Evolutionary dynamics of group interactions on structured populations: a review

PubMed Central

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

2013-01-01

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

Effects of model complexity and priors on estimation using sequential importance sampling/resampling for species conservation

USGS Publications Warehouse

Dunham, Kylee; Grand, James B.

2016-01-01

We examined the effects of complexity and priors on the accuracy of models used to estimate ecological and observational processes, and to make predictions regarding population size and structure. State-space models are useful for estimating complex, unobservable population processes and making predictions about future populations based on limited data. To better understand the utility of state space models in evaluating population dynamics, we used them in a Bayesian framework and compared the accuracy of models with differing complexity, with and without informative priors using sequential importance sampling/resampling (SISR). Count data were simulated for 25 years using known parameters and observation process for each model. We used kernel smoothing to reduce the effect of particle depletion, which is common when estimating both states and parameters with SISR. Models using informative priors estimated parameter values and population size with greater accuracy than their non-informative counterparts. While the estimates of population size and trend did not suffer greatly in models using non-informative priors, the algorithm was unable to accurately estimate demographic parameters. This model framework provides reasonable estimates of population size when little to no information is available; however, when information on some vital rates is available, SISR can be used to obtain more precise estimates of population size and process. Incorporating model complexity such as that required by structured populations with stage-specific vital rates affects precision and accuracy when estimating latent population variables and predicting population dynamics. These results are important to consider when designing monitoring programs and conservation efforts requiring management of specific population segments.

Rapid and Specific Method for Evaluating Streptomyces Competitive Dynamics in Complex Soil Communities

USDA-ARS?s Scientific Manuscript database

Quantifying target microbial populations in complex communities remains a barrier to studying species interactions in soil environments. Quantitative real-time PCR (qPCR) offers a rapid and specific means to assess populations of target microorganisms. SYBR Green and TaqMan-based qPCR assays were de...

Population and Environment

PubMed Central

de Sherbinin, Alex; Carr, David; Cassels, Susan; Jiang, Leiwen

2009-01-01

The interactions between human population dynamics and the environment have often been viewed mechanistically. This review elucidates the complexities and contextual specificities of population-environment relationships in a number of domains. It explores the ways in which demographers and other social scientists have sought to understand the relationships among a full range of population dynamics (e.g., population size, growth, density, age and sex composition, migration, urbanization, vital rates) and environmental changes. The chapter briefly reviews a number of the theories for understanding population and the environment and then proceeds to provide a state-of-the-art review of studies that have examined population dynamics and their relationship to five environmental issue areas. The review concludes by relating population-environment research to emerging work on human-environment systems. PMID:20011237

Evolutionary dynamics of the traveler's dilemma and minimum-effort coordination games on complex networks.

PubMed

Iyer, Swami; Killingback, Timothy

2014-10-01

The traveler's dilemma game and the minimum-effort coordination game are social dilemmas that have received significant attention resulting from the fact that the predictions of classical game theory are inconsistent with the results found when the games are studied experimentally. Moreover, both the traveler's dilemma and the minimum-effort coordination games have potentially important applications in evolutionary biology. Interestingly, standard deterministic evolutionary game theory, as represented by the replicator dynamics in a well-mixed population, is also inadequate to account for the behavior observed in these games. Here we study the evolutionary dynamics of both these games in populations with interaction patterns described by a variety of complex network topologies. We investigate the evolutionary dynamics of these games through agent-based simulations on both model and empirical networks. In particular, we study the effects of network clustering and assortativity on the evolutionary dynamics of both games. In general, we show that the evolutionary behavior of the traveler's dilemma and minimum-effort coordination games on complex networks is in good agreement with that observed experimentally. Thus, formulating the traveler's dilemma and the minimum-effort coordination games on complex networks neatly resolves the paradoxical aspects of these games.

Evolutionary dynamics of the traveler's dilemma and minimum-effort coordination games on complex networks

NASA Astrophysics Data System (ADS)

Iyer, Swami; Killingback, Timothy

2014-10-01

The traveler's dilemma game and the minimum-effort coordination game are social dilemmas that have received significant attention resulting from the fact that the predictions of classical game theory are inconsistent with the results found when the games are studied experimentally. Moreover, both the traveler's dilemma and the minimum-effort coordination games have potentially important applications in evolutionary biology. Interestingly, standard deterministic evolutionary game theory, as represented by the replicator dynamics in a well-mixed population, is also inadequate to account for the behavior observed in these games. Here we study the evolutionary dynamics of both these games in populations with interaction patterns described by a variety of complex network topologies. We investigate the evolutionary dynamics of these games through agent-based simulations on both model and empirical networks. In particular, we study the effects of network clustering and assortativity on the evolutionary dynamics of both games. In general, we show that the evolutionary behavior of the traveler's dilemma and minimum-effort coordination games on complex networks is in good agreement with that observed experimentally. Thus, formulating the traveler's dilemma and the minimum-effort coordination games on complex networks neatly resolves the paradoxical aspects of these games.

Sexual reproduction and population dynamics: the role of polygyny and demographic sex differences.

PubMed Central

Lindström, J; Kokko, H

1998-01-01

Most models of population dynamics do not take sexual reproduction into account (i.e., they do not consider the role of males). However, assumptions behind this practice--that no demographic sex differences exist and males are always abundant enough to fertilize all the females--are usually not justified in natural populations. On the contrary, demographic sex differences are common, especially in polygynous species. Previous models that consider sexual reproduction report a stabilizing effect through mixing of different genotypes, thus suggesting a decrease in the propensity for complex of dynamics in sexually reproducing populations. Here we show that considering the direct role of males in reproduction and density dependence leads to the conclusion that a two-sex model is not necessarily more stable compared with the corresponding one-sex model. Although solutions exist where sexual reproduction has a stabilizing effect even when no genotypic variability is included (primarily when associated with monogamy), factors like polygyny, sex differences in survival or density dependence, and possible alterations of the primary sex ratio (the Trivers-Willard mechanism), may enlarge the parametric region of complex dynamics. Sexual reproduction therefore does not necessarily increase the stability of population dynamics and can have destabilizing effects, at least in species with complicated mating systems and sexual dimorphism. PMID:9606132

Application of network methods for understanding evolutionary dynamics in discrete habitats.

PubMed

Greenbaum, Gili; Fefferman, Nina H

2017-06-01

In populations occupying discrete habitat patches, gene flow between habitat patches may form an intricate population structure. In such structures, the evolutionary dynamics resulting from interaction of gene-flow patterns with other evolutionary forces may be exceedingly complex. Several models describing gene flow between discrete habitat patches have been presented in the population-genetics literature; however, these models have usually addressed relatively simple settings of habitable patches and have stopped short of providing general methodologies for addressing nontrivial gene-flow patterns. In the last decades, network theory - a branch of discrete mathematics concerned with complex interactions between discrete elements - has been applied to address several problems in population genetics by modelling gene flow between habitat patches using networks. Here, we present the idea and concepts of modelling complex gene flows in discrete habitats using networks. Our goal is to raise awareness to existing network theory applications in molecular ecology studies, as well as to outline the current and potential contribution of network methods to the understanding of evolutionary dynamics in discrete habitats. We review the main branches of network theory that have been, or that we believe potentially could be, applied to population genetics and molecular ecology research. We address applications to theoretical modelling and to empirical population-genetic studies, and we highlight future directions for extending the integration of network science with molecular ecology. © 2017 John Wiley & Sons Ltd.

Task-phase-specific dynamics of basal forebrain neuronal ensembles

PubMed Central

Tingley, David; Alexander, Andrew S.; Kolbu, Sean; de Sa, Virginia R.; Chiba, Andrea A.; Nitz, Douglas A.

2014-01-01

Cortically projecting basal forebrain neurons play a critical role in learning and attention, and their degeneration accompanies age-related impairments in cognition. Despite the impressive anatomical and cell-type complexity of this system, currently available data suggest that basal forebrain neurons lack complexity in their response fields, with activity primarily reflecting only macro-level brain states such as sleep and wake, onset of relevant stimuli and/or reward obtainment. The current study examined the spiking activity of basal forebrain neuron populations across multiple phases of a selective attention task, addressing, in particular, the issue of complexity in ensemble firing patterns across time. Clustering techniques applied to the full population revealed a large number of distinct categories of task-phase-specific activity patterns. Unique population firing-rate vectors defined each task phase and most categories of task-phase-specific firing had counterparts with opposing firing patterns. An analogous set of task-phase-specific firing patterns was also observed in a population of posterior parietal cortex neurons. Thus, consistent with the known anatomical complexity, basal forebrain population dynamics are capable of differentially modulating their cortical targets according to the unique sets of environmental stimuli, motor requirements, and cognitive processes associated with different task phases. PMID:25309352

Parameter Estimation in Epidemiology: from Simple to Complex Dynamics

NASA Astrophysics Data System (ADS)

Aguiar, Maíra; Ballesteros, Sebastién; Boto, João Pedro; Kooi, Bob W.; Mateus, Luís; Stollenwerk, Nico

2011-09-01

We revisit the parameter estimation framework for population biological dynamical systems, and apply it to calibrate various models in epidemiology with empirical time series, namely influenza and dengue fever. When it comes to more complex models like multi-strain dynamics to describe the virus-host interaction in dengue fever, even most recently developed parameter estimation techniques, like maximum likelihood iterated filtering, come to their computational limits. However, the first results of parameter estimation with data on dengue fever from Thailand indicate a subtle interplay between stochasticity and deterministic skeleton. The deterministic system on its own already displays complex dynamics up to deterministic chaos and coexistence of multiple attractors.

Garter snake population dynamics from a 16-year study: considerations for ecological monitoring

Treesearch

Amy J. Lind; Hartwell H. Welsh Jr; David A. Tallmon

2005-01-01

Snakes have recently been proposed as model organisms for addressing both evolutionary and ecological questions. Because of their middle position in many food webs they may be useful indicators of trophic complexity and dynamics. However, reliable data on snake populations are rare due to the challenges of sampling these patchily distributed, cryptic, and often...

Dynamic-landscape metapopulation models predict complex response of wildlife populations to climate and landscape change

Treesearch

Thomas W. Bonnot; Frank R. Thompson; Joshua J. Millspaugh

2017-01-01

The increasing need to predict how climate change will impact wildlife species has exposed limitations in how well current approaches model important biological processes at scales at which those processes interact with climate. We used a comprehensive approach that combined recent advances in landscape and population modeling into dynamic-landscape metapopulation...

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

Approaching the molecular origins of collective dynamics in oscillating cell populations

PubMed Central

Mehta, Pankaj; Gregor, Thomas

2011-01-01

From flocking birds, to organ generation, to swarming bacterial colonies, biological systems often exhibit collective behaviors. Here, we review recent advances in our understanding of collective dynamics in cell populations. We argue that understanding population-level oscillations requires examining the system under consideration at three different levels of complexity: at the level of isolated cells, homogenous populations, and spatially structured populations. We discuss the experimental and theoretical challenges this poses and highlight how new experimental techniques, when combined with conceptual tools adapted from physics, may help us overcome these challenges. PMID:20934869

How Does a Divided Population Respond to Change?

PubMed

Qubbaj, Murad R; Muneepeerakul, Rachata; Aggarwal, Rimjhim M; Anderies, John M

2015-01-01

Most studies on the response of socioeconomic systems to a sudden shift focus on long-term equilibria or end points. Such narrow focus forgoes many valuable insights. Here we examine the transient dynamics of regime shift on a divided population, exemplified by societies divided ideologically, politically, economically, or technologically. Replicator dynamics is used to investigate the complex transient dynamics of the population response. Though simple, our modeling approach exhibits a surprisingly rich and diverse array of dynamics. Our results highlight the critical roles played by diversity in strategies and the magnitude of the shift. Importantly, it allows for a variety of strategies to arise organically as an integral part of the transient dynamics--as opposed to an independent process--of population response to a regime shift, providing a link between the population's past and future diversity patterns. Several combinations of different populations' strategy distributions and shifts were systematically investigated. Such rich dynamics highlight the challenges of anticipating the response of a divided population to a change. The findings in this paper can potentially improve our understanding of a wide range of socio-ecological and technological transitions.

Nonlinear Relaxation in Population Dynamics

NASA Astrophysics Data System (ADS)

Cirone, Markus A.; de Pasquale, Ferdinando; Spagnolo, Bernardo

We analyze the nonlinear relaxation of a complex ecosystem composed of many interacting species. The ecological system is described by generalized Lotka-Volterra equations with a multiplicative noise. The transient dynamics is studied in the framework of the mean field theory and with random interaction between the species. We focus on the statistical properties of the asymptotic behaviour of the time integral of the ith population and on the distribution of the population and of the local field.

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

PubMed

Kalinkin, D E; Karpov, A B; Takhauov, R M; Samoĭlova, Iu A

2013-01-01

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

Femtosecond dynamics of energy transfer in B800-850 light-harvesting complexes of Rhodobacter sphaeroides.

PubMed Central

Trautman, J K; Shreve, A P; Violette, C A; Frank, H A; Owens, T G; Albrecht, A C

1990-01-01

We report femtosecond transient absorption studies of energy transfer dynamics in the B800-850 light-harvesting complex (LHC) of Rhodobacter sphaeroides 2.4.1. For complexes solubilized in lauryldimethylamine-N-oxide (LDAO), the carotenoid to bacteriochlorophyll (Bchl) B800 and carotenoid to Bchl B850 energy transfer times are 0.34 and 0.20 ps, respectively. The B800 to B850 energy transfer time is 2.5 ps. For complexes treated with lithium dodecyl sulfate (LDS), a carotenoid to B850 energy transfer time of less than or equal to 0.2 ps is seen, and a portion of the total carotenoid population is decoupled from Bchl. In both LDAO-solubilized and LDS-treated complexes an intensity-dependent picosecond decay component of the excited B850 population is ascribed to excitation annihilation within minimal units of the LHC. PMID:2404276

Genetic consequences of forest population dynamics influenced by historic climatic variability in the western USA

Treesearch

Robert D. Westfall; Constance I. Millar

2004-01-01

We review recent advances in climate science that show cyclic climatic variation over multiple time scales and give examples of the impacts of this variation on plant populations in the western USA. The paleohistorical reconstructions we review and others indicate that plant specles track these cycles in individualistically complex ways. These dynamic histories suggest...

Life history determines genetic structure and evolutionary potential of host–parasite interactions

PubMed Central

Barrett, Luke G.; Thrall, Peter H.; Burdon, Jeremy J.; Linde, Celeste C.

2009-01-01

Measures of population genetic structure and diversity of disease-causing organisms are commonly used to draw inferences regarding their evolutionary history and potential to generate new variation in traits that determine interactions with their hosts. Parasite species exhibit a range of population structures and life-history strategies, including different transmission modes, life-cycle complexity, off-host survival mechanisms and dispersal ability. These are important determinants of the frequency and predictability of interactions with host species. Yet the complex causal relationships between spatial structure, life history and the evolutionary dynamics of parasite populations are not well understood. We demonstrate that a clear picture of the evolutionary potential of parasitic organisms and their demographic and evolutionary histories can only come from understanding the role of life history and spatial structure in influencing population dynamics and epidemiological patterns. PMID:18947899

Life history determines genetic structure and evolutionary potential of host-parasite interactions.

PubMed

Barrett, Luke G; Thrall, Peter H; Burdon, Jeremy J; Linde, Celeste C

2008-12-01

Measures of population genetic structure and diversity of disease-causing organisms are commonly used to draw inferences regarding their evolutionary history and potential to generate new variation in traits that determine interactions with their hosts. Parasite species exhibit a range of population structures and life-history strategies, including different transmission modes, life-cycle complexity, off-host survival mechanisms and dispersal ability. These are important determinants of the frequency and predictability of interactions with host species. Yet the complex causal relationships between spatial structure, life history and the evolutionary dynamics of parasite populations are not well understood. We demonstrate that a clear picture of the evolutionary potential of parasitic organisms and their demographic and evolutionary histories can only come from understanding the role of life history and spatial structure in influencing population dynamics and epidemiological patterns.

How Does a Divided Population Respond to Change?

PubMed Central

Qubbaj, Murad R.; Muneepeerakul, Rachata; Aggarwal, Rimjhim M.; Anderies, John M.

2015-01-01

Most studies on the response of socioeconomic systems to a sudden shift focus on long-term equilibria or end points. Such narrow focus forgoes many valuable insights. Here we examine the transient dynamics of regime shift on a divided population, exemplified by societies divided ideologically, politically, economically, or technologically. Replicator dynamics is used to investigate the complex transient dynamics of the population response. Though simple, our modeling approach exhibits a surprisingly rich and diverse array of dynamics. Our results highlight the critical roles played by diversity in strategies and the magnitude of the shift. Importantly, it allows for a variety of strategies to arise organically as an integral part of the transient dynamics—as opposed to an independent process—of population response to a regime shift, providing a link between the population's past and future diversity patterns. Several combinations of different populations' strategy distributions and shifts were systematically investigated. Such rich dynamics highlight the challenges of anticipating the response of a divided population to a change. The findings in this paper can potentially improve our understanding of a wide range of socio-ecological and technological transitions. PMID:26161859

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

NASA Astrophysics Data System (ADS)

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

2011-09-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-09-01

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

Population and coherence dynamics in light harvesting complex II (LH2).

PubMed

Yeh, Shu-Hao; Zhu, Jing; Kais, Sabre

2012-08-28

The electronic excitation population and coherence dynamics in the chromophores of the photosynthetic light harvesting complex 2 (LH2) B850 ring from purple bacteria (Rhodopseudomonas acidophila) have been studied theoretically at both physiological and cryogenic temperatures. Similar to the well-studied Fenna-Matthews-Olson (FMO) protein, oscillations of the excitation population and coherence in the site basis are observed in LH2 by using a scaled hierarchical equation of motion approach. However, this oscillation time (300 fs) is much shorter compared to the FMO protein (650 fs) at cryogenic temperature. Both environment and high temperature are found to enhance the propagation speed of the exciton wave packet yet they shorten the coherence time and suppress the oscillation amplitude of coherence and the population. Our calculations show that a long-lived coherence between chromophore electronic excited states can exist in such a noisy biological environment.

Can Evolution Supply What Ecology Demands?

PubMed

Kokko, Hanna; Chaturvedi, Anurag; Croll, Daniel; Fischer, Martin C; Guillaume, Frédéric; Karrenberg, Sophie; Kerr, Ben; Rolshausen, Gregor; Stapley, Jessica

2017-03-01

A simplistic view of the adaptive process pictures a hillside along which a population can climb: when ecological 'demands' change, evolution 'supplies' the variation needed for the population to climb to a new peak. Evolutionary ecologists point out that this simplistic view can be incomplete because the fitness landscape changes dynamically as the population evolves. Geneticists meanwhile have identified complexities relating to the nature of genetic variation and its architecture, and the importance of epigenetic variation is under debate. In this review, we highlight how complexity in both ecological 'demands' and the evolutionary 'supply' influences organisms' ability to climb fitness landscapes that themselves change dynamically as evolution proceeds, and encourage new synthetic effort across research disciplines towards ecologically realistic studies of adaptation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Identification of metapopulation dynamics among Northern Goshawks of the Alexander Archipelago, Alaska, and Coastal British Columbia

USGS Publications Warehouse

Sonsthagen, Sarah A.; McClaren, Erica L.; Doyle, Frank I.; Titus, K.; Sage, George K.; Wilson, Robert E.; Gust, Judy R.; Talbot, Sandra L.

2012-01-01

Northern Goshawks occupying the Alexander Archipelago, Alaska, and coastal British Columbia nest primarily in old-growth and mature forest, which results in spatial heterogeneity in the distribution of individuals across the landscape. We used microsatellite and mitochondrial data to infer genetic structure, gene flow, and fluctuations in population demography through evolutionary time. Patterns in the genetic signatures were used to assess predictions associated with the three population models: panmixia, metapopulation, and isolated populations. Population genetic structure was observed along with asymmetry in gene flow estimates that changed directionality at different temporal scales, consistent with metapopulation model predictions. Therefore, Northern Goshawk assemblages located in the Alexander Archipelago and coastal British Columbia interact through a metapopulation framework, though they may not fit the classic model of a metapopulation. Long-term population sources (coastal mainland British Columbia) and sinks (Revillagigedo and Vancouver islands) were identified. However, there was no trend through evolutionary time in the directionality of dispersal among the remaining assemblages, suggestive of a rescue-effect dynamic. Admiralty, Douglas, and Chichagof island complex appears to be an evolutionarily recent source population in the Alexander Archipelago. In addition, Kupreanof island complex and Kispiox Forest District populations have high dispersal rates to populations in close geographic proximity and potentially serve as local source populations. Metapopulation dynamics occurring in the Alexander Archipelago and coastal British Columbia by Northern Goshawks highlight the importance of both occupied and unoccupied habitats to long-term population persistence of goshawks in this region.

A Proposed Approach for Screening Level Assessment of Risk to Songbird Populations from Pesticide Application in Cotton Fields

EPA Science Inventory

Due to complex population dynamics and migration behaviors, the well-being of animal populations that host human diseases sometimes varies across landscapes in ways that cannot be deduced from geographic abundance patterns alone. In such cases, efficient management of ecologica...

Population Dynamics of Genetic Regulatory Networks

NASA Astrophysics Data System (ADS)

Braun, Erez

2005-03-01

Unlike common objects in physics, a biological cell processes information. The cell interprets its genome and transforms the genomic information content, through the action of genetic regulatory networks, into proteins which in turn dictate its metabolism, functionality and morphology. Understanding the dynamics of a population of biological cells presents a unique challenge. It requires to link the intracellular dynamics of gene regulation, through the mechanism of cell division, to the level of the population. We present experiments studying adaptive dynamics of populations of genetically homogeneous microorganisms (yeast), grown for long durations under steady conditions. We focus on population dynamics that do not involve random genetic mutations. Our experiments follow the long-term dynamics of the population distributions and allow to quantify the correlations among generations. We focus on three interconnected issues: adaptation of genetically homogeneous populations following environmental changes, selection processes on the population and population variability and expression distributions. We show that while the population exhibits specific short-term responses to environmental inputs, it eventually adapts to a robust steady-state, largely independent of external conditions. Cycles of medium-switch show that the adapted state is imprinted in the population and that this memory is maintained for many generations. To further study population adaptation, we utilize the process of gene recruitment whereby a gene naturally regulated by a specific promoter is placed under a different regulatory system. This naturally occurring process has been recognized as a major driving force in evolution. We have recruited an essential gene to a foreign regulatory network and followed the population long-term dynamics. Rewiring of the regulatory network allows us to expose their complex dynamics and phase space structure.

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

PubMed

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

2014-04-01

Two sources of complexity make predicting plant community response to global change particularly challenging. First, realistic global change scenarios involve multiple drivers of environmental change that can interact with one another to produce non-additive effects. Second, in addition to these direct effects, global change drivers can indirectly affect plants by modifying species interactions. In order to tackle both of these challenges, we propose a novel population modeling approach, requiring only measurements of abundance and climate over time. To demonstrate the applicability of this approach, we model population dynamics of eight abundant plant species in a multifactorial global change experiment in alpine tundra where we manipulated nitrogen, precipitation, and temperature over 7 years. We test whether indirect and interactive effects are important to population dynamics and whether explicitly incorporating species interactions can change predictions when models are forecast under future climate change scenarios. For three of the eight species, population dynamics were best explained by direct effect models, for one species neither direct nor indirect effects were important, and for the other four species indirect effects mattered. Overall, global change had negative effects on species population growth, although species responded to different global change drivers, and single-factor effects were slightly more common than interactive direct effects. When the fitted population dynamic models were extrapolated under changing climatic conditions to the end of the century, forecasts of community dynamics and diversity loss were largely similar using direct effect models that do not explicitly incorporate species interactions or best-fit models; however, inclusion of species interactions was important in refining the predictions for two of the species. The modeling approach proposed here is a powerful way of analyzing readily available datasets which should be added to our toolbox to tease apart complex drivers of global change. © 2013 John Wiley & Sons Ltd.

