and that the stronger the connection between SSB and recruitment, the better the diffusion process will be detected. On the other hand it showed that weak to moderate diffusion processes are not easy to identify and large differences between sub-populations productivities may be confounded with weak diffusion processes. The application to North Sea cod and Atlantic sardine exemplified how much insight can be gained. In both cases the results obtained were sufficiently robust to support the regional analysis. PMID:29364901

Modeling the impact of biota on polychlorinated biphenyls (PCBs) fate and transport in Lake Ontario using a population-based multi-compartment fugacity approach.

PubMed

Sun, Xiangfei; Ng, Carla A; Small, Mitchell J

2018-06-12

Organisms have long been treated as receptors in exposure studies of polychlorinated biphenyls (PCBs) and other persistent organic pollutants (POPs). The influences of environmental pollution on organisms are well recognized. However, the impact of biota on PCB transport in an environmental system has not been considered in sufficient detail. In this study, a population-based multi-compartment fugacity model is developed by reconfiguring the organisms as populated compartments and reconstructing all the exchange processes between the organism compartments and environmental compartments, especially the previously ignored feedback routes from biota to the environment. We evaluate the model performance by simulating the PCB concentration distribution in Lake Ontario using published loading records. The lake system is divided into three environment compartments (air, water, and sediment) and several organism groups according to the dominant local biotic species. The comparison indicates that the simulated results are well-matched by a list of published field measurements from different years. We identify a new process, called Facilitated Biotic Intermedia Transport (FBIT), to describe the enhanced pollution transport that occurs between environmental media and organisms. As the hydrophobicity of PCB congener increases, the organism population exerts greater influence on PCB mass flows. In a high biomass scenario, the model simulation indicates significant FBIT effects and biotic storage effects with hydrophobic PCB congeners, which also lead to significant shifts in systemic contaminant exchange rates between organisms and the environment. Copyright © 2018 Elsevier Ltd. All rights reserved.

Trap configuration and spacing influences parameter estimates in spatial capture-recapture models

USGS Publications Warehouse

Sun, Catherine C.; Fuller, Angela K.; Royle, J. Andrew

2014-01-01

An increasing number of studies employ spatial capture-recapture models to estimate population size, but there has been limited research on how different spatial sampling designs and trap configurations influence parameter estimators. Spatial capture-recapture models provide an advantage over non-spatial models by explicitly accounting for heterogeneous detection probabilities among individuals that arise due to the spatial organization of individuals relative to sampling devices. We simulated black bear (Ursus americanus) populations and spatial capture-recapture data to evaluate the influence of trap configuration and trap spacing on estimates of population size and a spatial scale parameter, sigma, that relates to home range size. We varied detection probability and home range size, and considered three trap configurations common to large-mammal mark-recapture studies: regular spacing, clustered, and a temporal sequence of different cluster configurations (i.e., trap relocation). We explored trap spacing and number of traps per cluster by varying the number of traps. The clustered arrangement performed well when detection rates were low, and provides for easier field implementation than the sequential trap arrangement. However, performance differences between trap configurations diminished as home range size increased. Our simulations suggest it is important to consider trap spacing relative to home range sizes, with traps ideally spaced no more than twice the spatial scale parameter. While spatial capture-recapture models can accommodate different sampling designs and still estimate parameters with accuracy and precision, our simulations demonstrate that aspects of sampling design, namely trap configuration and spacing, must consider study area size, ranges of individual movement, and home range sizes in the study population.

Bottleneck Effect on Evolutionary Rate in the Nearly Neutral Mutation Model

PubMed Central

Araki, H.; Tachida, H.

1997-01-01

Variances of evolutionary rates among lineages in some proteins are larger than those expected from simple Poisson processes. This phenomenon is called overdispersion of the molecular clock. If population size N is constant, the overdispersion is observed only in a limited range of 2Nσ under the nearly neutral mutation model, where σ represents the standard deviation of selection coefficients of new mutants. In this paper, we investigated effects of changing population size on the evolutionary rate by computer simulations assuming the nearly neutral mutation model. The size was changed cyclically between two numbers, N(1) and N(2) (N(1) > N(2)), in the simulations. The overdispersion is observed if 2N(2)σ is less than two and the state of reduced size (bottleneck state) continues for more than ~0.1/u generations, where u is the mutation rate. The overdispersion results mainly because the average fitnesses of only a portion of populations go down when the population size is reduced and only in these populations subsequent advantageous substitutions occur after the population size becomes large. Since the fitness reduction after the bottleneck is stochastic, acceleration of the evolutionary rate does not necessarily occur uniformly among loci. From these results, we argue that the nearly neutral mutation model is a candidate mechanism to explain the overdispersed molecular clock. PMID:9335622

Modeling Transformation and Conjugation in Bacteria Populations

NASA Astrophysics Data System (ADS)

Russo, John; Dong, J. J.

The rise of antibiotic resistance in bacteria populations is a growing threat to medical treatment of diseases. Transformation, where a cell absorbs a plasmid from its environment, and conjugation, direct transfer of a plasmid from one cell to another, are the two main mechanisms of emergence of antibiotic resistance. We model the processes using a combined approach of Kinetic Monte Carlo simulation and differential equations to describe the plasmid-carrying and plasmid-free populations. Through analysis of our results, we characterize the conditions that lead to dominance of the antibiotic resistant population. NSF-DMR #1248387.

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.

Comparing models on the genealogical relationships among Neandertal, Cro-Magnoid and modern Europeans by serial coalescent simulations.

PubMed

Belle, E M S; Benazzo, A; Ghirotto, S; Colonna, V; Barbujani, G

2009-03-01

Populations of anatomically archaic (Neandertal) and early modern (Cro-Magnoid) humans are jointly documented in the European fossil record, in the period between 40 000 and 25 000 years BP, but the large differences between their cultures, morphologies and DNAs suggest that the two groups were not close relatives. However, it is still unclear whether any genealogical continuity between them can be ruled out. Here, we simulated a broad range of demographic scenarios by means of a serial coalescence algorithm in which Neandertals, Cro-Magnoids and modern Europeans were either part of the same mitochondrial genealogy or of two separate genealogies. Mutation rates, population sizes, population structure and demographic growth rates varied across simulations. All models in which anatomically modern (that is, Cro-Magnoid and current) Europeans belong to a distinct genealogy performed better than any model in which the three groups were assigned to the same mitochondrial genealogy. The maximum admissible level of gene flow between Neandertals and the ancestors of current Europeans is 0.001% per generation, one order of magnitude lower than estimated in previous studies not considering genetic data on Cro-Magnoid people.

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

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.

Modelling Pseudocalanus elongatus stage-structured population dynamics embedded in a water column ecosystem model for the northern North Sea

NASA Astrophysics Data System (ADS)

Moll, Andreas; Stegert, Christoph

2007-01-01

This paper outlines an approach to couple a structured zooplankton population model with state variables for eggs, nauplii, two copepodites stages and adults adapted to Pseudocalanus elongatus into the complex marine ecosystem model ECOHAM2 with 13 state variables resolving the carbon and nitrogen cycle. Different temperature and food scenarios derived from laboratory culture studies were examined to improve the process parameterisation for copepod stage dependent development processes. To study annual cycles under realistic weather and hydrographic conditions, the coupled ecosystem-zooplankton model is applied to a water column in the northern North Sea. The main ecosystem state variables were validated against observed monthly mean values. Then vertical profiles of selected state variables were compared to the physical forcing to study differences between zooplankton as one biomass state variable or partitioned into five population state variables. Simulated generation times are more affected by temperature than food conditions except during the spring phytoplankton bloom. Up to six generations within the annual cycle can be discerned in the simulation.

A microcomputer based traffic evacuation modeling system for emergency planning application

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

Rathi, A.K.

1995-12-31

The US Army stockpiles unitary chemical weapons, both as bulk chemicals and as munitions, at eight major sites in the United States. The continued storage and disposal of the chemical stockpile has the potential for accidental releases of toxic gases that could escape the installation boundaries and pose a threat to the civilian population in the vicinity. Vehicular evacuation is one of the major and often preferred protective action options available for emergency management in a real or anticipated disaster. Computer simulation models of evacuation traffic flow are used to estimate the time required for the affected populations to evacuatemore » to safer areas, to evaluate effectiveness of vehicular evacuations as a protective action option, and to develop comprehensive evacuation plans when required. Following a review of the past efforts to simulate traffic flow during emergency evacuations, an overview of the key features in Version 2.0 of the Oak Ridge Evacuation Modeling System (OREMS) are presented in this paper. OREMS is a microcomputer-based model developed to simulate traffic flow during regional emergency evacuations. OREMS integrates a state-of-the-art dynamic traffic flow and simulation model with advanced data editing and output display programs operating under a MS-Windows environment.« less

Consistent post-reaction vibrational energy redistribution in DSMC simulations using TCE model

NASA Astrophysics Data System (ADS)

Borges Sebastião, Israel; Alexeenko, Alina

2016-10-01

The direct simulation Monte Carlo (DSMC) method has been widely applied to study shockwaves, hypersonic reentry flows, and other nonequilibrium flow phenomena. Although there is currently active research on high-fidelity models based on ab initio data, the total collision energy (TCE) and Larsen-Borgnakke (LB) models remain the most often used chemistry and relaxation models in DSMC simulations, respectively. The conventional implementation of the discrete LB model, however, may not satisfy detailed balance when recombination and exchange reactions play an important role in the flow energy balance. This issue can become even more critical in reacting mixtures involving polyatomic molecules, such as in combustion. In this work, this important shortcoming is addressed and an empirical approach to consistently specify the post-reaction vibrational states close to thermochemical equilibrium conditions is proposed within the TCE framework. Following Bird's quantum-kinetic (QK) methodology for populating post-reaction states, the new TCE-based approach involves two main steps. The state-specific TCE reaction probabilities for a forward reaction are first pre-computed from equilibrium 0-D simulations. These probabilities are then employed to populate the post-reaction vibrational states of the corresponding reverse reaction. The new approach is illustrated by application to exchange and recombination reactions relevant to H2-O2 combustion processes.

Assessing uncertainties in global cropland futures using a conditional probabilistic modelling framework

NASA Astrophysics Data System (ADS)

Engström, Kerstin; Olin, Stefan; Rounsevell, Mark D. A.; Brogaard, Sara; van Vuuren, Detlef P.; Alexander, Peter; Murray-Rust, Dave; Arneth, Almut

2016-11-01

We present a modelling framework to simulate probabilistic futures of global cropland areas that are conditional on the SSP (shared socio-economic pathway) scenarios. Simulations are based on the Parsimonious Land Use Model (PLUM) linked with the global dynamic vegetation model LPJ-GUESS (Lund-Potsdam-Jena General Ecosystem Simulator) using socio-economic data from the SSPs and climate data from the RCPs (representative concentration pathways). The simulated range of global cropland is 893-2380 Mha in 2100 (± 1 standard deviation), with the main uncertainties arising from differences in the socio-economic conditions prescribed by the SSP scenarios and the assumptions that underpin the translation of qualitative SSP storylines into quantitative model input parameters. Uncertainties in the assumptions for population growth, technological change and cropland degradation were found to be the most important for global cropland, while uncertainty in food consumption had less influence on the results. The uncertainties arising from climate variability and the differences between climate change scenarios do not strongly affect the range of global cropland futures. Some overlap occurred across all of the conditional probabilistic futures, except for those based on SSP3. We conclude that completely different socio-economic and climate change futures, although sharing low to medium population development, can result in very similar cropland areas on the aggregated global scale.

The Influence of Spatial Configuration of Residential Area and Vector Populations on Dengue Incidence Patterns in an Individual-Level Transmission Model.

PubMed

Kang, Jeon-Young; Aldstadt, Jared

2017-07-15

Dengue is a mosquito-borne infectious disease that is endemic in tropical and subtropical countries. Many individual-level simulation models have been developed to test hypotheses about dengue virus transmission. Often these efforts assume that human host and mosquito vector populations are randomly or uniformly distributed in the environment. Although, the movement of mosquitoes is affected by spatial configuration of buildings and mosquito populations are highly clustered in key buildings, little research has focused on the influence of the local built environment in dengue transmission models. We developed an agent-based model of dengue transmission in a village setting to test the importance of using realistic environments in individual-level models of dengue transmission. The results from one-way ANOVA analysis of simulations indicated that the differences between scenarios in terms of infection rates as well as serotype-specific dominance are statistically significant. Specifically, the infection rates in scenarios of a realistic environment are more variable than those of a synthetic spatial configuration. With respect to dengue serotype-specific cases, we found that a single dengue serotype is more often dominant in realistic environments than in synthetic environments. An agent-based approach allows a fine-scaled analysis of simulated dengue incidence patterns. The results provide a better understanding of the influence of spatial heterogeneity on dengue transmission at a local scale.

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-based respiratory 4D motion atlas construction and its application for VR simulations of liver punctures

NASA Astrophysics Data System (ADS)

Mastmeyer, Andre; Wilms, Matthias; Handels, Heinz

2018-03-01

Virtual reality (VR) training simulators of liver needle insertion in the hepatic area of breathing virtual patients often need 4D image data acquisitions as a prerequisite. Here, first a population-based breathing virtual patient 4D atlas is built and second the requirement of a dose-relevant or expensive acquisition of a 4D CT or MRI data set for a new patient can be mitigated by warping the mean atlas motion. The breakthrough contribution of this work is the construction and reuse of population-based, learned 4D motion models.

An Investigation of the Effectiveness of Computer Simulation Programs as Tutorial Tools for Teaching Population Ecology at University.

ERIC Educational Resources Information Center

Korfiatis, K.; Papatheodorou, E.; Paraskevopoulous, S.; Stamou, G. P.

1999-01-01

Describes a study of the effectiveness of computer-simulation programs in enhancing biology students' familiarity with ecological modeling and concepts. Finds that computer simulations improved student comprehension of ecological processes expressed in mathematical form, but did not allow a full understanding of ecological concepts. Contains 28…

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.

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.

Modeling the effect of transient populations on epidemics in Washington DC.

PubMed

Parikh, Nidhi; Youssef, Mina; Swarup, Samarth; Eubank, Stephen

2013-11-06

Large numbers of transients visit big cities, where they come into contact with many people at crowded areas. However, epidemiological studies have not paid much attention to the role of this subpopulation in disease spread. We evaluate the effect of transients on epidemics by extending a synthetic population model for the Washington DC metro area to include leisure and business travelers. A synthetic population is obtained by combining multiple data sources to build a detailed minute-by-minute simulation of population interaction resulting in a contact network. We simulate an influenza-like illness over the contact network to evaluate the effects of transients on the number of infected residents. We find that there are significantly more infections when transients are considered. Since much population mixing happens at major tourism locations, we evaluate two targeted interventions: closing museums and promoting healthy behavior (such as the use of hand sanitizers, covering coughs, etc.) at museums. Surprisingly, closing museums has no beneficial effect. However, promoting healthy behavior at the museums can both reduce and delay the epidemic peak. We analytically derive the reproductive number and perform stability analysis using an ODE-based model.

Deleterious mutations and selection for sex in finite diploid populations.

PubMed

Roze, Denis; Michod, Richard E

2010-04-01

In diploid populations, indirect benefits of sex may stem from segregation and recombination. Although it has been recognized that finite population size is an important component of selection for recombination, its effects on selection for segregation have been somewhat less studied. In this article, we develop analytical two- and three-locus models to study the effect of recurrent deleterious mutations on a modifier gene increasing sex, in a finite diploid population. The model also incorporates effects of mitotic recombination, causing loss of heterozygosity (LOH). Predictions are tested using multilocus simulations representing deleterious mutations occurring at a large number of loci. The model and simulations show that excess of heterozygosity generated by finite population size is an important component of selection for sex, favoring segregation when deleterious alleles are nearly additive to dominant. Furthermore, sex tends to break correlations in homozygosity among selected loci, which disfavors sex when deleterious alleles are either recessive or dominant. As a result, we find that it is difficult to maintain costly sex when deleterious alleles are recessive. LOH tends to favor sex when deleterious mutations are recessive, but the effect is relatively weak for rates of LOH corresponding to current estimates (of the order 10(-4)-10(-5)).

Modeling the effect of transient populations on epidemics in Washington DC

NASA Astrophysics Data System (ADS)

Parikh, Nidhi; Youssef, Mina; Swarup, Samarth; Eubank, Stephen

2013-11-01

Large numbers of transients visit big cities, where they come into contact with many people at crowded areas. However, epidemiological studies have not paid much attention to the role of this subpopulation in disease spread. We evaluate the effect of transients on epidemics by extending a synthetic population model for the Washington DC metro area to include leisure and business travelers. A synthetic population is obtained by combining multiple data sources to build a detailed minute-by-minute simulation of population interaction resulting in a contact network. We simulate an influenza-like illness over the contact network to evaluate the effects of transients on the number of infected residents. We find that there are significantly more infections when transients are considered. Since much population mixing happens at major tourism locations, we evaluate two targeted interventions: closing museums and promoting healthy behavior (such as the use of hand sanitizers, covering coughs, etc.) at museums. Surprisingly, closing museums has no beneficial effect. However, promoting healthy behavior at the museums can both reduce and delay the epidemic peak. We analytically derive the reproductive number and perform stability analysis using an ODE-based model.

Towards a realistic population of simulated galaxy groups and clusters

NASA Astrophysics Data System (ADS)

Le Brun, Amandine M. C.; McCarthy, Ian G.; Schaye, Joop; Ponman, Trevor J.

2014-06-01

We present a new suite of large-volume cosmological hydrodynamical simulations called cosmo-OWLS. They form an extension to the OverWhelmingly Large Simulations (OWLS) project, and have been designed to help improve our understanding of cluster astrophysics and non-linear structure formation, which are now the limiting systematic errors when using clusters as cosmological probes. Starting from identical initial conditions in either the Planck or WMAP7 cosmologies, we systematically vary the most important `sub-grid' physics, including feedback from supernovae and active galactic nuclei (AGN). We compare the properties of the simulated galaxy groups and clusters to a wide range of observational data, such as X-ray luminosity and temperature, gas mass fractions, entropy and density profiles, Sunyaev-Zel'dovich flux, I-band mass-to-light ratio, dominance of the brightest cluster galaxy and central massive black hole (BH) masses, by producing synthetic observations and mimicking observational analysis techniques. These comparisons demonstrate that some AGN feedback models can produce a realistic population of galaxy groups and clusters, broadly reproducing both the median trend and, for the first time, the scatter in physical properties over approximately two decades in mass (1013 M⊙ ≲ M500 ≲ 1015 M⊙) and 1.5 decades in radius (0.05 ≲ r/r500 ≲ 1.5). However, in other models, the AGN feedback is too violent (even though they reproduce the observed BH scaling relations), implying that calibration of the models is required. The production of realistic populations of simulated groups and clusters, as well as models that bracket the observations, opens the door to the creation of synthetic surveys for assisting the astrophysical and cosmological interpretation of cluster surveys, as well as quantifying the impact of selection effects.

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.

Exploring the persistence of stream-dwelling trout populations under alternative real-world turbidity regimes with an individual-based model

Treesearch

Bret C. Harvey; Steven F. Railsback

2009-01-01

We explored the effects of elevated turbidity on stream-resident populations of coastal cutthroat trout Oncorhynchus clarkii clarkii using a spatially explicit individual-based model. Turbidity regimes were contrasted by means of 15-year simulations in a third-order stream in northwestern California. The alternative regimes were based on multiple-year, continuous...

Effects of habitat characteristics on the growth of carrier population leading to increased spread of typhoid fever: a model.

PubMed

Shukla, J B; Goyal, Ashish; Singh, Shikha; Chandra, Peeyush

2014-06-01

In this paper, a non-linear model is proposed and analyzed to study the effects of habitat characteristics favoring logistically growing carrier population leading to increased spread of typhoid fever. It is assumed that the cumulative density of habitat characteristics and the density of carrier population are governed by logistic models; the growth rate of the former increases as the density of human population increases. The model is analyzed by stability theory of differential equations and computer simulation. The analysis shows that as the density of the infective carrier population increases due to habitat characteristics, the spread of typhoid fever increases in comparison with the case without such factors. Copyright © 2013 Ministry of Health, Saudi Arabia. Published by Elsevier Ltd. All rights reserved.