Effects of Dynamical Evolution on Globular Clusters’ Internal Kinematics

NASA Astrophysics Data System (ADS)

Tiongco, Maria; Vesperini, Enrico; Varri, Anna Lisa

2018-01-01

The synergy between recent photometric, spectroscopic, and astrometric studies is revealing that globular clusters deviate from the traditional picture of dynamically simple and single stellar population systems. Complex kinematical features such as velocity anisotropy and rotation, and the existence of multiple stellar populations are some of the key observational findings. My thesis work has aimed to build a theoretical framework to interpret these new observational results and to understand their link with a globular cluster’s dynamical history.I have focused on the study of the evolution of globular clusters' internal kinematics, as driven by two-body relaxation, and the interplay between internal angular momentum and the external Galactic tidal field. With a specifically-designed, large survey of direct N-body simulations, I have explored the three-dimensional structure of the velocity space of tidally-perturbed clusters, by characterizing their degree of anisotropy and their rotational properties. These studies have proved that a cluster's kinematical properties contain a distinct imprints of the cluster’s initial structural properties, dynamical history, and tidal environment. By relaxing a number of simplifying assumptions that are traditionally imposed, I have also showed how the interplay between a cluster's internal evolution and the interaction with the host galaxy can produce complex morphological and kinematical properties, such as a counter-rotating core and a twisting of the projected isodensity contours.Building on this fundamental understanding, I have then studied the dynamics of multiple stellar populations in globular clusters, with attention to the largely unexplored role of angular momentum. I have analyzed the evolution of clusters with stellar populations characterized by different initial structural and kinematical properties to determine how long these differences are preserved, and in what cases they could still be observable in present-day systems.This body of results provides essential guidance for a meaningful interpretation of the emerging dynamical complexity of globular clusters in the era of Gaia and other upcoming large spectroscopic surveys.

Combined effects of climate, predation, and density dependence on Greater and Lesser Scaup population dynamics

USGS Publications Warehouse

Ross, Beth E.; Hooten, Mevin B.; DeVink, Jean-Michel; Koons, David N.

2015-01-01

An understanding of species relationships is critical in the management and conservation of populations facing climate change, yet few studies address how climate alters species interactions and other population drivers. We use a long-term, broad-scale data set of relative abundance to examine the influence of climate, predators, and density dependence on the population dynamics of declining scaup (Aythya) species within the core of their breeding range. The state-space modeling approach we use applies to a wide range of wildlife species, especially populations monitored over broad spatiotemporal extents. Using this approach, we found that immediate snow cover extent in the preceding winter and spring had the strongest effects, with increases in mean snow cover extent having a positive effect on the local surveyed abundance of scaup. The direct effects of mesopredator abundance on scaup population dynamics were weaker, but the results still indicated a potential interactive process between climate and food web dynamics (mesopredators, alternative prey, and scaup). By considering climate variables and other potential effects on population dynamics, and using a rigorous estimation framework, we provide insight into complex ecological processes for guiding conservation and policy actions aimed at mitigating and reversing the decline of scaup.

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

PubMed Central

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

2014-01-01

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

High-amplitude fluctuations and alternative dynamical states of midges in Lake Myvatn.

PubMed

Ives, Anthony R; Einarsson, Arni; Jansen, Vincent A A; Gardarsson, Arnthor

2008-03-06

Complex dynamics are often shown by simple ecological models and have been clearly demonstrated in laboratory and natural systems. Yet many classes of theoretically possible dynamics are still poorly documented in nature. Here we study long-term time-series data of a midge, Tanytarsus gracilentus (Diptera: Chironomidae), in Lake Myvatn, Iceland. The midge undergoes density fluctuations of almost six orders of magnitude. Rather than regular cycles, however, these fluctuations have irregular periods of 4-7 years, indicating complex dynamics. We fit three consumer-resource models capable of qualitatively distinct dynamics to the data. Of these, the best-fitting model shows alternative dynamical states in the absence of environmental variability; depending on the initial midge densities, the model shows either fluctuations around a fixed point or high-amplitude cycles. This explains the observed complex population dynamics: high-amplitude but irregular fluctuations occur because stochastic variability causes the dynamics to switch between domains of attraction to the alternative states. In the model, the amplitude of fluctuations depends strongly on minute resource subsidies into the midge habitat. These resource subsidies may be sensitive to human-caused changes in the hydrology of the lake, with human impacts such as dredging leading to higher-amplitude fluctuations. Tanytarsus gracilentus is a key component of the Myvatn ecosystem, representing two-thirds of the secondary productivity of the lake and providing vital food resources to fish and to breeding bird populations. Therefore the high-amplitude, irregular fluctuations in midge densities generated by alternative dynamical states dominate much of the ecology of the lake.

Density dependence in group dynamics of a highly social mongoose, Suricata suricatta.

PubMed

Bateman, Andrew W; Ozgul, Arpat; Coulson, Tim; Clutton-Brock, Tim H

2012-05-01

1. For social species, the link between individual behaviour and population dynamics is mediated by group-level demography. 2. Populations of obligate cooperative breeders are structured into social groups, which may be subject to inverse density dependence (Allee effects) that result from a dependence on conspecific helpers, but evidence for population-wide Allee effects is rare. 3. We use field data from a long-term study of cooperative meerkats (Suricata suricatta; Schreber, 1776) - a species for which local Allee effects are not reflected in population-level dynamics - to empirically model interannual group dynamics. 4. Using phenomenological population models, modified to incorporate environmental conditions and potential Allee effects, we first investigate overall patterns of group dynamics and find support only for conventional density dependence that increases after years of low rainfall. 5. To explain the observed patterns, we examine specific demographic rates and assess their contributions to overall group dynamics. Although per-capita meerkat mortality is subject to a component Allee effect, it contributes relatively little to observed variation in group dynamics, and other (conventionally density dependent) demographic rates - especially emigration - govern group dynamics. 6. Our findings highlight the need to consider demographic processes and density dependence in subpopulations before drawing conclusions about how behaviour affects population processes in socially complex systems. © 2011 The Authors. Journal of Animal Ecology © 2011 British Ecological Society.

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.

Dynamic complexities in a pest control model with birth pulse and harvesting

NASA Astrophysics Data System (ADS)

Goel, A.; Gakkhar, S.

2016-04-01

In this paper, an impulsive model is discussed for an integrated pest management approach comprising of chemical and mechanical controls. The pesticides and harvesting are used to control the stage-structured pest population. The mature pest give birth to immature pest in pulses at regular intervals. The pest is controlled by spraying chemical pesticides affecting immature as well as mature pest. The harvesting of both immature and mature pest further reduce the pest population. The discrete dynamical system obtained from stroboscopic map is analyzed. The threshold conditions for stability of pest-free state as well as non-trivial period-1 solution is obtained. The effect of pesticide spray timing and harvesting on immature as well as mature pest are shown. Finally, by numerical simulation with MATLAB, the dynamical behaviors of the model is found to be complex. Above the threshold level there is a characteristic sequence of bifurcations leading to chaotic dynamics. Route to chaos is found to be period-doubling. Period halving bifurcations are also observed.

Coherence and population dynamics of chlorophyll excitations in FCP complex: Two-dimensional spectroscopy study

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

Butkus, Vytautas; Gelzinis, Andrius; Valkunas, Leonas

2015-06-07

Energy transfer processes and coherent phenomena in the fucoxanthin–chlorophyll protein complex, which is responsible for the light harvesting function in marine algae diatoms, were investigated at 77 K by using two-dimensional electronic spectroscopy. Experiments performed on femtosecond and picosecond timescales led to separation of spectral dynamics, witnessing evolutions of coherence and population states of the system in the spectral region of Q{sub y} transitions of chlorophylls a and c. Analysis of the coherence dynamics allowed us to identify chlorophyll (Chl) a and fucoxanthin intramolecular vibrations dominating over the first few picoseconds. Closer inspection of the spectral region of the Q{submore » y} transition of Chl c revealed previously not identified, mutually non-interacting chlorophyll c states participating in femtosecond or picosecond energy transfer to the Chl a molecules. Consideration of separated coherent and incoherent dynamics allowed us to hypothesize the vibrations-assisted coherent energy transfer between Chl c and Chl a and the overall spatial arrangement of chlorophyll molecules.« less

Dynamical responses to external stimuli for both cases of excitatory and inhibitory synchronization in a complex neuronal network.

PubMed

Kim, Sang-Yoon; Lim, Woochang

2017-10-01

For studying how dynamical responses to external stimuli depend on the synaptic-coupling type, we consider two types of excitatory and inhibitory synchronization (i.e., synchronization via synaptic excitation and inhibition) in complex small-world networks of excitatory regular spiking (RS) pyramidal neurons and inhibitory fast spiking (FS) interneurons. For both cases of excitatory and inhibitory synchronization, effects of synaptic couplings on dynamical responses to external time-periodic stimuli S ( t ) (applied to a fraction of neurons) are investigated by varying the driving amplitude A of S ( t ). Stimulated neurons are phase-locked to external stimuli for both cases of excitatory and inhibitory couplings. On the other hand, the stimulation effect on non-stimulated neurons depends on the type of synaptic coupling. The external stimulus S ( t ) makes a constructive effect on excitatory non-stimulated RS neurons (i.e., it causes external phase lockings in the non-stimulated sub-population), while S ( t ) makes a destructive effect on inhibitory non-stimulated FS interneurons (i.e., it breaks up original inhibitory synchronization in the non-stimulated sub-population). As results of these different effects of S ( t ), the type and degree of dynamical response (e.g., synchronization enhancement or suppression), characterized by the dynamical response factor [Formula: see text] (given by the ratio of synchronization degree in the presence and absence of stimulus), are found to vary in a distinctly different way, depending on the synaptic-coupling type. Furthermore, we also measure the matching degree between the dynamics of the two sub-populations of stimulated and non-stimulated neurons in terms of a "cross-correlation" measure [Formula: see text]. With increasing A , based on [Formula: see text], we discuss the cross-correlations between the two sub-populations, affecting the dynamical responses to S ( t ).

Unraveling the complexities of disaster management: a framework for critical social infrastructure to promote population health and resilience.

PubMed

O'Sullivan, Tracey L; Kuziemsky, Craig E; Toal-Sullivan, Darene; Corneil, Wayne

2013-09-01

Complexity is a useful frame of reference for disaster management and understanding population health. An important means to unraveling the complexities of disaster management is to recognize the interdependencies between health care and broader social systems and how they intersect to promote health and resilience before, during and after a crisis. While recent literature has expanded our understanding of the complexity of disasters at the macro level, few studies have examined empirically how dynamic elements of critical social infrastructure at the micro level influence community capacity. The purpose of this study was to explore empirically the complexity of disasters, to determine levers for action where interventions can be used to facilitate collaborative action and promote health among high risk populations. A second purpose was to build a framework for critical social infrastructure and develop a model to identify potential points of intervention to promote population health and resilience. A community-based participatory research design was used in nine focus group consultations (n = 143) held in five communities in Canada, between October 2010 and March 2011, using the Structured Interview Matrix facilitation technique. The findings underscore the importance of interconnectedness of hard and soft systems at the micro level, with culture providing the backdrop for the social fabric of each community. Open coding drawing upon the tenets of complexity theory was used to develop four core themes that provide structure for the framework that evolved; they relate to dynamic context, situational awareness and connectedness, flexible planning, and collaboration, which are needed to foster adaptive responses to disasters. Seven action recommendations are presented, to promote community resilience and population health. Copyright © 2012 Elsevier Ltd. All rights reserved.

Vegetation changes associated with a population irruption by Roosevelt elk

USGS Publications Warehouse

Starns, H D; Weckerly, Floyd W.; Ricca, Mark; Duarte, Adam

2015-01-01

Interactions between large herbivores and their food supply are central to the study of population dynamics. We assessed temporal and spatial patterns in meadow plant biomass over a 23-year period for meadow complexes that were spatially linked to three distinct populations of Roosevelt elk (Cervus elaphus roosevelti) in northwestern California. Our objectives were to determine whether the plant community exhibited a tolerant or resistant response when elk population growth became irruptive. Plant biomass for the three meadow complexes inhabited by the elk populations was measured using Normalized Difference Vegetation Index (NDVI), which was derived from Landsat 5 Thematic Mapper imagery. Elk populations exhibited different patterns of growth through the time series, whereby one population underwent a complete four-stage irruptive growth pattern while the other two did not. Temporal changes in NDVI for the meadow complex used by the irruptive population suggested a decline in forage biomass during the end of the dry season and a temporal decline in spatial variation of NDVI at the peak of plant biomass in May. Conversely, no such patterns were detected in the meadow complexes inhabited by the nonirruptive populations. Our findings suggest that the meadow complex used by the irruptive elk population may have undergone changes in plant community composition favoring plants that were resistant to elk grazing.

Dynamics of weakly inhomogeneous oscillator populations: perturbation theory on top of Watanabe-Strogatz integrability

NASA Astrophysics Data System (ADS)

Vlasov, Vladimir; Rosenblum, Michael; Pikovsky, Arkady

2016-08-01

As has been shown by Watanabe and Strogatz (WS) (1993 Phys. Rev. Lett. 70 2391), a population of identical phase oscillators, sine-coupled to a common field, is a partially integrable system: for any ensemble size its dynamics reduce to equations for three collective variables. Here we develop a perturbation approach for weakly nonidentical ensembles. We calculate corrections to the WS dynamics for two types of perturbations: those due to a distribution of natural frequencies and of forcing terms, and those due to small white noise. We demonstrate that in both cases, the complex mean field for which the dynamical equations are written is close to the Kuramoto order parameter, up to the leading order in the perturbation. This supports the validity of the dynamical reduction suggested by Ott and Antonsen (2008 Chaos 18 037113) for weakly inhomogeneous populations.

Interacting Effects of Newcastle Disease Transmission and Illegal Trade on a Wild Population of White-Winged Parakeets in Peru: A Modeling Approach

PubMed Central

Daut, Elizabeth F.; Lahodny, Glenn; Peterson, Markus J.; Ivanek, Renata

2016-01-01

Illegal wildlife-pet trade can threaten wildlife populations directly from overharvest, but also indirectly as a pathway for introduction of infectious diseases. This study evaluated consequences of a hypothetical introduction of Newcastle disease (ND) into a wild population of Peru’s most trafficked psittacine, the white-winged parakeet (Brotogeris versicolurus), through release of infected confiscated individuals. We developed two mathematical models that describe ND transmission and the influence of illegal harvest in a homogeneous (model 1) and age-structured population of parakeets (model 2). Infection transmission dynamics and harvest were consistent for all individuals in model 1, which rendered it mathematically more tractable compared to the more complex, age-structured model 2 that separated the host population into juveniles and adults. We evaluated the interaction of ND transmission and harvest through changes in the basic reproduction number (R0) and short-term host population dynamics. Our findings demonstrated that ND introduction would likely provoke considerable disease-related mortality, up to 24% population decline in two years, but high harvest rates would dampen the magnitude of the outbreak. Model 2 produced moderate differences in disease dynamics compared to model 1 (R0 = 3.63 and 2.66, respectively), but highlighted the importance of adult disease dynamics in diminishing the epidemic potential. Therefore, we suggest that future studies should use a more realistic, age-structured model. Finally, for the presumptive risk that illegal trade of white-winged parakeets could introduce ND into wild populations, our results suggest that while high harvest rates may have a protective effect on the population by reducing virus transmission, the combined effects of high harvest and disease-induced mortality may threaten population survival. These results capture the complexity and consequences of the interaction between ND transmission and harvest in a wild parrot population and highlight the importance of preventing illegal trade. PMID:26816214

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

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

Schmieder, R.W.

The author presents a new approach for modeling the dynamics of collections of objects with internal structure. Based on the fact that the behavior of an individual in a population is modified by its knowledge of other individuals, a procedure for accounting for knowledge in a population of interacting objects is presented. It is assumed that each object has partial (or complete) knowledge of some (or all) other objects in the population. The dynamical equations for the objects are then modified to include the effects of this pairwise knowledge. This procedure has the effect of projecting out what the populationmore » will do from the much larger space of what it could do, i.e., filtering or smoothing the dynamics by replacing the complex detailed physical model with an effective model that produces the behavior of interest. The procedure therefore provides a minimalist approach for obtaining emergent collective behavior. The use of knowledge as a dynamical quantity, and its relationship to statistical mechanics, thermodynamics, information theory, and cognition microstructure are discussed.« less

Animal population dynamics: Identification of critical components

USGS Publications Warehouse

Emlen, J.M.; Pikitch, E.K.

1989-01-01

There is a growing interest in the use of population dynamics models in environmental risk assessment and the promulgation of environmental regulatory policies. Unfortunately, because of species and areal differences in the physical and biotic influences on population dynamics, such models must almost inevitably be both complex and species- or site-specific. Given the emormous variety of species and sites of potential concern, this fact presents a problem; it simply is not possible to construct models for all species and circumstances. Therefore, it is useful, before building predictive population models, to discover what input parameters are of critical importance to the desired output. This information should enable the construction of simpler and more generalizable models. As a first step, it is useful to consider population models as composed to two, partly separable classes, one comprising the purely mechanical descriptors of dynamics from given demographic parameter values, and the other describing the modulation of the demographic parameters by environmental factors (changes in physical environment, species interactions, pathogens, xenobiotic chemicals). This division permits sensitivity analyses to be run on the first of these classes, providing guidance for subsequent model simplification. We here apply such a sensitivity analysis to network models of mammalian and avian population dynamics.

Dancing to the rhythms of the Pleistocene? Early Middle Paleolithic population dynamics in NW Iberia (Duero Basin and Cantabrian Region)

NASA Astrophysics Data System (ADS)

Sánchez Yustos, Policarpo; Diez Martín, Fernando

2015-08-01

The Northwest of Iberia has yielded one of the most complete European Middle Paleolithic records. Despite this wealth of information, very little is known about population dynamics during this period. For that reason, the main concern of this paper is to provide socio-environmental models that may help explain Early Middle Paleolithic (EMP) population dynamics in NW Iberia, assessing to what extent they were shaped by climate forces. The archaeological record is analyzed on the basis of the heuristics of ecological models, already employed in the European Pleistocene record but never at a regional scale, in order to detect long-term changes in the composition of EMP populations, and the environmental, biological and sociocultural process influencing those changes. According to the models proposed, we have detected a long-term population dynamic between MIS 11 and MIS 6, characterized by low environmental stress, high biological productivity, interaction among populations and sociocultural complexity. Eventually, this population dynamic was broken due to an extreme climate phase in late MIS 6 that had a profound impact on populations and sociocultural structures. As a result, the Upper Pleistocene population of NW Iberia was concentrated in the Cantabrian region. This area became an isolated Neanderthal glacial refugium that hosted a population with different origins and fragile long-term demographic stability.

High population variability and source-sink dynamics in a solitary bee species.

PubMed

Franzén, Markus; Nilsson, Sven G

2013-06-01

Although solitary bees are considered to play key roles in ecosystem functions, surprisingly few studies have explored their population dynamics. We investigated the population dynamics of a rare, declining, solitary bee (Andrena humilis) in a landscape of 80 km2 in southern Sweden from 2003 to 2011. Only one population was persistent throughout all years studied; most likely this population supplied the surrounding landscape with 11 smaller, temporary local populations. Despite stable pollen availability, the size of the persistent population fluctuated dramatically in a two-year cycle over the nine years, with 490-1230 nests in odd-numbered years and 21-48 nests in even-numbered years. These fluctuations were not significantly related to climatic variables or pollen availability. Nineteen colonization and 14 extinction events were recorded. Occupancy decreased with distance from the persistent population and increased with increasing resource (pollen) availability. There were significant positive correlations between the size of the persistent population and patch occupancy and colonization. Colonizations were generally more common in patches closer to the persistent population, whereas extinctions were independent of distance from the persistent population. Our results highlight the complex population dynamics that exist for this solitary bee species, which could be due to source-sink dynamics, a prolonged diapause, or can represent a bet-hedging strategy to avoid natural enemies and survive in small habitat patches. If large fluctuations in solitary bee populations prove to be widespread, it will have important implications for interpreting ecological relationships, bee conservation, and pollination.

Evolutionary dynamics of cooperation in neutral populations

NASA Astrophysics Data System (ADS)

Szolnoki, Attila; Perc, Matjaž

2018-01-01

Cooperation is a difficult proposition in the face of Darwinian selection. Those that defect have an evolutionary advantage over cooperators who should therefore die out. However, spatial structure enables cooperators to survive through the formation of homogeneous clusters, which is the hallmark of network reciprocity. Here we go beyond this traditional setup and study the spatiotemporal dynamics of cooperation in a population of populations. We use the prisoner's dilemma game as the mathematical model and show that considering several populations simultaneously gives rise to fascinating spatiotemporal dynamics and pattern formation. Even the simplest assumption that strategies between different populations are payoff-neutral with one another results in the spontaneous emergence of cyclic dominance, where defectors of one population become prey of cooperators in the other population, and vice versa. Moreover, if social interactions within different populations are characterized by significantly different temptations to defect, we observe that defectors in the population with the largest temptation counterintuitively vanish the fastest, while cooperators that hang on eventually take over the whole available space. Our results reveal that considering the simultaneous presence of different populations significantly expands the complexity of evolutionary dynamics in structured populations, and it allows us to understand the stability of cooperation under adverse conditions that could never be bridged by network reciprocity alone.

Centennial-scale fluctuations and regional complexity characterize Pacific salmon population dynamics over the past five centuries.

PubMed

Rogers, Lauren A; Schindler, Daniel E; Lisi, Peter J; Holtgrieve, Gordon W; Leavitt, Peter R; Bunting, Lynda; Finney, Bruce P; Selbie, Daniel T; Chen, Guangjie; Gregory-Eaves, Irene; Lisac, Mark J; Walsh, Patrick B

2013-01-29

Observational data from the past century have highlighted the importance of interdecadal modes of variability in fish population dynamics, but how these patterns of variation fit into a broader temporal and spatial context remains largely unknown. We analyzed time series of stable nitrogen isotopes from the sediments of 20 sockeye salmon nursery lakes across western Alaska to characterize temporal and spatial patterns in salmon abundance over the past ∼500 y. Although some stocks varied on interdecadal time scales (30- to 80-y cycles), centennial-scale variation, undetectable in modern-day catch records and survey data, has dominated salmon population dynamics over the past 500 y. Before 1900, variation in abundance was clearly not synchronous among stocks, and the only temporal signal common to lake sediment records from this region was the onset of commercial fishing in the late 1800s. Thus, historical changes in climate did not synchronize stock dynamics over centennial time scales, emphasizing that ecosystem complexity can produce a diversity of ecological responses to regional climate forcing. Our results show that marine fish populations may alternate between naturally driven periods of high and low abundance over time scales of decades to centuries and suggest that management models that assume time-invariant productivity or carrying capacity parameters may be poor representations of the biological reality in these systems.

Centennial-scale fluctuations and regional complexity characterize Pacific salmon population dynamics over the past five centuries

PubMed Central

Rogers, Lauren A.; Schindler, Daniel E.; Lisi, Peter J.; Holtgrieve, Gordon W.; Leavitt, Peter R.; Bunting, Lynda; Finney, Bruce P.; Selbie, Daniel T.; Chen, Guangjie; Gregory-Eaves, Irene; Lisac, Mark J.; Walsh, Patrick B.

2013-01-01

Observational data from the past century have highlighted the importance of interdecadal modes of variability in fish population dynamics, but how these patterns of variation fit into a broader temporal and spatial context remains largely unknown. We analyzed time series of stable nitrogen isotopes from the sediments of 20 sockeye salmon nursery lakes across western Alaska to characterize temporal and spatial patterns in salmon abundance over the past ∼500 y. Although some stocks varied on interdecadal time scales (30- to 80-y cycles), centennial-scale variation, undetectable in modern-day catch records and survey data, has dominated salmon population dynamics over the past 500 y. Before 1900, variation in abundance was clearly not synchronous among stocks, and the only temporal signal common to lake sediment records from this region was the onset of commercial fishing in the late 1800s. Thus, historical changes in climate did not synchronize stock dynamics over centennial time scales, emphasizing that ecosystem complexity can produce a diversity of ecological responses to regional climate forcing. Our results show that marine fish populations may alternate between naturally driven periods of high and low abundance over time scales of decades to centuries and suggest that management models that assume time-invariant productivity or carrying capacity parameters may be poor representations of the biological reality in these systems. PMID:23322737

Games of multicellularity.

PubMed

Kaveh, Kamran; Veller, Carl; Nowak, Martin A

2016-08-21

Evolutionary game dynamics are often studied in the context of different population structures. Here we propose a new population structure that is inspired by simple multicellular life forms. In our model, cells reproduce but can stay together after reproduction. They reach complexes of a certain size, n, before producing single cells again. The cells within a complex derive payoff from an evolutionary game by interacting with each other. The reproductive rate of cells is proportional to their payoff. We consider all two-strategy games. We study deterministic evolutionary dynamics with mutations, and derive exact conditions for selection to favor one strategy over another. Our main result has the same symmetry as the well-known sigma condition, which has been proven for stochastic game dynamics and weak selection. For a maximum complex size of n=2 our result holds for any intensity of selection. For n≥3 it holds for weak selection. As specific examples we study the prisoner's dilemma and hawk-dove games. Our model advances theoretical work on multicellularity by allowing for frequency-dependent interactions within groups. Copyright © 2016 Elsevier Ltd. All rights reserved.

Small-scale fisheries, population dynamics, and resource use in Africa: the case of Moree, Ghana.

PubMed

Marquette, Catherine M; Koranteng, Kwame A; Overå, Ragnhild; Aryeetey, Ellen Bortei-Doku

2002-06-01

We consider population dynamics and sustainable use and development of fishery resources in Moree, a small-scale fishing and coastal community of 20,000 people in the Central Region of Ghana near Cape Coast. Moree suggests that relationships between population dynamics and fishery resources are more complex than the concept of Malthusian overfishing implies. Reasons include changing biophysical characteristics of the upwelling system along the coast of West Africa; qualitative as well as quantitative changes in fishing activity throughout the year; the market nature of fishing activity and nonlocal demands for fish; regular fishery migration; and institutions regulating fishery resource access at home and at migration destinations. Population and resource relationships in Moree may be the effects of fishery resource and economic changes on migration rather than population pressure on fishery resources. Fisheries management policies must take into account processes that lie beyond the influence of local fishermen.

Fine-scale population dynamics in a marine fish species inferred from dynamic state-space models.

PubMed

Rogers, Lauren A; Storvik, Geir O; Knutsen, Halvor; Olsen, Esben M; Stenseth, Nils C

2017-07-01

Identifying the spatial scale of population structuring is critical for the conservation of natural populations and for drawing accurate ecological inferences. However, population studies often use spatially aggregated data to draw inferences about population trends and drivers, potentially masking ecologically relevant population sub-structure and dynamics. The goals of this study were to investigate how population dynamics models with and without spatial structure affect inferences on population trends and the identification of intrinsic drivers of population dynamics (e.g. density dependence). Specifically, we developed dynamic, age-structured, state-space models to test different hypotheses regarding the spatial structure of a population complex of coastal Atlantic cod (Gadus morhua). Data were from a 93-year survey of juvenile (age 0 and 1) cod sampled along >200 km of the Norwegian Skagerrak coast. We compared two models: one which assumes all sampled cod belong to one larger population, and a second which assumes that each fjord contains a unique population with locally determined dynamics. Using the best supported model, we then reconstructed the historical spatial and temporal dynamics of Skagerrak coastal cod. Cross-validation showed that the spatially structured model with local dynamics had better predictive ability. Furthermore, posterior predictive checks showed that a model which assumes one homogeneous population failed to capture the spatial correlation pattern present in the survey data. The spatially structured model indicated that population trends differed markedly among fjords, as did estimates of population parameters including density-dependent survival. Recent biomass was estimated to be at a near-record low all along the coast, but the finer scale model indicated that the decline occurred at different times in different regions. Warm temperatures were associated with poor recruitment, but local changes in habitat and fishing pressure may have played a role in driving local dynamics. More generally, we demonstrated how state-space models can be used to test evidence for population spatial structure based on survey time-series data. Our study shows the importance of considering spatially structured dynamics, as the inferences from such an approach can lead to a different ecological understanding of the drivers of population declines, and fundamentally different management actions to restore populations. © 2017 The Authors. Journal of Animal Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society.

The pre-existing population of 5S rRNA effects p53 stabilization during ribosome biogenesis inhibition.

PubMed

Onofrillo, Carmine; Galbiati, Alice; Montanaro, Lorenzo; Derenzini, Massimo

2017-01-17

Pre-ribosomal complex RPL5/RPL11/5S rRNA (5S RNP) is considered the central MDM2 inhibitory complex that control p53 stabilization during ribosome biogenesis inhibition. Despite its role is well defined, the dynamic of 5S RNP assembly still requires further characterization. In the present work, we report that MDM2 inhibition is dependent by a pre-existing population of 5S rRNA.

Benchmarking novel approaches for modelling species range dynamics

PubMed Central

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

2016-01-01

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

Benchmarking novel approaches for modelling species range dynamics.

PubMed

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

2016-08-01

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

Synchronisation of chaos and its applications

NASA Astrophysics Data System (ADS)

Eroglu, Deniz; Lamb, Jeroen S. W.; Pereira, Tiago

2017-07-01

Dynamical networks are important models for the behaviour of complex systems, modelling physical, biological and societal systems, including the brain, food webs, epidemic disease in populations, power grids and many other. Such dynamical networks can exhibit behaviour in which deterministic chaos, exhibiting unpredictability and disorder, coexists with synchronisation, a classical paradigm of order. We survey the main theory behind complete, generalised and phase synchronisation phenomena in simple as well as complex networks and discuss applications to secure communications, parameter estimation and the anticipation of chaos.

Causes and consequences of complex population dynamics in an annual plant, Cardamine pensylvanica

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

Crone, E.E.

1995-11-08

The relative importance of density-dependent and density-independent factors in determining the population dynamics of plants has been widely debated with little resolution. In this thesis, the author explores the effects of density-dependent population regulation on population dynamics in Cardamine pensylvanica, an annual plant. In the first chapter, she shows that experimental populations of C. pensylvanica cycled from high to low density in controlled constant-environment conditions. These cycles could not be explained by external environmental changes or simple models of direct density dependence (N{sub t+1} = f[N{sub t}]), but they could be explained by delayed density dependence (N{sub t+1} = f[N{submore » t}, N{sub t+1}]). In the second chapter, she shows that the difference in the stability properties of population growth models with and without delayed density dependence is due to the presence of Hopf as well as slip bifurcations from stable to chaotic population dynamics. She also measures delayed density dependence due to effects of parental density on offspring quality in C. pensylvanica and shows that this is large enough to be the cause of the population dynamics observed in C. pensylvanica. In the third chapter, the author extends her analyses of density-dependent population growth models to include interactions between competing species. In the final chapter, she compares the effects of fixed spatial environmental variation and variation in population size on the evolutionary response of C. pensylvanica populations.« less

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.

Spreading dynamics on complex networks: a general stochastic approach.

PubMed

Noël, Pierre-André; Allard, Antoine; Hébert-Dufresne, Laurent; Marceau, Vincent; Dubé, Louis J

2014-12-01

Dynamics on networks is considered from the perspective of Markov stochastic processes. We partially describe the state of the system through network motifs and infer any missing data using the available information. This versatile approach is especially well adapted for modelling spreading processes and/or population dynamics. In particular, the generality of our framework and the fact that its assumptions are explicitly stated suggests that it could be used as a common ground for comparing existing epidemics models too complex for direct comparison, such as agent-based computer simulations. We provide many examples for the special cases of susceptible-infectious-susceptible and susceptible-infectious-removed dynamics (e.g., epidemics propagation) and we observe multiple situations where accurate results may be obtained at low computational cost. Our perspective reveals a subtle balance between the complex requirements of a realistic model and its basic assumptions.

Positive and Negative Feedbacks and Free-Scale Pattern Distribution in Rural-Population Dynamics

PubMed Central

Alados, Concepción L.; Errea, Paz; Gartzia, Maite; Saiz, Hugo; Escós, Juan

2014-01-01

Depopulation of rural areas is a widespread phenomenon that has occurred in most industrialized countries, and has contributed significantly to a reduction in the productivity of agro-ecological resources. In this study, we identified the main trends in the dynamics of rural populations in the Central Pyrenees in the 20th C and early 21st C, and used density independent and density dependent models and identified the main factors that have influenced the dynamics. In addition, we investigated the change in the power law distribution of population size in those periods. Populations exhibited density-dependent positive feedback between 1960 and 2010, and a long-term positive correlation between agricultural activity and population size, which has resulted in a free-scale population distribution that has been disrupted by the collapse of the traditional agricultural society and by emigration to the industrialized cities. We concluded that complex socio-ecological systems that have strong feedback mechanisms can contribute to disruptive population collapses, which can be identified by changes in the pattern of population distribution. PMID:25474704

Lentiviral and targeted cellular barcoding reveals ongoing clonal dynamics of cell lines in vitro and in vivo

PubMed Central

2014-01-01

Background Cell lines are often regarded as clonal, even though this simplifies what is known about mutagenesis, transformation and other processes that destabilize them over time. Monitoring these clonal dynamics is important for multiple areas of biomedical research, including stem cell and cancer biology. Tracking the contributions of individual cells to large populations, however, has been constrained by limitations in sensitivity and complexity. Results We utilize cellular barcoding methods to simultaneously track the clonal contributions of tens of thousands of cells. We demonstrate that even with optimal culturing conditions, common cell lines including HeLa, K562 and HEK-293 T exhibit ongoing clonal dynamics. Starting a population with a single clone diminishes but does not eradicate this phenomenon. Next, we compare lentiviral and zinc-finger nuclease barcode insertion approaches, finding that the zinc-finger nuclease protocol surprisingly results in reduced clonal diversity. We also document the expected reduction in clonal complexity when cells are challenged with genotoxic stress. Finally, we demonstrate that xenografts maintain clonal diversity to a greater extent than in vitro culturing of the human non-small-cell lung cancer cell line HCC827. Conclusions We demonstrate the feasibility of tracking and quantifying the clonal dynamics of entire cell populations within multiple cultured cell lines. Our results suggest that cell heterogeneity should be considered in the design and interpretation of in vitro culture experiments. Aside from clonal cell lines, we propose that cellular barcoding could prove valuable in modeling the clonal behavior of heterogeneous cell populations over time, including tumor populations treated with chemotherapeutic agents. PMID:24886633

Undecidability and Irreducibility Conditions for Open-Ended Evolution and Emergence.

PubMed

Hernández-Orozco, Santiago; Hernández-Quiroz, Francisco; Zenil, Hector

2018-01-01

Is undecidability a requirement for open-ended evolution (OEE)? Using methods derived from algorithmic complexity theory, we propose robust computational definitions of open-ended evolution and the adaptability of computable dynamical systems. Within this framework, we show that decidability imposes absolute limits on the stable growth of complexity in computable dynamical systems. Conversely, systems that exhibit (strong) open-ended evolution must be undecidable, establishing undecidability as a requirement for such systems. Complexity is assessed in terms of three measures: sophistication, coarse sophistication, and busy beaver logical depth. These three complexity measures assign low complexity values to random (incompressible) objects. As time grows, the stated complexity measures allow for the existence of complex states during the evolution of a computable dynamical system. We show, however, that finding these states involves undecidable computations. We conjecture that for similar complexity measures that assign low complexity values, decidability imposes comparable limits on the stable growth of complexity, and that such behavior is necessary for nontrivial evolutionary systems. We show that the undecidability of adapted states imposes novel and unpredictable behavior on the individuals or populations being modeled. Such behavior is irreducible. Finally, we offer an example of a system, first proposed by Chaitin, that exhibits strong OEE.

The pre-existing population of 5S rRNA effects p53 stabilization during ribosome biogenesis inhibition

PubMed Central

Onofrillo, Carmine; Galbiati, Alice; Montanaro, Lorenzo; Derenzini, Massimo

2017-01-01

Pre-ribosomal complex RPL5/RPL11/5S rRNA (5S RNP) is considered the central MDM2 inhibitory complex that control p53 stabilization during ribosome biogenesis inhibition. Despite its role is well defined, the dynamic of 5S RNP assembly still requires further characterization. In the present work, we report that MDM2 inhibition is dependent by a pre-existing population of 5S rRNA. PMID:28032591

Aging, memory, and nonhierarchical energy landscape of spin jam

NASA Astrophysics Data System (ADS)

Samarakoon, Anjana; Sato, Taku J.; Chen, Tianran; Chern, Gai-Wei; Yang, Junjie; Klich, Israel; Sinclair, Ryan; Zhou, Haidong; Lee, Seung-Hun

2016-10-01

The notion of complex energy landscape underpins the intriguing dynamical behaviors in many complex systems ranging from polymers, to brain activity, to social networks and glass transitions. The spin glass state found in dilute magnetic alloys has been an exceptionally convenient laboratory frame for studying complex dynamics resulting from a hierarchical energy landscape with rugged funnels. Here, we show, by a bulk susceptibility and Monte Carlo simulation study, that densely populated frustrated magnets in a spin jam state exhibit much weaker memory effects than spin glasses, and the characteristic properties can be reproduced by a nonhierarchical landscape with a wide and nearly flat but rough bottom. Our results illustrate that the memory effects can be used to probe different slow dynamics of glassy materials, hence opening a window to explore their distinct energy landscapes.

Generalized Master Equation with Non-Markovian Multichromophoric Förster Resonance Energy Transfer for Modular Exciton Densities

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

Jang, Seogjoo; Hoyer, Stephan; Fleming, Graham

2014-10-31

A generalized master equation (GME) governing quantum evolution of modular exciton density (MED) is derived for large scale light harvesting systems composed of weakly interacting modules of multiple chromophores. The GME-MED offers a practical framework to incorporate real time coherent quantum dynamics calculations of small length scales into dynamics over large length scales, and also provides a non-Markovian generalization and rigorous derivation of the Pauli master equation employing multichromophoric Förster resonance energy transfer rates. A test of the GME-MED for four sites of the Fenna-Matthews-Olson complex demonstrates how coherent dynamics of excitonic populations over coupled chromophores can be accurately describedmore » by transitions between subgroups (modules) of delocalized excitons. Application of the GME-MED to the exciton dynamics between a pair of light harvesting complexes in purple bacteria demonstrates its promise as a computationally efficient tool to investigate large scale exciton dynamics in complex environments.« less

Dynamic complexities in a pest control model with birth pulse and harvesting

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

Goel, A., E-mail: goelanju23@gmail.com; Gakkhar, S., E-mail: sungkfma@iitr.ernet.in

In this paper, an impulsive model is discussed for an integrated pest management approach comprising of chemical and mechanical controls. The pesticides and harvesting are used to control the stage-structured pest population. The mature pest give birth to immature pest in pulses at regular intervals. The pest is controlled by spraying chemical pesticides affecting immature as well as mature pest. The harvesting of both immature and mature pest further reduce the pest population. The discrete dynamical system obtained from stroboscopic map is analyzed. The threshold conditions for stability of pest-free state as well as non-trivial period-1 solution is obtained. Themore » effect of pesticide spray timing and harvesting on immature as well as mature pest are shown. Finally, by numerical simulation with MATLAB, the dynamical behaviors of the model is found to be complex. Above the threshold level there is a characteristic sequence of bifurcations leading to chaotic dynamics. Route to chaos is found to be period-doubling. Period halving bifurcations are also observed.« less

How to analytically characterize the epidemic threshold within the coupled disease-behavior systems?. Comment on "Coupled disease-behavior dynamics on complex networks: A review" by Z. Wang et al.

NASA Astrophysics Data System (ADS)

Xia, Cheng-Yi; Ding, Shuai; Sun, Shi-Wen; Wang, Li; Gao, Zhong-Ke; Wang, Juan

2015-12-01

As is well known, outbreak of epidemics may drive the human population to take some necessary measures to protect themselves from not being infected by infective ones, these precautions in turn will also keep from the further spreading of infectious diseases among the population. Thus, to fully comprehend the epidemic spreading behavior within real-world systems, the interplay between disease dynamics and human behavioral and social dynamics needs to be considered simultaneously, such that some effective containment-measures can be successfully developed [1-3].

Multiple scales modelling approaches to social interaction in crowd dynamics and crisis management. Comment on "Human behaviours in evacuation crowd dynamics: From modelling to "big data" toward crisis management" by Nicola Bellomo et al.

NASA Astrophysics Data System (ADS)

Trucu, Dumitru

2016-09-01

In this comprehensive review concerning the modelling of human behaviours in crowd dynamics [3], the authors explore a wide range of mathematical approaches spanning over multiple scales that are suitable to describe emerging crowd behaviours in extreme situations. Focused on deciphering the key aspects leading to emerging crowd patterns evolutions in challenging times such as those requiring an evacuation on a complex venue, the authors address this complex dynamics at both microscale (individual level), mesoscale (probability distributions of interacting individuals), and macroscale (population level), ultimately aiming to gain valuable understanding and knowledge that would inform decision making in managing crisis situations.

Stochastic population dynamics in spatially extended predator-prey systems

NASA Astrophysics Data System (ADS)

Dobramysl, Ulrich; Mobilia, Mauro; Pleimling, Michel; Täuber, Uwe C.

2018-02-01

Spatially extended population dynamics models that incorporate demographic noise serve as case studies for the crucial role of fluctuations and correlations in biological systems. Numerical and analytic tools from non-equilibrium statistical physics capture the stochastic kinetics of these complex interacting many-particle systems beyond rate equation approximations. Including spatial structure and stochastic noise in models for predator-prey competition invalidates the neutral Lotka-Volterra population cycles. Stochastic models yield long-lived erratic oscillations stemming from a resonant amplification mechanism. Spatially extended predator-prey systems display noise-stabilized activity fronts that generate persistent correlations. Fluctuation-induced renormalizations of the oscillation parameters can be analyzed perturbatively via a Doi-Peliti field theory mapping of the master equation; related tools allow detailed characterization of extinction pathways. The critical steady-state and non-equilibrium relaxation dynamics at the predator extinction threshold are governed by the directed percolation universality class. Spatial predation rate variability results in more localized clusters, enhancing both competing species’ population densities. Affixing variable interaction rates to individual particles and allowing for trait inheritance subject to mutations induces fast evolutionary dynamics for the rate distributions. Stochastic spatial variants of three-species competition with ‘rock-paper-scissors’ interactions metaphorically describe cyclic dominance. These models illustrate intimate connections between population dynamics and evolutionary game theory, underscore the role of fluctuations to drive populations toward extinction, and demonstrate how space can support species diversity. Two-dimensional cyclic three-species May-Leonard models are characterized by the emergence of spiraling patterns whose properties are elucidated by a mapping onto a complex Ginzburg-Landau equation. Multiple-species extensions to general ‘food networks’ can be classified on the mean-field level, providing both fundamental understanding of ensuing cooperativity and profound insight into the rich spatio-temporal features and coarsening kinetics in the corresponding spatially extended systems. Novel space-time patterns emerge as a result of the formation of competing alliances; e.g. coarsening domains that each incorporate rock-paper-scissors competition games.

Multi-event capture–recapture modeling of host–pathogen dynamics among European rabbit populations exposed to myxoma and Rabbit Hemorrhagic Disease Viruses: common and heterogeneous patterns

PubMed Central

2014-01-01

Host–pathogen epidemiological processes are often unclear due both to their complexity and over-simplistic approaches used to quantify them. We applied a multi-event capture–recapture procedure on two years of data from three rabbit populations to test hypotheses about the effects on survival of, and the dynamics of host immunity to, both myxoma virus and Rabbit Hemorrhagic Disease Virus (MV and RHDV). Although the populations shared the same climatic and management conditions, MV and RHDV dynamics varied greatly among them; MV and RHDV seroprevalences were positively related to density in one population, but RHDV seroprevalence was negatively related to density in another. In addition, (i) juvenile survival was most often negatively related to seropositivity, (ii) RHDV seropositives never had considerably higher survival, and (iii) seroconversion to seropositivity was more likely than the reverse. We suggest seropositivity affects survival depending on trade-offs among antibody protection, immunosuppression and virus lethality. Negative effects of seropositivity might be greater on juveniles due to their immature immune system. Also, while RHDV directly affects survival through the hemorrhagic syndrome, MV lack of direct lethal effects means that interactions influencing survival are likely to be more complex. Multi-event modeling allowed us to quantify patterns of host–pathogen dynamics otherwise difficult to discern. Such an approach offers a promising tool to shed light on causative mechanisms. PMID:24708296

Conceptualising population health: from mechanistic thinking to complexity science.

PubMed

Jayasinghe, Saroj

2011-01-20

The mechanistic interpretation of reality can be traced to the influential work by René Descartes and Sir Isaac Newton. Their theories were able to accurately predict most physical phenomena relating to motion, optics and gravity. This paradigm had at least three principles and approaches: reductionism, linearity and hierarchy. These ideas appear to have influenced social scientists and the discourse on population health. In contrast, Complexity Science takes a more holistic view of systems. It views natural systems as being 'open', with fuzzy borders, constantly adapting to cope with pressures from the environment. These are called Complex Adaptive Systems (CAS). The sub-systems within it lack stable hierarchies, and the roles of agency keep changing. The interactions with the environment and among sub-systems are non-linear interactions and lead to self-organisation and emergent properties. Theoretical frameworks such as epi+demos+cracy and the ecosocial approach to health have implicitly used some of these concepts of interacting dynamic sub-systems. Using Complexity Science we can view population health outcomes as an emergent property of CAS, which has numerous dynamic non-linear interactions among its interconnected sub-systems or agents. In order to appreciate these sub-systems and determinants, one should acquire a basic knowledge of diverse disciplines and interact with experts from different disciplines. Strategies to improve health should be multi-pronged, and take into account the diversity of actors, determinants and contexts. The dynamic nature of the system requires that the interventions are constantly monitored to provide early feedback to a flexible system that takes quick corrections.