Modeling the clinical and economic implications of obesity using microsimulation.

PubMed

Su, W; Huang, J; Chen, F; Iacobucci, W; Mocarski, M; Dall, T M; Perreault, L

2015-01-01

The obesity epidemic has raised considerable public health concerns, but there are few validated longitudinal simulation models examining the human and economic cost of obesity. This paper describes a microsimulation model as a comprehensive tool to understand the relationship between body weight, health, and economic outcomes. Patient health and economic outcomes were simulated annually over 10 years using a Markov-based microsimulation model. The obese population examined is nationally representative of obese adults in the US from the 2005-2012 National Health and Nutrition Examination Surveys, while a matched normal weight population was constructed to have similar demographics as the obese population during the same period. Prediction equations for onset of obesity-related comorbidities, medical expenditures, economic outcomes, mortality, and quality-of-life came from published trials and studies supplemented with original research. Model validation followed International Society for Pharmacoeconomics and Outcomes Research practice guidelines. Among surviving adults, relative to a matched normal weight population, obese adults averaged $3900 higher medical expenditures in the initial year, growing to $4600 higher expenditures in year 10. Obese adults had higher initial prevalence and higher simulated onset of comorbidities as they aged. Over 10 years, excess medical expenditures attributed to obesity averaged $4280 annually-ranging from $2820 for obese category I to $5100 for obese category II, and $8710 for obese category III. Each excess kilogram of weight contributed to $140 higher annual costs, on average, ranging from $136 (obese I) to $152 (obese III). Poor health associated with obesity increased work absenteeism and mortality, and lowered employment probability, personal income, and quality-of-life. This validated model helps illustrate why obese adults have higher medical and indirect costs relative to normal weight adults, and shows that medical costs for obese adults rise more rapidly with aging relative to normal weight adults.

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.

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

Simulating fish assemblages in riverine networks - September 2013

EPA Science Inventory

We describe a modeling approach for simulating assemblages of fish in riverine landscapes. The approach allows a user to determine the grain and extent of river networks within which fish populations reproduce, move, and survive in response to both environmental drivers and assem...

A Population Synthesis Study of Terrestrial Gamma-ray Flashes

NASA Astrophysics Data System (ADS)

Cramer, E. S.; Briggs, M. S.; Stanbro, M.; Dwyer, J. R.; Mailyan, B. G.; Roberts, O.

2017-12-01

In astrophysics, population synthesis models are tools used to determine what mix of stars could be consistent with the observations, e.g. how the intrinsic mass-to-light ratio changes by the measurement process. A similar technique could be used to understand the production of TGFs. The models used for this type of population study probe the conditions of electron acceleration inside the high electric field regions of thunderstorms, i.e. acceleration length, electric field strength, and beaming angles. In this work, we use a Monte Carlo code to generate bremsstrahlung photons from relativistic electrons that are accelerated by a large-scale RREA thunderstorm electric field. The code simulates the propagation of photons through the atmosphere at various source altitudes, where they interact with air via Compton scattering, pair production, and photoelectric absorption. We then show the differences in the hardness ratio at spacecraft altitude between these different simulations and compare them with TGF data from Fermi-GBM. Such comparisons can lead to constraints that can be applied to popular TGF beaming models, and help determine whether the population presented in this study is consistent or not with reality.

Modeling Test and Treatment Strategies for Presymptomatic Alzheimer Disease

PubMed Central

Burke, James F.; Langa, Kenneth M.; Hayward, Rodney A.; Albin, Roger L.

2014-01-01

Objectives In this study, we developed a model of presymptomatic treatment of Alzheimer disease (AD) after a screening diagnostic evaluation and explored the circumstances required for an AD prevention treatment to produce aggregate net population benefit. Methods Monte Carlo simulation methods were used to estimate outcomes in a simulated population derived from data on AD incidence and mortality. A wide variety of treatment parameters were explored. Net population benefit was estimated in aggregated QALYs. Sensitivity analyses were performed by individually varying the primary parameters. Findings In the base-case scenario, treatment effects were uniformly positive, and net benefits increased with increasing age at screening. A highly efficacious treatment (i.e. relative risk 0.6) modeled in the base-case is estimated to save 20 QALYs per 1000 patients screened and 221 QALYs per 1000 patients treated. Conclusions Highly efficacious presymptomatic screen and treat strategies for AD are likely to produce substantial aggregate population benefits that are likely greater than the benefits of aspirin in primary prevention of moderate risk cardiovascular disease (28 QALYS per 1000 patients treated), even in the context of an imperfect treatment delivery environment. PMID:25474698

Toll-like receptor variation in the bottlenecked population of the Seychelles warbler: computer simulations see the 'ghost of selection past' and quantify the 'drift debt'.

PubMed

Gilroy, D L; Phillips, K P; Richardson, D S; van Oosterhout, C

2017-07-01

Balancing selection can maintain immunogenetic variation within host populations, but detecting its signal in a postbottlenecked population is challenging due to the potentially overriding effects of drift. Toll-like receptor genes (TLRs) play a fundamental role in vertebrate immune defence and are predicted to be under balancing selection. We previously characterized variation at TLR loci in the Seychelles warbler (Acrocephalus sechellensis), an endemic passerine that has undergone a historical bottleneck. Five of seven TLR loci were polymorphic, which is in sharp contrast to the low genomewide variation observed. However, standard population genetic statistical methods failed to detect a contemporary signature of selection at any TLR locus. We examined whether the observed TLR polymorphism could be explained by neutral evolution, simulating the population's demography in the software DIYABC. This showed that the posterior distributions of mutation rates had to be unrealistically high to explain the observed genetic variation. We then conducted simulations with an agent-based model using typical values for the mutation rate, which indicated that weak balancing selection has acted on the three TLR genes. The model was able to detect evidence of past selection elevating TLR polymorphism in the prebottleneck populations, but was unable to discern any effects of balancing selection in the contemporary population. Our results show drift is the overriding evolutionary force that has shaped TLR variation in the contemporary Seychelles warbler population, and the observed TLR polymorphisms might be merely the 'ghost of selection past'. Forecast models predict immunogenetic variation in this species will continue to be eroded in the absence of contemporary balancing selection. Such 'drift debt' occurs when a gene pool has not yet reached its new equilibrium level of polymorphism, and this loss could be an important threat to many recently bottlenecked populations. © 2017 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2017 European Society For Evolutionary Biology.

Exploring first-order phase transitions with population annealing

NASA Astrophysics Data System (ADS)

Barash, Lev Yu.; Weigel, Martin; Shchur, Lev N.; Janke, Wolfhard

2017-03-01

Population annealing is a hybrid of sequential and Markov chain Monte Carlo methods geared towards the efficient parallel simulation of systems with complex free-energy landscapes. Systems with first-order phase transitions are among the problems in computational physics that are difficult to tackle with standard methods such as local-update simulations in the canonical ensemble, for example with the Metropolis algorithm. It is hence interesting to see whether such transitions can be more easily studied using population annealing. We report here our preliminary observations from population annealing runs for the two-dimensional Potts model with q > 4, where it undergoes a first-order transition.

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

A trans-national monarch butterfly population model and implications for regional conservation priorities

USGS Publications Warehouse

Oberhauser, Karen; Wiederholt, Ruscena; Diffendorfer, James E.; Semmens, Darius J.; Ries, Leslie; Thogmartin, Wayne E.; Lopez-Hoffman, Laura; Semmens, Brice

2017-01-01

1. The monarch has undergone considerable population declines over the past decade, and the governments of Mexico, Canada, and the United States have agreed to work together to conserve the species.2. Given limited resources, understanding where to focus conservation action is key for widespread species like monarchs. To support planning for continental-scale monarch habitat restoration, we address the question of where restoration efforts are likely to have the largest impacts on monarch butterfly (Danaus plexippus Linn.) population growth rates.3. We present a spatially explicit demographic model simulating the multi-generational annual cycle of the eastern monarch population, and use the model to examine management scenarios, some of which focus on particular regions of North America.4. Improving the monarch habitat in the north central or southern parts of the monarch range yields a slightly greater increase in the population growth rate than restoration in other regions. However, combining restoration efforts across multiple regions yields population growth rates above 1 with smaller simulated improvements in habitat per region than single-region strategies.5. Synthesis and applications: These findings suggest that conservation investment in projects across the full monarch range will be more effective than focusing on one or a few regions, and will require international cooperation across many land use categories.

Evaluating estimators for numbers of females with cubs-of-the-year in the Yellowstone grizzly bear population

USGS Publications Warehouse

Cherry, S.; White, G.C.; Keating, K.A.; Haroldson, Mark A.; Schwartz, Charles C.

2007-01-01

Current management of the grizzly bear (Ursus arctos) population in Yellowstone National Park and surrounding areas requires annual estimation of the number of adult female bears with cubs-of-the-year. We examined the performance of nine estimators of population size via simulation. Data were simulated using two methods for different combinations of population size, sample size, and coefficient of variation of individual sighting probabilities. We show that the coefficient of variation does not, by itself, adequately describe the effects of capture heterogeneity, because two different distributions of capture probabilities can have the same coefficient of variation. All estimators produced biased estimates of population size with bias decreasing as effort increased. Based on the simulation results we recommend the Chao estimator for model M h be used to estimate the number of female bears with cubs of the year; however, the estimator of Chao and Shen may also be useful depending on the goals of the research.

[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.

Impacts of high resolution data on traveler compliance levels in emergency evacuation simulations

DOE PAGES

Lu, Wei; Han, Lee D.; Liu, Cheng; ...

2016-05-05

In this article, we conducted a comparison study of evacuation assignment based on Traffic Analysis Zones (TAZ) and high resolution LandScan USA Population Cells (LPC) with detailed real world roads network. A platform for evacuation modeling built on high resolution population distribution data and activity-based microscopic traffic simulation was proposed. This platform can be extended to any cities in the world. The results indicated that evacuee compliance behavior affects evacuation efficiency with traditional TAZ assignment, but it did not significantly compromise the performance with high resolution LPC assignment. The TAZ assignment also underestimated the real travel time during evacuation. Thismore » suggests that high data resolution can improve the accuracy of traffic modeling and simulation. The evacuation manager should consider more diverse assignment during emergency evacuation to avoid congestions.« less

PSRPOPPy: an open-source package for pulsar population simulations

NASA Astrophysics Data System (ADS)

Bates, S. D.; Lorimer, D. R.; Rane, A.; Swiggum, J.

2014-04-01

We have produced a new software package for the simulation of pulsar populations, PSRPOPPY, based on the PSRPOP package. The codebase has been re-written in Python (save for some external libraries, which remain in their native Fortran), utilizing the object-oriented features of the language, and improving the modularity of the code. Pre-written scripts are provided for running the simulations in `standard' modes of operation, but the code is flexible enough to support the writing of personalised scripts. The modular structure also makes the addition of experimental features (such as new models for period or luminosity distributions) more straightforward than with the previous code. We also discuss potential additions to the modelling capabilities of the software. Finally, we demonstrate some potential applications of the code; first, using results of surveys at different observing frequencies, we find pulsar spectral indices are best fitted by a normal distribution with mean -1.4 and standard deviation 1.0. Secondly, we model pulsar spin evolution to calculate the best fit for a relationship between a pulsar's luminosity and spin parameters. We used the code to replicate the analysis of Faucher-Giguère & Kaspi, and have subsequently optimized their power-law dependence of radio luminosity, L, with period, P, and period derivative, Ṗ. We find that the underlying population is best described by L ∝ P-1.39±0.09 Ṗ0.48±0.04 and is very similar to that found for γ-ray pulsars by Perera et al. Using this relationship, we generate a model population and examine the age-luminosity relation for the entire pulsar population, which may be measurable after future large-scale surveys with the Square Kilometre Array.

Multi-scale modeling in cell biology

PubMed Central

Meier-Schellersheim, Martin; Fraser, Iain D. C.; Klauschen, Frederick

2009-01-01

Biomedical research frequently involves performing experiments and developing hypotheses that link different scales of biological systems such as, for instance, the scales of intracellular molecular interactions to the scale of cellular behavior and beyond to the behavior of cell populations. Computational modeling efforts that aim at exploring such multi-scale systems quantitatively with the help of simulations have to incorporate several different simulation techniques due to the different time and space scales involved. Here, we provide a non-technical overview of how different scales of experimental research can be combined with the appropriate computational modeling techniques. We also show that current modeling software permits building and simulating multi-scale models without having to become involved with the underlying technical details of computational modeling. PMID:20448808

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

From blackbirds to black holes: Investigating capture-recapture methods for time domain astronomy

NASA Astrophysics Data System (ADS)

Laycock, Silas G. T.

2017-07-01

In time domain astronomy, recurrent transients present a special problem: how to infer total populations from limited observations. Monitoring observations may give a biassed view of the underlying population due to limitations on observing time, visibility and instrumental sensitivity. A similar problem exists in the life sciences, where animal populations (such as migratory birds) or disease prevalence, must be estimated from sparse and incomplete data. The class of methods termed Capture-Recapture is used to reconstruct population estimates from time-series records of encounters with the study population. This paper investigates the performance of Capture-Recapture methods in astronomy via a series of numerical simulations. The Blackbirds code simulates monitoring of populations of transients, in this case accreting binary stars (neutron star or black hole accreting from a stellar companion) under a range of observing strategies. We first generate realistic light-curves for populations of binaries with contrasting orbital period distributions. These models are then randomly sampled at observing cadences typical of existing and planned monitoring surveys. The classical capture-recapture methods, Lincoln-Peterson, Schnabel estimators, related techniques, and newer methods implemented in the Rcapture package are compared. A general exponential model based on the radioactive decay law is introduced which is demonstrated to recover (at 95% confidence) the underlying population abundance and duty cycle, in a fraction of the observing visits (10-50%) required to discover all the sources in the simulation. Capture-Recapture is a promising addition to the toolbox of time domain astronomy, and methods implemented in R by the biostats community can be readily called from within python.

Comparing predictions of extinction risk using models and subjective judgement

NASA Astrophysics Data System (ADS)

McCarthy, Michael A.; Keith, David; Tietjen, Justine; Burgman, Mark A.; Maunder, Mark; Master, Larry; Brook, Barry W.; Mace, Georgina; Possingham, Hugh P.; Medellin, Rodrigo; Andelman, Sandy; Regan, Helen; Regan, Tracey; Ruckelshaus, Mary

2004-10-01

Models of population dynamics are commonly used to predict risks in ecology, particularly risks of population decline. There is often considerable uncertainty associated with these predictions. However, alternatives to predictions based on population models have not been assessed. We used simulation models of hypothetical species to generate the kinds of data that might typically be available to ecologists and then invited other researchers to predict risks of population declines using these data. The accuracy of the predictions was assessed by comparison with the forecasts of the original model. The researchers used either population models or subjective judgement to make their predictions. Predictions made using models were only slightly more accurate than subjective judgements of risk. However, predictions using models tended to be unbiased, while subjective judgements were biased towards over-estimation. Psychology literature suggests that the bias of subjective judgements is likely to vary somewhat unpredictably among people, depending on their stake in the outcome. This will make subjective predictions more uncertain and less transparent than those based on models.

Medicanes in an ocean-atmosphere coupled regional climate model

NASA Astrophysics Data System (ADS)

Akhtar, Naveed; Brauch, Jennifer; Ahrens, Bodo

2014-05-01

So-called medicanes (Mediterranean hurricanes) are meso-scale, marine and warm core Mediterranean cyclones which exhibit some similarities with tropical cyclones. The strong cyclonic winds associated with them are a potential thread for highly populated coastal areas around the Mediterranean basin. In this study we employ an atmospheric limited-area model (COSMO-CLM) coupled with a one-dimensional ocean model (NEMO-1d) to simulate medicanes. The goal of this study is to assess the robustness of the coupled model to simulate these extreme events. For this purpose 11 historical medicane events are simulated by the atmosphere-only and the coupled models using different set-ups (horizontal grid-spacings: 0.44o, 0.22o, 0.088o; with/with-out spectral nudging). The results show that at high resolution the coupled model is not only able to simulate all medicane events but also improves the simulated track length, warm core, and wind speed of simulated medicanes compared to atmosphere-only simulations. In most of the cases the medicanes trajectories and structures are better represented in coupled simulations compared to atmosphere-only simulations. We conclude that the coupled model is a suitable tool for systemic and detailed study of historical medicane events and also for future projections.

Conserving genomic variability in large mammals: Effect of population fluctuations and variance in male reproductive success on variability in Yellowstone bison

Treesearch

Andres Perez-Figueroa; Rick L. Wallen; Tiago Antao; Jason A. Coombs; Michael K. Schwartz; P. J. White; Gordon Luikart

2012-01-01

Loss of genetic variation through genetic drift can reduce population viability. However, relatively little is known about loss of variation caused by the combination of fluctuating population size and variance in reproductive success in age structured populations. We built an individual-based computer simulation model to examine how actual culling and hunting...

Computer simulations for lab experiences in secondary physics

NASA Astrophysics Data System (ADS)

Murphy, David Shannon

Physical science instruction often involves modeling natural systems, such as electricity that possess particles which are invisible to the unaided eye. The effect of these particles' motion is observable, but the particles are not directly observable to humans. Simulations have been developed in physics, chemistry and biology that, under certain circumstances, have been found to allow students to gain insight into the operation of the systems they model. This study compared the use of a DC circuit simulation, a modified simulation, static graphics, and traditional bulbs and wires to compare gains in DC circuit knowledge as measured by the DIRECT instrument, a multiple choice instrument previously developed to assess DC circuit knowledge. Gender, prior DC circuit knowledge and subsets of DC circuit knowledge of students were also compared. The population (n=166) was comprised of high school freshmen students from an eastern Kentucky public school with a population of 1100 students and followed a quantitative quasi experimental research design. Differences between treatment groups were not statistically significant. Keywords: Simulations, Static Images, Science Education, DC Circuit Instruction, Phet.

A systems approach to healthcare: agent-based modeling, community mental health, and population well-being.

PubMed

Silverman, Barry G; Hanrahan, Nancy; Bharathy, Gnana; Gordon, Kim; Johnson, Dan

2015-02-01

Explore whether agent-based modeling and simulation can help healthcare administrators discover interventions that increase population wellness and quality of care while, simultaneously, decreasing costs. Since important dynamics often lie in the social determinants outside the health facilities that provide services, this study thus models the problem at three levels (individuals, organizations, and society). The study explores the utility of translating an existing (prize winning) software for modeling complex societal systems and agent's daily life activities (like a Sim City style of software), into a desired decision support system. A case study tests if the 3 levels of system modeling approach is feasible, valid, and useful. The case study involves an urban population with serious mental health and Philadelphia's Medicaid population (n=527,056), in particular. Section 3 explains the models using data from the case study and thereby establishes feasibility of the approach for modeling a real system. The models were trained and tuned using national epidemiologic datasets and various domain expert inputs. To avoid co-mingling of training and testing data, the simulations were then run and compared (Section 4.1) to an analysis of 250,000 Philadelphia patient hospital admissions for the year 2010 in terms of re-hospitalization rate, number of doctor visits, and days in hospital. Based on the Student t-test, deviations between simulated vs. real world outcomes are not statistically significant. Validity is thus established for the 2008-2010 timeframe. We computed models of various types of interventions that were ineffective as well as 4 categories of interventions (e.g., reduced per-nurse caseload, increased check-ins and stays, etc.) that result in improvement in well-being and cost. The 3 level approach appears to be useful to help health administrators sort through system complexities to find effective interventions at lower costs. Copyright © 2014 Elsevier B.V. All rights reserved.

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.

Modeling the effects of trophy selection and environmental disturbance on a simulated population of African lions.