Modeling of Wildlife-Associated Zoonoses: Applications and Caveats

PubMed Central

Lewis, Bryan L.; Marathe, Madhav; Eubank, Stephen; Blackburn, Jason K.

2012-01-01

Abstract Wildlife species are identified as an important source of emerging zoonotic disease. Accordingly, public health programs have attempted to expand in scope to include a greater focus on wildlife and its role in zoonotic disease outbreaks. Zoonotic disease transmission dynamics involving wildlife are complex and nonlinear, presenting a number of challenges. First, empirical characterization of wildlife host species and pathogen systems are often lacking, and insight into one system may have little application to another involving the same host species and pathogen. Pathogen transmission characterization is difficult due to the changing nature of population size and density associated with wildlife hosts. Infectious disease itself may influence wildlife population demographics through compensatory responses that may evolve, such as decreased age to reproduction. Furthermore, wildlife reservoir dynamics can be complex, involving various host species and populations that may vary in their contribution to pathogen transmission and persistence over space and time. Mathematical models can provide an important tool to engage these complex systems, and there is an urgent need for increased computational focus on the coupled dynamics that underlie pathogen spillover at the human–wildlife interface. Often, however, scientists conducting empirical studies on emerging zoonotic disease do not have the necessary skill base to choose, develop, and apply models to evaluate these complex systems. How do modeling frameworks differ and what considerations are important when applying modeling tools to the study of zoonotic disease? Using zoonotic disease examples, we provide an overview of several common approaches and general considerations important in the modeling of wildlife-associated zoonoses. PMID:23199265

A bacterial pioneer produces cellulase complexes that persist through community succession

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

Kolinko, Sebastian; Wu, Yu-Wei; Tachea, Firehiwot

Cultivation of microbial consortia provides low-complexity communities that can serve as tractable models to understand community dynamics. Time-resolved metagenomics demonstrated that an aerobic cellulolytic consortium cultivated from compost exhibited community dynamics consistent with the definition of an endogenous heterotrophic succession. The genome of the proposed pioneer population, 'Candidatus Reconcilibacillus cellulovorans', possessed a gene cluster containing multidomain glycoside hydrolases (GHs). Purification of the soluble cellulase activity from a 300litre cultivation of this consortium revealed that ~70% of the activity arose from the 'Ca. Reconcilibacillus cellulovorans' multidomain GHs assembled into cellulase complexes through glycosylation. These remarkably stable complexes have supramolecular structures formore » enzymatic cellulose hydrolysis that are distinct from cellulosomes. The persistence of these complexes during cultivation indicates that they may be active through multiple cultivations of this consortium and act as public goods that sustain the community. Thus, the provision of extracellular GHs as public goods may influence microbial community dynamics in native biomass-deconstructing communities relevant to agriculture, human health and biotechnology.« less

A bacterial pioneer produces cellulase complexes that persist through community succession

DOE PAGES

Kolinko, Sebastian; Wu, Yu-Wei; Tachea, Firehiwot; ...

2017-11-06

Cultivation of microbial consortia provides low-complexity communities that can serve as tractable models to understand community dynamics. Time-resolved metagenomics demonstrated that an aerobic cellulolytic consortium cultivated from compost exhibited community dynamics consistent with the definition of an endogenous heterotrophic succession. The genome of the proposed pioneer population, 'Candidatus Reconcilibacillus cellulovorans', possessed a gene cluster containing multidomain glycoside hydrolases (GHs). Purification of the soluble cellulase activity from a 300litre cultivation of this consortium revealed that ~70% of the activity arose from the 'Ca. Reconcilibacillus cellulovorans' multidomain GHs assembled into cellulase complexes through glycosylation. These remarkably stable complexes have supramolecular structures formore » enzymatic cellulose hydrolysis that are distinct from cellulosomes. The persistence of these complexes during cultivation indicates that they may be active through multiple cultivations of this consortium and act as public goods that sustain the community. Thus, the provision of extracellular GHs as public goods may influence microbial community dynamics in native biomass-deconstructing communities relevant to agriculture, human health and biotechnology.« less

The RNA polymerase clamp interconverts dynamically among three states and is stabilized in a partly closed state by ppGpp.

PubMed

Duchi, Diego; Mazumder, Abhishek; Malinen, Anssi M; Ebright, Richard H; Kapanidis, Achillefs N

2018-06-06

RNA polymerase (RNAP) contains a mobile structural module, the 'clamp,' that forms one wall of the RNAP active-center cleft and that has been linked to crucial aspects of the transcription cycle, including promoter melting, transcription elongation complex stability, transcription pausing, and transcription termination. Using single-molecule FRET on surface-immobilized RNAP molecules, we show that the clamp in RNAP holoenzyme populates three distinct conformational states and interconvert between these states on the 0.1-1 s time-scale. Similar studies confirm that the RNAP clamp is closed in open complex (RPO) and in initial transcribing complexes (RPITC), including paused initial transcribing complexes, and show that, in these complexes, the clamp does not exhibit dynamic behaviour. We also show that, the stringent-response alarmone ppGpp, which reprograms transcription during amino acid starvation stress, selectively stabilizes the partly-closed-clamp state and prevents clamp opening; these results raise the possibility that ppGpp controls promoter opening by modulating clamp dynamics.

A bacterial pioneer produces cellulase complexes that persist through community succession.

PubMed

Kolinko, Sebastian; Wu, Yu-Wei; Tachea, Firehiwot; Denzel, Evelyn; Hiras, Jennifer; Gabriel, Raphael; Bäcker, Nora; Chan, Leanne Jade G; Eichorst, Stephanie A; Frey, Dario; Chen, Qiushi; Azadi, Parastoo; Adams, Paul D; Pray, Todd R; Tanjore, Deepti; Petzold, Christopher J; Gladden, John M; Simmons, Blake A; Singer, Steven W

2018-01-01

Cultivation of microbial consortia provides low-complexity communities that can serve as tractable models to understand community dynamics. Time-resolved metagenomics demonstrated that an aerobic cellulolytic consortium cultivated from compost exhibited community dynamics consistent with the definition of an endogenous heterotrophic succession. The genome of the proposed pioneer population, 'Candidatus Reconcilibacillus cellulovorans', possessed a gene cluster containing multidomain glycoside hydrolases (GHs). Purification of the soluble cellulase activity from a 300litre cultivation of this consortium revealed that ~70% of the activity arose from the 'Ca. Reconcilibacillus cellulovorans' multidomain GHs assembled into cellulase complexes through glycosylation. These remarkably stable complexes have supramolecular structures for enzymatic cellulose hydrolysis that are distinct from cellulosomes. The persistence of these complexes during cultivation indicates that they may be active through multiple cultivations of this consortium and act as public goods that sustain the community. The provision of extracellular GHs as public goods may influence microbial community dynamics in native biomass-deconstructing communities relevant to agriculture, human health and biotechnology.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

The impact of natural transformation on adaptation in spatially structured bacterial populations.

PubMed

Moradigaravand, Danesh; Engelstädter, Jan

2014-06-20

Recent studies have demonstrated that natural transformation and the formation of highly structured populations in bacteria are interconnected. In spite of growing evidence about this connection, little is known about the dynamics of natural transformation in spatially structured bacterial populations. In this work, we model the interdependency between the dynamics of the bacterial gene pool and those of environmental DNA in space to dissect the effect of transformation on adaptation. Our model reveals that even with only a single locus under consideration, transformation with a free DNA fragment pool results in complex adaptation dynamics that do not emerge in previous models focusing only on the gene shuffling effect of transformation at multiple loci. We demonstrate how spatial restriction on population growth and DNA diffusion in the environment affect the impact of transformation on adaptation. We found that in structured bacterial populations intermediate DNA diffusion rates predominantly cause transformation to impede adaptation by spreading deleterious alleles in the population. Overall, our model highlights distinctive evolutionary consequences of bacterial transformation in spatially restricted compared to planktonic bacterial populations.

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

A high-content image-based method for quantitatively studying context-dependent cell population dynamics

PubMed Central

Garvey, Colleen M.; Spiller, Erin; Lindsay, Danika; Chiang, Chun-Te; Choi, Nathan C.; Agus, David B.; Mallick, Parag; Foo, Jasmine; Mumenthaler, Shannon M.

2016-01-01

Tumor progression results from a complex interplay between cellular heterogeneity, treatment response, microenvironment and heterocellular interactions. Existing approaches to characterize this interplay suffer from an inability to distinguish between multiple cell types, often lack environmental context, and are unable to perform multiplex phenotypic profiling of cell populations. Here we present a high-throughput platform for characterizing, with single-cell resolution, the dynamic phenotypic responses (i.e. morphology changes, proliferation, apoptosis) of heterogeneous cell populations both during standard growth and in response to multiple, co-occurring selective pressures. The speed of this platform enables a thorough investigation of the impacts of diverse selective pressures including genetic alterations, therapeutic interventions, heterocellular components and microenvironmental factors. The platform has been applied to both 2D and 3D culture systems and readily distinguishes between (1) cytotoxic versus cytostatic cellular responses; and (2) changes in morphological features over time and in response to perturbation. These important features can directly influence tumor evolution and clinical outcome. Our image-based approach provides a deeper insight into the cellular dynamics and heterogeneity of tumors (or other complex systems), with reduced reagents and time, offering advantages over traditional biological assays. PMID:27452732

A high-content image-based method for quantitatively studying context-dependent cell population dynamics

NASA Astrophysics Data System (ADS)

Garvey, Colleen M.; Spiller, Erin; Lindsay, Danika; Chiang, Chun-Te; Choi, Nathan C.; Agus, David B.; Mallick, Parag; Foo, Jasmine; Mumenthaler, Shannon M.

2016-07-01

Tumor progression results from a complex interplay between cellular heterogeneity, treatment response, microenvironment and heterocellular interactions. Existing approaches to characterize this interplay suffer from an inability to distinguish between multiple cell types, often lack environmental context, and are unable to perform multiplex phenotypic profiling of cell populations. Here we present a high-throughput platform for characterizing, with single-cell resolution, the dynamic phenotypic responses (i.e. morphology changes, proliferation, apoptosis) of heterogeneous cell populations both during standard growth and in response to multiple, co-occurring selective pressures. The speed of this platform enables a thorough investigation of the impacts of diverse selective pressures including genetic alterations, therapeutic interventions, heterocellular components and microenvironmental factors. The platform has been applied to both 2D and 3D culture systems and readily distinguishes between (1) cytotoxic versus cytostatic cellular responses; and (2) changes in morphological features over time and in response to perturbation. These important features can directly influence tumor evolution and clinical outcome. Our image-based approach provides a deeper insight into the cellular dynamics and heterogeneity of tumors (or other complex systems), with reduced reagents and time, offering advantages over traditional biological assays.

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

PubMed

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

2008-10-23

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

Service Learning for At-Risk Student Populations: The Contextual Dynamism of Implementation

ERIC Educational Resources Information Center

Akin, Jacob T.; Vesely, Randall S.

2016-01-01

The central purpose of this article is to explore research, issues, and perspectives on the implementation of service learning programs to improve student achievement in at-risk student populations. The implementation of service learning programs takes place within multiple contexts and across several terrains. The complexities of implementing…

Recruitment dynamics in complex life cycles. [of organisms living in marine rocky zone

NASA Technical Reports Server (NTRS)

Roughgarden, Jonathan; Possingham, Hugh; Gaines, Steven

1988-01-01

Factors affecting marine population fluctuations are discussed with particular attention given to a common barnacle species of the Pacific coast of North America. It is shown how models combining larval circulation with adult interactions can potentially forecast population fluctuations. These findings demonstrate how processes in different ecological habitats are coupled.

Modelling real disease dynamics with behaviourally adaptive complex networks. Comment on "Coupled disease-behavior dynamics on complex networks: A review" by Z. Wang et al.

NASA Astrophysics Data System (ADS)

Small, Michael

2015-12-01

Mean field compartmental models of disease transmission have been successfully applied to a host of different scenarios, and the Kermack-McKendrick equations are now a staple of mathematical biology text books. In Susceptible-Infected-Removed format these equations provide three coupled first order ordinary differential equations with a very mild nonlinearity and they are very well understood. However, underpinning these equations are two important assumptions: that the population is (a) homogeneous, and (b) well-mixed. These assumptions become closest to being true for diseases infecting a large portion of the population for which inevitable individual effects can be averaged away. Emerging infectious disease (such as, in recent times, SARS, avian influenza, swine flu and ebola) typically does not conform to this scenario. Individual contacts and peculiarities of the transmission network play a vital role in understanding the dynamics of such relatively rare infections - particularly during the early stages of an outbreak.

Simulations for designing and interpreting intervention trials in infectious diseases.

PubMed

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

2017-12-29

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

Coupled disease-behavior dynamics on complex networks: A review

NASA Astrophysics Data System (ADS)

Wang, Zhen; Andrews, Michael A.; Wu, Zhi-Xi; Wang, Lin; Bauch, Chris T.

2015-12-01

It is increasingly recognized that a key component of successful infection control efforts is understanding the complex, two-way interaction between disease dynamics and human behavioral and social dynamics. Human behavior such as contact precautions and social distancing clearly influence disease prevalence, but disease prevalence can in turn alter human behavior, forming a coupled, nonlinear system. Moreover, in many cases, the spatial structure of the population cannot be ignored, such that social and behavioral processes and/or transmission of infection must be represented with complex networks. Research on studying coupled disease-behavior dynamics in complex networks in particular is growing rapidly, and frequently makes use of analysis methods and concepts from statistical physics. Here, we review some of the growing literature in this area. We contrast network-based approaches to homogeneous-mixing approaches, point out how their predictions differ, and describe the rich and often surprising behavior of disease-behavior dynamics on complex networks, and compare them to processes in statistical physics. We discuss how these models can capture the dynamics that characterize many real-world scenarios, thereby suggesting ways that policy makers can better design effective prevention strategies. We also describe the growing sources of digital data that are facilitating research in this area. Finally, we suggest pitfalls which might be faced by researchers in the field, and we suggest several ways in which the field could move forward in the coming years.

Population dynamics of two antilisterial cheese surface consortia revealed by temporal temperature gradient gel electrophoresis

PubMed Central

2010-01-01

Background Surface contamination of smear cheese by Listeria spp. is of major concern for the industry. Complex smear ecosystems have been shown to harbor antilisterial potential but the microorganisms and mechanisms involved in the inhibition mostly remain unclear, and are likely related to complex interactions than to production of single antimicrobial compounds. Bacterial biodiversity and population dynamics of complex smear ecosystems exhibiting antilisterial properties in situ were investigated by Temporal temperature gradient gel electrophoresis (TTGE), a culture independent technique, for two microbial consortia isolated from commercial Raclette type cheeses inoculated with defined commercial ripening cultures (F) or produced with an old-young smearing process (M). Results TTGE revealed nine bacterial species common to both F and M consortia, but consortium F exhibited a higher diversity than consortium M, with thirteen and ten species, respectively. Population dynamics were studied after application of the consortia on fresh-produced Raclette cheeses. TTGE analyses revealed a similar sequential development of the nine species common to both consortia. Beside common cheese surface bacteria (Staphylococcus equorum, Corynebacterium spp., Brevibacterium linens, Microbacterium gubbeenense, Agrococcus casei), the two consortia contained marine lactic acid bacteria (Alkalibacterium kapii, Marinilactibacillus psychrotolerans) that developed early in ripening (day 14 to 20), shortly after the growth of staphylococci (day 7). A decrease of Listeria counts was observed on cheese surface inoculated at day 7 with 0.1-1 × 102 CFU cm-2, when cheeses were smeared with consortium F or M. Listeria counts went below the detection limit of the method between day 14 and 28 and no subsequent regrowth was detected over 60 to 80 ripening days. In contrast, Listeria grew to high counts (105 CFU cm-2) on cheeses smeared with a defined surface culture. Conclusions This work reports the first population dynamics study of complex smear ecosystems exhibiting in situ antilisterial activity. TTGE revealed the presence of marine lactic acid bacteria that are likely related to the strong Listeria inhibition, as their early development in the smear occurred simultaneously with a decrease in Listeria cell count. PMID:20222967

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.

Equation-free modeling unravels the behavior of complex ecological systems

USGS Publications Warehouse

DeAngelis, Donald L.; Yurek, Simeon

2015-01-01

Ye et al. (1) address a critical problem confronting the management of natural ecosystems: How can we make forecasts of possible future changes in populations to help guide management actions? This problem is especially acute for marine and anadromous fisheries, where the large interannual fluctuations of populations, arising from complex nonlinear interactions among species and with varying environmental factors, have defied prediction over even short time scales. The empirical dynamic modeling (EDM) described in Ye et al.’s report, the latest in a series of papers by Sugihara and his colleagues, offers a promising quantitative approach to building models using time series to successfully project dynamics into the future. With the term “equation-free” in the article title, Ye et al. (1) are suggesting broader implications of their approach, considering the centrality of equations in modern science. From the 1700s on, nature has been increasingly described by mathematical equations, with differential or difference equations forming the basic framework for describing dynamics. The use of mathematical equations for ecological systems came much later, pioneered by Lotka and Volterra, who showed that population cycles might be described in terms of simple coupled nonlinear differential equations. It took decades for Lotka–Volterra-type models to become established, but the development of appropriate differential equations is now routine in modeling ecological dynamics. There is no question that the injection of mathematical equations, by forcing “clarity and precision into conjecture” (2), has led to increased understanding of population and community dynamics. As in science in general, in ecology equations are a key method of communication and of framing hypotheses. These equations serve as compact representations of an enormous amount of empirical data and can be analyzed by the powerful methods of mathematics.

Experts' Perspectives Toward a Population Health Approach for Children With Medical Complexity.

PubMed

Barnert, Elizabeth S; Coller, Ryan J; Nelson, Bergen B; Thompson, Lindsey R; Chan, Vincent; Padilla, Cesar; Klitzner, Thomas S; Szilagyi, Moira; Chung, Paul J

2017-08-01

Because children with medical complexity (CMC) display very different health trajectories, needs, and resource utilization than other children, it is unclear how well traditional conceptions of population health apply to CMC. We sought to identify key health outcome domains for CMC as a step toward determining core health metrics for this distinct population of children. We conducted and analyzed interviews with 23 diverse national experts on CMC to better understand population health for CMC. Interviewees included child and family advocates, health and social service providers, and research, health systems, and policy leaders. We performed thematic content analyses to identify emergent themes regarding population health for CMC. Overall, interviewees conveyed that defining and measuring population health for CMC is an achievable, worthwhile goal. Qualitative themes from interviews included: 1) CMC share unifying characteristics that could serve as the basis for population health outcomes; 2) optimal health for CMC is child specific and dynamic; 3) health of CMC is intertwined with health of families; 4) social determinants of health are especially important for CMC; and 5) measuring population health for CMC faces serious conceptual and logistical challenges. Experts have taken initial steps in defining the population health of CMC. Population health for CMC involves a dynamic concept of health that is attuned to individual, health-related goals for each child. We propose a framework that can guide the identification and development of population health metrics for CMC. Copyright © 2017 Academic Pediatric Association. Published by Elsevier Inc. All rights reserved.

Aging, memory, and nonhierarchical energy landscape of spin jam

PubMed Central

Samarakoon, Anjana; Sato, Taku J.; Chen, Tianran; Chern, Gai-Wei; Yang, Junjie; Klich, Israel; Sinclair, Ryan; Zhou, Haidong; Lee, Seung-Hun

2016-01-01

The notion of complex energy landscape underpins the intriguing dynamical behaviors in many complex systems ranging from polymers, to brain activity, to social networks and glass transitions. The spin glass state found in dilute magnetic alloys has been an exceptionally convenient laboratory frame for studying complex dynamics resulting from a hierarchical energy landscape with rugged funnels. Here, we show, by a bulk susceptibility and Monte Carlo simulation study, that densely populated frustrated magnets in a spin jam state exhibit much weaker memory effects than spin glasses, and the characteristic properties can be reproduced by a nonhierarchical landscape with a wide and nearly flat but rough bottom. Our results illustrate that the memory effects can be used to probe different slow dynamics of glassy materials, hence opening a window to explore their distinct energy landscapes. PMID:27698141

Differential Dynamic Engagement within 24 SH3 Domain: Peptide Complexes Revealed by Co-Linear Chemical Shift Perturbation Analysis

PubMed Central

Stollar, Elliott J.; Lin, Hong; Davidson, Alan R.; Forman-Kay, Julie D.

2012-01-01

There is increasing evidence for the functional importance of multiple dynamically populated states within single proteins. However, peptide binding by protein-protein interaction domains, such as the SH3 domain, has generally been considered to involve the full engagement of peptide to the binding surface with minimal dynamics and simple methods to determine dynamics at the binding surface for multiple related complexes have not been described. We have used NMR spectroscopy combined with isothermal titration calorimetry to comprehensively examine the extent of engagement to the yeast Abp1p SH3 domain for 24 different peptides. Over one quarter of the domain residues display co-linear chemical shift perturbation (CCSP) behavior, in which the position of a given chemical shift in a complex is co-linear with the same chemical shift in the other complexes, providing evidence that each complex exists as a unique dynamic rapidly inter-converting ensemble. The extent the specificity determining sub-surface of AbpSH3 is engaged as judged by CCSP analysis correlates with structural and thermodynamic measurements as well as with functional data, revealing the basis for significant structural and functional diversity amongst the related complexes. Thus, CCSP analysis can distinguish peptide complexes that may appear identical in terms of general structure and percent peptide occupancy but have significant local binding differences across the interface, affecting their ability to transmit conformational change across the domain and resulting in functional differences. PMID:23251481

The dynamics of diverse segmental amplifications in populations of Saccharomyces cerevisiae adapting to strong selection.

PubMed

Payen, Celia; Di Rienzi, Sara C; Ong, Giang T; Pogachar, Jamie L; Sanchez, Joseph C; Sunshine, Anna B; Raghuraman, M K; Brewer, Bonita J; Dunham, Maitreya J

2014-03-20

Population adaptation to strong selection can occur through the sequential or parallel accumulation of competing beneficial mutations. The dynamics, diversity, and rate of fixation of beneficial mutations within and between populations are still poorly understood. To study how the mutational landscape varies across populations during adaptation, we performed experimental evolution on seven parallel populations of Saccharomyces cerevisiae continuously cultured in limiting sulfate medium. By combining quantitative polymerase chain reaction, array comparative genomic hybridization, restriction digestion and contour-clamped homogeneous electric field gel electrophoresis, and whole-genome sequencing, we followed the trajectory of evolution to determine the identity and fate of beneficial mutations. During a period of 200 generations, the yeast populations displayed parallel evolutionary dynamics that were driven by the coexistence of independent beneficial mutations. Selective amplifications rapidly evolved under this selection pressure, in particular common inverted amplifications containing the sulfate transporter gene SUL1. Compared with single clones, detailed analysis of the populations uncovers a greater complexity whereby multiple subpopulations arise and compete despite a strong selection. The most common evolutionary adaptation to strong selection in these populations grown in sulfate limitation is determined by clonal interference, with adaptive variants both persisting and replacing one another.

The Dynamics of Diverse Segmental Amplifications in Populations of Saccharomyces cerevisiae Adapting to Strong Selection

PubMed Central

Payen, Celia; Di Rienzi, Sara C.; Ong, Giang T.; Pogachar, Jamie L.; Sanchez, Joseph C.; Sunshine, Anna B.; Raghuraman, M. K.; Brewer, Bonita J.; Dunham, Maitreya J.

2014-01-01

Population adaptation to strong selection can occur through the sequential or parallel accumulation of competing beneficial mutations. The dynamics, diversity, and rate of fixation of beneficial mutations within and between populations are still poorly understood. To study how the mutational landscape varies across populations during adaptation, we performed experimental evolution on seven parallel populations of Saccharomyces cerevisiae continuously cultured in limiting sulfate medium. By combining quantitative polymerase chain reaction, array comparative genomic hybridization, restriction digestion and contour-clamped homogeneous electric field gel electrophoresis, and whole-genome sequencing, we followed the trajectory of evolution to determine the identity and fate of beneficial mutations. During a period of 200 generations, the yeast populations displayed parallel evolutionary dynamics that were driven by the coexistence of independent beneficial mutations. Selective amplifications rapidly evolved under this selection pressure, in particular common inverted amplifications containing the sulfate transporter gene SUL1. Compared with single clones, detailed analysis of the populations uncovers a greater complexity whereby multiple subpopulations arise and compete despite a strong selection. The most common evolutionary adaptation to strong selection in these populations grown in sulfate limitation is determined by clonal interference, with adaptive variants both persisting and replacing one another. PMID:24368781

The problem of ecological scaling in spatially complex, nonequilibrium ecological systems [chapter 3

Treesearch

Samuel A. Cushman; Jeremy Littell; Kevin McGarigal

2010-01-01

In the previous chapter we reviewed the challenges posed by spatial complexity and temporal disequilibrium to efforts to understand and predict the structure and dynamics of ecological systems. The central theme was that spatial variability in the environment and population processes fundamentally alters the interactions between species and their environments, largely...

Emergent patterns in interacting neuronal sub-populations

NASA Astrophysics Data System (ADS)

Kamal, Neeraj Kumar; Sinha, Sudeshna

2015-05-01

We investigate an ensemble of coupled model neurons, consisting of groups of varying sizes and intrinsic dynamics, ranging from periodic to chaotic, where the inter-group coupling interaction is effectively like a dynamic signal from a different sub-population. We observe that the minority group can significantly influence the majority group. For instance, when a small chaotic group is coupled to a large periodic group, the chaotic group de-synchronizes. However, counter-intuitively, when a small periodic group couples strongly to a large chaotic group, it leads to complete synchronization in the majority chaotic population, which also spikes at the frequency of the small periodic group. It then appears that the small group of periodic neurons can act like a pacemaker for the whole network. Further, we report the existence of varied clustering patterns, ranging from sets of synchronized clusters to anti-phase clusters, governed by the interplay of the relative sizes and dynamics of the sub-populations. So these results have relevance in understanding how a group can influence the synchrony of another group of dynamically different elements, reminiscent of event-related synchronization/de-synchronization in complex networks.

A phase transition induces chaos in a predator-prey ecosystem with a dynamic fitness landscape.

PubMed

Gilpin, William; Feldman, Marcus W

2017-07-01

In many ecosystems, natural selection can occur quickly enough to influence the population dynamics and thus future selection. This suggests the importance of extending classical population dynamics models to include such eco-evolutionary processes. Here, we describe a predator-prey model in which the prey population growth depends on a prey density-dependent fitness landscape. We show that this two-species ecosystem is capable of exhibiting chaos even in the absence of external environmental variation or noise, and that the onset of chaotic dynamics is the result of the fitness landscape reversibly alternating between epochs of stabilizing and disruptive selection. We draw an analogy between the fitness function and the free energy in statistical mechanics, allowing us to use the physical theory of first-order phase transitions to understand the onset of rapid cycling in the chaotic predator-prey dynamics. We use quantitative techniques to study the relevance of our model to observational studies of complex ecosystems, finding that the evolution-driven chaotic dynamics confer community stability at the "edge of chaos" while creating a wide distribution of opportunities for speciation during epochs of disruptive selection-a potential observable signature of chaotic eco-evolutionary dynamics in experimental studies.

Rethinking the logistic approach for population dynamics of mutualistic interactions.

PubMed

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

2014-12-21

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

Social determinants of health inequalities: towards a theoretical perspective using systems science.

PubMed

Jayasinghe, Saroj

2015-08-25

A systems approach offers a novel conceptualization to natural and social systems. In recent years, this has led to perceiving population health outcomes as an emergent property of a dynamic and open, complex adaptive system. The current paper explores these themes further and applies the principles of systems approach and complexity science (i.e. systems science) to conceptualize social determinants of health inequalities. The conceptualization can be done in two steps: viewing health inequalities from a systems approach and extending it to include complexity science. Systems approach views health inequalities as patterns within the larger rubric of other facets of the human condition, such as educational outcomes and economic development. This anlysis requires more sophisticated models such as systems dynamic models. An extension of the approach is to view systems as complex adaptive systems, i.e. systems that are 'open' and adapt to the environment. They consist of dynamic adapting subsystems that exhibit non-linear interactions, while being 'open' to a similarly dynamic environment of interconnected systems. They exhibit emergent properties that cannot be estimated with precision by using the known interactions among its components (such as economic development, political freedom, health system, culture etc.). Different combinations of the same bundle of factors or determinants give rise to similar patterns or outcomes (i.e. property of convergence), and minor variations in the initial condition could give rise to widely divergent outcomes. Novel approaches using computer simulation models (e.g. agent-based models) would shed light on possible mechanisms as to how factors or determinants interact and lead to emergent patterns of health inequalities of populations.

Spatial and temporal synchrony in reptile population dynamics in variable environments.

PubMed

Greenville, Aaron C; Wardle, Glenda M; Nguyen, Vuong; Dickman, Chris R

2016-10-01

Resources are seldom distributed equally across space, but many species exhibit spatially synchronous population dynamics. Such synchrony suggests the operation of large-scale external drivers, such as rainfall or wildfire, or the influence of oasis sites that provide water, shelter, or other resources. However, testing the generality of these factors is not easy, especially in variable environments. Using a long-term dataset (13-22 years) from a large (8000 km(2)) study region in arid Central Australia, we tested firstly for regional synchrony in annual rainfall and the dynamics of six reptile species across nine widely separated sites. For species that showed synchronous spatial dynamics, we then used multivariate follow a multivariate auto-regressive state-space (MARSS) models to predict that regional rainfall would be positively associated with their populations. For asynchronous species, we used MARSS models to explore four other possible population structures: (1) populations were asynchronous, (2) differed between oasis and non-oasis sites, (3) differed between burnt and unburnt sites, or (4) differed between three sub-regions with different rainfall gradients. Only one species showed evidence of spatial population synchrony and our results provide little evidence that rainfall synchronizes reptile populations. The oasis or the wildfire hypotheses were the best-fitting models for the other five species. Thus, our six study species appear generally to be structured in space into one or two populations across the study region. Our findings suggest that for arid-dwelling reptile populations, spatial and temporal dynamics are structured by abiotic events, but individual responses to covariates at smaller spatial scales are complex and poorly understood.

Hydration dynamics promote bacterial coexistence on rough surfaces

PubMed Central

Wang, Gang; Or, Dani

2013-01-01

Identification of mechanisms that promote and maintain the immense microbial diversity found in soil is a central challenge for contemporary microbial ecology. Quantitative tools for systematic integration of complex biophysical and trophic processes at spatial scales, relevant for individual cell interactions, are essential for making progress. We report a modeling study of competing bacterial populations cohabiting soil surfaces subjected to highly dynamic hydration conditions. The model explicitly tracks growth, motion and life histories of individual bacterial cells on surfaces spanning dynamic aqueous networks that shape heterogeneous nutrient fields. The range of hydration conditions that confer physical advantages for rapidly growing species and support competitive exclusion is surprisingly narrow. The rapid fragmentation of soil aqueous phase under most natural conditions suppresses bacterial growth and cell dispersion, thereby balancing conditions experienced by competing populations with diverse physiological traits. In addition, hydration fluctuations intensify localized interactions that promote coexistence through disproportional effects within densely populated regions during dry periods. Consequently, bacterial population dynamics is affected well beyond responses predicted from equivalent and uniform hydration conditions. New insights on hydration dynamics could be considered in future designs of soil bioremediation activities, affect longevity of dry food products, and advance basic understanding of bacterial diversity dynamics and its role in global biogeochemical cycles. PMID:23051694

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

PubMed

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

2005-10-07

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

Evolutionary dynamics on any population structure

NASA Astrophysics Data System (ADS)

Allen, Benjamin; Lippner, Gabor; Chen, Yu-Ting; Fotouhi, Babak; Momeni, Naghmeh; Yau, Shing-Tung; Nowak, Martin A.

2017-03-01

Evolution occurs in populations of reproducing individuals. The structure of a population can affect which traits evolve. Understanding evolutionary game dynamics in structured populations remains difficult. Mathematical results are known for special structures in which all individuals have the same number of neighbours. The general case, in which the number of neighbours can vary, has remained open. For arbitrary selection intensity, the problem is in a computational complexity class that suggests there is no efficient algorithm. Whether a simple solution for weak selection exists has remained unanswered. Here we provide a solution for weak selection that applies to any graph or network. Our method relies on calculating the coalescence times of random walks. We evaluate large numbers of diverse population structures for their propensity to favour cooperation. We study how small changes in population structure—graph surgery—affect evolutionary outcomes. We find that cooperation flourishes most in societies that are based on strong pairwise ties.

Energetic and flexibility properties captured by long molecular dynamics simulations of a membrane-embedded pMHCII-TCR complex.

PubMed

Bello, Martiniano; Correa-Basurto, José

2016-04-01

Although crystallographic data have provided important molecular insight into the interactions in the pMHC-TCR complex, the inherent features of this structural approach cause it to only provide a static picture of the interactions. While unbiased molecular dynamics simulations (UMDSs) have provided important information about the dynamic structural behavior of the pMHC-TCR complex, most of them have modeled the pMHC-TCR complex as soluble, when in physiological conditions, this complex is membrane bound; therefore, following this latter UMDS protocol might hamper important dynamic results. In this contribution, we performed three independent 300 ns-long UMDSs of the pMHCII-TCR complex anchored in two opposing membranes to explore the structural and energetic properties of the recognition of pMHCII by the TCR. The conformational ensemble generated through UMDSs was subjected to clustering and Cartesian principal component analyses (cPCA) to explore the dynamical behavior of the pMHCII-TCR association. Furthermore, based on the conformational population sampled through UMDSs, the effective binding free energy, per-residue free energy decomposition, and alanine scanning mutations were explored for the native pMHCII-TCR complex, as well as for 12 mutations (p1-p12MHCII-TCR) introduced in the native peptide. Clustering analyses and cPCA provide insight into the rocking motion of the TCR onto pMHCII, together with the presence of new electrostatic interactions not observed through crystallographic methods. Energetic results provide evidence of the main contributors to the pMHC-TCR complex formation as well as the key residues involved in this molecular recognition process.

New science from the phase space of old stellar systems

NASA Astrophysics Data System (ADS)

Varri, Anna Lisa; Breen, Philip G.; Heggie, Douglas C.; Tiongco, Maria; Vesperini, Enrico

2017-06-01

Our traditional interpretative picture of the internal dynamics of globular clusters has been recently revolutionized by a series of discoveries about their chemical, structural, and kinematic properties. The empirical evidence that their velocity space is much more complex than usually expected encourages us to use them as refreshingly novel phase space laboratories for some long-forgotten aspects of collisional gravitational dynamics. Such a realization, coupled with the discovery that the stars in clusters were not all born at once in a single population, makes them new, challenging chemodynamical puzzles.Thanks to the proper motions of thousands of stars that will be available from the Gaia mission, we are about to enter a new ''golden age'' for the study of the dynamics of this class of stellar systems, as the full phase space of several Galactic globular clusters will be soon unlocked for the first time. In this context, I will present the highlights of a more realistic dynamical paradigm for these intriguing stellar systems, with emphasis on the role of angular momentum, velocity anisotropy and external tidal field. Such a fundamental understanding of the emerging phase space complexity of globulars will allow us to address many open questions about their rich dynamical evolution, their elusive stellar populations and putative black holes, and their role within the history of our Galaxy.

Small Modifications to Network Topology Can Induce Stochastic Bistable Spiking Dynamics in a Balanced Cortical Model

PubMed Central

McDonnell, Mark D.; Ward, Lawrence M.

2014-01-01

Abstract Directed random graph models frequently are used successfully in modeling the population dynamics of networks of cortical neurons connected by chemical synapses. Experimental results consistently reveal that neuronal network topology is complex, however, in the sense that it differs statistically from a random network, and differs for classes of neurons that are physiologically different. This suggests that complex network models whose subnetworks have distinct topological structure may be a useful, and more biologically realistic, alternative to random networks. Here we demonstrate that the balanced excitation and inhibition frequently observed in small cortical regions can transiently disappear in otherwise standard neuronal-scale models of fluctuation-driven dynamics, solely because the random network topology was replaced by a complex clustered one, whilst not changing the in-degree of any neurons. In this network, a small subset of cells whose inhibition comes only from outside their local cluster are the cause of bistable population dynamics, where different clusters of these cells irregularly switch back and forth from a sparsely firing state to a highly active state. Transitions to the highly active state occur when a cluster of these cells spikes sufficiently often to cause strong unbalanced positive feedback to each other. Transitions back to the sparsely firing state rely on occasional large fluctuations in the amount of non-local inhibition received. Neurons in the model are homogeneous in their intrinsic dynamics and in-degrees, but differ in the abundance of various directed feedback motifs in which they participate. Our findings suggest that (i) models and simulations should take into account complex structure that varies for neuron and synapse classes; (ii) differences in the dynamics of neurons with similar intrinsic properties may be caused by their membership in distinctive local networks; (iii) it is important to identify neurons that share physiological properties and location, but differ in their connectivity. PMID:24743633

Characterizing complex networks through statistics of Möbius transformations

NASA Astrophysics Data System (ADS)

Jaćimović, Vladimir; Crnkić, Aladin

2017-04-01

It is well-known now that dynamics of large populations of globally (all-to-all) coupled oscillators can be reduced to low-dimensional submanifolds (WS transformation and OA ansatz). Marvel et al. (2009) described an intriguing algebraic structure standing behind this reduction: oscillators evolve by the action of the group of Möbius transformations. Of course, dynamics in complex networks of coupled oscillators is highly complex and not reducible. Still, closer look unveils that even in complex networks some (possibly overlapping) groups of oscillators evolve by Möbius transformations. In this paper, we study properties of the network by identifying Möbius transformations in the dynamics of oscillators. This enables us to introduce some new (statistical) concepts that characterize the network. In particular, the notion of coherence of the network (or subnetwork) is proposed. This conceptual approach is meaningful for the broad class of networks, including those with time-delayed, noisy or mixed interactions. In this paper, several simple (random) graphs are studied illustrating the meaning of the concepts introduced in the paper.

How does selfing affect the dynamics of selfish transposable elements?

PubMed

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

2012-03-07

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

Complete Firing-Rate Response of Neurons with Complex Intrinsic Dynamics

PubMed Central

Puelma Touzel, Maximilian; Wolf, Fred

2015-01-01

The response of a neuronal population over a space of inputs depends on the intrinsic properties of its constituent neurons. Two main modes of single neuron dynamics–integration and resonance–have been distinguished. While resonator cell types exist in a variety of brain areas, few models incorporate this feature and fewer have investigated its effects. To understand better how a resonator’s frequency preference emerges from its intrinsic dynamics and contributes to its local area’s population firing rate dynamics, we analyze the dynamic gain of an analytically solvable two-degree of freedom neuron model. In the Fokker-Planck approach, the dynamic gain is intractable. The alternative Gauss-Rice approach lifts the resetting of the voltage after a spike. This allows us to derive a complete expression for the dynamic gain of a resonator neuron model in terms of a cascade of filters on the input. We find six distinct response types and use them to fully characterize the routes to resonance across all values of the relevant timescales. We find that resonance arises primarily due to slow adaptation with an intrinsic frequency acting to sharpen and adjust the location of the resonant peak. We determine the parameter regions for the existence of an intrinsic frequency and for subthreshold and spiking resonance, finding all possible intersections of the three. The expressions and analysis presented here provide an account of how intrinsic neuron dynamics shape dynamic population response properties and can facilitate the construction of an exact theory of correlations and stability of population activity in networks containing populations of resonator neurons. PMID:26720924

Complex dynamics in the Leslie-Gower type of the food chain system with multiple delays

NASA Astrophysics Data System (ADS)

Guo, Lei; Song, Zi-Gen; Xu, Jian

2014-08-01

In this paper, we present a Leslie-Gower type of food chain system composed of three species, which are resource, consumer, and predator, respectively. The digestion time delays corresponding to consumer-eat-resource and predator-eat-consumer are introduced for more realistic consideration. It is called the resource digestion delay (RDD) and consumer digestion delay (CDD) for simplicity. Analyzing the corresponding characteristic equation, the stabilities of the boundary and interior equilibrium points are studied. The food chain system exhibits the species coexistence for the small values of digestion delays. Large RDD/CDD may destabilize the species coexistence and induce the system dynamic into recurrent bloom or system collapse. Further, the present of multiple delays can control species population into the stable coexistence. To investigate the effect of time delays on the recurrent bloom of species population, the Hopf bifurcation and periodic solution are investigated in detail in terms of the central manifold reduction and normal form method. Finally, numerical simulations are performed to display some complex dynamics, which include multiple periodic solution and chaos motion for the different values of system parameters. The system dynamic behavior evolves into the chaos motion by employing the period-doubling bifurcation.

Rapid processing of chemosensor transients in a neuromorphic implementation of the insect macroglomerular complex

PubMed Central

Pearce, Timothy C.; Karout, Salah; Rácz, Zoltán; Capurro, Alberto; Gardner, Julian W.; Cole, Marina

2012-01-01

We present a biologically-constrained neuromorphic spiking model of the insect antennal lobe macroglomerular complex that encodes concentration ratios of chemical components existing within a blend, implemented using a set of programmable logic neuronal modeling cores. Depending upon the level of inhibition and symmetry in its inhibitory connections, the model exhibits two dynamical regimes: fixed point attractor (winner-takes-all type), and limit cycle attractor (winnerless competition type) dynamics. We show that, when driven by chemosensor input in real-time, the dynamical trajectories of the model's projection neuron population activity accurately encode the concentration ratios of binary odor mixtures in both dynamical regimes. By deploying spike timing-dependent plasticity in a subset of the synapses in the model, we demonstrate that a Hebbian-like associative learning rule is able to organize weights into a stable configuration after exposure to a randomized training set comprising a variety of input ratios. Examining the resulting local interneuron weights in the model shows that each inhibitory neuron competes to represent possible ratios across the population, forming a ratiometric representation via mutual inhibition. After training the resulting dynamical trajectories of the projection neuron population activity show amplification and better separation in their response to inputs of different ratios. Finally, we demonstrate that by using limit cycle attractor dynamics, it is possible to recover and classify blend ratio information from the early transient phases of chemosensor responses in real-time more rapidly and accurately compared to a nearest-neighbor classifier applied to the normalized chemosensor data. Our results demonstrate the potential of biologically-constrained neuromorphic spiking models in achieving rapid and efficient classification of early phase chemosensor array transients with execution times well beyond biological timescales. PMID:23874265

Coupled disease-behavior dynamics on complex networks: A review.

PubMed

Wang, Zhen; Andrews, Michael A; Wu, Zhi-Xi; Wang, Lin; Bauch, Chris T

2015-12-01

It is increasingly recognized that a key component of successful infection control efforts is understanding the complex, two-way interaction between disease dynamics and human behavioral and social dynamics. Human behavior such as contact precautions and social distancing clearly influence disease prevalence, but disease prevalence can in turn alter human behavior, forming a coupled, nonlinear system. Moreover, in many cases, the spatial structure of the population cannot be ignored, such that social and behavioral processes and/or transmission of infection must be represented with complex networks. Research on studying coupled disease-behavior dynamics in complex networks in particular is growing rapidly, and frequently makes use of analysis methods and concepts from statistical physics. Here, we review some of the growing literature in this area. We contrast network-based approaches to homogeneous-mixing approaches, point out how their predictions differ, and describe the rich and often surprising behavior of disease-behavior dynamics on complex networks, and compare them to processes in statistical physics. We discuss how these models can capture the dynamics that characterize many real-world scenarios, thereby suggesting ways that policy makers can better design effective prevention strategies. We also describe the growing sources of digital data that are facilitating research in this area. Finally, we suggest pitfalls which might be faced by researchers in the field, and we suggest several ways in which the field could move forward in the coming years. Copyright © 2015 Elsevier B.V. All rights reserved.

Stable and Dynamic Coding for Working Memory in Primate Prefrontal Cortex

PubMed Central

Watanabe, Kei; Funahashi, Shintaro; Stokes, Mark G.

2017-01-01

Working memory (WM) provides the stability necessary for high-level cognition. Influential theories typically assume that WM depends on the persistence of stable neural representations, yet increasing evidence suggests that neural states are highly dynamic. Here we apply multivariate pattern analysis to explore the population dynamics in primate lateral prefrontal cortex (PFC) during three variants of the classic memory-guided saccade task (recorded in four animals). We observed the hallmark of dynamic population coding across key phases of a working memory task: sensory processing, memory encoding, and response execution. Throughout both these dynamic epochs and the memory delay period, however, the neural representational geometry remained stable. We identified two characteristics that jointly explain these dynamics: (1) time-varying changes in the subpopulation of neurons coding for task variables (i.e., dynamic subpopulations); and (2) time-varying selectivity within neurons (i.e., dynamic selectivity). These results indicate that even in a very simple memory-guided saccade task, PFC neurons display complex dynamics to support stable representations for WM. SIGNIFICANCE STATEMENT Flexible, intelligent behavior requires the maintenance and manipulation of incoming information over various time spans. For short time spans, this faculty is labeled “working memory” (WM). Dominant models propose that WM is maintained by stable, persistent patterns of neural activity in prefrontal cortex (PFC). However, recent evidence suggests that neural activity in PFC is dynamic, even while the contents of WM remain stably represented. Here, we explored the neural dynamics in PFC during a memory-guided saccade task. We found evidence for dynamic population coding in various task epochs, despite striking stability in the neural representational geometry of WM. Furthermore, we identified two distinct cellular mechanisms that contribute to dynamic population coding. PMID:28559375

Scale-invariance underlying the logistic equation and its social applications

NASA Astrophysics Data System (ADS)

Hernando, A.; Plastino, A.