PubMed

Whitman, Karyl L; Starfield, Anthony M; Quadling, Henley; Packer, Craig

2007-06-01

Tanzania is a premier destination for trophy hunting of African lions (Panthera leo) and is home to the most extensive long-term study of unhunted lions. Thus, it provides a unique opportunity to apply data from a long-term field study to a conservation dilemma: How can a trophy-hunted species whose reproductive success is closely tied to social stability be harvested sustainably? We used an individually based, spatially explicit, stochastic model, parameterized with nearly 40 years of behavioral and demographic data on lions in the Serengeti, to examine the separate effects of trophy selection and environmental disturbance on the viability of a simulated lion population in response to annual harvesting. Female population size was sensitive to the harvesting of young males (> or = 3 years), whereas hunting represented a relatively trivial threat to population viability when the harvest was restricted to mature males (> or = 6 years). Overall model performance was robust to environmental disturbance and to errors in age assessment based on nose coloration as an index used to age potential trophies. Introducing an environmental disturbance did not eliminate the capacity to maintain a viable breeding population when harvesting only older males, and initially depleted populations recovered within 15-25 years after the disturbance to levels comparable to hunted populations that did not experience a catastrophic event. These results are consistent with empirical observations of lion resilience to environmental stochasticity.

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 ...

A model for evaluation of satellite population management alternatives

NASA Astrophysics Data System (ADS)

Penny, R. E., Jr.; Jones, R. K.

1983-12-01

A Q-GERT model was developed to simulate the satellite environment, including the untracked man-made population, and to calculate a probability of collision for any satellite of interest. Provision for launches, explosions, collisions (including ASAT), retrieval, reposition, and decay was made. The model is structured to easily vary the rates at which these activities occur and to observe changes in the satellite population through which a satellite of interest must travel. Variance of the rates, and the resultant change in probability of collision allows evaluation of satellite population management alternatives such as reducing launch rates or increasing retrieval of spent, but still capable of exploding, satellites. The model is proposed for use by both the USAF SPACE COMMAND and NASA.

Cosmic reionization on computers. Ultraviolet continuum slopes and dust opacities in high redshift galaxies

DOE PAGES

Khakhaleva-Li, Zimu; Gnedin, Nickolay Y.

2016-03-30

In this study, we compare the properties of stellar populations of model galaxies from the Cosmic Reionization On Computers (CROC) project with the exiting UV and IR data. Since CROC simulations do not follow cosmic dust directly, we adopt two variants of the dust-follows-metals ansatz to populate model galaxies with dust. Using the dust radiative transfer code Hyperion, we compute synthetic stellar spectra, UV continuum slopes, and IR fluxes for simulated galaxies. We find that the simulation results generally match observational measurements, but, perhaps, not in full detail. The differences seem to indicate that our adopted dust-follows-metals ansatzes are notmore » fully sufficient. While the discrepancies with the exiting data are marginal, the future JWST data will be of much higher precision, rendering highly significant any tentative difference between theory and observations. It is, therefore, likely, that in order to fully utilize the precision of JWST observations, fully dynamical modeling of dust formation, evolution, and destruction may be required.« less

Cosmic reionization on computers. Ultraviolet continuum slopes and dust opacities in high redshift galaxies

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

Khakhaleva-Li, Zimu; Gnedin, Nickolay Y.

In this study, we compare the properties of stellar populations of model galaxies from the Cosmic Reionization On Computers (CROC) project with the exiting UV and IR data. Since CROC simulations do not follow cosmic dust directly, we adopt two variants of the dust-follows-metals ansatz to populate model galaxies with dust. Using the dust radiative transfer code Hyperion, we compute synthetic stellar spectra, UV continuum slopes, and IR fluxes for simulated galaxies. We find that the simulation results generally match observational measurements, but, perhaps, not in full detail. The differences seem to indicate that our adopted dust-follows-metals ansatzes are notmore » fully sufficient. While the discrepancies with the exiting data are marginal, the future JWST data will be of much higher precision, rendering highly significant any tentative difference between theory and observations. It is, therefore, likely, that in order to fully utilize the precision of JWST observations, fully dynamical modeling of dust formation, evolution, and destruction may be required.« 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

A dynamic population model to investigate effects of climate and climate-independent factors on the lifecycle of the tick Amblyomma americanum (Acari: Ixodidae)

USGS Publications Warehouse

Ludwig, Antoinette; Ginsberg, Howard; Hickling, Graham J.; Ogden, Nicholas H.

2016-01-01

The lone star tick, Amblyomma americanum, is a disease vector of significance for human and animal health throughout much of the eastern United States. To model the potential effects of climate change on this tick, a better understanding is needed of the relative roles of temperature-dependent and temperature-independent (day-length-dependent behavioral or morphogenetic diapause) processes acting on the tick lifecycle. In this study, we explored the roles of these processes by simulating seasonal activity patterns using models with site-specific temperature and day-length-dependent processes. We first modeled the transitions from engorged larvae to feeding nymphs, engorged nymphs to feeding adults, and engorged adult females to feeding larvae. The simulated seasonal patterns were compared against field observations at three locations in United States. Simulations suggested that 1) during the larva-to-nymph transition, some larvae undergo no diapause while others undergo morphogenetic diapause of engorged larvae; 2) molted adults undergo behavioral diapause during the transition from nymph-to-adult; and 3) there is no diapause during the adult-to-larva transition. A model constructed to simulate the full lifecycle of A. americanum successfully predicted observed tick activity at the three U.S. study locations. Some differences between observed and simulated seasonality patterns were observed, however, identifying the need for research to refine some model parameters. In simulations run using temperature data for Montreal, deterministic die-out of A. americanum populations did not occur, suggesting the possibility that current climate in parts of southern Canada is suitable for survival and reproduction of this tick.

A Dynamic Population Model to Investigate Effects of Climate and Climate-Independent Factors on the Lifecycle of Amblyomma americanum (Acari: Ixodidae).

PubMed

Ludwig, Antoinette; Ginsberg, Howard S; Hickling, Graham J; Ogden, Nicholas H

2016-01-01

The lone star tick, Amblyomma americanum, is a disease vector of significance for human and animal health throughout much of the eastern United States. To model the potential effects of climate change on this tick, a better understanding is needed of the relative roles of temperature-dependent and temperature-independent (day-length-dependent behavioral or morphogenetic diapause) processes acting on the tick lifecycle. In this study, we explored the roles of these processes by simulating seasonal activity patterns using models with site-specific temperature and day-length-dependent processes. We first modeled the transitions from engorged larvae to feeding nymphs, engorged nymphs to feeding adults, and engorged adult females to feeding larvae. The simulated seasonal patterns were compared against field observations at three locations in United States. Simulations suggested that 1) during the larva-to-nymph transition, some larvae undergo no diapause while others undergo morphogenetic diapause of engorged larvae; 2) molted adults undergo behavioral diapause during the transition from nymph-to-adult; and 3) there is no diapause during the adult-to-larva transition. A model constructed to simulate the full lifecycle of A. americanum successfully predicted observed tick activity at the three U.S. study locations. Some differences between observed and simulated seasonality patterns were observed, however, identifying the need for research to refine some model parameters. In simulations run using temperature data for Montreal, deterministic die-out of A. americanum populations did not occur, suggesting the possibility that current climate in parts of southern Canada is suitable for survival and reproduction of this tick. © Crown copyright 2015.

Leveraging social networks for understanding the evolution of epidemics

PubMed Central

2011-01-01

Background To understand how infectious agents disseminate throughout a population it is essential to capture the social model in a realistic manner. This paper presents a novel approach to modeling the propagation of the influenza virus throughout a realistic interconnection network based on actual individual interactions which we extract from online social networks. The advantage is that these networks can be extracted from existing sources which faithfully record interactions between people in their natural environment. We additionally allow modeling the characteristics of each individual as well as customizing his daily interaction patterns by making them time-dependent. Our purpose is to understand how the infection spreads depending on the structure of the contact network and the individuals who introduce the infection in the population. This would help public health authorities to respond more efficiently to epidemics. Results We implement a scalable, fully distributed simulator and validate the epidemic model by comparing the simulation results against the data in the 2004-2005 New York State Department of Health Report (NYSDOH), with similar temporal distribution results for the number of infected individuals. We analyze the impact of different types of connection models on the virus propagation. Lastly, we analyze and compare the effects of adopting several different vaccination policies, some of them based on individual characteristics -such as age- while others targeting the super-connectors in the social model. Conclusions This paper presents an approach to modeling the propagation of the influenza virus via a realistic social model based on actual individual interactions extracted from online social networks. We implemented a scalable, fully distributed simulator and we analyzed both the dissemination of the infection and the effect of different vaccination policies on the progress of the epidemics. The epidemic values predicted by our simulator match real data from NYSDOH. Our results show that our simulator can be a useful tool in understanding the differences in the evolution of an epidemic within populations with different characteristics and can provide guidance with regard to which, and how many, individuals should be vaccinated to slow down the virus propagation and reduce the number of infections. PMID:22784620

Demographic Consequences of Gender Discrimination in China: Simulation Analysis of Policy Options.

PubMed

Quanbao, Jiang; Shuzhuo, Li; Marcus W, Feldman

2011-08-01

The large number of missing females in China, a consequence of gender discrimination, is having and will continue to have a profound effect on the country's population development. In this paper, we analyze the causes of this gender discrimination in terms of institutions, culture and, economy, and suggest public policies that might help eliminate gender discrimination. Using a population simulation model, we study the effect of public policies on the sex ratio at birth and excess female child mortality, and the effect of gender discrimination on China's population development. We find that gender discrimination will decrease China's population size, number of births, and working age population, accelerate population aging and exacerbate the male marriage squeeze. These results provide theoretical support for suggesting that the government enact and implement public policies aimed at eliminating gender discrimination.

Demographic Consequences of Gender Discrimination in China: Simulation Analysis of Policy Options

PubMed Central

Quanbao, Jiang; Marcus W., Feldman

2013-01-01

The large number of missing females in China, a consequence of gender discrimination, is having and will continue to have a profound effect on the country's population development. In this paper, we analyze the causes of this gender discrimination in terms of institutions, culture and, economy, and suggest public policies that might help eliminate gender discrimination. Using a population simulation model, we study the effect of public policies on the sex ratio at birth and excess female child mortality, and the effect of gender discrimination on China's population development. We find that gender discrimination will decrease China's population size, number of births, and working age population, accelerate population aging and exacerbate the male marriage squeeze. These results provide theoretical support for suggesting that the government enact and implement public policies aimed at eliminating gender discrimination. PMID:24363477

Modelling obesity trends in Australia: unravelling the past and predicting the future.

PubMed

Hayes, A J; Lung, T W C; Bauman, A; Howard, K

2017-01-01

Modelling is increasingly being used to predict the epidemiology of obesity progression and its consequences. The aims of this study were: (a) to present and validate a model for prediction of obesity among Australian adults and (b) to use the model to project the prevalence of obesity and severe obesity by 2025. Individual level simulation combined with survey estimation techniques to model changing population body mass index (BMI) distribution over time. The model input population was derived from a nationally representative survey in 1995, representing over 12 million adults. Simulations were run for 30 years. The model was validated retrospectively and then used to predict obesity and severe obesity by 2025 among different aged cohorts and at a whole population level. The changing BMI distribution over time was well predicted by the model and projected prevalence of weight status groups agreed with population level data in 2008, 2012 and 2014.The model predicts more growth in obesity among younger than older adult cohorts. Projections at a whole population level, were that healthy weight will decline, overweight will remain steady, but obesity and severe obesity prevalence will continue to increase beyond 2016. Adult obesity prevalence was projected to increase from 19% in 1995 to 35% by 2025. Severe obesity (BMI>35), which was only around 5% in 1995, was projected to be 13% by 2025, two to three times the 1995 levels. The projected rise in obesity severe obesity will have more substantial cost and healthcare system implications than in previous decades. Having a robust epidemiological model is key to predicting these long-term costs and health outcomes into the future.

GalMod: A Galactic Synthesis Population Model

NASA Astrophysics Data System (ADS)

Pasetto, Stefano; Grebel, Eva K.; Chiosi, Cesare; Crnojević, Denija; Zeidler, Peter; Busso, Giorgia; Cassarà, Letizia P.; Piovan, Lorenzo; Tantalo, Rosaria; Brogliato, Claudio

2018-06-01

We present a new Galaxy population synthesis Model, GalMod. GalMod is a star-count model featuring an asymmetric bar/bulge as well as spiral arms and related extinction. The model, initially introduced in Pasetto et al., has been here completed with a central bar, a new bulge description, new disk vertical profiles, and several new bolometric corrections. The model can generate synthetic mock catalogs of visible portions of the Milky Way, external galaxies like M31, or N-body simulation initial conditions. At any given time, e.g., at a chosen age of the Galaxy, the model contains a sum of discrete stellar populations, namely the bulge/bar, disk, and halo. These populations are in turn the sum of different components: the disk is the sum of the spiral arms, thin disks, a thick disk, and various gas components, while the halo is the sum of a stellar component, a hot coronal gas, and a dark-matter component. The Galactic potential is computed from these population density profiles and used to generate detailed kinematics by considering up to the first four moments of the collisionless Boltzmann equation. The same density profiles are then used to define the observed color–magnitude diagrams in a user-defined field of view (FoV) from an arbitrary solar location. Several photometric systems have been included and made available online, and no limits on the size of the FoV are imposed thus allowing full-sky simulations, too. Finally, we model the extinction by adopting a dust model with advanced ray-tracing solutions. The model's Web page (and tutorial) can be accessed at www.GalMod.org and support is provided at Galaxy.Model@yahoo.com.

Current levels of gonorrhoea screening in MSM in Belgium may have little effect on prevalence: a modelling study.

PubMed

Buyze, J; Vanden Berghe, W; Hens, N; Kenyon, C

2018-02-01

There is considerable uncertainty as to the effectiveness of Neisseria gonorrhoeae (NG) screening in men who have sex with men. It is important to ensure that screening has benefits that outweigh the risks of increased antibiotics resistance. We develop a mathematical model to estimate the effectiveness of screening on prevalence. Separable Temporal Exponential family Random Graph Models are used to model the sexual relationships network, both with main and casual partners. Next, the transmission of Gonorrhoea is simulated on this network. The models are implemented using the R package 'statnet', which we adapted among other things to incorporate infection status at the pharynx, urethra and rectum separately and to distinguish between anal sex, oral sex and rimming. The different screening programmes compared are no screening, 3.5% of the population screened, 32% screened and 50% screened. The model simulates day-by-day evolution for 10 years of a population of 10 000. If half of the population would be screened, the prevalence in the pharynx decreases from 11.9% to 10.2%. We conclude that the limited impact of screening on NG prevalence may not outweigh the increased risk of antibiotic resistance.

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

Hierarchical demographic approaches for assessing invasion dynamics of non-indigenous species: An example using northern snakehead (Channa argus)

USGS Publications Warehouse

Jiao, Y.; Lapointe, N.W.R.; Angermeier, P.L.; Murphy, B.R.

2009-01-01

Models of species' demographic features are commonly used to understand population dynamics and inform management tactics. Hierarchical demographic models are ideal for the assessment of non-indigenous species because our knowledge of non-indigenous populations is usually limited, data on demographic traits often come from a species' native range, these traits vary among populations, and traits are likely to vary considerably over time as species adapt to new environments. Hierarchical models readily incorporate this spatiotemporal variation in species' demographic traits by representing demographic parameters as multi-level hierarchies. As is done for traditional non-hierarchical matrix models, sensitivity and elasticity analyses are used to evaluate the contributions of different life stages and parameters to estimates of population growth rate. We applied a hierarchical model to northern snakehead (Channa argus), a fish currently invading the eastern United States. We used a Monte Carlo approach to simulate uncertainties in the sensitivity and elasticity analyses and to project future population persistence under selected management tactics. We gathered key biological information on northern snakehead natural mortality, maturity and recruitment in its native Asian environment. We compared the model performance with and without hierarchy of parameters. Our results suggest that ignoring the hierarchy of parameters in demographic models may result in poor estimates of population size and growth and may lead to erroneous management advice. In our case, the hierarchy used multi-level distributions to simulate the heterogeneity of demographic parameters across different locations or situations. The probability that the northern snakehead population will increase and harm the native fauna is considerable. Our elasticity and prognostic analyses showed that intensive control efforts immediately prior to spawning and/or juvenile-dispersal periods would be more effective (and probably require less effort) than year-round control efforts. Our study demonstrates the importance of considering the hierarchy of parameters in estimating population growth rate and evaluating different management strategies for non-indigenous invasive species. ?? 2009 Elsevier B.V.

Detecting directional selection in the presence of recent admixture in African-Americans.

PubMed

Lohmueller, Kirk E; Bustamante, Carlos D; Clark, Andrew G

2011-03-01

We investigate the performance of tests of neutrality in admixed populations using plausible demographic models for African-American history as well as resequencing data from African and African-American populations. The analysis of both simulated and human resequencing data suggests that recent admixture does not result in an excess of false-positive results for neutrality tests based on the frequency spectrum after accounting for the population growth in the parental African population. Furthermore, when simulating positive selection, Tajima's D, Fu and Li's D, and haplotype homozygosity have lower power to detect population-specific selection using individuals sampled from the admixed population than from the nonadmixed population. Fay and Wu's H test, however, has more power to detect selection using individuals from the admixed population than from the nonadmixed population, especially when the selective sweep ended long ago. Our results have implications for interpreting recent genome-wide scans for positive selection in human populations. © 2011 by the Genetics Society of America

Analysis and optimization of population annealing

NASA Astrophysics Data System (ADS)

Amey, Christopher; Machta, Jonathan

2018-03-01

Population annealing is an easily parallelizable sequential Monte Carlo algorithm that is well suited for simulating the equilibrium properties of systems with rough free-energy landscapes. In this work we seek to understand and improve the performance of population annealing. We derive several useful relations between quantities that describe the performance of population annealing and use these relations to suggest methods to optimize the algorithm. These optimization methods were tested by performing large-scale simulations of the three-dimensional (3D) Edwards-Anderson (Ising) spin glass and measuring several observables. The optimization methods were found to substantially decrease the amount of computational work necessary as compared to previously used, unoptimized versions of population annealing. We also obtain more accurate values of several important observables for the 3D Edwards-Anderson model.

Improving Agent Based Models and Validation through Data Fusion

PubMed Central

Laskowski, Marek; Demianyk, Bryan C.P.; Friesen, Marcia R.; McLeod, Robert D.; Mukhi, Shamir N.

2011-01-01

This work is contextualized in research in modeling and simulation of infection spread within a community or population, with the objective to provide a public health and policy tool in assessing the dynamics of infection spread and the qualitative impacts of public health interventions. This work uses the integration of real data sources into an Agent Based Model (ABM) to simulate respiratory infection spread within a small municipality. Novelty is derived in that the data sources are not necessarily obvious within ABM infection spread models. The ABM is a spatial-temporal model inclusive of behavioral and interaction patterns between individual agents on a real topography. The agent behaviours (movements and interactions) are fed by census / demographic data, integrated with real data from a telecommunication service provider (cellular records) and person-person contact data obtained via a custom 3G Smartphone application that logs Bluetooth connectivity between devices. Each source provides data of varying type and granularity, thereby enhancing the robustness of the model. The work demonstrates opportunities in data mining and fusion that can be used by policy and decision makers. The data become real-world inputs into individual SIR disease spread models and variants, thereby building credible and non-intrusive models to qualitatively simulate and assess public health interventions at the population level. PMID:23569606

Improving Agent Based Models and Validation through Data Fusion.