2013-01-01

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

Emulating a System Dynamics Model with Agent-Based Models: A Methodological Case Study in Simulation of Diabetes Progression

DOE PAGES

Schryver, Jack; Nutaro, James; Shankar, Mallikarjun

2015-10-30

An agent-based simulation model hierarchy emulating disease states and behaviors critical to progression of diabetes type 2 was designed and implemented in the DEVS framework. The models are translations of basic elements of an established system dynamics model of diabetes. In this model hierarchy, which mimics diabetes progression over an aggregated U.S. population, was dis-aggregated and reconstructed bottom-up at the individual (agent) level. Four levels of model complexity were defined in order to systematically evaluate which parameters are needed to mimic outputs of the system dynamics model. Moreover, the four estimated models attempted to replicate stock counts representing disease statesmore » in the system dynamics model, while estimating impacts of an elderliness factor, obesity factor and health-related behavioral parameters. Health-related behavior was modeled as a simple realization of the Theory of Planned Behavior, a joint function of individual attitude and diffusion of social norms that spread over each agent s social network. Although the most complex agent-based simulation model contained 31 adjustable parameters, all models were considerably less complex than the system dynamics model which required numerous time series inputs to make its predictions. In all three elaborations of the baseline model provided significantly improved fits to the output of the system dynamics model. The performances of the baseline agent-based model and its extensions illustrate a promising approach to translate complex system dynamics models into agent-based model alternatives that are both conceptually simpler and capable of capturing main effects of complex local agent-agent interactions.« less

Emulating a System Dynamics Model with Agent-Based Models: A Methodological Case Study in Simulation of Diabetes Progression

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

Schryver, Jack; Nutaro, James; Shankar, Mallikarjun

An agent-based simulation model hierarchy emulating disease states and behaviors critical to progression of diabetes type 2 was designed and implemented in the DEVS framework. The models are translations of basic elements of an established system dynamics model of diabetes. In this model hierarchy, which mimics diabetes progression over an aggregated U.S. population, was dis-aggregated and reconstructed bottom-up at the individual (agent) level. Four levels of model complexity were defined in order to systematically evaluate which parameters are needed to mimic outputs of the system dynamics model. Moreover, the four estimated models attempted to replicate stock counts representing disease statesmore » in the system dynamics model, while estimating impacts of an elderliness factor, obesity factor and health-related behavioral parameters. Health-related behavior was modeled as a simple realization of the Theory of Planned Behavior, a joint function of individual attitude and diffusion of social norms that spread over each agent s social network. Although the most complex agent-based simulation model contained 31 adjustable parameters, all models were considerably less complex than the system dynamics model which required numerous time series inputs to make its predictions. In all three elaborations of the baseline model provided significantly improved fits to the output of the system dynamics model. The performances of the baseline agent-based model and its extensions illustrate a promising approach to translate complex system dynamics models into agent-based model alternatives that are both conceptually simpler and capable of capturing main effects of complex local agent-agent interactions.« less

Mapping the ecological networks of microbial communities.

PubMed

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

2017-12-11

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

Determination of the formation of dark state via depleted spontaneous emission in a complex solvated molecule.

PubMed

Guo, Xunmin; Wang, Sufan; Xia, Andong; Su, Hongmei

2007-07-05

We present a general two-color two-pulse femtosecond pump-dump approach to study the specific population transfer along the reaction coordinate through the higher vibrational energy levels of excited states of a complex solvated molecule via the depleted spontaneous emission. The time-dependent fluorescence depletion provides the correlated dynamical information between the monitored fluorescence state and the SEP "dumped" dark states, and therefore allow us to obtain the dynamics of the formation of the dark states corresponding to the ultrafast photoisomerization processes. The excited-state dynamics of LDS 751 have been investigated as a function of solvent viscosity and solvent polarity, where a cooperative two-step isomerization process is clearly identified within LDS 751 upon excitation.

Deciphering the Interdependence between Ecological and Evolutionary Networks.

PubMed

Melián, Carlos J; Matthews, Blake; de Andreazzi, Cecilia S; Rodríguez, Jorge P; Harmon, Luke J; Fortuna, Miguel A

2018-05-24

Biological systems consist of elements that interact within and across hierarchical levels. For example, interactions among genes determine traits of individuals, competitive and cooperative interactions among individuals influence population dynamics, and interactions among species affect the dynamics of communities and ecosystem processes. Such systems can be represented as hierarchical networks, but can have complex dynamics when interdependencies among levels of the hierarchy occur. We propose integrating ecological and evolutionary processes in hierarchical networks to explore interdependencies in biological systems. We connect gene networks underlying predator-prey trait distributions to food webs. Our approach addresses longstanding questions about how complex traits and intraspecific trait variation affect the interdependencies among biological levels and the stability of meta-ecosystems. Copyright © 2018 Elsevier Ltd. All rights reserved.

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

PubMed

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

2013-05-10

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

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.

Comparative trends in log populations in northern Arizona mixed-conifer and ponderosa pine forests following severe drought

Treesearch

Joseph L. Ganey; Scott C. Vojta

2017-01-01

Logs provide an important form of coarse woody debris in forest systems, contributing to numerous ecological processes and affecting wildlife habitat and fuel complexes. Despite this, little information is available on the dynamics of log populations in southwestern ponderosa pine (Pinus ponderosa) and especially mixed-conifer forests. A recent episode of elevated tree...

Conformational Sub-states and Populations in Enzyme Catalysis

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

Agarwal, Pratul K; Doucet, Nicholas; Chennubholta, C

reactants in the active site, chemical turnover, and release of products. In addition to formation of crucial structural interactions between enzyme and substrate(s), coordinated motions within the enzyme substrate complex allow reaction to proceed at a much faster rate, compared to the reaction in solution and in the absence of enzyme. An increasing number of enzyme systems show the presence of conserved protein motions that are important for function. A wide variety of motions are naturally sampled (over femtosecond to millisecond time-scales) as the enzyme complex moves along the energetic landscape, driven by temperature and dynamical events from the surroundingmore » environment. Areas of low energy along the landscape form conformational sub-states, which show higher conformational populations than surrounding areas. A small number of these protein conformational sub-states contain functionally important structural and dynamical features, which assist the enzyme mechanism along the catalytic cycle. Identification and characterization of these higher-energy (also called excited) sub-states and the associated populations are challenging, as these sub-states are very short-lived and therefore rarely populated. Specialized techniques based on computer simulations, theoretical modeling, and nuclear magnetic resonance have been developed for quantitative characterization of these sub-states and populations. This chapter discusses these techniques and provides examples of their applications to enzyme systems.« less

Multiscale structure in eco-evolutionary dynamics

NASA Astrophysics Data System (ADS)

Stacey, Blake C.

In a complex system, the individual components are neither so tightly coupled or correlated that they can all be treated as a single unit, nor so uncorrelated that they can be approximated as independent entities. Instead, patterns of interdependency lead to structure at multiple scales of organization. Evolution excels at producing such complex structures. In turn, the existence of these complex interrelationships within a biological system affects the evolutionary dynamics of that system. I present a mathematical formalism for multiscale structure, grounded in information theory, which makes these intuitions quantitative, and I show how dynamics defined in terms of population genetics or evolutionary game theory can lead to multiscale organization. For complex systems, "more is different," and I address this from several perspectives. Spatial host--consumer models demonstrate the importance of the structures which can arise due to dynamical pattern formation. Evolutionary game theory reveals the novel effects which can result from multiplayer games, nonlinear payoffs and ecological stochasticity. Replicator dynamics in an environment with mesoscale structure relates to generalized conditionalization rules in probability theory. The idea of natural selection "acting at multiple levels" has been mathematized in a variety of ways, not all of which are equivalent. We will face down the confusion, using the experience developed over the course of this thesis to clarify the situation.

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

NASA Astrophysics Data System (ADS)

Teh, Hung-Hsuan; Cheng, Yuan-Chung

2017-04-01

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

Modeling Population and Ecosystem Response to Sublethal Toxicant Exposure

DTIC Science & Technology

2001-09-30

mutualism utilized modified Lotka - Volterra (L-V) competition equations in which the sign of the interspecific interaction term was changed from...within complex communities and ecosystems. Prior to the current award, the PIs formulated and tested general dynamic energy budget models...Nisbet, 1998; chapter 7) make a convincing case that ecosystems do truly have dynamics that can be described by relatively simple, general , models

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

PubMed Central

Dann, Benjamin

2016-01-01

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

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

PubMed

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

2016-11-01

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

Concepts and tools for predictive modeling of microbial dynamics.

PubMed

Bernaerts, Kristel; Dens, Els; Vereecken, Karen; Geeraerd, Annemie H; Standaert, Arnout R; Devlieghere, Frank; Debevere, Johan; Van Impe, Jan F

2004-09-01

Description of microbial cell (population) behavior as influenced by dynamically changing environmental conditions intrinsically needs dynamic mathematical models. In the past, major effort has been put into the modeling of microbial growth and inactivation within a constant environment (static models). In the early 1990s, differential equation models (dynamic models) were introduced in the field of predictive microbiology. Here, we present a general dynamic model-building concept describing microbial evolution under dynamic conditions. Starting from an elementary model building block, the model structure can be gradually complexified to incorporate increasing numbers of influencing factors. Based on two case studies, the fundamentals of both macroscopic (population) and microscopic (individual) modeling approaches are revisited. These illustrations deal with the modeling of (i) microbial lag under variable temperature conditions and (ii) interspecies microbial interactions mediated by lactic acid production (product inhibition). Current and future research trends should address the need for (i) more specific measurements at the cell and/or population level, (ii) measurements under dynamic conditions, and (iii) more comprehensive (mechanistically inspired) model structures. In the context of quantitative microbial risk assessment, complexity of the mathematical model must be kept under control. An important challenge for the future is determination of a satisfactory trade-off between predictive power and manageability of predictive microbiology models.

A phase transition induces chaos in a predator-prey ecosystem with a dynamic fitness landscape

PubMed Central

2017-01-01

In many ecosystems, natural selection can occur quickly enough to influence the population dynamics and thus future selection. This suggests the importance of extending classical population dynamics models to include such eco-evolutionary processes. Here, we describe a predator-prey model in which the prey population growth depends on a prey density-dependent fitness landscape. We show that this two-species ecosystem is capable of exhibiting chaos even in the absence of external environmental variation or noise, and that the onset of chaotic dynamics is the result of the fitness landscape reversibly alternating between epochs of stabilizing and disruptive selection. We draw an analogy between the fitness function and the free energy in statistical mechanics, allowing us to use the physical theory of first-order phase transitions to understand the onset of rapid cycling in the chaotic predator-prey dynamics. We use quantitative techniques to study the relevance of our model to observational studies of complex ecosystems, finding that the evolution-driven chaotic dynamics confer community stability at the “edge of chaos” while creating a wide distribution of opportunities for speciation during epochs of disruptive selection—a potential observable signature of chaotic eco-evolutionary dynamics in experimental studies. PMID:28678792

Application of Sequence-Dependent Electrophoresis Fingerprinting in Exploring Biodiversity and Population Dynamics of Human Intestinal Microbiota: What Can Be Revealed?

PubMed Central

Huys, Geert; Vanhoutte, Tom; Vandamme, Peter

2008-01-01

Sequence-dependent electrophoresis (SDE) fingerprinting techniques such as denaturing gradient gel electrophoresis (DGGE) have become commonplace in the field of molecular microbial ecology. The success of the SDE technology lays in the fact that it allows visualization of the predominant members of complex microbial ecosystems independent of their culturability and without prior knowledge on the complexity and diversity of the ecosystem. Mainly using the prokaryotic 16S rRNA gene as PCR amplification target, SDE-based community fingerprinting turned into one of the leading molecular tools to unravel the diversity and population dynamics of human intestinal microbiota. The first part of this review covers the methodological concept of SDE fingerprinting and the technical hurdles for analyzing intestinal samples. Subsequently, the current state-of-the-art of DGGE and related techniques to analyze human intestinal microbiota from healthy individuals and from patients with intestinal disorders is surveyed. In addition, the applicability of SDE analysis to monitor intestinal population changes upon nutritional or therapeutic interventions is critically evaluated. PMID:19277102

Genetic diversity affects the strength of population regulation in a marine fish.

PubMed

Johnson, D W; Freiwald, J; Bernardi, G

2016-03-01

Variation is an essential feature of biological populations, yet much of ecological theory treats individuals as though they are identical. This simplifying assumption is often justified by the perception that variation among individuals does not have significant effects on the dynamics of whole populations. However, this perception may be skewed by a historic focus on studying single populations. A true evaluation of the extent to which among-individual variation affects the dynamics of populations requires the study of multiple populations. In this study, we examined variation in the dynamics of populations of a live-bearing, marine fish (black surfperch; Embiotoca jacksoni). In collaboration with an organization of citizen scientists (Reef Check California), we were able to examine the dynamics of eight populations that were distributed throughout approximately 700 km of coastline, a distance that encompasses much of this species' range. We hypothesized that genetic variation within a local population would be related to the intensity of competition and to the strength of population regulation. To test this hypothesis, we examined whether genetic diversity (measured by the diversity of mitochondrial DNA haplotypes) was related to the strength of population regulation. Low-diversity populations experienced strong density dependence in population growth rates and population sizes were regulated much more tightly than they were in high-diversity populations. Mechanisms that contributed to this pattern include links between genetic diversity, habitat use, and spatial crowding. On average, low-diversity populations used less of the available habitat and exhibited greater spatial clustering (and more intense competition) for a given level of density (measured at the scale of the reef). Although the populations we studied also varied with respect to exogenous characteristics (habitat complexity, densities of predators, and interspecific competitors), none of these characteristics was significantly related to the strength of population regulation. In contrast, an endogenous characteristic of the population (genetic diversity) explained 77% of the variation in the strength of population regulation (95% CI: 27-94%). Our results suggest that the genetic and phenotypic composition of populations can play a major role in their dynamics.

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

USGS Publications Warehouse

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

2005-01-01

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

STRUCTURAL DYNAMICS OF METAL PARTITIONING TO MINERAL SURFACES

EPA Science Inventory

The conceptual understanding of surface complexation reactions that control trace element partitioning to mineral surfaces is limited by the assumption that the solid reactant possesses a finite, time-invariant population of surface functional groups. This assumption has limited...

Population size does not explain past changes in cultural complexity.

PubMed

Vaesen, Krist; Collard, Mark; Cosgrove, Richard; Roebroeks, Wil

2016-04-19

Demography is increasingly being invoked to account for features of the archaeological record, such as the technological conservatism of the Lower and Middle Pleistocene, the Middle to Upper Paleolithic transition, and cultural loss in Holocene Tasmania. Such explanations are commonly justified in relation to population dynamic models developed by Henrich [Henrich J (2004)Am Antiq69:197-214] and Powell et al. [Powell A, et al. (2009)Science324(5932):1298-1301], which appear to demonstrate that population size is the crucial determinant of cultural complexity. Here, we show that these models fail in two important respects. First, they only support a relationship between demography and culture in implausible conditions. Second, their predictions conflict with the available archaeological and ethnographic evidence. We conclude that new theoretical and empirical research is required to identify the factors that drove the changes in cultural complexity that are documented by the archaeological record.

Population size does not explain past changes in cultural complexity

PubMed Central

Vaesen, Krist; Collard, Mark; Cosgrove, Richard; Roebroeks, Wil

2016-01-01

Demography is increasingly being invoked to account for features of the archaeological record, such as the technological conservatism of the Lower and Middle Pleistocene, the Middle to Upper Paleolithic transition, and cultural loss in Holocene Tasmania. Such explanations are commonly justified in relation to population dynamic models developed by Henrich [Henrich J (2004) Am Antiq 69:197–214] and Powell et al. [Powell A, et al. (2009) Science 324(5932):1298–1301], which appear to demonstrate that population size is the crucial determinant of cultural complexity. Here, we show that these models fail in two important respects. First, they only support a relationship between demography and culture in implausible conditions. Second, their predictions conflict with the available archaeological and ethnographic evidence. We conclude that new theoretical and empirical research is required to identify the factors that drove the changes in cultural complexity that are documented by the archaeological record. PMID:27044082

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.

Computational analysis of complex systems: Applications to population dynamics and networks

NASA Astrophysics Data System (ADS)

Molnar, Ferenc

In most complex evolving systems, we can often find a critical subset of the constituents that can initiate a global change in the entire system. For example, in complex networks, a critical subset of nodes can efficiently spread information, influence, or control dynamical processes over the entire network. Similarly, in nonlinear dynamics, we can locate key variables, or find the necessary parameters, to reach the attraction basin of a desired global state. In both cases, a fundamental goal is finding the ability to efficiently control these systems. We study two distinct complex systems in this dissertation, exploring these topics. First, we analyze a population dynamics model describing interactions of sex-structured population groups. Specifically, we analyze how a sex-linked genetic trait's ecological consequence (population survival or extinction) can be influenced by the presence of sex-specific cultural mortality traits, motivated by the desire to expand the theoretical understanding of the role of biased sex ratios in organisms. We analyze dynamics within a single population group, as well as between competing groups. We find that there is a finite range of sex ratio bias that can be maintained in stable equilibrium by sex-specific mortalities. We also find that the outcome of an invasion and the ensuing between-group competition depends not on larger equilibrium group densities, but on the higher allocation of sex-ratio genes. When we extend the model with diffusive dispersal, we find that a critical patch size for achieving positive growth only exists if the population expands into an empty environment. If a resident population is already present that can be exploited by the invading group, then any small seed of invader can advance from rarity, in the mean-field approximation, as long as the local competition dynamics favors the invader's survival. Most spatial models assume initial populations with a uniform distribution inside a finite patch; a simple, but not a cost-efficient approach. We show, using a novel application of simulated annealing, that a specific, non-trivial shape of spatial distribution can minimize the total cost of successful invasion, i.e., the cost of ecological restoration. Further, our approach can be generalized to essentially any reaction-diffusion model with diffusive spreading. In the second part of the dissertation we conduct an extensive study of minimum dominating sets (MDS) in complex networks; particularly, in scale-free networks. MDS is the smallest subset of nodes in a network that can reach every other node as nearest neighbors, thus it provides a key subset of nodes that play critical role in controllability and observability of social, biological, and technological networks. Continued interest in network control, monitoring and influencing of complex networks motivates our research of understanding the properties and practical application-related issues of the MDS. Our study of the scaling behavior reveals that the size of MDS always scales linearly with network size, as long as the power-law degree exponent gamma of the degree distribution is larger than 2. However, when gamma<2, a domination transition occurs, allowing the MDS size to become O(1), leading to easily dominated networks, under certain structural conditions. Motivated by practical applicability in large networks, we develop a new dominating set selection method, derived from probabilistic node selection techniques, which can select small dominating sets without complete network topology information. We also show that the effectiveness of our method, as well as the effectiveness of other heuristics of dominating set selection, strongly depends on the assortativity of networks. Finally, we conduct a numerical study to analyze the fraction of nodes that remain dominated, after the network is damaged, and some nodes are removed. We find that dominating sets optimized for small size are particularly vulnerable to damage; a significant amount of "domination coverage" may be lost if key dominator nodes are deleted. However, we also find that increasing the redundancy of dominating sets by adding a few well-picked nodes can successfully increase the post-damage dominated fraction of the network. Based on this idea, we develop two algorithms to build dominating sets with flexible balance between size and damage resilience.

A Complex-Valued Firing-Rate Model That Approximates the Dynamics of Spiking Networks

PubMed Central

Schaffer, Evan S.; Ostojic, Srdjan; Abbott, L. F.

2013-01-01

Firing-rate models provide an attractive approach for studying large neural networks because they can be simulated rapidly and are amenable to mathematical analysis. Traditional firing-rate models assume a simple form in which the dynamics are governed by a single time constant. These models fail to replicate certain dynamic features of populations of spiking neurons, especially those involving synchronization. We present a complex-valued firing-rate model derived from an eigenfunction expansion of the Fokker-Planck equation and apply it to the linear, quadratic and exponential integrate-and-fire models. Despite being almost as simple as a traditional firing-rate description, this model can reproduce firing-rate dynamics due to partial synchronization of the action potentials in a spiking model, and it successfully predicts the transition to spike synchronization in networks of coupled excitatory and inhibitory neurons. PMID:24204236

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

NASA Astrophysics Data System (ADS)

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

2015-06-01

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

Stochastic Dynamics through Hierarchically Embedded Markov Chains

NASA Astrophysics Data System (ADS)

Vasconcelos, Vítor V.; Santos, Fernando P.; Santos, Francisco C.; Pacheco, Jorge M.

2017-02-01

Studying dynamical phenomena in finite populations often involves Markov processes of significant mathematical and/or computational complexity, which rapidly becomes prohibitive with increasing population size or an increasing number of individual configuration states. Here, we develop a framework that allows us to define a hierarchy of approximations to the stationary distribution of general systems that can be described as discrete Markov processes with time invariant transition probabilities and (possibly) a large number of states. This results in an efficient method for studying social and biological communities in the presence of stochastic effects—such as mutations in evolutionary dynamics and a random exploration of choices in social systems—including situations where the dynamics encompasses the existence of stable polymorphic configurations, thus overcoming the limitations of existing methods. The present formalism is shown to be general in scope, widely applicable, and of relevance to a variety of interdisciplinary problems.

Stochastic Dynamics through Hierarchically Embedded Markov Chains.

PubMed

Vasconcelos, Vítor V; Santos, Fernando P; Santos, Francisco C; Pacheco, Jorge M

2017-02-03

Studying dynamical phenomena in finite populations often involves Markov processes of significant mathematical and/or computational complexity, which rapidly becomes prohibitive with increasing population size or an increasing number of individual configuration states. Here, we develop a framework that allows us to define a hierarchy of approximations to the stationary distribution of general systems that can be described as discrete Markov processes with time invariant transition probabilities and (possibly) a large number of states. This results in an efficient method for studying social and biological communities in the presence of stochastic effects-such as mutations in evolutionary dynamics and a random exploration of choices in social systems-including situations where the dynamics encompasses the existence of stable polymorphic configurations, thus overcoming the limitations of existing methods. The present formalism is shown to be general in scope, widely applicable, and of relevance to a variety of interdisciplinary problems.

Range expansion through fragmented landscapes under a variable climate

PubMed Central

Bennie, Jonathan; Hodgson, Jenny A; Lawson, Callum R; Holloway, Crispin TR; Roy, David B; Brereton, Tom; Thomas, Chris D; Wilson, Robert J

2013-01-01

Ecological responses to climate change may depend on complex patterns of variability in weather and local microclimate that overlay global increases in mean temperature. Here, we show that high-resolution temporal and spatial variability in temperature drives the dynamics of range expansion for an exemplar species, the butterfly Hesperia comma. Using fine-resolution (5 m) models of vegetation surface microclimate, we estimate the thermal suitability of 906 habitat patches at the species' range margin for 27 years. Population and metapopulation models that incorporate this dynamic microclimate surface improve predictions of observed annual changes to population density and patch occupancy dynamics during the species' range expansion from 1982 to 2009. Our findings reveal how fine-scale, short-term environmental variability drives rates and patterns of range expansion through spatially localised, intermittent episodes of expansion and contraction. Incorporating dynamic microclimates can thus improve models of species range shifts at spatial and temporal scales relevant to conservation interventions. PMID:23701124

Spatio-temporal dynamics of a fish predator: Density-dependent and hydrographic effects on Baltic Sea cod population

PubMed Central

Bartolino, Valerio; Tian, Huidong; Bergström, Ulf; Jounela, Pekka; Aro, Eero; Dieterich, Christian; Meier, H. E. Markus; Cardinale, Massimiliano; Bland, Barbara

2017-01-01

Understanding the mechanisms of spatial population dynamics is crucial for the successful management of exploited species and ecosystems. However, the underlying mechanisms of spatial distribution are generally complex due to the concurrent forcing of both density-dependent species interactions and density-independent environmental factors. Despite the high economic value and central ecological importance of cod in the Baltic Sea, the drivers of its spatio-temporal population dynamics have not been analytically investigated so far. In this paper, we used an extensive trawl survey dataset in combination with environmental data to investigate the spatial dynamics of the distribution of the Eastern Baltic cod during the past three decades using Generalized Additive Models. The results showed that adult cod distribution was mainly affected by cod population size, and to a minor degree by small-scale hydrological factors and the extent of suitable reproductive areas. As population size decreases, the cod population concentrates to the southern part of the Baltic Sea, where the preferred more marine environment conditions are encountered. Using the fitted models, we predicted the Baltic cod distribution back to the 1970s and a temporal index of cod spatial occupation was developed. Our study will contribute to the management and conservation of this important resource and of the ecosystem where it occurs, by showing the forces shaping its spatial distribution and therefore the potential response of the population to future exploitation and environmental changes. PMID:28207804

Extending and expanding the Darwinian synthesis: the role of complex systems dynamics.