PubMed

Laskowski, Marek; Demianyk, Bryan C P; Friesen, Marcia R; McLeod, Robert D; Mukhi, Shamir N

2011-01-01

This work is contextualized in research in modeling and simulation of infection spread within a community or population, with the objective to provide a public health and policy tool in assessing the dynamics of infection spread and the qualitative impacts of public health interventions. This work uses the integration of real data sources into an Agent Based Model (ABM) to simulate respiratory infection spread within a small municipality. Novelty is derived in that the data sources are not necessarily obvious within ABM infection spread models. The ABM is a spatial-temporal model inclusive of behavioral and interaction patterns between individual agents on a real topography. The agent behaviours (movements and interactions) are fed by census / demographic data, integrated with real data from a telecommunication service provider (cellular records) and person-person contact data obtained via a custom 3G Smartphone application that logs Bluetooth connectivity between devices. Each source provides data of varying type and granularity, thereby enhancing the robustness of the model. The work demonstrates opportunities in data mining and fusion that can be used by policy and decision makers. The data become real-world inputs into individual SIR disease spread models and variants, thereby building credible and non-intrusive models to qualitatively simulate and assess public health interventions at the population level.

Poster - Thur Eve - 55: Monte Carlo simulations of variations in planned dose distributions in a prostate patient population.

PubMed

Balderson, M J; Brown, D W; Quirk, S; Ghasroddashti, E; Kirkby, C

2012-07-01

Clinical outcome studies with clear and objective endpoints are necessary to make informed radiotherapy treatment decisions. Commonly, clinical outcomes are established after lengthy and costly clinical trials are performed and the data are analyzed and published. One the challenges with obtaining meaningful data from clinical trials is that by the time the information gets to the medical profession the results may be less clinically relevant than when the trial began, An alternative approach is to estimate clinical outcomes through patient population modeling. We are developing a mathematical tool that uses Monte Carlo techniques to simulate variations in planned and delivered dose distributions of prostate patients receiving radiotherapy. Ultimately, our simulation will calculate a distribution of Tumor Control Probabilities (TCPs) for a population of patients treated under a given protocol. Such distributions can serve as a metric for comparing different treatment modalities, planning and setup approaches, and machine parameter settings or tolerances with respect to outcomes on broad patient populations. It may also help researchers understand differences one might expect to find before actually doing the clinical trial. As a first step and for the focus of this abstract we wanted to see if we could answer the question: "Can a population of dose distributions of prostate patients be accurately modeled by a set of randomly generated Gaussian functions?" Our results have demonstrated that using a set of randomly generated Gaussian functions can simulate a distribution of prostate patients. © 2012 American Association of Physicists in Medicine.

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.

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.

A new method for calculating time-dependent atomic level populations

NASA Technical Reports Server (NTRS)

Kastner, S. O.

1981-01-01

A method is described for reducing the number of levels to be dealt with in calculating time-dependent populations of atoms or ions in plasmas. The procedure effectively extends the collisional-radiative model to consecutive stages of ionization, treating ground and metastable levels explicitly and excited levels implicitly. Direct comparisons of full and simulated systems are carried out for five-level models.

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.

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).

Estimation of the sensitive volume for gravitational-wave source populations using weighted Monte Carlo integration

NASA Astrophysics Data System (ADS)

Tiwari, Vaibhav

2018-07-01

The population analysis and estimation of merger rates of compact binaries is one of the important topics in gravitational wave astronomy. The primary ingredient in these analyses is the population-averaged sensitive volume. Typically, sensitive volume, of a given search to a given simulated source population, is estimated by drawing signals from the population model and adding them to the detector data as injections. Subsequently injections, which are simulated gravitational waveforms, are searched for by the search pipelines and their signal-to-noise ratio (SNR) is determined. Sensitive volume is estimated, by using Monte-Carlo (MC) integration, from the total number of injections added to the data, the number of injections that cross a chosen threshold on SNR and the astrophysical volume in which the injections are placed. So far, only fixed population models have been used in the estimation of binary black holes (BBH) merger rates. However, as the scope of population analysis broaden in terms of the methodologies and source properties considered, due to an increase in the number of observed gravitational wave (GW) signals, the procedure will need to be repeated multiple times at a large computational cost. In this letter we address the problem by performing a weighted MC integration. We show how a single set of generic injections can be weighted to estimate the sensitive volume for multiple population models; thereby greatly reducing the computational cost. The weights in this MC integral are the ratios of the output probabilities, determined by the population model and standard cosmology, and the injection probability, determined by the distribution function of the generic injections. Unlike analytical/semi-analytical methods, which usually estimate sensitive volume using single detector sensitivity, the method is accurate within statistical errors, comes at no added cost and requires minimal computational resources.

Population profiling in China by gender and age: implication for HIV incidences.

PubMed

Pan, Yuanyi; Wu, Jianhong

2009-11-18

With the world's largest population, HIV spread in China has been closely watched and widely studied by its government and the international community. One important factor that might contribute to the epidemic is China's numerous surplus of men, due to its imbalanced sex ratio in newborns. However, the sex ratio in the human population is often assumed to be 1:1 in most studies of sexually transmitted diseases (STDs). Here, a mathematical model is proposed to estimate the population size in each gender and within different stages of reproduction and sexual activities. This population profiling by age and gender will assist in more precise prediction of HIV incidences. The total population is divided into 6 subgroups by gender and age. A deterministic compartmental model is developed to describe birth, death, age and the interactions among different subgroups, with a focus on the preference for newborn boys and its impact for the sex ratios. Data from 2003 to 2007 is used to estimate model parameters, and simulations predict short-term and long-term population profiles. The population of China will go to a descending track around 2030. Despite the possible underestimated number of newborns in the last couple of years, model-based simulations show that there will be about 28 million male individuals in 2055 without female partners during their sexually active stages. The birth rate in China must be increased to keep the population viable. But increasing the birth rate without balancing the sex ratio in newborns is problematic, as this will generate a large number of surplus males. Besides other social, economic and psychological issues, the impact of this surplus of males on STD incidences, including HIV infections, must be dealt with as early as possible.

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.

Particle-Size-Grouping Model of Precipitation Kinetics in Microalloyed Steels

NASA Astrophysics Data System (ADS)

Xu, Kun; Thomas, Brian G.

2012-03-01

The formation, growth, and size distribution of precipitates greatly affects the microstructure and properties of microalloyed steels. Computational particle-size-grouping (PSG) kinetic models based on population balances are developed to simulate precipitate particle growth resulting from collision and diffusion mechanisms. First, the generalized PSG method for collision is explained clearly and verified. Then, a new PSG method is proposed to model diffusion-controlled precipitate nucleation, growth, and coarsening with complete mass conservation and no fitting parameters. Compared with the original population-balance models, this PSG method saves significant computation and preserves enough accuracy to model a realistic range of particle sizes. Finally, the new PSG method is combined with an equilibrium phase fraction model for plain carbon steels and is applied to simulate the precipitated fraction of aluminum nitride and the size distribution of niobium carbide during isothermal aging processes. Good matches are found with experimental measurements, suggesting that the new PSG method offers a promising framework for the future development of realistic models of precipitation.

The migraine ACE model: evaluating the impact on time lost and medical resource Use.

PubMed

Caro, J J; Caro, G; Getsios, D; Raggio, G; Burrows, M; Black, L

2000-04-01

To describe the Migraine Adaptive Cost-Effectiveness Model in the context of an analysis of a simulated population of Canadian patients with migraine. The high prevalence of migraine and its substantial impact on patients' ability to function normally present a significant economic burden to society. In light of the recent availability of improved pharmaceutical treatments, a model was developed to assess their economic impact. The Migraine Adaptive Cost-Effectiveness Model incorporates the costs of time lost from both work and nonwork activities, as well as medical resource and medication use. Using Monte Carlo techniques, the model simulates the experience of a population of patients with migraine over the course of 1 year. As an example, analyses of a Canadian population were carried out using data from a multinational trial, surveys, national statistics, and the available literature. Using customary therapy, mean productivity losses (amounting to 84 hours of paid work time, 48 hours of unpaid work time, and 113 hours of leisure time lost) were estimated to cost $1949 (in 1997 Canadian dollars) per patient, with medical expenditures adding an average of $280 to the cost of illness. With customary treatment patterns, the costs of migraine associated with reduced functional capacity are substantial. The migraine model represents a flexible tool for the economic evaluation of different migraine treatments in various populations.

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.

A Mathematical Tumor Model with Immune Resistance and Drug Therapy: An Optimal Control Approach

DOE PAGES

De Pillis, L. G.; Radunskaya, A.

2001-01-01

We present a competition model of cancer tumor growth that includes both the immune system response and drug therapy. This is a four-population model that includes tumor cells, host cells, immune cells, and drug interaction. We analyze the stability of the drug-free equilibria with respect to the immune response in order to look for target basins of attraction. One of our goals was to simulate qualitatively the asynchronous tumor-drug interaction known as “Jeffs phenomenon.” The model we develop is successful in generating this asynchronous response behavior. Our other goal was to identify treatment protocols that could improve standard pulsed chemotherapymore » regimens. Using optimal control theory with constraints and numerical simulations, we obtain new therapy protocols that we then compare with traditional pulsed periodic treatment. The optimal control generated therapies produce larger oscillations in the tumor population over time. However, by the end of the treatment period, total tumor size is smaller than that achieved through traditional pulsed therapy, and the normal cell population suffers nearly no oscillations.« less

A Mathematical Tumor Model with Immune Resistance and Drug Therapy: An Optimal Control Approach

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

De Pillis, L. G.; Radunskaya, A.

We present a competition model of cancer tumor growth that includes both the immune system response and drug therapy. This is a four-population model that includes tumor cells, host cells, immune cells, and drug interaction. We analyze the stability of the drug-free equilibria with respect to the immune response in order to look for target basins of attraction. One of our goals was to simulate qualitatively the asynchronous tumor-drug interaction known as “Jeffs phenomenon.” The model we develop is successful in generating this asynchronous response behavior. Our other goal was to identify treatment protocols that could improve standard pulsed chemotherapymore » regimens. Using optimal control theory with constraints and numerical simulations, we obtain new therapy protocols that we then compare with traditional pulsed periodic treatment. The optimal control generated therapies produce larger oscillations in the tumor population over time. However, by the end of the treatment period, total tumor size is smaller than that achieved through traditional pulsed therapy, and the normal cell population suffers nearly no oscillations.« less

Population growth, interest rate, and housing tax in the transitional China

NASA Astrophysics Data System (ADS)

He, Ling-Yun; Wen, Xing-Chun

2017-03-01

This paper combines and develops the models in Lastrapes (2002) and Mankiw and Weil (1989), which enables us to analyze the effects of interest rate and population growth shocks on housing price in one integrated framework. Based on this model, we carry out policy simulations to examine whether the housing (stock or flow) tax reduces the housing price fluctuations caused by interest rate or population growth shocks. Simulation results imply that the choice of housing tax tools depends on the kind of shock that housing market faces. In the situation where the housing price volatility is caused by the population growth shock, the flow tax can reduce the volatility of housing price while the stock tax makes no difference to it. If the shock is resulting from the interest rate, the policy maker should not impose any kind of the housing taxes. Furthermore, the effect of one kind of the housing tax can be strengthened by that of the other type of housing tax.

Modeling the effect of surgical sterilization on owned dog population size in Villa de Tezontepec, Hidalgo, Mexico, using an individual-based computer simulation model

PubMed Central

Kisiel, Luz Maria; Jones-Bitton, Andria; Sargeant, Jan M.; Coe, Jason B.; Flockhart, D. T. Tyler; Canales Vargas, Erick J.

2018-01-01

Surgical sterilization programs for dogs have been proposed as interventions to control dog population size. Models can be used to help identify the long-term impact of reproduction control interventions for dogs. The objective of this study was to determine the projected impact of surgical sterilization interventions on the owned dog population size in Villa de Tezontepec, Hidalgo, Mexico. A stochastic, individual-based simulation model was constructed and parameterized using a combination of empirical data collected on the demographics of owned dogs in Villa de Tezontepec and data available from the peer-reviewed literature. Model outcomes were assessed using a 20-year time horizon. The model was used to examine: the effect of surgical sterilization strategies focused on: 1) dogs of any age and sex, 2) female dogs of any age, 3) young dogs (i.e., not yet reached sexual maturity) of any sex, and 4) young, female dogs. Model outcomes suggested that as surgical capacity increases from 21 to 84 surgeries/month, (8.6% to 34.5% annual sterilization) for dogs of any age, the mean dog population size after 20 years was reduced between 14% and 79% compared to the base case scenario (i.e. in the absence of intervention). Surgical sterilization interventions focused only on young dogs of any sex yielded greater reductions (81% - 90%) in the mean population size, depending on the level of surgical capacity. More focused sterilization targeted at female dogs of any age, resulted in reductions that were similar to focusing on mixed sex sterilization of only young dogs (82% - 92%). The greatest mean reduction in population size (90% - 91%) was associated with sterilization of only young, female dogs. Our model suggests that targeting sterilization to young females could enhance the efficacy of existing surgical dog population control interventions in this location, without investing extra resources. PMID:29856830

Treatment cost and life expectancy of diffuse large B-cell lymphoma (DLBCL): a discrete event simulation model on a UK population-based observational cohort.

PubMed

Wang, Han-I; Smith, Alexandra; Aas, Eline; Roman, Eve; Crouch, Simon; Burton, Cathy; Patmore, Russell

2017-03-01

Diffuse large B-cell lymphoma (DLBCL) is the commonest non-Hodgkin lymphoma. Previous studies examining the cost of treating DLBCL have generally focused on a specific first-line therapy alone; meaning that their findings can neither be extrapolated to the general patient population nor to other points along the treatment pathway. Based on empirical data from a representative population-based patient cohort, the objective of this study was to develop a simulation model that could predict costs and life expectancy of treating DLBCL. All patients newly diagnosed with DLBCL in the UK's population-based Haematological Malignancy Research Network ( www.hmrn.org ) in 2007 were followed until 2013 (n = 271). Mapped treatment pathways, alongside cost information derived from the National Tariff 2013/14, were incorporated into a patient-level simulation model in order to reflect the heterogeneities of patient characteristics and treatment options. The NHS and social services perspective was adopted, and all outcomes were discounted at 3.5 % per annum. Overall, the expected total medical costs were £22,122 for those treated with curative intent, and £2930 for those managed palliatively. For curative chemotherapy, the predicted medical costs were £14,966, £23,449 and £7376 for first-, second- and third-line treatments, respectively. The estimated annual cost for treating DLBCL across the UK was around £88-92 million. This is the first cost modelling study using empirical data to provide 'real world' evidence throughout the DLBCL treatment pathway. Future application of the model could include evaluation of new technologies/treatments to support healthcare decision makers, especially in the era of personalised medicine.

A Global System for Transportation Simulation and Visualization in Emergency Evacuation Scenarios

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

Lu, Wei; Liu, Cheng; Thomas, Neil

2015-01-01

Simulation-based studies are frequently used for evacuation planning and decision making processes. Given the transportation systems complexity and data availability, most evacuation simulation models focus on certain geographic areas. With routine improvement of OpenStreetMap road networks and LandScanTM global population distribution data, we present WWEE, a uniform system for world-wide emergency evacuation simulations. WWEE uses unified data structure for simulation inputs. It also integrates a super-node trip distribution model as the default simulation parameter to improve the system computational performance. Two levels of visualization tools are implemented for evacuation performance analysis, including link-based macroscopic visualization and vehicle-based microscopic visualization. Formore » left-hand and right-hand traffic patterns in different countries, the authors propose a mirror technique to experiment with both scenarios without significantly changing traffic simulation models. Ten cities in US, Europe, Middle East, and Asia are modeled for demonstration. With default traffic simulation models for fast and easy-to-use evacuation estimation and visualization, WWEE also retains the capability of interactive operation for users to adopt customized traffic simulation models. For the first time, WWEE provides a unified platform for global evacuation researchers to estimate and visualize their strategies performance of transportation systems under evacuation scenarios.« less

Assessing uncertainty in ecological systems using global sensitivity analyses: a case example of simulated wolf reintroduction effects on elk

USGS Publications Warehouse

Fieberg, J.; Jenkins, Kurt J.

2005-01-01

Often landmark conservation decisions are made despite an incomplete knowledge of system behavior and inexact predictions of how complex ecosystems will respond to management actions. For example, predicting the feasibility and likely effects of restoring top-level carnivores such as the gray wolf (Canis lupus) to North American wilderness areas is hampered by incomplete knowledge of the predator-prey system processes and properties. In such cases, global sensitivity measures, such as Sobola?? indices, allow one to quantify the effect of these uncertainties on model predictions. Sobola?? indices are calculated by decomposing the variance in model predictions (due to parameter uncertainty) into main effects of model parameters and their higher order interactions. Model parameters with large sensitivity indices can then be identified for further study in order to improve predictive capabilities. Here, we illustrate the use of Sobola?? sensitivity indices to examine the effect of parameter uncertainty on the predicted decline of elk (Cervus elaphus) population sizes following a hypothetical reintroduction of wolves to Olympic National Park, Washington, USA. The strength of density dependence acting on survival of adult elk and magnitude of predation were the most influential factors controlling elk population size following a simulated wolf reintroduction. In particular, the form of density dependence in natural survival rates and the per-capita predation rate together accounted for over 90% of variation in simulated elk population trends. Additional research on wolf predation rates on elk and natural compensations in prey populations is needed to reliably predict the outcome of predatora??prey system behavior following wolf reintroductions.

Conceptualizing socio‐hydrological drought processes: The case of the Maya collapse

PubMed Central

Carr, Gemma; Viglione, Alberto; Prskawetz, Alexia; Blöschl, Günter

2016-01-01

Abstract With population growth, increasing water demands and climate change the need to understand the current and future pathways to water security is becoming more pressing. To contribute to addressing this challenge, we examine the link between water stress and society through socio‐hydrological modeling. We conceptualize the interactions between an agricultural society with its environment in a stylized way. We apply the model to the case of the ancient Maya, a population that experienced a peak during the Classic Period (AD 600–830) and then declined during the ninth century. The hypothesis that modest drought periods played a major role in the society's collapse is explored. Simulating plausible feedbacks between water and society we show that a modest reduction in rainfall may lead to an 80% population collapse. Population density and crop sensitivity to droughts, however, may play an equally important role. The simulations indicate that construction of reservoirs results in less frequent drought impacts, but if the reservoirs run dry, drought impact may be more severe and the population drop may be larger. PMID:27840455

Conceptualizing socio-hydrological drought processes: The case of the Maya collapse.

PubMed

Kuil, Linda; Carr, Gemma; Viglione, Alberto; Prskawetz, Alexia; Blöschl, Günter

2016-08-01

With population growth, increasing water demands and climate change the need to understand the current and future pathways to water security is becoming more pressing. To contribute to addressing this challenge, we examine the link between water stress and society through socio-hydrological modeling. We conceptualize the interactions between an agricultural society with its environment in a stylized way. We apply the model to the case of the ancient Maya, a population that experienced a peak during the Classic Period (AD 600-830) and then declined during the ninth century. The hypothesis that modest drought periods played a major role in the society's collapse is explored. Simulating plausible feedbacks between water and society we show that a modest reduction in rainfall may lead to an 80% population collapse. Population density and crop sensitivity to droughts, however, may play an equally important role. The simulations indicate that construction of reservoirs results in less frequent drought impacts, but if the reservoirs run dry, drought impact may be more severe and the population drop may be larger.

Conceptualizing socio-hydrological drought processes: The case of the Maya collapse

NASA Astrophysics Data System (ADS)

Kuil, Linda; Carr, Gemma; Viglione, Alberto; Prskawetz, Alexia; Blöschl, Günter

2016-08-01

With population growth, increasing water demands and climate change the need to understand the current and future pathways to water security is becoming more pressing. To contribute to addressing this challenge, we examine the link between water stress and society through socio-hydrological modeling. We conceptualize the interactions between an agricultural society with its environment in a stylized way. We apply the model to the case of the ancient Maya, a population that experienced a peak during the Classic Period (AD 600-830) and then declined during the ninth century. The hypothesis that modest drought periods played a major role in the society's collapse is explored. Simulating plausible feedbacks between water and society we show that a modest reduction in rainfall may lead to an 80% population collapse. Population density and crop sensitivity to droughts, however, may play an equally important role. The simulations indicate that construction of reservoirs results in less frequent drought impacts, but if the reservoirs run dry, drought impact may be more severe and the population drop may be larger.

A supply model for nurse workforce projection in Malaysia.

PubMed

Abas, Zuraida Abal; Ramli, Mohamad Raziff; Desa, Mohamad Ishak; Saleh, Nordin; Hanafiah, Ainul Nadziha; Aziz, Nuraini; Abidin, Zaheera Zainal; Shibghatullah, Abdul Samad; Rahman, Ahmad Fadzli Nizam Abdul; Musa, Haslinda

2017-08-18

The paper aims to provide an insight into the significance of having a simulation model to forecast the supply of registered nurses for health workforce planning policy using System Dynamics. A model is highly in demand to predict the workforce demand for nurses in the future, which it supports for complete development of a needs-based nurse workforce projection using Malaysia as a case study. The supply model consists of three sub-models to forecast the number of registered nurses for the next 15 years: training model, population model and Full Time Equivalent (FTE) model. In fact, the training model is for predicting the number of newly registered nurses after training is completed. Furthermore, the population model is for indicating the number of registered nurses in the nation and the FTE model is useful for counting the number of registered nurses with direct patient care. Each model is described in detail with the logical connection and mathematical governing equation for accurate forecasting. The supply model is validated using error analysis approach in terms of the root mean square percent error and the Theil inequality statistics, which is mportant for evaluating the simulation results. Moreover, the output of simulation results provides a useful insight for policy makers as a what-if analysis is conducted. Some recommendations are proposed in order to deal with the nursing deficit. It must be noted that the results from the simulation model will be used for the next stage of the Needs-Based Nurse Workforce projection project. The impact of this study is that it provides the ability for greater planning and policy making with better predictions.

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.

Local Variability Mediates Vulnerability of Trout Populations to Land Use and Climate Change

PubMed Central

Penaluna, Brooke E.; Dunham, Jason B.; Railsback, Steve F.; Arismendi, Ivan; Johnson, Sherri L.; Bilby, Robert E.; Safeeq, Mohammad; Skaugset, Arne E.

2015-01-01

Land use and climate change occur simultaneously around the globe. Fully understanding their separate and combined effects requires a mechanistic understanding at the local scale where their effects are ultimately realized. Here we applied an individual-based model of fish population dynamics to evaluate the role of local stream variability in modifying responses of Coastal Cutthroat Trout (Oncorhynchus clarkii clarkii) to scenarios simulating identical changes in temperature and stream flows linked to forest harvest, climate change, and their combined effects over six decades. We parameterized the model for four neighboring streams located in a forested headwater catchment in northwestern Oregon, USA with multi-year, daily measurements of stream temperature, flow, and turbidity (2007–2011), and field measurements of both instream habitat structure and three years of annual trout population estimates. Model simulations revealed that variability in habitat conditions among streams (depth, available habitat) mediated the effects of forest harvest and climate change. Net effects for most simulated trout responses were different from or less than the sum of their separate scenarios. In some cases, forest harvest countered the effects of climate change through increased summer flow. Climate change most strongly influenced trout (earlier fry emergence, reductions in biomass of older trout, increased biomass of young-of-year), but these changes did not consistently translate into reductions in biomass over time. Forest harvest, in contrast, produced fewer and less consistent responses in trout. Earlier fry emergence driven by climate change was the most consistent simulated response, whereas survival, growth, and biomass were inconsistent. Overall our findings indicate a host of local processes can strongly influence how populations respond to broad scale effects of land use and climate change. PMID:26295478

Local variability mediates vulnerability of trout populations to land use and climate change

USGS Publications Warehouse

Penaluna, Brooke E.; Dunham, Jason B.; Railsback, Steve F.; Arismendi, Ivan; Johnson, Sherri L.; Bilby, Robert E; Safeeq, Mohammad; Skaugset, Arne E.

2015-01-01

Land use and climate change occur simultaneously around the globe. Fully understanding their separate and combined effects requires a mechanistic understanding at the local scale where their effects are ultimately realized. Here we applied an individual-based model of fish population dynamics to evaluate the role of local stream variability in modifying responses of Coastal Cutthroat Trout (Oncorhynchus clarkii clarkii) to scenarios simulating identical changes in temperature and stream flows linked to forest harvest, climate change, and their combined effects over six decades. We parameterized the model for four neighboring streams located in a forested headwater catchment in northwestern Oregon, USA with multi-year, daily measurements of stream temperature, flow, and turbidity (2007–2011), and field measurements of both instream habitat structure and three years of annual trout population estimates. Model simulations revealed that variability in habitat conditions among streams (depth, available habitat) mediated the effects of forest harvest and climate change. Net effects for most simulated trout responses were different from or less than the sum of their separate scenarios. In some cases, forest harvest countered the effects of climate change through increased summer flow. Climate change most strongly influenced trout (earlier fry emergence, reductions in biomass of older trout, increased biomass of young-of-year), but these changes did not consistently translate into reductions in biomass over time. Forest harvest, in contrast, produced fewer and less consistent responses in trout. Earlier fry emergence driven by climate change was the most consistent simulated response, whereas survival, growth, and biomass were inconsistent. Overall our findings indicate a host of local processes can strongly influence how populations respond to broad scale effects of land use and climate change.

Impact of Sampling Schemes on Demographic Inference: An Empirical Study in Two Species with Different Mating Systems and Demographic Histories

PubMed Central

St. Onge, K. R.; Palmé, A. E.; Wright, S. I.; Lascoux, M.

2012-01-01

Most species have at least some level of genetic structure. Recent simulation studies have shown that it is important to consider population structure when sampling individuals to infer past population history. The relevance of the results of these computer simulations for empirical studies, however, remains unclear. In the present study, we use DNA sequence datasets collected from two closely related species with very different histories, the selfing species Capsella rubella and its outcrossing relative C. grandiflora, to assess the impact of different sampling strategies on summary statistics and the inference of historical demography. Sampling strategy did not strongly influence the mean values of Tajima’s D in either species, but it had some impact on the variance. The general conclusions about demographic history were comparable across sampling schemes even when resampled data were analyzed with approximate Bayesian computation (ABC). We used simulations to explore the effects of sampling scheme under different demographic models. We conclude that when sequences from modest numbers of loci (<60) are analyzed, the sampling strategy is generally of limited importance. The same is true under intermediate or high levels of gene flow (4Nm > 2–10) in models in which global expansion is combined with either local expansion or hierarchical population structure. Although we observe a less severe effect of sampling than predicted under some earlier simulation models, our results should not be seen as an encouragement to neglect this issue. In general, a good coverage of the natural range, both within and between populations, will be needed to obtain a reliable reconstruction of a species’s demographic history, and in fact, the effect of sampling scheme on polymorphism patterns may itself provide important information about demographic history. PMID:22870403

Local Variability Mediates Vulnerability of Trout Populations to Land Use and Climate Change.

PubMed

Penaluna, Brooke E; Dunham, Jason B; Railsback, Steve F; Arismendi, Ivan; Johnson, Sherri L; Bilby, Robert E; Safeeq, Mohammad; Skaugset, Arne E

2015-01-01

Land use and climate change occur simultaneously around the globe. Fully understanding their separate and combined effects requires a mechanistic understanding at the local scale where their effects are ultimately realized. Here we applied an individual-based model of fish population dynamics to evaluate the role of local stream variability in modifying responses of Coastal Cutthroat Trout (Oncorhynchus clarkii clarkii) to scenarios simulating identical changes in temperature and stream flows linked to forest harvest, climate change, and their combined effects over six decades. We parameterized the model for four neighboring streams located in a forested headwater catchment in northwestern Oregon, USA with multi-year, daily measurements of stream temperature, flow, and turbidity (2007-2011), and field measurements of both instream habitat structure and three years of annual trout population estimates. Model simulations revealed that variability in habitat conditions among streams (depth, available habitat) mediated the effects of forest harvest and climate change. Net effects for most simulated trout responses were different from or less than the sum of their separate scenarios. In some cases, forest harvest countered the effects of climate change through increased summer flow. Climate change most strongly influenced trout (earlier fry emergence, reductions in biomass of older trout, increased biomass of young-of-year), but these changes did not consistently translate into reductions in biomass over time. Forest harvest, in contrast, produced fewer and less consistent responses in trout. Earlier fry emergence driven by climate change was the most consistent simulated response, whereas survival, growth, and biomass were inconsistent. Overall our findings indicate a host of local processes can strongly influence how populations respond to broad scale effects of land use and climate change.

GAPPARD: a computationally efficient method of approximating gap-scale disturbance in vegetation models

NASA Astrophysics Data System (ADS)

Scherstjanoi, M.; Kaplan, J. O.; Thürig, E.; Lischke, H.

2013-09-01

Models of vegetation dynamics that are designed for application at spatial scales larger than individual forest gaps suffer from several limitations. Typically, either a population average approximation is used that results in unrealistic tree allometry and forest stand structure, or models have a high computational demand because they need to simulate both a series of age-based cohorts and a number of replicate patches to account for stochastic gap-scale disturbances. The detail required by the latter method increases the number of calculations by two to three orders of magnitude compared to the less realistic population average approach. In an effort to increase the efficiency of dynamic vegetation models without sacrificing realism, we developed a new method for simulating stand-replacing disturbances that is both accurate and faster than approaches that use replicate patches. The GAPPARD (approximating GAP model results with a Probabilistic Approach to account for stand Replacing Disturbances) method works by postprocessing the output of deterministic, undisturbed simulations of a cohort-based vegetation model by deriving the distribution of patch ages at any point in time on the basis of a disturbance probability. With this distribution, the expected value of any output variable can be calculated from the output values of the deterministic undisturbed run at the time corresponding to the patch age. To account for temporal changes in model forcing (e.g., as a result of climate change), GAPPARD performs a series of deterministic simulations and interpolates between the results in the postprocessing step. We integrated the GAPPARD method in the vegetation model LPJ-GUESS, and evaluated it in a series of simulations along an altitudinal transect of an inner-Alpine valley. We obtained results very similar to the output of the original LPJ-GUESS model that uses 100 replicate patches, but simulation time was reduced by approximately the factor 10. Our new method is therefore highly suited for rapidly approximating LPJ-GUESS results, and provides the opportunity for future studies over large spatial domains, allows easier parameterization of tree species, faster identification of areas of interesting simulation results, and comparisons with large-scale datasets and results of other forest models.

Effects of food conditions on the development of the population of Temora stylifera: A modeling approach

NASA Astrophysics Data System (ADS)

Mazzocchi, M. G.; Buffoni, G.; Carotenuto, Y.; Pasquali, S.; Ribera d'Alcalà, M.

2006-08-01

We integrated field and laboratory data with modeling to determine the extent to which the temporal patterns in population abundance of a copepod species as observed at sea may be explained by differences in production and mortality rates due to diet. A Lagrangian individual-based model utilizing birth and mortality rates whose values and variance were derived from the effects of dietary composition was implemented to simulate the growth of the multi-staged population of Temora stylifera. The four diets considered were represented by unialgal cultures of the dinoflagellate Prorocentrum minimum or the diatom Thalassiosira rotula, a mixture of the two species, and natural particle assemblages < 50 μm. The aim of this work was to set up an exemplary study on a debated issue, i.e., whether the insidious effect of a diatom diet demonstrated in laboratory experiments plays a role in the time course of copepod populations in situ. Our numerical simulations showed that differences in life history parameters, as mainly dependent on diet, caused remarkably different population growth rates. However, our model reproduced the pattern of an average seasonal cycle of T. stylifera in Mediterranean coastal waters only when it utilized time-dependent field data, which evidently integrate all conditions the animals experience at sea. Proper tuning of the mortality term of developmental stages was crucial to reproduce the pattern of the time course of T. stylifera abundance in situ, which confirms that this term plays a major role in shaping the copepod population dynamics. The model also showed that, while dietary composition affects the population growth, it is far from being the only determinant of the cycle of abundance of T. stylifera at sea.

A model study of assisted adiabatic transfer of population in the presence of collisional dephasing

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

Masuda, Shumpei, E-mail: shumpei.masuda@aalto.fi; Rice, Stuart A., E-mail: s-rice@uchicago.edu

2015-06-28

Previous studies have demonstrated that when experimental conditions generate non-adiabatic dynamics that prevents highly efficient population transfer between states of an isolated system by stimulated Raman adiabatic passage (STIRAP), the addition of an auxiliary counter-diabatic field (CDF) can restore most or all of that efficiency. This paper examines whether that strategy is also successful in a non-isolated system in which the energies of the states fluctuate, e.g., when a solute is subject to collisions with solvent. We study population transfer in two model systems: (i) the three-state system used by Demirplak and Rice [J. Chem. Phys. 116, 8028 (2002)] andmore » (ii) a four-state system, derived from the simulation studies of Demirplak and Rice [J. Chem. Phys. 125, 194517 (2006)], that mimics HCl in liquid Ar. Simulation studies of the vibrational manifold of HCl in dense fluid Ar show that the collision induced vibrational energy level fluctuations have asymmetric distributions. Representations of these asymmetric energy level fluctuation distributions are used in both models (i) and (ii). We identify three sources of degradation of the efficiency of STIRAP generated selective population transfer in model (ii): too small pulse areas of the laser fields, unwanted interference arising from use of strong fields, and the vibrational detuning. For both models (i) and (ii), our examination of the efficiency of STIRAP + CDF population transfer under the influence of the asymmetric distribution of the vibrational energy fluctuations shows that there is a range of field strengths and pulse durations under which STIRAP + CDF control of population transfer has greater efficiency than does STIRAP generated population transfer.« less

Bee++: An Object-Oriented, Agent-Based Simulator for Honey Bee Colonies

PubMed Central

Betti, Matthew; LeClair, Josh; Wahl, Lindi M.; Zamir, Mair

2017-01-01

We present a model and associated simulation package (www.beeplusplus.ca) to capture the natural dynamics of a honey bee colony in a spatially-explicit landscape, with temporally-variable, weather-dependent parameters. The simulation tracks bees of different ages and castes, food stores within the colony, pollen and nectar sources and the spatial position of individual foragers outside the hive. We track explicitly the intake of pesticides in individual bees and their ability to metabolize these toxins, such that the impact of sub-lethal doses of pesticides can be explored. Moreover, pathogen populations (in particular, Nosema apis, Nosema cerenae and Varroa mites) have been included in the model and may be introduced at any time or location. The ability to study interactions among pesticides, climate, biodiversity and pathogens in this predictive framework should prove useful to a wide range of researchers studying honey bee populations. To this end, the simulation package is written in open source, object-oriented code (C++) and can be easily modified by the user. Here, we demonstrate the use of the model by exploring the effects of sub-lethal pesticide exposure on the flight behaviour of foragers. PMID:28287445

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.

Preliminary forecasts of Pacific bigeye tuna population trends under the A2 IPCC scenario

NASA Astrophysics Data System (ADS)

Lehodey, P.; Senina, I.; Sibert, J.; Bopp, L.; Calmettes, B.; Hampton, J.; Murtugudde, R.

2010-07-01

An improved version of the spatial ecosystem and population dynamics model SEAPODYM was used to investigate the potential impacts of global warming on tuna populations. The model included an enhanced definition of habitat indices, movements, and accessibility of tuna predators to different vertically migrant and non-migrant micronekton functional groups. The simulations covered the Pacific basin (model domain) at a 2° × 2° geographic resolution. The structure of the model allows an evaluation from multiple data sources, and parameterization can be optimized by adjoint techniques and maximum likelihood using fishing data. A first such optimized parameterization was obtained for bigeye tuna ( Thunnus obesus) in the Pacific Ocean using historical catch data for the last 50 years and a hindcast from a coupled physical-biogeochemical model driven by the NCEP atmospheric reanalysis. The parameterization provided very plausible biological parameter values and a good fit to fishing data from the different fisheries, both within and outside the time period used for optimization. We then employed this model to forecast the future of bigeye tuna populations in the Pacific Ocean. The simulation was driven by the physical-biogeochemical fields predicted from a global marine biogeochemistry - climate simulation. This global simulation was performed with the IPSL climate model version 4 (IPSL-CM4) coupled to the oceanic biogeochemical model PISCES and forced by atmospheric CO 2, from historical records over 1860-2000, and under the SRES A2 IPCC scenario for the 21st century (i.e. atmospheric CO 2 concentration reaching 850 ppm in the year 2100). Potential future changes in distribution and abundance under the IPCC scenario are presented but without taking into account any fishing effort. The simulation showed an improvement in bigeye tuna spawning habitat both in subtropical latitudes and in the eastern tropical Pacific (ETP) where the surface temperature becomes optimal for bigeye tuna spawning. The adult feeding habitat also improved in the ETP due to the increase of dissolved oxygen concentration in the sub-surface allowing adults to access deeper forage. Conversely, in the Western Central Pacific the temperature becomes too warm for bigeye tuna spawning. The decrease in spawning is compensated by an increase of larvae biomass in subtropical regions. However, natural mortality of older stages increased due to lower habitat values (too warm surface temperatures, decreasing oxygen concentration in the sub-surface and less food). This increased mortality and the displacement of surviving fish to the eastern region led to stable then declining adult biomass at the end of the century.

Do You See What I See? Exploring the Consequences of Luminosity Limits in Black Hole-Galaxy Evolution Studies

NASA Astrophysics Data System (ADS)

Jones, Mackenzie L.; Hickox, Ryan C.; Mutch, Simon J.; Croton, Darren J.; Ptak, Andrew F.; DiPompeo, Michael A.

2017-07-01

In studies of the connection between active galactic nuclei (AGNs) and their host galaxies, there is widespread disagreement on some key aspects of the connection. These disagreements largely stem from a lack of understanding of the nature of the full underlying AGN population. Recent attempts to probe this connection utilize both observations and simulations to correct for a missed population, but presently are limited by intrinsic biases and complicated models. We take a simple simulation for galaxy evolution and add a new prescription for AGN activity to connect galaxy growth to dark matter halo properties and AGN activity to star formation. We explicitly model selection effects to produce an “observed” AGN population for comparison with observations and empirically motivated models of the local universe. This allows us to bypass the difficulties inherent in models that attempt to infer the AGN population by inverting selection effects. We investigate the impact of selecting AGNs based on thresholds in luminosity or Eddington ratio on the “observed” AGN population. By limiting our model AGN sample in luminosity, we are able to recreate the observed local AGN luminosity function and specific star formation-stellar mass distribution, and show that using an Eddington ratio threshold introduces less bias into the sample by selecting the full range of growing black holes, despite the challenge of selecting low-mass black holes. We find that selecting AGNs using these various thresholds yield samples with different AGN host galaxy properties.

Population size and stopover duration estimation using mark–resight data and Bayesian analysis of a superpopulation model

USGS Publications Warehouse

Lyons, James E.; Kendall, William L.; Royle, J. Andrew; Converse, Sarah J.; Andres, Brad A.; Buchanan, Joseph B.

2016-01-01

We present a novel formulation of a mark–recapture–resight model that allows estimation of population size, stopover duration, and arrival and departure schedules at migration areas. Estimation is based on encounter histories of uniquely marked individuals and relative counts of marked and unmarked animals. We use a Bayesian analysis of a state–space formulation of the Jolly–Seber mark–recapture model, integrated with a binomial model for counts of unmarked animals, to derive estimates of population size and arrival and departure probabilities. We also provide a novel estimator for stopover duration that is derived from the latent state variable representing the interim between arrival and departure in the state–space model. We conduct a simulation study of field sampling protocols to understand the impact of superpopulation size, proportion marked, and number of animals sampled on bias and precision of estimates. Simulation results indicate that relative bias of estimates of the proportion of the population with marks was low for all sampling scenarios and never exceeded 2%. Our approach does not require enumeration of all unmarked animals detected or direct knowledge of the number of marked animals in the population at the time of the study. This provides flexibility and potential application in a variety of sampling situations (e.g., migratory birds, breeding seabirds, sea turtles, fish, pinnipeds, etc.). Application of the methods is demonstrated with data from a study of migratory sandpipers.