PubMed

Weber, Bruce H

2011-03-01

Darwinism is defined here as an evolving research tradition based upon the concepts of natural selection acting upon heritable variation articulated via background assumptions about systems dynamics. Darwin's theory of evolution was developed within a context of the background assumptions of Newtonian systems dynamics. The Modern Evolutionary Synthesis, or neo-Darwinism, successfully joined Darwinian selection and Mendelian genetics by developing population genetics informed by background assumptions of Boltzmannian systems dynamics. Currently the Darwinian Research Tradition is changing as it incorporates new information and ideas from molecular biology, paleontology, developmental biology, and systems ecology. This putative expanded and extended synthesis is most perspicuously deployed using background assumptions from complex systems dynamics. Such attempts seek to not only broaden the range of phenomena encompassed by the Darwinian Research Tradition, such as neutral molecular evolution, punctuated equilibrium, as well as developmental biology, and systems ecology more generally, but to also address issues of the emergence of evolutionary novelties as well as of life itself. Copyright © 2010 Elsevier Ltd. All rights reserved.

Fixation, transient landscape, and diffusion dilemma in stochastic evolutionary game dynamics

NASA Astrophysics Data System (ADS)

Zhou, Da; Qian, Hong

2011-09-01

Agent-based stochastic models for finite populations have recently received much attention in the game theory of evolutionary dynamics. Both the ultimate fixation and the pre-fixation transient behavior are important to a full understanding of the dynamics. In this paper, we study the transient dynamics of the well-mixed Moran process through constructing a landscape function. It is shown that the landscape playing a central theoretical “device” that integrates several lines of inquiries: the stable behavior of the replicator dynamics, the long-time fixation, and continuous diffusion approximation associated with asymptotically large population. Several issues relating to the transient dynamics are discussed: (i) multiple time scales phenomenon associated with intra- and inter-attractoral dynamics; (ii) discontinuous transition in stochastically stationary process akin to Maxwell construction in equilibrium statistical physics; and (iii) the dilemma diffusion approximation facing as a continuous approximation of the discrete evolutionary dynamics. It is found that rare events with exponentially small probabilities, corresponding to the uphill movements and barrier crossing in the landscape with multiple wells that are made possible by strong nonlinear dynamics, plays an important role in understanding the origin of the complexity in evolutionary, nonlinear biological systems.

Exploiting Fast-Variables to Understand Population Dynamics and Evolution

NASA Astrophysics Data System (ADS)

Constable, George W. A.; McKane, Alan J.

2018-07-01

We describe a continuous-time modelling framework for biological population dynamics that accounts for demographic noise. In the spirit of the methodology used by statistical physicists, transitions between the states of the system are caused by individual events while the dynamics are described in terms of the time-evolution of a probability density function. In general, the application of the diffusion approximation still leaves a description that is quite complex. However, in many biological applications one or more of the processes happen slowly relative to the system's other processes, and the dynamics can be approximated as occurring within a slow low-dimensional subspace. We review these time-scale separation arguments and analyse the more simple stochastic dynamics that result in a number of cases. We stress that it is important to retain the demographic noise derived in this way, and emphasise this point by showing that it can alter the direction of selection compared to the prediction made from an analysis of the corresponding deterministic model.

Exploiting Fast-Variables to Understand Population Dynamics and Evolution

NASA Astrophysics Data System (ADS)

Constable, George W. A.; McKane, Alan J.

2017-11-01

We describe a continuous-time modelling framework for biological population dynamics that accounts for demographic noise. In the spirit of the methodology used by statistical physicists, transitions between the states of the system are caused by individual events while the dynamics are described in terms of the time-evolution of a probability density function. In general, the application of the diffusion approximation still leaves a description that is quite complex. However, in many biological applications one or more of the processes happen slowly relative to the system's other processes, and the dynamics can be approximated as occurring within a slow low-dimensional subspace. We review these time-scale separation arguments and analyse the more simple stochastic dynamics that result in a number of cases. We stress that it is important to retain the demographic noise derived in this way, and emphasise this point by showing that it can alter the direction of selection compared to the prediction made from an analysis of the corresponding deterministic model.

The transmission dynamics of groups A and B human respiratory syncytial virus (hRSV) in England & Wales and Finland: seasonality and cross-protection.

PubMed

White, L J; Waris, M; Cane, P A; Nokes, D J; Medley, G F

2005-04-01

Human respiratory syncytial virus (hRSV) transmission dynamics are inherently cyclical, and the observed genetic diversity (between groups A and B) also appears to have a repeating pattern. A key unknown is the extent to which genetic variants interact immunologically, and thus impact on epidemiology. We developed a novel mathematical model for hRSV transmission including seasonal forcing of incidence and temporary intra- and inter-group partial immunity. Simultaneous model fits to data from two locations (England & Wales, UK, and Turku, Finland) successfully reproduced the contrasting infection dynamics and group A/B dominance patterns. Parameter estimates are consistent with direct estimates. Differences in the magnitude and seasonal variation in contact rate between the two populations alone could account for the variation in dynamics between these populations. The A/B group dominance patterns are explained by reductions in susceptibility to and infectiousness of secondary homologous and heterologous infections. The consequences of the observed dynamic complexity are discussed.

Living in the branches: population dynamics and ecological processes in dendritic networks

USGS Publications Warehouse

Grant, E.H.C.; Lowe, W.H.; Fagan, W.F.

2007-01-01

Spatial structure regulates and modifies processes at several levels of ecological organization (e.g. individual/genetic, population and community) and is thus a key component of complex systems, where knowledge at a small scale can be insufficient for understanding system behaviour at a larger scale. Recent syntheses outline potential applications of network theory to ecological systems, but do not address the implications of physical structure for network dynamics. There is a specific need to examine how dendritic habitat structure, such as that found in stream, hedgerow and cave networks, influences ecological processes. Although dendritic networks are one type of ecological network, they are distinguished by two fundamental characteristics: (1) both the branches and the nodes serve as habitat, and (2) the specific spatial arrangement and hierarchical organization of these elements interacts with a species' movement behaviour to alter patterns of population distribution and abundance, and community interactions. Here, we summarize existing theory relating to ecological dynamics in dendritic networks, review empirical studies examining the population- and community-level consequences of these networks, and suggest future research integrating spatial pattern and processes in dendritic systems.

Resource-driven changes to host population stability alter the evolution of virulence and transmission.

PubMed

Hite, Jessica L; Cressler, Clayton E

2018-05-05

What drives the evolution of parasite life-history traits? Recent studies suggest that linking within- and between-host processes can provide key insight into both disease dynamics and parasite evolution. Still, it remains difficult to understand how to pinpoint the critical factors connecting these cross-scale feedbacks, particularly under non-equilibrium conditions; many natural host populations inherently fluctuate and parasites themselves can strongly alter the stability of host populations. Here, we develop a general model framework that mechanistically links resources to parasite evolution across a gradient of stable and unstable conditions. First, we dynamically link resources and between-host processes (host density, stability, transmission) to virulence evolution, using a 'non-nested' model. Then, we consider a 'nested' model where population-level processes (transmission and virulence) depend on resource-driven changes to individual-level (within-host) processes (energetics, immune function, parasite production). Contrary to 'non-nested' model predictions, the 'nested' model reveals complex effects of host population dynamics on parasite evolution, including regions of evolutionary bistability; evolution can push parasites towards strongly or weakly stabilizing strategies. This bistability results from dynamic feedbacks between resource-driven changes to host density, host immune function and parasite production. Together, these results highlight how cross-scale feedbacks can provide key insights into the structuring role of parasites and parasite evolution.This article is part of the theme issue 'Anthropogenic resource subsidies and host-parasite dynamics in wildlife'. © 2018 The Author(s).

Exploring reservoir dynamics: a case study of rabies in the Serengeti ecosystem

PubMed Central

Lembo, Tiziana; Hampson, Katie; Haydon, Daniel T.; Craft, Meggan; Dobson, Andy; Dushoff, Jonathan; Ernest, Eblate; Hoare, Richard; Kaare, Magai; Mlengeya, Titus; Mentzel, Christine; Cleaveland, Sarah

2012-01-01

Summary Knowledge of infection reservoir dynamics is critical for effective disease control, but identifying reservoirs of multi-host pathogens is challenging. Here, we synthesize several lines of evidence to investigate rabies reservoirs in complex carnivore communities of the Serengeti ecological region in northwest Tanzania, where the disease has been confirmed in 12 carnivore species.Long-term monitoring data suggest that rabies persists in high-density domestic dog Canis familiaris populations (> 11 dogs km−2) and occurs less frequently in lower-density (< 5 dogs km−2) populations and only sporadically in wild carnivores.Genetic data show that a single rabies virus variant belonging to the group of southern Africa canid-associated viruses (Africa 1b) circulates among a range of species, with no evidence of species-specific virus–host associations.Within-species transmission was more frequently inferred from high-resolution epidemiological data than between-species transmission. Incidence patterns indicate that spill-over of rabies from domestic dog populations sometimes initiates short-lived chains of transmission in other carnivores.Synthesis and applications. The balance of evidence suggests that the reservoir of rabies in the Serengeti ecosystem is a complex multi-host community where domestic dogs are the only population essential for persistence, although other carnivores contribute to the reservoir as non-maintenance populations. Control programmes that target domestic dog populations should therefore have the greatest impact on reducing the risk of infection in all other species including humans, livestock and endangered wildlife populations, but transmission in other species may increase the level of vaccination coverage in domestic dog populations necessary to eliminate rabies. PMID:22427710

Dynamically rich, yet parameter-sparse models for spatial epidemiology. Comment on "Coupled disease-behavior dynamics on complex networks: A review" by Z. Wang et al.

NASA Astrophysics Data System (ADS)

Jusup, Marko; Iwami, Shingo; Podobnik, Boris; Stanley, H. Eugene

2015-12-01

Since the very inception of mathematical modeling in epidemiology, scientists exploited the simplicity ingrained in the assumption of a well-mixed population. For example, perhaps the earliest susceptible-infectious-recovered (SIR) model developed by L. Reed and W.H. Frost in the 1920s [1], included the well-mixed assumption such that any two individuals in the population could meet each other. The problem was that, unlike many other simplifying assumptions used in epidemiological modeling whose validity holds in one situation or the other, well-mixed populations are almost non-existent in reality because the nature of human socio-economic interactions is, for the most part, highly heterogeneous (e.g. [2-6]).

Computational Study of the Genomic and Epigenomic Phenomena

NASA Astrophysics Data System (ADS)

Yang, Wenjing

Biological systems are perhaps the ultimate complex systems, uniquely capable of processing and communicating information, reproducing in their lifetimes, and adapting in evolutionary time scales. My dissertation research focuses on using computational approaches to understand the biocomplexity manifested in the multitude of length scales and time scales. At the molecular and cellular level, central to the complex behavior of a biological system is the regulatory network. My research study focused on epigenetics, which is essential for multicellular organisms to establish cellular identity during development or in response to intracellular and environmental stimuli. My computational study of epigenomics is greatly facilitated by recent advances in high-throughput sequencing technology, which enables high-resolution snapshots of epigenomes and transcriptomes. Using human CD4+ T cell as a model system, the dynamical changes in epigenome and transcriptome pertinent to T cell activation were investigated at the genome scale. Going beyond traditional focus on transcriptional regulation, I provided evidences that post-transcriptional regulation may serve as a major component of the regulatory network. In addition, I explored alternative polyadenylation, another novel aspect of gene regulation, and how it cross-talks with the local chromatin structure. As the renowned theoretical biologist Theodosius Dobzhansky said eloquently, "Nothing in biology makes sense except in the light of evolution''. To better understand this ubiquitous driving force in the biological world, I went beyond molecular events in a single organism, and investigated the dynamical changes of population structure along the evolutionary time scale. To this end, we used HIV virus population dynamics in the host immune system as a model system. The evolution of HIV viral population plays a key role in AIDS immunopathogenesis with its exceptionally high mutation rate. However, the theoretical studies of the effect of recombination have been rather limited. Given the phylogenetic and experimental evidences for the high recombination rate and its important role in HIV evolution and epidemics, I established a mathematical model to study the effect of recombination, and explored the complex behavior of this dynamics system.

Molecular population dynamics of DNA structures in a bcl-2 promoter sequence is regulated by small molecules and the transcription factor hnRNP LL

PubMed Central

Cui, Yunxi; Koirala, Deepak; Kang, HyunJin; Dhakal, Soma; Yangyuoru, Philip; Hurley, Laurence H.; Mao, Hanbin

2014-01-01

Minute difference in free energy change of unfolding among structures in an oligonucleotide sequence can lead to a complex population equilibrium, which is rather challenging for ensemble techniques to decipher. Herein, we introduce a new method, molecular population dynamics (MPD), to describe the intricate equilibrium among non-B deoxyribonucleic acid (DNA) structures. Using mechanical unfolding in laser tweezers, we identified six DNA species in a cytosine (C)-rich bcl-2 promoter sequence. Population patterns of these species with and without a small molecule (IMC-76 or IMC-48) or the transcription factor hnRNP LL are compared to reveal the MPD of different species. With a pattern recognition algorithm, we found that IMC-48 and hnRNP LL share 80% similarity in stabilizing i-motifs with 60 s incubation. In contrast, IMC-76 demonstrates an opposite behavior, preferring flexible DNA hairpins. With 120–180 s incubation, IMC-48 and hnRNP LL destabilize i-motifs, which has been previously proposed to activate bcl-2 transcriptions. These results provide strong support, from the population equilibrium perspective, that small molecules and hnRNP LL can modulate bcl-2 transcription through interaction with i-motifs. The excellent agreement with biochemical results firmly validates the MPD analyses, which, we expect, can be widely applicable to investigate complex equilibrium of biomacromolecules. PMID:24609386

Multiphase Modelling of Bacteria Removal in a CSO Stream

EPA Science Inventory

Indicator bacteria are an important determinant of water quality in many water resources management situations. They are also one of the more complex phenomena to model and predict. Sources abound, the populations are dynamic and influenced by many factors, and mobility through...

PROCEEDINGS OF THE CROSS DISCIPLINE ECOSYTEM MODELING AND ANALYSIS WORKSHOP

EPA Science Inventory

The complexity of environmental problems we face now and in the future is ever increasing. Process linkages among air, land, surface and subsurface water require interdisciplinary modeling approaches. The dynamics of land use change spurred by population and economic growth, ...

Ecological and economic analysis of poaching of the greater one-horned rhinoceros (Rhinoceros unicornis) in Nepal.

PubMed

Poudyal, Mahesh; Rothley, Kristina; Knowler, Duncan

2009-10-01

Nepal's greater one-horned rhinoceros (Rhinoceros unicornis) faces serious threats from poaching. Poaching of these rhinos is a complex problem, influenced by such diverse factors as the price of rhino horn on the international market, local socioeconomic factors, and the population dynamics of the species. Few studies have attempted to address this complexity. In this study, we model the poaching and population dynamics of the one-horned rhinoceros within an integrated framework of ecological, socioeconomic, political, and legal dimensions. The poaching model for rhinos in Royal Chitwan National Park (RCNP) in Nepal is combined with the population model for the species within a simulation framework and explored under various alternative policy scenarios with differing external socioeconomic and political conditions as well as internal policy response. We predict that, under the current (2003-2005) rhino conservation strategy, poaching would continue to be a major threat to the rhino population in RCNP. Furthermore, the internal policy response must begin to consider external factors such as socioeconomic conditions within the park buffer zone to be more effective in the long run. Finally, we find that, for long-run control, antipoaching policies should be directed at increasing the opportunity costs of poaching by creating better alternative economic opportunities, and at antipoaching enforcement.

Place knowing of persons and populations: restoring the place work of nursing.

PubMed

Thomas, Elizabeth A

2013-12-01

Place emerges when space acquires definition in social constructions of meaning as landscape-languages, which reflect assumptions about physical and social realities. The place work of nursing, which resonated throughout Nightingale's work and the profession's evolution, focuses on human health and healing in the historical transitions and landscape-languages of populations. However, evidence-based practice dominated by empirical knowing inadequately addresses complex health and illness dynamics between place and populations. Translating evidence to the life course experiences of individuals and populations requires place knowing of human situated embodiment within discrete space. An exploration of the concept of place, its application to nursing, and the need for a place paradigm for practice is presented. A sense of salience and situated cognition has been identified as the essential element of the transformation needed in the education of nurses. Place knowing integrates other patterns of knowing (empirical, ethical, aesthetical, personal, unknowing, sociopolitical, and emancipatory) in a situated cognition. Place knowing, like other established patterns of knowing, is a significant epistemological foundation of nursing. Place knowing allows the nuanced intricately complex dynamics of embodied situated human health and illness to be examined, the salience of the particulars to be considered, and the whole of the landscape-languages to emerge.

Extinction in neutrally stable stochastic Lotka-Volterra models

NASA Astrophysics Data System (ADS)

Dobrinevski, Alexander; Frey, Erwin

2012-05-01

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

Extinction in neutrally stable stochastic Lotka-Volterra models.

PubMed

Dobrinevski, Alexander; Frey, Erwin

2012-05-01

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

Investigating large-scale brain dynamics using field potential recordings: analysis and interpretation.

PubMed

Pesaran, Bijan; Vinck, Martin; Einevoll, Gaute T; Sirota, Anton; Fries, Pascal; Siegel, Markus; Truccolo, Wilson; Schroeder, Charles E; Srinivasan, Ramesh

2018-06-25

New technologies to record electrical activity from the brain on a massive scale offer tremendous opportunities for discovery. Electrical measurements of large-scale brain dynamics, termed field potentials, are especially important to understanding and treating the human brain. Here, our goal is to provide best practices on how field potential recordings (electroencephalograms, magnetoencephalograms, electrocorticograms and local field potentials) can be analyzed to identify large-scale brain dynamics, and to highlight critical issues and limitations of interpretation in current work. We focus our discussion of analyses around the broad themes of activation, correlation, communication and coding. We provide recommendations for interpreting the data using forward and inverse models. The forward model describes how field potentials are generated by the activity of populations of neurons. The inverse model describes how to infer the activity of populations of neurons from field potential recordings. A recurring theme is the challenge of understanding how field potentials reflect neuronal population activity given the complexity of the underlying brain systems.

Wave of chaos in a spatial eco-epidemiological system: Generating realistic patterns of patchiness in rabbit-lynx dynamics.

PubMed

Upadhyay, Ranjit Kumar; Roy, Parimita; Venkataraman, C; Madzvamuse, A

2016-11-01

In the present paper, we propose and analyze an eco-epidemiological model with diffusion to study the dynamics of rabbit populations which are consumed by lynx populations. Existence, boundedness, stability and bifurcation analyses of solutions for the proposed rabbit-lynx model are performed. Results show that in the presence of diffusion the model has the potential of exhibiting Turing instability. Numerical results (finite difference and finite element methods) reveal the existence of the wave of chaos and this appears to be a dominant mode of disease dispersal. We also show the mechanism of spatiotemporal pattern formation resulting from the Hopf bifurcation analysis, which can be a potential candidate for understanding the complex spatiotemporal dynamics of eco-epidemiological systems. Implications of the asymptotic transmission rate on disease eradication among rabbit population which in turn enhances the survival of Iberian lynx are discussed. Crown Copyright © 2016. Published by Elsevier Inc. All rights reserved.

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.

[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.

Public health impact of disease-behavior dynamics. Comment on "Coupled disease-behavior dynamics on complex networks: A review" by Z. Wang et al.

NASA Astrophysics Data System (ADS)

Wells, Chad R.; Galvani, Alison P.

2015-12-01

In a loop of dynamic feedback, behavior such as the decision to vaccinate, hand washing, or avoidance influences the progression of the epidemic, yet behavior is driven by the individual's and population's perceived risk of infection during an outbreak. In what we believe will become a seminal paper that stimulates future research as well as an informative teaching aid, Wang et. al. comprehensively review methodological advances that have been used to incorporate human behavior into epidemiological models on the effects of coupling disease transmission and behavior on complex social networks [1]. As illustrated by the recent outbreaks of measles and Middle Eastern Respiratory Syndrome (MERS), here we highlight the importance of coupling behavior and disease transmission that Wang et al. address.

Complex dynamics of selection and cellular memory in adaptation to a changing environment

NASA Astrophysics Data System (ADS)

Kussell, Edo; Lin, Wei-Hsiang

We study a synthetic evolutionary system in bacteria in which an antibiotic resistance gene is controlled by a stochastic on/off switching promoter. At the population level, this system displays all the basic ingredients for evolutionary selection, including diversity, fitness differences, and heritability. At the single cell level, physiological processes can modulate the ability of selection to act. We expose the stochastic switching strains to pulses of antibiotics of different durations in periodically changing environments using microfluidics. Small populations are tracked over a large number of periods at single cell resolution, allowing the visualization and quantification of selective sweeps and counter-sweeps at the population level, as well as detailed single cell analysis. A simple model is introduced to predict long-term population growth rates from single cell measurements, and reveals unexpected aspects of population dynamics, including cellular memory that acts on a fast timescale to modulate growth rates. This work is supported by NIH Grant No. R01-GM097356.

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

EPA Science Inventory

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

Control entropy identifies differential changes in complexity of walking and running gait patterns with increasing speed in highly trained runners

NASA Astrophysics Data System (ADS)

McGregor, Stephen J.; Busa, Michael A.; Skufca, Joseph; Yaggie, James A.; Bollt, Erik M.

2009-06-01

Regularity statistics have been previously applied to walking gait measures in the hope of gaining insight into the complexity of gait under different conditions and in different populations. Traditional regularity statistics are subject to the requirement of stationarity, a limitation for examining changes in complexity under dynamic conditions such as exhaustive exercise. Using a novel measure, control entropy (CE), applied to triaxial continuous accelerometry, we report changes in complexity of walking and running during increasing speeds up to exhaustion in highly trained runners. We further apply Karhunen-Loeve analysis in a new and novel way to the patterns of CE responses in each of the three axes to identify dominant modes of CE responses in the vertical, mediolateral, and anterior/posterior planes. The differential CE responses observed between the different axes in this select population provide insight into the constraints of walking and running in those who may have optimized locomotion. Future comparisons between athletes, healthy untrained, and clinical populations using this approach may help elucidate differences between optimized and diseased locomotor control.

Genetic addiction: selfish gene's strategy for symbiosis in the genome.