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

An in silico approach helped to identify the best experimental design, population, and outcome for future randomized clinical trials.

PubMed

Bajard, Agathe; Chabaud, Sylvie; Cornu, Catherine; Castellan, Anne-Charlotte; Malik, Salma; Kurbatova, Polina; Volpert, Vitaly; Eymard, Nathalie; Kassai, Behrouz; Nony, Patrice

2016-01-01

The main objective of our work was to compare different randomized clinical trial (RCT) experimental designs in terms of power, accuracy of the estimation of treatment effect, and number of patients receiving active treatment using in silico simulations. A virtual population of patients was simulated and randomized in potential clinical trials. Treatment effect was modeled using a dose-effect relation for quantitative or qualitative outcomes. Different experimental designs were considered, and performances between designs were compared. One thousand clinical trials were simulated for each design based on an example of modeled disease. According to simulation results, the number of patients needed to reach 80% power was 50 for crossover, 60 for parallel or randomized withdrawal, 65 for drop the loser (DL), and 70 for early escape or play the winner (PW). For a given sample size, each design had its own advantage: low duration (parallel, early escape), high statistical power and precision (crossover), and higher number of patients receiving the active treatment (PW and DL). Our approach can help to identify the best experimental design, population, and outcome for future RCTs. This may be particularly useful for drug development in rare diseases, theragnostic approaches, or personalized medicine. Copyright © 2016 Elsevier Inc. All rights reserved.

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.

Hysteresis in simulations of malaria transmission

NASA Astrophysics Data System (ADS)

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

2017-10-01

Malaria transmission is a complex system and in many parts of the world is closely related to climate conditions. However, studies on environmental determinants of malaria generally consider only concurrent climate conditions and ignore the historical or initial conditions of the system. Here, we demonstrate the concept of hysteresis in malaria transmission, defined as non-uniqueness of the relationship between malaria prevalence and concurrent climate conditions. We show the dependence of simulated malaria transmission on initial prevalence and the initial level of human immunity in the population. Using realistic time series of environmental variables, we quantify the effect of hysteresis in a modeled population. In a set of numerical experiments using HYDREMATS, a field-tested mechanistic model of malaria transmission, the simulated maximum malaria prevalence depends on both the initial prevalence and the initial level of human immunity in the population. We found the effects of initial conditions to be of comparable magnitude to the effects of interannual variability in environmental conditions in determining malaria prevalence. The memory associated with this hysteresis effect is longer in high transmission settings than in low transmission settings. Our results show that efforts to simulate and forecast malaria transmission must consider the exposure history of a location as well as the concurrent environmental drivers.

Costs of detection bias in index-based population monitoring

USGS Publications Warehouse

Moore, C.T.; Kendall, W.L.

2004-01-01

Managers of wildlife populations commonly rely on indirect, count-based measures of the population in making decisions regarding conservation, harvest, or control. The main appeal in the use of such counts is their low material expense compared to methods that directly measure the population. However, their correct use rests on the rarely-tested but often-assumed premise that they proportionately reflect population size, i.e., that they constitute a population index. This study investigates forest management for the endangered Red-cockaded Woodpecker (Picoides borealis) and the Wood Thrush (Hylocichla mustelina) at the Piedmont National Wildlife Refuge in central Georgia, U.S.A. Optimal decision policies for a joint species objective were derived for two alternative models of Wood Thrush population dynamics. Policies were simulated under scenarios of unbiasedness, consistent negative bias, and habitat-dependent negative bias in observed Wood Thrush densities. Differences in simulation outcomes between biased and unbiased detection scenarios indicated the expected loss in resource objectives (here, forest habitat and birds) through decision-making based on biased population counts. Given the models and objective function used in our analysis, expected losses were as great as 11%, a degree of loss perhaps not trivial for applications such as endangered species management. Our analysis demonstrates that costs of uncertainty about the relationship between the population and its observation can be measured in units of the resource, costs which may offset apparent savings achieved by collecting uncorrected population counts.

Agent-based modeling for the landuse change of hunter-gather societies and the impacts on biodiversity in Guyana

NASA Astrophysics Data System (ADS)

Iwamura, T.; Fragoso, J.; Lambin, E.

2012-12-01

The interactions with animals are vital to the Amerindian, indigenous people, of Rupunini savannah-forest in Guyana. Their connections extend from basic energy and protein resource to spiritual bonding through "paring" to a certain animal in the forest. We collected extensive dataset of 23 indigenous communities for 3.5 years, consisting 9900 individuals from 1307 households, as well as animal observation data in 8 transects per communities (47,000 data entries). In this presentation, our research interest is to model the driver of land use change of the indigenous communities and its impacts on the ecosystem in the Rupunini area under global change. Overarching question we would like to answer with this program is to find how and why "tipping-point" from hunting gathering society to the agricultural society occurs in the future. Secondary question is what is the implication of the change to agricultural society in terms of biodiversity and carbon stock in the area, and eventually the well-being of Rupunini people. To answer the questions regarding the society shift in agriculture activities, we built as simulation with Agent-Based Modeling (Multi Agents Simulation). We developed this simulation by using Netlogo, the programming environment specialized for spatially explicit agent-based modeling (ABM). This simulation consists of four different process in the Rupunini landscape; forest succession, animal population growth, hunting of animals, and land clearing for agriculture. All of these processes are carried out by a set of computational unit, called "agents". In this program, there are four types of agents - patches, villages, households, and animals. Here, we describe the impacts of hunting on the biodiversity based on actual demographic data from one village named Crush Water. Animal population within the hunting territory of the village stabilized but Agouti/Paca dominates the landscape with little population of armadillos and peccaries. White-tailed deers, Tapirs, Capybara exist but very low. This finding is well aligned with the hunting dataset - Agouti/Paca consists 27% of total hunting. Based on our simulation, it seems the dominance of Agouti/Paca among hunted animals shown in the field data can be explained solely by their high carrying capacity against human extraction (population density of the Paca/Agouti = 60 per square km, whereas other animals ranges 0.63 to 7). When we incorporate agriculture, the "rodentation" of the animal population toward Agouti/Paca becomes more obvious. This simulation shows the interactions of people and animals through land change and hunting, which were observed in our fields.

An energy-circuit population model for great egrets (Ardea alba) at Lake Okeechobee, Florida, U.S.A

USGS Publications Warehouse

Smith, Jeff P.

1997-01-01

I simulated the annual population cycles of Great Egrets (Ardea alba) at Lake Okeechobee, Florida, to provide a framework for evaluating the local population dynamics of nesting and foraging wading birds. The external forcing functions were solar energy, minimum air temperature, water depth, surface-water drying rate, and season. Solar input controlled the production of prey at moderate to high lake stages, but water area exerted primary control during a two-year drought. Modeling prey production as a linear function of water area resulted in underestimation of prey density during the drought, suggesting that prey organisms maintained high fecundity while concentrated in submerged vegetation at the lakeward fringe of the littoral zone. Simulation confirmed that large influxes of wading birds during the drought were the combined result of a regional refuge response and the availability of concentrated prey. Modeling immigration and emigration as primarily functions of the surface-water drying rate, rather than lake stage, resulted in a closer match of observed and simulated population trends for foraging birds, suggesting that the pattern of surface-water fluctuations was a more important factor than water depth. Simulation indicated an abrupt-threshold response rather than a linear association between foraging efficiency and low temperatures, which reduce activity levels of forage fishes. Great Egret breeder recruitment is primarily a function of prey availability, climate, and hydrologic trends, but simulation confirmed the concurrent involvement of a seasonal or physiological-readiness factor. An attractor function driven by high winter lake stages was necessary to reproduce observed patterns of breeder recruitment, suggesting that Great Egrets initiate nesting based on environmental cues that lead to peak food availability when nestlings are present. Poor correspondence of reproductive effort and nest productivity suggested that the drought compromised the birds' predictive abilities. The need to model breeder recruitment as a function of a maximum rate rather than the size of the local foraging population suggested that birds may nest on the lake even though on-lake foraging conditions are poor. Simulated and observed estimates of egg and hatching production did not match, suggesting that the causes of failure during incubation were complex or more localized than could be accounted for with lakewide hydrologic and climatic data. A forced increase in prey consumption of 12% was necessary to reproduce observed, high levels of nest productivity in 1990, which corresponded to the finding that panhandled fish constituted 10–12% of the biomass fed to Great Egret nestlings that year.

DEMOGRAPHIC UNCERTAINTY IN ECOLOGICAL RISK ASSESSMENTS. (R825347)

EPA Science Inventory

We built a Ricker's model incorporating demographic stochasticity to simulate the effects of demographic uncertainty on responses of gray-tailed vole (Microtus canicaudus) populations to pesticide applications. We constructed models with mark-recapture data collected from populat...

Modeling disturbance-based native invasive species control and its implications for management.

PubMed

Shackelford, Nancy; Renton, Michael; Perring, Michael P; Hobbs, Richard J

2013-09-01

Shifts in disturbance regime have often been linked to invasion in systems by native and nonnative species. This process can have negative effects on biodiversity and ecosystem function. Degradation may be ameliorated by the reinstatement of the disturbance regimes, such as the reintroduction of fire in pyrogenic systems. Modeling is one method through which potential outcomes of different regimes can be investigated. We created a population model to examine the control of a native invasive that is expanding and increasing in abundance due to suppressed fire. Our model, parameterized with field data from a case study of the tree Allocasuarina huegeliana in Australian sandplain heath, simulated different fire return intervals with and without the additional management effort of mechanical removal of the native invader. Population behavior under the different management options was assessed, and general estimates of potential biodiversity impacts were compared. We found that changes in fire return intervals made no significant difference in the increase and spread of the population. However, decreased fire return intervals did lower densities reached in the simulated heath patch as well as the estimated maximum biodiversity impacts. When simulating both mechanical removal and fire, we found that the effects of removal depended on the return intervals and the strategy used. Increase rates were not significantly affected by any removal strategy. However, we found that removal, particularly over the whole patch rather than focusing on satellite populations, could decrease average and maximum densities reached and thus decrease the predicted biodiversity impacts. Our simulation model shows that disturbance-based management has the potential to control native invasion in cases where shifted disturbance is the likely driver of the invasion. The increased knowledge gained through the modeling methods outlined can inform management decisions in fire regime planning that takes into consideration control of an invasive species. Although particularly applicable to native invasives, when properly informed by empirical knowledge these techniques can be expanded to management of invasion by nonnative species, either by restoring historic disturbance regimes or by instating novel regimes in innovative ways.

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

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.

Discrete event simulation model of sudden cardiac death predicts high impact of preventive interventions.

PubMed

Andreev, Victor P; Head, Trajen; Johnson, Neil; Deo, Sapna K; Daunert, Sylvia; Goldschmidt-Clermont, Pascal J

2013-01-01

Sudden Cardiac Death (SCD) is responsible for at least 180,000 deaths a year and incurs an average cost of $286 billion annually in the United States alone. Herein, we present a novel discrete event simulation model of SCD, which quantifies the chains of events associated with the formation, growth, and rupture of atheroma plaques, and the subsequent formation of clots, thrombosis and on-set of arrhythmias within a population. The predictions generated by the model are in good agreement both with results obtained from pathological examinations on the frequencies of three major types of atheroma, and with epidemiological data on the prevalence and risk of SCD. These model predictions allow for identification of interventions and importantly for the optimal time of intervention leading to high potential impact on SCD risk reduction (up to 8-fold reduction in the number of SCDs in the population) as well as the increase in life expectancy.

Population Pharmacokinetic Modeling and Dosing Simulations of Nitrogen-Scavenging Compounds: Disposition of Glycerol Phenylbutyrate and Sodium Phenylbutyrate in Adult and Pediatric Patients with Urea Cycle Disorders

PubMed Central

Monteleone, Jon P. R.; Mokhtarani, M.; Diaz, G. A.; Rhead, W.; Lichter-Konecki, U.; Berry, S. A.; LeMons, C.; Dickinson, K.; Coakley, D.; Lee, B.; Scharschmidt, B. F.

2014-01-01

Sodium phenylbutyrate and glycerol phenylbutyrate mediate waste nitrogen excretion in the form of urinary phenylacetylglutamine (PAGN) in patients with urea cycle disorders (UCDs); rare genetic disorders characterized by impaired urea synthesis and hyperammonemia. Sodium phenylbutyrate is approved for UCD treatment; the development of glycerol phenylbutyrate afforded the opportunity to characterize the pharmacokinetics (PK) of both compounds. A population PK model was developed using data from four Phase II/III trials that collectively enrolled patients ages 2 months to 72 years. Dose simulations were performed with particular attention to phenylacetic acid (PAA), which has been associated with adverse events in non-UCD populations. The final model described metabolite levels in plasma and urine for both drugs and was characterized by (a) partial presystemic metabolism of phenylbutyric acid (PBA) to PAA and/or PAGN, (b) slower PBA absorption and greater presystemic conversion with glycerol phenylbutyrate, (c) similar systemic disposition with saturable conversion of PAA to PAGN for both drugs, and (d) body surface area (BSA) as a significant covariate accounting for age-related PK differences. Dose simulations demonstrated similar PAA exposure following mole-equivalent PBA dosing of both drugs and greater PAA exposure in younger patients based on BSA. PMID:23775211

Population pharmacokinetic modeling and dosing simulations of nitrogen-scavenging compounds: disposition of glycerol phenylbutyrate and sodium phenylbutyrate in adult and pediatric patients with urea cycle disorders.

PubMed

Monteleone, Jon P R; Mokhtarani, M; Diaz, G A; Rhead, W; Lichter-Konecki, U; Berry, S A; Lemons, C; Dickinson, K; Coakley, D; Lee, B; Scharschmidt, B F

2013-07-01

Sodium phenylbutyrate and glycerol phenylbutyrate mediate waste nitrogen excretion in the form of urinary phenylacetylglutamine (PAGN) in patients with urea cycle disorders (UCDs); rare genetic disorders characterized by impaired urea synthesis and hyperammonemia. Sodium phenylbutyrate is approved for UCD treatment; the development of glycerol phenylbutyrate afforded the opportunity to characterize the pharmacokinetics (PK) of both compounds. A population PK model was developed using data from four Phase II/III trials that collectively enrolled patients ages 2 months to 72 years. Dose simulations were performed with particular attention to phenylacetic acid (PAA), which has been associated with adverse events in non-UCD populations. The final model described metabolite levels in plasma and urine for both drugs and was characterized by (a) partial presystemic metabolism of phenylbutyric acid (PBA) to PAA and/or PAGN, (b) slower PBA absorption and greater presystemic conversion with glycerol phenylbutyrate, (c) similar systemic disposition with saturable conversion of PAA to PAGN for both drugs, and (d) body surface area (BSA) as a significant covariate accounting for age-related PK differences. Dose simulations demonstrated similar PAA exposure following mole-equivalent PBA dosing of both drugs and greater PAA exposure in younger patients based on BSA. © The Author(s) 2013.

Methods for modeling non-equilibrium degenerate statistics and quantum-confined scattering in 3D ensemble Monte Carlo transport simulations

NASA Astrophysics Data System (ADS)

Crum, Dax M.; Valsaraj, Amithraj; David, John K.; Register, Leonard F.; Banerjee, Sanjay K.

2016-12-01

Particle-based ensemble semi-classical Monte Carlo (MC) methods employ quantum corrections (QCs) to address quantum confinement and degenerate carrier populations to model tomorrow's ultra-scaled metal-oxide-semiconductor-field-effect-transistors. Here, we present the most complete treatment of quantum confinement and carrier degeneracy effects in a three-dimensional (3D) MC device simulator to date, and illustrate their significance through simulation of n-channel Si and III-V FinFETs. Original contributions include our treatment of far-from-equilibrium degenerate statistics and QC-based modeling of surface-roughness scattering, as well as considering quantum-confined phonon and ionized-impurity scattering in 3D. Typical MC simulations approximate degenerate carrier populations as Fermi distributions to model the Pauli-blocking (PB) of scattering to occupied final states. To allow for increasingly far-from-equilibrium non-Fermi carrier distributions in ultra-scaled and III-V devices, we instead generate the final-state occupation probabilities used for PB by sampling the local carrier populations as function of energy and energy valley. This process is aided by the use of fractional carriers or sub-carriers, which minimizes classical carrier-carrier scattering intrinsically incompatible with degenerate statistics. Quantum-confinement effects are addressed through quantum-correction potentials (QCPs) generated from coupled Schrödinger-Poisson solvers, as commonly done. However, we use these valley- and orientation-dependent QCPs not just to redistribute carriers in real space, or even among energy valleys, but also to calculate confinement-dependent phonon, ionized-impurity, and surface-roughness scattering rates. FinFET simulations are used to illustrate the contributions of each of these QCs. Collectively, these quantum effects can substantially reduce and even eliminate otherwise expected benefits of considered In0.53Ga0.47 As FinFETs over otherwise identical Si FinFETs despite higher thermal velocities in In0.53Ga0.47 As. It also may be possible to extend these basic uses of QCPs, however calculated, to still more computationally efficient drift-diffusion and hydrodynamic simulations, and the basic concepts even to compact device modeling.

Prediction of Fetal Darunavir Exposure by Integrating Human Ex-Vivo Placental Transfer and Physiologically Based Pharmacokinetic Modeling.

PubMed

Schalkwijk, Stein; Buaben, Aaron O; Freriksen, Jolien J M; Colbers, Angela P; Burger, David M; Greupink, Rick; Russel, Frans G M

2017-07-25

Fetal antiretroviral exposure is usually derived from the cord-to-maternal concentration ratio. This static parameter does not provide information on the pharmacokinetics in utero, limiting the assessment of a fetal exposure-effect relationship. The aim of this study was to incorporate placental transfer into a pregnancy physiologically based pharmacokinetic model to simulate and evaluate fetal darunavir exposure at term. An existing and validated pregnancy physiologically based pharmacokinetic model of maternal darunavir/ritonavir exposure was extended with a feto-placental unit. To parameterize the model, we determined maternal-to-fetal and fetal-to-maternal darunavir/ritonavir placental clearance with an ex-vivo human cotyledon perfusion model. Simulated maternal and fetal pharmacokinetic profiles were compared with observed clinical data to qualify the model for simulation. Next, population fetal pharmacokinetic profiles were simulated for different maternal darunavir/ritonavir dosing regimens. An average (±standard deviation) maternal-to-fetal cotyledon clearance of 0.91 ± 0.11 mL/min and fetal-to-maternal clearance of 1.6 ± 0.3 mL/min was determined (n = 6 perfusions). Scaled placental transfer was integrated into the pregnancy physiologically based pharmacokinetic model. For darunavir 600/100 mg twice a day, the predicted fetal maximum plasma concentration, trough concentration, time to maximum plasma concentration, and half-life were 1.1, 0.57 mg/L, 3, and 21 h, respectively. This indicates that the fetal population trough concentration is higher or around the half-maximal effective darunavir concentration for a resistant virus (0.55 mg/L). The results indicate that the population fetal exposure after oral maternal darunavir dosing is therapeutic and this may provide benefits to the prevention of mother-to-child transmission of human immunodeficiency virus. Moreover, this integrated approach provides a tool to prevent fetal toxicity or enhance the development of more selectively targeted fetal drug treatments.

Land Use Change on Household Farms in the Ecuadorian Amazon: Design and Implementation of an Agent-Based Model

PubMed Central

Mena, Carlos F.; Walsh, Stephen J.; Frizzelle, Brian G.; Xiaozheng, Yao; Malanson, George P.

2010-01-01

This paper describes the design and implementation of an Agent-Based Model (ABM) used to simulate land use change on household farms in the Northern Ecuadorian Amazon (NEA). The ABM simulates decision-making processes at the household level that is examined through a longitudinal, socio-economic and demographic survey that was conducted in 1990 and 1999. Geographic Information Systems (GIS) are used to establish spatial relationships between farms and their environment, while classified Landsat Thematic Mapper (TM) imagery is used to set initial land use/land cover conditions for the spatial simulation, assess from-to land use/land cover change patterns, and describe trajectories of land use change at the farm and landscape levels. Results from prior studies in the NEA provide insights into the key social and ecological variables, describe human behavioral functions, and examine population-environment interactions that are linked to deforestation and agricultural extensification, population migration, and demographic change. Within the architecture of the model, agents are classified as active or passive. The model comprises four modules, i.e., initialization, demography, agriculture, and migration that operate individually, but are linked through key household processes. The main outputs of the model include a spatially-explicit representation of the land use/land cover on survey and non-survey farms and at the landscape level for each annual time-step, as well as simulated socio-economic and demographic characteristics of households and communities. The work describes the design and implementation of the model and how population-environment interactions can be addressed in a frontier setting. The paper contributes to land change science by examining important pattern-process relations, advocating a spatial modeling approach that is capable of synthesizing fundamental relationships at the farm level, and links people and environment in complex ways. PMID:24436501

Human impact on wildfires varies between regions and with vegetation productivity

NASA Astrophysics Data System (ADS)

Lasslop, Gitta; Kloster, Silvia

2017-11-01

We assess the influence of humans on burned area simulated with a dynamic global vegetation model. The human impact in the model is based on population density and cropland fraction, which were identified as important drivers of burned area in analyses of global datasets, and are commonly used in global models. After an evaluation of the sensitivity to these two variables we extend the model by including an additional effect of the cropland fraction on the fire duration. The general pattern of human influence is similar in both model versions: the strongest human impact is found in regions with intermediate productivity, where fire occurrence is not limited by fuel load or climatic conditions. Human effects in the model increases burned area in the tropics, while in temperate regions burned area is reduced. While the population density is similar on average for the tropical and temperate regions, the cropland fraction is higher in temperate regions, and leads to a strong suppression of fire. The model shows a low human impact in the boreal region, where both population density and cropland fraction is very low and the climatic conditions, as well as the vegetation productivity limit fire. Previous studies attributed a decrease in fire activity found in global charcoal datasets to human activity. This is confirmed by our simulations, which only show a decrease in burned area when the human influence on fire is accounted for, and not with only natural effects on fires. We assess how the vegetation-fire feedback influences the results, by comparing simulations with dynamic vegetation biogeography to simulations with prescribed vegetation. The vegetation-fire feedback increases the human impact on burned area by 10% for present day conditions. These results emphasize that projections of burned area need to account for the interactions between fire, climate, vegetation and humans.

Computer simulation for integrated pest management of spruce budworms

Treesearch

Carroll B. Williams; Patrick J. Shea

1982-01-01

Some field studies of the effects of various insecticides on the spruce budworm (Choristoneura sp.) and their parasites have shown severe suppression of host (budworm) populations and increased parasitism after treatment. Computer simulation using hypothetical models of spruce budworm-parasite systems based on these field data revealed that (1)...

Simulating Fish Assemblages in Riverine Networks: Response to Habitat in the Willamette Watershed

EPA Science Inventory

We describe a modeling approach for simulating assemblages of fish in riverine landscapes. The approach allows a user to determine the scale and extent of river networks within which fish populations reproduce, move, and survive in response to both environmental drivers and assem...

Evaluating the Simulation of MetacommUnities for Riverine Fishes (SMURF) in the Calapooia Basin, OR

EPA Science Inventory

We describe a modeling approach for simulating assemblages of fish in riverine landscapes. The approach allows a user to determine the grain and extent of river networks within which fish populations reproduce, move, and survive in response to both environmental drivers and assem...

A microcomputer based traffic evacuation modeling system for emergency planning application

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

Rathi, A.K.

1994-12-01

Vehicular evacuation is one of the major and often preferred protective action options available for emergency management in a real or anticipated disaster. Computer simulation models of evacuation traffic flow are used to estimate the time required for the affected populations to evacuate to safer areas, to evaluate effectiveness of vehicular evacuations as a protective action option. and to develop comprehensive evacuation plans when required. Following a review of the past efforts to simulate traffic flow during emergency evacuations, an overview of the key features in Version 2.0 of the Oak Ridge Evacuation Modeling System (OREMS) are presented in thismore » paper. OREMS is a microcomputer-based model developed to simulate traffic flow during regional emergency evacuations. OREMS integrates a state-of-the-art dynamic traffic flow and simulation model with advanced data editing and output display programs operating under a MS-Windows environment.« less

A Framework for Daylighting Optimization in Whole Buildings with OpenStudio

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

None

2016-08-12

We present a toolkit and workflow for leveraging the OpenStudio (Guglielmetti et al. 2010) platform to perform daylighting analysis and optimization in a whole building energy modeling (BEM) context. We have re-implemented OpenStudio's integrated Radiance and EnergyPlus functionality as an OpenStudio Measure. The OpenStudio Radiance Measure works within the OpenStudio Application and Parametric Analysis Tool, as well as the OpenStudio Server large scale analysis framework, allowing a rigorous daylighting simulation to be performed on a single building model or potentially an entire population of programmatically generated models. The Radiance simulation results can automatically inform the broader building energy model, andmore » provide dynamic daylight metrics as a basis for decision. Through introduction and example, this paper illustrates the utility of the OpenStudio building energy modeling platform to leverage existing simulation tools for integrated building energy performance simulation, daylighting analysis, and reportage.« less

Simulations indicate that scores of lionfish (Pterois volitans) colonized the Atlantic Ocean.

PubMed

Selwyn, Jason D; Johnson, John E; Downey-Wall, Alan M; Bynum, Adam M; Hamner, Rebecca M; Hogan, J Derek; Bird, Christopher E

2017-01-01

The invasion of the western Atlantic Ocean by the Indo-Pacific red lionfish ( Pterois volitans ) has had devastating consequences for marine ecosystems. Estimating the number of colonizing lionfish can be useful in identifying the introduction pathway and can inform policy decisions aimed at preventing similar invasions. It is well-established that at least ten lionfish were initially introduced. However, that estimate has not faced probabilistic scrutiny and is based solely on the number of haplotypes in the maternally-inherited mitochondrial control region. To rigorously estimate the number of lionfish that were introduced, we used a forward-time, Wright-Fisher, population genetic model in concert with a demographic, life-history model to simulate the invasion across a range of source population sizes and colonizing population fecundities. Assuming a balanced sex ratio and no Allee effects, the simulations indicate that the Atlantic population was founded by 118 (54-514, 95% HPD) lionfish from the Indo-Pacific, the Caribbean by 84 (22-328, 95% HPD) lionfish from the Atlantic, and the Gulf of Mexico by at least 114 (no upper bound on 95% HPD) lionfish from the Caribbean. Increasing the size, and therefore diversity, of the Indo-Pacific source population and fecundity of the founding population caused the number of colonists to decrease, but with rapidly diminishing returns. When the simulation was parameterized to minimize the number of colonists (high θ and relative fecundity), 96 (48-216, 95% HPD) colonists were most likely. In a more realistic scenario with Allee effects (e.g., 50% reduction in fecundity) plaguing the colonists, the most likely number of lionfish increased to 272 (106-950, 95% HPD). These results, in combination with other published data, support the hypothesis that lionfish were introduced to the Atlantic via the aquarium trade, rather than shipping. When building the model employed here, we made assumptions that minimize the number of colonists, such as the lionfish being introduced in a single event. While we conservatively modelled the introduction pathway as a single release of lionfish in one location, it is more likely that a combination of smaller and larger releases from a variety of aquarium trade stakeholders occurred near Miami, Florida, which could have led to even larger numbers of colonists than simulated here. Efforts to prevent future invasions via the aquarium trade should focus on the education of stakeholders and the prohibition of release, with adequate rewards for compliance and penalties for violations.

Simulations indicate that scores of lionfish (Pterois volitans) colonized the Atlantic Ocean

PubMed Central

Selwyn, Jason D.; Johnson, John E.; Downey-Wall, Alan M.; Bynum, Adam M.; Hamner, Rebecca M.; Hogan, J. Derek

2017-01-01

The invasion of the western Atlantic Ocean by the Indo-Pacific red lionfish (Pterois volitans) has had devastating consequences for marine ecosystems. Estimating the number of colonizing lionfish can be useful in identifying the introduction pathway and can inform policy decisions aimed at preventing similar invasions. It is well-established that at least ten lionfish were initially introduced. However, that estimate has not faced probabilistic scrutiny and is based solely on the number of haplotypes in the maternally-inherited mitochondrial control region. To rigorously estimate the number of lionfish that were introduced, we used a forward-time, Wright-Fisher, population genetic model in concert with a demographic, life-history model to simulate the invasion across a range of source population sizes and colonizing population fecundities. Assuming a balanced sex ratio and no Allee effects, the simulations indicate that the Atlantic population was founded by 118 (54–514, 95% HPD) lionfish from the Indo-Pacific, the Caribbean by 84 (22–328, 95% HPD) lionfish from the Atlantic, and the Gulf of Mexico by at least 114 (no upper bound on 95% HPD) lionfish from the Caribbean. Increasing the size, and therefore diversity, of the Indo-Pacific source population and fecundity of the founding population caused the number of colonists to decrease, but with rapidly diminishing returns. When the simulation was parameterized to minimize the number of colonists (high θ and relative fecundity), 96 (48–216, 95% HPD) colonists were most likely. In a more realistic scenario with Allee effects (e.g., 50% reduction in fecundity) plaguing the colonists, the most likely number of lionfish increased to 272 (106–950, 95% HPD). These results, in combination with other published data, support the hypothesis that lionfish were introduced to the Atlantic via the aquarium trade, rather than shipping. When building the model employed here, we made assumptions that minimize the number of colonists, such as the lionfish being introduced in a single event. While we conservatively modelled the introduction pathway as a single release of lionfish in one location, it is more likely that a combination of smaller and larger releases from a variety of aquarium trade stakeholders occurred near Miami, Florida, which could have led to even larger numbers of colonists than simulated here. Efforts to prevent future invasions via the aquarium trade should focus on the education of stakeholders and the prohibition of release, with adequate rewards for compliance and penalties for violations. PMID:29302383

Predation and fragmentation portrayed in the statistical structure of prey time series

PubMed Central

Hendrichsen, Ditte K; Topping, Chris J; Forchhammer, Mads C

2009-01-01

Background Statistical autoregressive analyses of direct and delayed density dependence are widespread in ecological research. The models suggest that changes in ecological factors affecting density dependence, like predation and landscape heterogeneity are directly portrayed in the first and second order autoregressive parameters, and the models are therefore used to decipher complex biological patterns. However, independent tests of model predictions are complicated by the inherent variability of natural populations, where differences in landscape structure, climate or species composition prevent controlled repeated analyses. To circumvent this problem, we applied second-order autoregressive time series analyses to data generated by a realistic agent-based computer model. The model simulated life history decisions of individual field voles under controlled variations in predator pressure and landscape fragmentation. Analyses were made on three levels: comparisons between predated and non-predated populations, between populations exposed to different types of predators and between populations experiencing different degrees of habitat fragmentation. Results The results are unambiguous: Changes in landscape fragmentation and the numerical response of predators are clearly portrayed in the statistical time series structure as predicted by the autoregressive model. Populations without predators displayed significantly stronger negative direct density dependence than did those exposed to predators, where direct density dependence was only moderately negative. The effects of predation versus no predation had an even stronger effect on the delayed density dependence of the simulated prey populations. In non-predated prey populations, the coefficients of delayed density dependence were distinctly positive, whereas they were negative in predated populations. Similarly, increasing the degree of fragmentation of optimal habitat available to the prey was accompanied with a shift in the delayed density dependence, from strongly negative to gradually becoming less negative. Conclusion We conclude that statistical second-order autoregressive time series analyses are capable of deciphering interactions within and across trophic levels and their effect on direct and delayed density dependence. PMID:19419539

Hydrology of malaria: Model development and application to a Sahelian village

NASA Astrophysics Data System (ADS)

Bomblies, Arne; Duchemin, Jean-Bernard; Eltahir, Elfatih A. B.

2008-12-01

We present a coupled hydrology and entomology model for the mechanistic simulation of local-scale response of malaria transmission to hydrological and climatological determinants in semiarid, desert fringe environments. The model is applied to the Sahel village of Banizoumbou, Niger, to predict interannual variability in malaria vector mosquito populations that lead to variations in malaria transmission. Using a high-resolution, small-scale distributed hydrology model that incorporates remotely sensed data for land cover and topography, we simulate the formation and persistence of the pools constituting the primary breeding habitat of Anopheles gambiae s.l. mosquitoes, the principal regional malaria vector mosquitoes. An agent-based mosquito population model is coupled to the distributed hydrology model, with aquatic-stage and adult-stage components. Through a dependence of aquatic-stage mosquito development and adult emergence on pool persistence, we model small-scale hydrology as a dominant control of mosquito abundance. For each individual adult mosquito, the model tracks attributes relevant to population dynamics and malaria transmission, which are updated as mosquitoes interact with their environment, humans, and animals. Weekly field observations were made in 2005 and 2006. A 16% increase in rainfall between the two years was accompanied by a 132% increase in mosquito abundance between 2005 and 2006. The model reproduces mosquito population variability at seasonal and interannual timescales and highlights individual pool persistence as a dominant control. Future developments of the presented model can be used in the evaluation of impacts of climate change on malaria, as well as the a priori evaluation of environmental management-based interventions.

The PEDA Model. An advocacy tool modeling the interrelationships between population, development, the environment and agriculture in Africa.

PubMed

1999-01-01

This article reports on the PEDA (population changes, environment, socioeconomic development and agriculture) model and its implication for policy-making in Africa. PEDA is an interactive computer simulation model (developed for a Windows environment) demonstrating the long-term impacts of alternative national policies on food security status of the population. The model is based on multistate demographic techniques, projecting at the same time 8 different subgroups (by age and sex) in the population, and based on 3 dichotomous individual characteristics: urban/rural place of residence; literacy status; and food security status. Through the manipulation of scenario variables, the model enables the user to project the proportion of the population that will be food secure and food insecure for a chosen point in time. This model developed by Dr. W. Lutz, Director of the International Institute for Applied Systems Analysis, will serve as an advocacy tool to help convince policy-makers and country experts in Africa of the negative synergy arising from the interconnections of population growth, environmental deterioration, and declining agricultural production.

Designing environmental campaigns by using agent-based simulations: strategies for changing environmental attitudes.

PubMed

Mosler, Hans-Joachim; Martens, Thomas

2008-09-01

Agent-based computer simulation was used to create artificial communities in which each individual was constructed according to the principles of the elaboration likelihood model of Petty and Cacioppo [1986. The elaboration likelihood model of persuasion. In: Berkowitz, L. (Ed.), Advances in Experimental Social Psychology. Academic Press, New York, NY, pp. 123-205]. Campaigning strategies and community characteristics were varied systematically to understand and test their impact on attitudes towards environmental protection. The results show that strong arguments influence a green (environmentally concerned) population with many contacts most effectively, while peripheral cues have the greatest impact on a non-green population with fewer contacts. Overall, deeper information scrutiny increases the impact of strong arguments but is especially important for convincing green populations. Campaigns involving person-to-person communication are superior to mass-media campaigns because they can be adapted to recipients' characteristics.

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.

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.

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.

Domain learning naming game for color categorization.

PubMed

Li, Doujie; Fan, Zhongyan; Tang, Wallace K S

2017-01-01

Naming game simulates the evolution of vocabulary in a population of agents. Through pairwise interactions in the games, agents acquire a set of vocabulary in their memory for object naming. The existing model confines to a one-to-one mapping between a name and an object. Focus is usually put onto name consensus in the population rather than knowledge learning in agents, and hence simple learning model is usually adopted. However, the cognition system of human being is much more complex and knowledge is usually presented in a complicated form. Therefore, in this work, we extend the agent learning model and design a new game to incorporate domain learning, which is essential for more complicated form of knowledge. In particular, we demonstrate the evolution of color categorization and naming in a population of agents. We incorporate the human perceptive model into the agents and introduce two new concepts, namely subjective perception and subliminal stimulation, in domain learning. Simulation results show that, even without any supervision or pre-requisition, a consensus of a color naming system can be reached in a population solely via the interactions. Our work confirms the importance of society interactions in color categorization, which is a long debate topic in human cognition. Moreover, our work also demonstrates the possibility of cognitive system development in autonomous intelligent agents.

Forecasting Trends in Disability in a Super-Aging Society: Adapting the Future Elderly Model to Japan.

PubMed

Chen, Brian K; Jalal, Hawre; Hashimoto, Hideki; Suen, Sze-Chuan; Eggleston, Karen; Hurley, Michael; Schoemaker, Lena; Bhattacharya, Jay

2016-12-01

Japan has experienced pronounced population aging, and now has the highest proportion of elderly adults in the world. Yet few projections of Japan's future demography go beyond estimating population by age and sex to forecast the complex evolution of the health and functioning of the future elderly. This study estimates a new state-transition microsimulation model - the Japanese Future Elderly Model (FEM) - for Japan. We use the model to forecast disability and health for Japan's future elderly. Our simulation suggests that by 2040, over 27 percent of Japan's elderly will exhibit 3 or more limitations in IADLs and social functioning; almost one in 4 will experience difficulties with 3 or more ADLs; and approximately one in 5 will suffer limitations in cognitive or intellectual functioning. Since the majority of the increase in disability arises from the aging of the Japanese population, prevention efforts that reduce age-specific morbidity can help reduce the burden of disability but may have only a limited impact on reducing the overall prevalence of disability among Japanese elderly. While both age and morbidity contribute to a predicted increase in disability burden among elderly Japanese in the future, our simulation results suggest that the impact of population aging exceeds the effect of age-specific morbidity on increasing disability in Japan's future.

Domain learning naming game for color categorization

PubMed Central

2017-01-01

Naming game simulates the evolution of vocabulary in a population of agents. Through pairwise interactions in the games, agents acquire a set of vocabulary in their memory for object naming. The existing model confines to a one-to-one mapping between a name and an object. Focus is usually put onto name consensus in the population rather than knowledge learning in agents, and hence simple learning model is usually adopted. However, the cognition system of human being is much more complex and knowledge is usually presented in a complicated form. Therefore, in this work, we extend the agent learning model and design a new game to incorporate domain learning, which is essential for more complicated form of knowledge. In particular, we demonstrate the evolution of color categorization and naming in a population of agents. We incorporate the human perceptive model into the agents and introduce two new concepts, namely subjective perception and subliminal stimulation, in domain learning. Simulation results show that, even without any supervision or pre-requisition, a consensus of a color naming system can be reached in a population solely via the interactions. Our work confirms the importance of society interactions in color categorization, which is a long debate topic in human cognition. Moreover, our work also demonstrates the possibility of cognitive system development in autonomous intelligent agents. PMID:29136661

Is population structure sufficient to generate area-level inequalities in influenza rates? An examination using agent-based models.

PubMed

Kumar, Supriya; Piper, Kaitlin; Galloway, David D; Hadler, James L; Grefenstette, John J

2015-09-23

In New Haven County, CT (NHC), influenza hospitalization rates have been shown to increase with census tract poverty in multiple influenza seasons. Though multiple factors have been hypothesized to cause these inequalities, including population structure, differential vaccine uptake, and differential access to healthcare, the impact of each in generating observed inequalities remains unknown. We can design interventions targeting factors with the greatest explanatory power if we quantify the proportion of observed inequalities that hypothesized factors are able to generate. Here, we ask if population structure is sufficient to generate the observed area-level inequalities in NHC. To our knowledge, this is the first use of simulation models to examine the causes of differential poverty-related influenza rates. Using agent-based models with a census-informed, realistic representation of household size, age-structure, population density in NHC census tracts, and contact rates in workplaces, schools, households, and neighborhoods, we measured poverty-related differential influenza attack rates over the course of an epidemic with a 23 % overall clinical attack rate. We examined the role of asthma prevalence rates as well as individual contact rates and infection susceptibility in generating observed area-level influenza inequalities. Simulated attack rates (AR) among adults increased with census tract poverty level (F = 30.5; P < 0.001) in an epidemic caused by a virus similar to A (H1N1) pdm09. We detected a steeper, earlier influenza rate increase in high-poverty census tracts-a finding that we corroborate with a temporal analysis of NHC surveillance data during the 2009 H1N1 pandemic. The ratio of the simulated adult AR in the highest- to lowest-poverty tracts was 33 % of the ratio observed in surveillance data. Increasing individual contact rates in the neighborhood did not increase simulated area-level inequalities. When we modified individual susceptibility such that it was inversely proportional to household income, inequalities in AR between high- and low-poverty census tracts were comparable to those observed in reality. To our knowledge, this is the first study to use simulations to probe the causes of observed inequalities in influenza disease patterns. Knowledge of the causes and their relative explanatory power will allow us to design interventions that have the greatest impact on reducing inequalities. Differential exposure due to population structure in our realistic simulation model explains a third of the observed inequality. Differential susceptibility to disease due to prevailing chronic conditions, vaccine uptake, and smoking should be considered in future models in order to quantify the role of additional factors in generating influenza inequalities.

Modeling the impact of climate and landscape on the efficacy of white tailed deer vaccination for cattle tick control in northeastern Mexico.

PubMed

Estrada-Peña, Agustín; Carreón, Diana; Almazán, Consuelo; de la Fuente, José

2014-01-01

Cattle ticks are distributed worldwide and affect animal health and livestock production. White tailed deer (WTD) sustain and spread cattle tick populations. The aim of this study was to model the efficacy of anti-tick vaccination of WTD to control tick infestations in the absence of cattle vaccination in a territory where both host species coexist and sustain cattle tick populations. Agent-based models that included land cover/landscape properties (patch size, distances to patches) and climatic conditions were built in a GIS environment to simulate WTD vaccine effectiveness under conditions where unvaccinated cattle shared the landscape. Published and validated information on tick life cycle was used to build models describing tick mortality and developmental rates. Data from simulations were applied to a large territory in northeastern Mexico where cattle ticks are endemic and WTD and cattle share substantial portions of the habitat. WTD movements were simulated together with tick population dynamics considering the actual landscape and climatic features. The size of the vegetation patches and the distance between patches were critical for the successful control of tick infestations after WTD vaccination. The presence of well-connected, large vegetation patches proved essential for tick control, since the tick could persist in areas of highly fragmented habitat. The continued application of one yearly vaccination on days 1-70 for three years reduced tick abundance/animal/patch by a factor of 40 and 60 for R. annulatus and R. microplus, respectively when compared to non-vaccinated controls. The study showed that vaccination of WTD alone during three consecutive years could result in the reduction of cattle tick populations in northeastern Mexico. Furthermore, the results of the simulations suggested the possibility of using vaccines to prevent the spread and thus the re-introduction of cattle ticks into tick-free areas.

Modeling the effects of land use and climate change on riverine smallmouth bass

USGS Publications Warehouse

Peterson, J.T.; Kwak, T.J.

1999-01-01

Anthropogenic changes in temperature and stream flow, associated with watershed land use and climate change, are critical influences on the distribution and abundance of riverine fishes. To project the effects of changing land use and climate, we modeled a smallmouth bass (Micropterus dolomieu) population in a midwestern USA, large river- floodplain ecosystem under historical (1915-1925), present (1977-1990), and future (2060, influenced by climate change) temperature and flow regimes. The age-structured model included parameters for temperature and river discharge during critical seasonal periods, fish population dynamics, and fishing harvest. Model relationships were developed from empirical field data collected over a 13-yr period. Sensitivity analyses indicated that discharge during the spawning/rearing period had a greater effect on adult density and fishing yield than did spawning/rearing temperature or winter discharge. Simulations for 100 years projected a 139% greater mean fish density under a historical flow regime (64.9 fish/ha) than that estimated for the present (27.1 fish/ha) with a sustainable fishing harvest under both flow regimes. Simulations under future climate-change-induced temperature and flow regimes with present land use projected a 69% decrease in mean fish density (8.5 fish/ha) from present and an unstable population that went extinct during 56% of the simulations. However, when simulated under a future climate-altered temperature and flow regime with historical land use, the population increased by 66% (45.0 fish/ha) from present and sustained a harvest. Our findings suggest that land-use changes may be a greater detriment to riverine fishes than projected climate change and that the combined effects of both factors may lead to local species extinction. However, the negative effects of increased temperature and precipitation associated with future global warming could be mitigated by river channel, floodplain, and watershed restoration.

The Lagrangian Ensemble metamodel for simulating plankton ecosystems

NASA Astrophysics Data System (ADS)

Woods, J. D.

2005-10-01

This paper presents a detailed account of the Lagrangian Ensemble (LE) metamodel for simulating plankton ecosystems. It uses agent-based modelling to describe the life histories of many thousands of individual plankters. The demography of each plankton population is computed from those life histories. So too is bio-optical and biochemical feedback to the environment. The resulting “virtual ecosystem” is a comprehensive simulation of the plankton ecosystem. It is based on phenotypic equations for individual micro-organisms. LE modelling differs significantly from population-based modelling. The latter uses prognostic equations to compute demography and biofeedback directly. LE modelling diagnoses them from the properties of individual micro-organisms, whose behaviour is computed from prognostic equations. That indirect approach permits the ecosystem to adjust gracefully to changes in exogenous forcing. The paper starts with theory: it defines the Lagrangian Ensemble metamodel and explains how LE code performs a number of computations “behind the curtain”. They include budgeting chemicals, and deriving biofeedback and demography from individuals. The next section describes the practice of LE modelling. It starts with designing a model that complies with the LE metamodel. Then it describes the scenario for exogenous properties that provide the computation with initial and boundary conditions. These procedures differ significantly from those used in population-based modelling. The next section shows how LE modelling is used in research, teaching and planning. The practice depends largely on hindcasting to overcome the limits to predictability of weather forecasting. The scientific method explains observable ecosystem phenomena in terms of finer-grained processes that cannot be observed, but which are controlled by the basic laws of physics, chemistry and biology. What-If? Prediction ( WIP), used for planning, extends hindcasting by adding events that describe natural or man-made hazards and remedial actions. Verification is based on the Ecological Turing Test, which takes account of uncertainties in the observed and simulated versions of a target ecological phenomenon. The rest of the paper is devoted to a case study designed to show what LE modelling offers the biological oceanographer. The case study is presented in two parts. The first documents the WB model (Woods & Barkmann, 1994) and scenario used to simulate the ecosystem in a mesocosm moored in deep water off the Azores. The second part illustrates the emergent properties of that virtual ecosystem. The behaviour and development of an individual plankton lineage are revealed by an audit trail of the agent used in the computation. The fields of environmental properties reveal the impact of biofeedback. The fields of demographic properties show how changes in individuals cumulatively affect the birth and death rates of their population. This case study documents the virtual ecosystem used by Woods, Perilli and Barkmann (2005; hereafter WPB); to investigate the stability of simulations created by the Lagrangian Ensemble metamodel. The Azores virtual ecosystem was created and analysed on the Virtual Ecology Workbench (VEW) which is described briefly in the Appendix.

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.

Statistical power calculations for mixed pharmacokinetic study designs using a population approach.

PubMed

Kloprogge, Frank; Simpson, Julie A; Day, Nicholas P J; White, Nicholas J; Tarning, Joel

2014-09-01

Simultaneous modelling of dense and sparse pharmacokinetic data is possible with a population approach. To determine the number of individuals required to detect the effect of a covariate, simulation-based power calculation methodologies can be employed. The Monte Carlo Mapped Power method (a simulation-based power calculation methodology using the likelihood ratio test) was extended in the current study to perform sample size calculations for mixed pharmacokinetic studies (i.e. both sparse and dense data collection). A workflow guiding an easy and straightforward pharmacokinetic study design, considering also the cost-effectiveness of alternative study designs, was used in this analysis. Initially, data were simulated for a hypothetical drug and then for the anti-malarial drug, dihydroartemisinin. Two datasets (sampling design A: dense; sampling design B: sparse) were simulated using a pharmacokinetic model that included a binary covariate effect and subsequently re-estimated using (1) the same model and (2) a model not including the covariate effect in NONMEM 7.2. Power calculations were performed for varying numbers of patients with sampling designs A and B. Study designs with statistical power >80% were selected and further evaluated for cost-effectiveness. The simulation studies of the hypothetical drug and the anti-malarial drug dihydroartemisinin demonstrated that the simulation-based power calculation methodology, based on the Monte Carlo Mapped Power method, can be utilised to evaluate and determine the sample size of mixed (part sparsely and part densely sampled) study designs. The developed method can contribute to the design of robust and efficient pharmacokinetic studies.

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.

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.

Game dynamic model for yeast development.

PubMed

Huang, Yuanyuan; Wu, Zhijun

2012-07-01

Game theoretic models, along with replicator equations, have been applied successfully to the study of evolution of populations of competing species, including the growth of a population, the reaching of the population to an equilibrium state, and the evolutionary stability of the state. In this paper, we analyze a game model proposed by Gore et al. (Nature 456:253-256, 2009) in their recent study on the co-development of two mixed yeast strains. We examine the mathematical properties of this model with varying experimental parameters. We simulate the growths of the yeast strains and compare them with the experimental results. We also compute and analyze the equilibrium state of the system and prove that it is asymptotically and evolutionarily stable.

A novel quantitative model of cell cycle progression based on cyclin-dependent kinases activity and population balances.

PubMed

Pisu, Massimo; Concas, Alessandro; Cao, Giacomo

2015-04-01

Cell cycle regulates proliferative cell capacity under normal or pathologic conditions, and in general it governs all in vivo/in vitro cell growth and proliferation processes. Mathematical simulation by means of reliable and predictive models represents an important tool to interpret experiment results, to facilitate the definition of the optimal operating conditions for in vitro cultivation, or to predict the effect of a specific drug in normal/pathologic mammalian cells. Along these lines, a novel model of cell cycle progression is proposed in this work. Specifically, it is based on a population balance (PB) approach that allows one to quantitatively describe cell cycle progression through the different phases experienced by each cell of the entire population during its own life. The transition between two consecutive cell cycle phases is simulated by taking advantage of the biochemical kinetic model developed by Gérard and Goldbeter (2009) which involves cyclin-dependent kinases (CDKs) whose regulation is achieved through a variety of mechanisms that include association with cyclins and protein inhibitors, phosphorylation-dephosphorylation, and cyclin synthesis or degradation. This biochemical model properly describes the entire cell cycle of mammalian cells by maintaining a sufficient level of detail useful to identify check point for transition and to estimate phase duration required by PB. Specific examples are discussed to illustrate the ability of the proposed model to simulate the effect of drugs for in vitro trials of interest in oncology, regenerative medicine and tissue engineering. Copyright © 2015 Elsevier Ltd. All rights reserved.

Signatures of criticality arise from random subsampling in simple population models.

PubMed

Nonnenmacher, Marcel; Behrens, Christian; Berens, Philipp; Bethge, Matthias; Macke, Jakob H

2017-10-01

The rise of large-scale recordings of neuronal activity has fueled the hope to gain new insights into the collective activity of neural ensembles. How can one link the statistics of neural population activity to underlying principles and theories? One attempt to interpret such data builds upon analogies to the behaviour of collective systems in statistical physics. Divergence of the specific heat-a measure of population statistics derived from thermodynamics-has been used to suggest that neural populations are optimized to operate at a "critical point". However, these findings have been challenged by theoretical studies which have shown that common inputs can lead to diverging specific heat. Here, we connect "signatures of criticality", and in particular the divergence of specific heat, back to statistics of neural population activity commonly studied in neural coding: firing rates and pairwise correlations. We show that the specific heat diverges whenever the average correlation strength does not depend on population size. This is necessarily true when data with correlations is randomly subsampled during the analysis process, irrespective of the detailed structure or origin of correlations. We also show how the characteristic shape of specific heat capacity curves depends on firing rates and correlations, using both analytically tractable models and numerical simulations of a canonical feed-forward population model. To analyze these simulations, we develop efficient methods for characterizing large-scale neural population activity with maximum entropy models. We find that, consistent with experimental findings, increases in firing rates and correlation directly lead to more pronounced signatures. Thus, previous reports of thermodynamical criticality in neural populations based on the analysis of specific heat can be explained by average firing rates and correlations, and are not indicative of an optimized coding strategy. We conclude that a reliable interpretation of statistical tests for theories of neural coding is possible only in reference to relevant ground-truth models.

Cell lineage tracing in the developing enteric nervous system: superstars revealed by experiment and simulation

PubMed Central

Cheeseman, Bevan L.; Zhang, Dongcheng; Binder, Benjamin J.; Newgreen, Donald F.; Landman, Kerry A.

2014-01-01

Cell lineage tracing is a powerful tool for understanding how proliferation and differentiation of individual cells contribute to population behaviour. In the developing enteric nervous system (ENS), enteric neural crest (ENC) cells move and undergo massive population expansion by cell division within self-growing mesenchymal tissue. We show that single ENC cells labelled to follow clonality in the intestine reveal extraordinary and unpredictable variation in number and position of descendant cells, even though ENS development is highly predictable at the population level. We use an agent-based model to simulate ENC colonization and obtain agent lineage tracing data, which we analyse using econometric data analysis tools. In all realizations, a small proportion of identical initial agents accounts for a substantial proportion of the total final agent population. We term these individuals superstars. Their existence is consistent across individual realizations and is robust to changes in model parameters. This inequality of outcome is amplified at elevated proliferation rate. The experiments and model suggest that stochastic competition for resources is an important concept when understanding biological processes which feature high levels of cell proliferation. The results have implications for cell-fate processes in the ENS. PMID:24501272

Simulated effect of pig-population density on epidemic size and choice of control strategy for classical swine fever epidemics in The Netherlands.

PubMed

Mangen, M-J J; Nielen, M; Burrell, A M

2002-12-18

We examined the importance of pig-population density in the area of an outbreak of classical swine fever (CSF) for the spread of the infection and the choice of control measures. A spatial, stochastic, dynamic epidemiological simulation model linked to a sector-level market-and-trade model for The Netherlands were used. Outbreaks in sparsely and densely populated areas were compared under four different control strategies and with two alternative trade assumptions. The obligatory control strategy required by current EU legislation was predicted to be enough to eradicate an epidemic starting in an area with sparse pig population. By contrast, additional control measures would be necessary if the outbreak began in an area with high pig density. The economic consequences of using preventive slaughter rather than emergency vaccination as an additional control measure depended strongly on the reactions of trading partners. Reducing the number of animal movements significantly reduced the size and length of epidemics in areas with high pig density. The phenomenon of carrier piglets was included in the model with realistic probabilities of infection by this route, but it made a negligible contribution to the spread of the infection.

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

Proline puckering parameters for collagen structure simulations

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

Wu, Di, E-mail: diwu@fudan.edu.cn

Collagen is made of triple helices rich in proline residues, and hence is influenced by the conformational motions of prolines. Because the backbone motions of prolines are restricted by the helical structures, the only side chain motion—proline puckering—becomes an influential factor that may affect the stability of collagen structures. In molecular simulations, a proper proline puckering population is desired so to yield valid results of the collagen properties. Here we design the proline puckering parameters in order to yield suitable proline puckering populations as demonstrated in the experimental results. We test these parameters in collagen and the proline dipeptide simulations.more » Compared with the results of the PDB and the quantum calculations, we propose the proline puckering parameters for the selected collagen model simulations.« less

Stochastic foundations in nonlinear density-regulation growth

NASA Astrophysics Data System (ADS)

Méndez, Vicenç; Assaf, Michael; Horsthemke, Werner; Campos, Daniel

2017-08-01

In this work we construct individual-based models that give rise to the generalized logistic model at the mean-field deterministic level and that allow us to interpret the parameters of these models in terms of individual interactions. We also study the effect of internal fluctuations on the long-time dynamics for the different models that have been widely used in the literature, such as the theta-logistic and Savageau models. In particular, we determine the conditions for population extinction and calculate the mean time to extinction. If the population does not become extinct, we obtain analytical expressions for the population abundance distribution. Our theoretical results are based on WKB theory and the probability generating function formalism and are verified by numerical simulations.

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.

Assessing impacts of simulated oil spills on the Northeast Arctic cod fishery.

PubMed

Carroll, JoLynn; Vikebø, Frode; Howell, Daniel; Broch, Ole Jacob; Nepstad, Raymond; Augustine, Starrlight; Skeie, Geir Morten; Bast, Radovan; Juselius, Jonas

2018-01-01

We simulate oil spills of 1500 and 4500m 3 /day lasting 14, 45, and 90days in the spawning grounds of the commercial fish species, Northeast Arctic cod. Modeling the life history of individual fish eggs and larvae, we predict deviations from the historical pattern of recruitment to the adult population due to toxic oil exposures. Reductions in survival for pelagic stages of cod were 0-10%, up to a maximum of 43%. These reductions resulted in a decrease in adult cod biomass of <3% for most scenarios, up to a maximum of 12%. In all simulations, the adult population remained at full reproductive potential with a sufficient number of juveniles surviving to replenish the population. The diverse age distribution helps protect the adult cod population from reductions in a single year's recruitment after a major oil spill. These results provide insights to assist in managing oil spill impacts on fisheries. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Evolutionary Dynamics and Diversity in Microbial Populations

NASA Astrophysics Data System (ADS)

Thompson, Joel; Fisher, Daniel

2013-03-01

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

The “Dry-Run” Analysis: A Method for Evaluating Risk Scores for Confounding Control

PubMed Central

Wyss, Richard; Hansen, Ben B.; Ellis, Alan R.; Gagne, Joshua J.; Desai, Rishi J.; Glynn, Robert J.; Stürmer, Til

2017-01-01

Abstract A propensity score (PS) model's ability to control confounding can be assessed by evaluating covariate balance across exposure groups after PS adjustment. The optimal strategy for evaluating a disease risk score (DRS) model's ability to control confounding is less clear. DRS models cannot be evaluated through balance checks within the full population, and they are usually assessed through prediction diagnostics and goodness-of-fit tests. A proposed alternative is the “dry-run” analysis, which divides the unexposed population into “pseudo-exposed” and “pseudo-unexposed” groups so that differences on observed covariates resemble differences between the actual exposed and unexposed populations. With no exposure effect separating the pseudo-exposed and pseudo-unexposed groups, a DRS model is evaluated by its ability to retrieve an unconfounded null estimate after adjustment in this pseudo-population. We used simulations and an empirical example to compare traditional DRS performance metrics with the dry-run validation. In simulations, the dry run often improved assessment of confounding control, compared with the C statistic and goodness-of-fit tests. In the empirical example, PS and DRS matching gave similar results and showed good performance in terms of covariate balance (PS matching) and controlling confounding in the dry-run analysis (DRS matching). The dry-run analysis may prove useful in evaluating confounding control through DRS models. PMID:28338910

Spatial structuring within a reservoir fish population: implications for management

USGS Publications Warehouse

Stewart, David R.; Long, James M.; Shoup, Daniel E.

2014-01-01

Spatial structuring in reservoir fish populations can exist because of environmental gradients, species-specific behaviour, or even localised fishing effort. The present study investigated whether white crappie exhibited evidence of improved population structure where the northern more productive half of a lake is closed to fishing to provide waterfowl hunting opportunities. Population response to angling was modelled for each substock of white crappie (north (protected) and south (unprotected) areas), the entire lake (single-stock model) and by combining simulations of the two independent substock models (additive model). White crappie in the protected area were more abundant, consisting of larger, older individuals, and exhibited a lower total annual mortality rate than in the unprotected area. Population modelling found that fishing mortality rates between 0.1 and 0.3 resulted in sustainable populations (spawning potential ratios (SPR) >0.30). The population in the unprotected area appeared to be more resilient (SPR > 0.30) at the higher fishing intensities (0.35–0.55). Considered additively, the whole-lake fishery appeared more resilient than when modelled as a single-panmictic stock. These results provided evidence of spatial structuring in reservoir fish populations, and we recommend model assessments used to guide management decisions should consider those spatial differences in other populations where they exist.