PubMed

Mochizuki, Atsushi; Yahara, Koji; Kobayashi, Ichizo; Iwasa, Yoh

2006-02-01

The evolution and maintenance of the phenomenon of postsegregational host killing or genetic addiction are paradoxical. In this phenomenon, a gene complex, once established in a genome, programs death of a host cell that has eliminated it. The intact form of the gene complex would survive in other members of the host population. It is controversial as to why these genetic elements are maintained, due to the lethal effects of host killing, or perhaps some other properties are beneficial to the host. We analyzed their population dynamics by analytical methods and computer simulations. Genetic addiction turned out to be advantageous to the gene complex in the presence of a competitor genetic element. The advantage is, however, limited in a population without spatial structure, such as that in a well-mixed liquid culture. In contrast, in a structured habitat, such as the surface of a solid medium, the addiction gene complex can increase in frequency, irrespective of its initial density. Our demonstration that genomes can evolve through acquisition of addiction genes has implications for the general question of how a genome can evolve as a community of potentially selfish genes.

Population estimates of Hyla cinerea (Schneider) (Green Tree frog) in an urban environment

USGS Publications Warehouse

Pham, L.; Boudreaux, S.; Karhbet, S.; Price, B.; Ackleh, A.S.; Carter, J.; Pal, N.

2007-01-01

Hyla cinerea (Green Treefrog) is a common wetlands species in the southeastern US. To better understand its population dynamics, we followed a relatively isolated population of Green Treefrogs from June 2004 through October 2004 at a federal office complex in Lafayette, LA. Weekly, Green Treefrogs were caught, measured, marked with VIE tags, and released. The data were used to estimate population size. The time frame was split into two periods: before and after August 17, 2004. Before August 17, 2004, the average estimated population size was 143, and after August 24, 2005, this value jumped to 446, an increase possibly due to tadpoles metamorphosing into adults.

Phenotypically heterogeneous populations in spatially heterogeneous environments

NASA Astrophysics Data System (ADS)

Patra, Pintu; Klumpp, Stefan

2014-03-01

The spatial expansion of a population in a nonuniform environment may benefit from phenotypic heterogeneity with interconverting subpopulations using different survival strategies. We analyze the crossing of an antibiotic-containing environment by a bacterial population consisting of rapidly growing normal cells and slow-growing, but antibiotic-tolerant persister cells. The dynamics of crossing is characterized by mean first arrival times and is found to be surprisingly complex. It displays three distinct regimes with different scaling behavior that can be understood based on an analytical approximation. Our results suggest that a phenotypically heterogeneous population has a fitness advantage in nonuniform environments and can spread more rapidly than a homogeneous population.

System Dynamics Modeling for Public Health: Background and Opportunities

PubMed Central

Homer, Jack B.; Hirsch, Gary B.

2006-01-01

The systems modeling methodology of system dynamics is well suited to address the dynamic complexity that characterizes many public health issues. The system dynamics approach involves the development of computer simulation models that portray processes of accumulation and feedback and that may be tested systematically to find effective policies for overcoming policy resistance. System dynamics modeling of chronic disease prevention should seek to incorporate all the basic elements of a modern ecological approach, including disease outcomes, health and risk behaviors, environmental factors, and health-related resources and delivery systems. System dynamics shows promise as a means of modeling multiple interacting diseases and risks, the interaction of delivery systems and diseased populations, and matters of national and state policy. PMID:16449591

Evolutionary game theory for physical and biological scientists. II. Population dynamics equations can be associated with interpretations

PubMed Central

Liao, David; Tlsty, Thea D.

2014-01-01

The use of mathematical equations to analyse population dynamics measurements is being increasingly applied to elucidate complex dynamic processes in biological systems, including cancer. Purely ‘empirical’ equations may provide sufficient accuracy to support predictions and therapy design. Nevertheless, interpretation of fitting equations in terms of physical and biological propositions can provide additional insights that can be used both to refine models that prove inconsistent with data and to understand the scope of applicability of models that validate. The purpose of this tutorial is to assist readers in mathematically associating interpretations with equations and to provide guidance in choosing interpretations and experimental systems to investigate based on currently available biological knowledge, techniques in mathematical and computational analysis and methods for in vitro and in vivo experiments. PMID:25097752

How spatio-temporal habitat connectivity affects amphibian genetic structure.

PubMed

Watts, Alexander G; Schlichting, Peter E; Billerman, Shawn M; Jesmer, Brett R; Micheletti, Steven; Fortin, Marie-Josée; Funk, W Chris; Hapeman, Paul; Muths, Erin; Murphy, Melanie A

2015-01-01

Heterogeneous landscapes and fluctuating environmental conditions can affect species dispersal, population genetics, and genetic structure, yet understanding how biotic and abiotic factors affect population dynamics in a fluctuating environment is critical for species management. We evaluated how spatio-temporal habitat connectivity influences dispersal and genetic structure in a population of boreal chorus frogs (Pseudacris maculata) using a landscape genetics approach. We developed gravity models to assess the contribution of various factors to the observed genetic distance as a measure of functional connectivity. We selected (a) wetland (within-site) and (b) landscape matrix (between-site) characteristics; and (c) wetland connectivity metrics using a unique methodology. Specifically, we developed three networks that quantify wetland connectivity based on: (i) P. maculata dispersal ability, (ii) temporal variation in wetland quality, and (iii) contribution of wetland stepping-stones to frog dispersal. We examined 18 wetlands in Colorado, and quantified 12 microsatellite loci from 322 individual frogs. We found that genetic connectivity was related to topographic complexity, within- and between-wetland differences in moisture, and wetland functional connectivity as contributed by stepping-stone wetlands. Our results highlight the role that dynamic environmental factors have on dispersal-limited species and illustrate how complex asynchronous interactions contribute to the structure of spatially-explicit metapopulations.

Dynamics and stellar population of the Galactic Center (French Title: Étude de la cinématique et de la population stellaire du Centre Galactique)

NASA Astrophysics Data System (ADS)

Paumard, Thibaut

2003-09-01

The central parsec of the Galaxy has been observed using BEAR spectroimagery at high spectral resolution (up to 21 km/s) and medium spatial resolution (0.5"), in Bracket gamma (2.16 microns) and He I (2.06 microns), and high resolution imaging. These data were used to study the young, massive stars of the central parsec, and the structure and dynamics of ionized gas in Sgr A West. The stellar population has been separated into two groups: the IRS 16 complex of 6 LBVs, and at least 20 Wolf-Rayets. The IRS 13E complex has been identified as a cluster of at least 6 massive stars. All this is consistent with the young stars being born in a massive cluster a few tens of parsecs from the Galactic Centre. Providing a deep insight into the morphology of Sgr A West, our data allowed us to derive a kinematic model for the Northern Arm. Our results are in agreement with the idea that the Minispiral is made of ionisation fronts of wider neutral clouds, gravitationally stretched, coming from the CND.

Scaling up complexity in host-pathogens interaction models. Comment on "Coupled disease-behavior dynamics on complex networks: A review" by Z. Wang et al.

NASA Astrophysics Data System (ADS)

Aguiar, Maíra

2015-12-01

Caused by micro-organisms that are pathogenic to the host, infectious diseases have caused debilitation and premature death to large portions of the human population, leading to serious social-economic concerns. The persistence and increase in the occurrence of infectious diseases as well the emergence or resurgence of vector-borne diseases are closely related with demographic factors such as the uncontrolled urbanization and remarkable population growth, political, social and economical changes, deforestation, development of resistance to insecticides and drugs and increased human travel. In recent years, mathematical modeling became an important tool for the understanding of infectious disease epidemiology and dynamics, addressing ideas about the components of host-pathogen interactions. Acting as a possible tool to understand, predict the spread of infectious diseases these models are also used to evaluate the introduction of intervention strategies like vector control and vaccination. Many scientific papers have been published recently on these topics, and most of the models developed try to incorporate factors focusing on several different aspects of the disease (and eventually biological aspects of the vector), which can imply rich dynamic behavior even in the most basic dynamical models. As one example to be cited, there is a minimalistic dengue model that has shown rich dynamic structures, with bifurcations (Hopf, pitchfork, torus and tangent bifurcations) up to chaotic attractors in unexpected parameter regions [1,2], which was able to describe the large fluctuations observed in empirical outbreak data [3,4].

Demographic variation across successional stages and their effects on the population dynamics of the neotropical palm Euterpe precatoria.

PubMed

Otárola, Mauricio Fernández; Avalos, Gerardo

2014-06-01

• Premise of the study: Environmental heterogeneity is a strong selective force shaping adaptation and population dynamics across temporal and spatial scales. Natural and anthropogenic gradients influence the variation of environmental and biotic factors, which determine population demography and dynamics. Successional gradients are expected to influence demographic parameters, but the relationship between these gradients and the species life history, habitat requirements, and degree of variation in demographic traits remains elusive.• Methods: We used the palm Euterpe precatoria to test the effect of successional stage on plant demography within a continuous population. We calculated demographic parameters for size stages and performed matrix analyses to investigate the demographic variation within primary and secondary forests of La Selva, Costa Rica.• Key results: We observed differences in mortality and recruitment of small juveniles between primary and secondary forests. Matrix models described satisfactorily the chronosequence of population changes, which were characterized by high population growth rate in disturbed areas, and decreased growth rate in old successional forests until reaching stability.• Conclusions: Different demographic parameters can be expressed in contiguous subpopulations along a gradient of successional stages with important consequences for population dynamics. Demographic variation superimposed on these gradients contributes to generate subpopulations with different demographic composition, density, and ecological properties. Therefore, the effects of spatial variation must be reconsidered in the design of demographic analyses of tropical palms, which are prime examples of subtle local adaptation. These considerations are crucial in the implementation of management plans for palm species within spatially complex and heterogeneous tropical landscapes. © 2014 Botanical Society of America, Inc.

Bringing consistency to simulation of population models--Poisson simulation as a bridge between micro and macro simulation.

PubMed

Gustafsson, Leif; Sternad, Mikael

2007-10-01

Population models concern collections of discrete entities such as atoms, cells, humans, animals, etc., where the focus is on the number of entities in a population. Because of the complexity of such models, simulation is usually needed to reproduce their complete dynamic and stochastic behaviour. Two main types of simulation models are used for different purposes, namely micro-simulation models, where each individual is described with its particular attributes and behaviour, and macro-simulation models based on stochastic differential equations, where the population is described in aggregated terms by the number of individuals in different states. Consistency between micro- and macro-models is a crucial but often neglected aspect. This paper demonstrates how the Poisson Simulation technique can be used to produce a population macro-model consistent with the corresponding micro-model. This is accomplished by defining Poisson Simulation in strictly mathematical terms as a series of Poisson processes that generate sequences of Poisson distributions with dynamically varying parameters. The method can be applied to any population model. It provides the unique stochastic and dynamic macro-model consistent with a correct micro-model. The paper also presents a general macro form for stochastic and dynamic population models. In an appendix Poisson Simulation is compared with Markov Simulation showing a number of advantages. Especially aggregation into state variables and aggregation of many events per time-step makes Poisson Simulation orders of magnitude faster than Markov Simulation. Furthermore, you can build and execute much larger and more complicated models with Poisson Simulation than is possible with the Markov approach.

Simulating living organisms with populations of point vortices

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

Schmieder, R.W.

1995-07-01

The author has found that time-averaged images of small populations of point vortices can exhibit motions suggestive of the behavior of individual organisms. As an example, the author shows that collections of point vortices confined in a box and subjected to heating can generate patterns that are broadly similar to interspecies defense in certain sea anemones. It is speculated that other simple dynamical systems can be found to produce similar complex organism-like behavior.

Complex Ancient Genetic Structure and Cultural Transitions in Southern African Populations.

PubMed

Montinaro, Francesco; Busby, George B J; Gonzalez-Santos, Miguel; Oosthuitzen, Ockie; Oosthuitzen, Erika; Anagnostou, Paolo; Destro-Bisol, Giovanni; Pascali, Vincenzo L; Capelli, Cristian

2017-01-01

The characterization of the structure of southern African populations has been the subject of numerous genetic, medical, linguistic, archaeological, and anthropological investigations. Current diversity in the subcontinent is the result of complex events of genetic admixture and cultural contact between early inhabitants and migrants that arrived in the region over the last 2000 years. Here, we analyze 1856 individuals from 91 populations, comprising novel and published genotype data, to characterize the genetic ancestry profiles of 631 individuals from 51 southern African populations. Combining both local ancestry and allele frequency based analyses, we identify a tripartite, ancient, Khoesan-related genetic structure. This structure correlates neither with linguistic affiliation nor subsistence strategy, but with geography, revealing the importance of isolation-by-distance dynamics in the area. Fine-mapping of these components in southern African populations reveals admixture and cultural reversion involving several Khoesan groups, and highlights that Bantu speakers and Coloured individuals have different mixtures of these ancient ancestries. Copyright © 2017 Montinaro et al.

DYNAMIC ORDER IN COMPLEX SYSTEMS FROM FISHER INFORMATION

EPA Science Inventory

At its core, sustainability asks whether the planet will persist into the indefinite future in a regime which is amenable to human existence in a manner that is acceptable. The issue of sustainability has naturally arisen from the observation that a growing human population is c...

Adaptive contact networks change effective disease infectiousness and dynamics.

PubMed

Van Segbroeck, Sven; Santos, Francisco C; Pacheco, Jorge M

2010-08-19

Human societies are organized in complex webs that are constantly reshaped by a social dynamic which is influenced by the information individuals have about others. Similarly, epidemic spreading may be affected by local information that makes individuals aware of the health status of their social contacts, allowing them to avoid contact with those infected and to remain in touch with the healthy. Here we study disease dynamics in finite populations in which infection occurs along the links of a dynamical contact network whose reshaping may be biased based on each individual's health status. We adopt some of the most widely used epidemiological models, investigating the impact of the reshaping of the contact network on the disease dynamics. We derive analytical results in the limit where network reshaping occurs much faster than disease spreading and demonstrate numerically that this limit extends to a much wider range of time scales than one might anticipate. Specifically, we show that from a population-level description, disease propagation in a quickly adapting network can be formulated equivalently as disease spreading on a well-mixed population but with a rescaled infectiousness. We find that for all models studied here--SI, SIS and SIR--the effective infectiousness of a disease depends on the population size, the number of infected in the population, and the capacity of healthy individuals to sever contacts with the infected. Importantly, we indicate how the use of available information hinders disease progression, either by reducing the average time required to eradicate a disease (in case recovery is possible), or by increasing the average time needed for a disease to spread to the entire population (in case recovery or immunity is impossible).

Dynamical analogy between economical crisis and earthquake dynamics within the nonextensive statistical mechanics framework

NASA Astrophysics Data System (ADS)

Potirakis, Stelios M.; Zitis, Pavlos I.; Eftaxias, Konstantinos

2013-07-01

The field of study of complex systems considers that the dynamics of complex systems are founded on universal principles that may be used to describe a great variety of scientific and technological approaches of different types of natural, artificial, and social systems. Several authors have suggested that earthquake dynamics and the dynamics of economic (financial) systems can be analyzed within similar mathematical frameworks. We apply concepts of the nonextensive statistical physics, on time-series data of observable manifestations of the underlying complex processes ending up with these different extreme events, in order to support the suggestion that a dynamical analogy exists between a financial crisis (in the form of share or index price collapse) and a single earthquake. We also investigate the existence of such an analogy by means of scale-free statistics (the Gutenberg-Richter distribution of event sizes). We show that the populations of: (i) fracto-electromagnetic events rooted in the activation of a single fault, emerging prior to a significant earthquake, (ii) the trade volume events of different shares/economic indices, prior to a collapse, and (iii) the price fluctuation (considered as the difference of maximum minus minimum price within a day) events of different shares/economic indices, prior to a collapse, follow both the traditional Gutenberg-Richter law as well as a nonextensive model for earthquake dynamics, with similar parameter values. The obtained results imply the existence of a dynamic analogy between earthquakes and economic crises, which moreover follow the dynamics of seizures, magnetic storms and solar flares.

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.

“Invisible” Conformers of an Antifungal Disulfide Protein Revealed by Constrained Cold and Heat Unfolding, CEST-NMR Experiments, and Molecular Dynamics Calculations

PubMed Central

Fizil, Ádám; Gáspári, Zoltán; Barna, Terézia; Marx, Florentine; Batta, Gyula

2015-01-01

Transition between conformational states in proteins is being recognized as a possible key factor of function. In support of this, hidden dynamic NMR structures were detected in several cases up to populations of a few percent. Here, we show by two- and three-state analysis of thermal unfolding, that the population of hidden states may weight 20–40 % at 298 K in a disulfide-rich protein. In addition, sensitive 15N-CEST NMR experiments identified a low populated (0.15 %) state that was in slow exchange with the folded PAF protein. Remarkably, other techniques failed to identify the rest of the NMR “dark matter”. Comparison of the temperature dependence of chemical shifts from experiments and molecular dynamics calculations suggests that hidden conformers of PAF differ in the loop and terminal regions and are most similar in the evolutionary conserved core. Our observations point to the existence of a complex conformational landscape with multiple conformational states in dynamic equilibrium, with diverse exchange rates presumably responsible for the completely hidden nature of a considerable fraction. PMID:25676351

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.

Empirical evidence that metabolic theory describes the temperature dependency of within-host parasite dynamics.

PubMed

Kirk, Devin; Jones, Natalie; Peacock, Stephanie; Phillips, Jessica; Molnár, Péter K; Krkošek, Martin; Luijckx, Pepijn

2018-02-01

The complexity of host-parasite interactions makes it difficult to predict how host-parasite systems will respond to climate change. In particular, host and parasite traits such as survival and virulence may have distinct temperature dependencies that must be integrated into models of disease dynamics. Using experimental data from Daphnia magna and a microsporidian parasite, we fitted a mechanistic model of the within-host parasite population dynamics. Model parameters comprising host aging and mortality, as well as parasite growth, virulence, and equilibrium abundance, were specified by relationships arising from the metabolic theory of ecology. The model effectively predicts host survival, parasite growth, and the cost of infection across temperature while using less than half the parameters compared to modeling temperatures discretely. Our results serve as a proof of concept that linking simple metabolic models with a mechanistic host-parasite framework can be used to predict temperature responses of parasite population dynamics at the within-host level.

Empirical evidence that metabolic theory describes the temperature dependency of within-host parasite dynamics

PubMed Central

Jones, Natalie; Peacock, Stephanie; Phillips, Jessica; Molnár, Péter K.; Krkošek, Martin; Luijckx, Pepijn

2018-01-01

The complexity of host–parasite interactions makes it difficult to predict how host–parasite systems will respond to climate change. In particular, host and parasite traits such as survival and virulence may have distinct temperature dependencies that must be integrated into models of disease dynamics. Using experimental data from Daphnia magna and a microsporidian parasite, we fitted a mechanistic model of the within-host parasite population dynamics. Model parameters comprising host aging and mortality, as well as parasite growth, virulence, and equilibrium abundance, were specified by relationships arising from the metabolic theory of ecology. The model effectively predicts host survival, parasite growth, and the cost of infection across temperature while using less than half the parameters compared to modeling temperatures discretely. Our results serve as a proof of concept that linking simple metabolic models with a mechanistic host–parasite framework can be used to predict temperature responses of parasite population dynamics at the within-host level. PMID:29415043

Plasmodium vivax population structure and transmission dynamics in Sabah Malaysia.

PubMed

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

2013-01-01

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

Plasmodium vivax Population Structure and Transmission Dynamics in Sabah Malaysia

PubMed Central

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

2013-01-01

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

Beech Fructification and Bank Vole Population Dynamics - Combined Analyses of Promoters of Human Puumala Virus Infections in Germany

PubMed Central

Reil, Daniela; Imholt, Christian; Eccard, Jana Anja; Jacob, Jens

2015-01-01

The transmission of wildlife zoonoses to humans depends, amongst others, on complex interactions of host population ecology and pathogen dynamics within host populations. In Europe, the Puumala virus (PUUV) causes nephropathia epidemica in humans. In this study we investigated complex interrelations within the epidemic system of PUUV and its rodent host, the bank vole (Myodes glareolus). We suggest that beech fructification and bank vole abundance are both decisive factors affecting human PUUV infections. While rodent host dynamics are expected to be directly linked to human PUUV infections, beech fructification is a rather indirect predictor by serving as food source for PUUV rodent hosts. Furthermore, we examined the dependence of bank vole abundance on beech fructification. We analysed a 12-year (2001-2012) time series of the parameters: beech fructification (as food resource for the PUUV host), bank vole abundance and human incidences from 7 Federal States of Germany. For the first time, we could show the direct interrelation between these three parameters involved in human PUUV epidemics and we were able to demonstrate on a large scale that human PUUV infections are highly correlated with bank vole abundance in the present year, as well as beech fructification in the previous year. By using beech fructification and bank vole abundance as predictors in one model we significantly improved the degree of explanation of human PUUV incidence. Federal State was included as random factor because human PUUV incidence varies considerably among states. Surprisingly, the effect of rodent abundance on human PUUV infections is less strong compared to the indirect effect of beech fructification. Our findings are useful to facilitate the development of predictive models for host population dynamics and the related PUUV infection risk for humans and can be used for plant protection and human health protection purposes. PMID:26214509

Beech Fructification and Bank Vole Population Dynamics--Combined Analyses of Promoters of Human Puumala Virus Infections in Germany.

PubMed

Reil, Daniela; Imholt, Christian; Eccard, Jana Anja; Jacob, Jens

2015-01-01

The transmission of wildlife zoonoses to humans depends, amongst others, on complex interactions of host population ecology and pathogen dynamics within host populations. In Europe, the Puumala virus (PUUV) causes nephropathia epidemica in humans. In this study we investigated complex interrelations within the epidemic system of PUUV and its rodent host, the bank vole (Myodes glareolus). We suggest that beech fructification and bank vole abundance are both decisive factors affecting human PUUV infections. While rodent host dynamics are expected to be directly linked to human PUUV infections, beech fructification is a rather indirect predictor by serving as food source for PUUV rodent hosts. Furthermore, we examined the dependence of bank vole abundance on beech fructification. We analysed a 12-year (2001-2012) time series of the parameters: beech fructification (as food resource for the PUUV host), bank vole abundance and human incidences from 7 Federal States of Germany. For the first time, we could show the direct interrelation between these three parameters involved in human PUUV epidemics and we were able to demonstrate on a large scale that human PUUV infections are highly correlated with bank vole abundance in the present year, as well as beech fructification in the previous year. By using beech fructification and bank vole abundance as predictors in one model we significantly improved the degree of explanation of human PUUV incidence. Federal State was included as random factor because human PUUV incidence varies considerably among states. Surprisingly, the effect of rodent abundance on human PUUV infections is less strong compared to the indirect effect of beech fructification. Our findings are useful to facilitate the development of predictive models for host population dynamics and the related PUUV infection risk for humans and can be used for plant protection and human health protection purposes.

A combined crossed-beam and theoretical study of the reaction dynamics of O(3P) + C2H3 → C2H2 + OH: analysis of the nascent OH products with the preferential population of the Π(A') component.

PubMed

Park, Min-Jin; Jang, Su-Chan; Choi, Jong-Ho

2012-11-28

The gas-phase reaction dynamics of ground-state atomic oxygen [O((3)P) from the photo-dissociation of NO(2)] with vinyl radicals [C(2)H(3) from the supersonic flash pyrolysis of vinyl iodide, C(2)H(3)I] has been investigated using a combination of high-resolution laser-induced fluorescence spectroscopy in a crossed-beam configuration and ab initio calculations. Unlike the previous gas-phase bulk kinetic experiments by Baulch et al. [J. Phys. Chem. Ref. Data 34, 757 (2005)], a new exothermic channel of O((3)P) + C(2)H(3) → C(2)H(2) + OH (X (2)Π: υ" = 0) has been identified for the first time, and the population analysis shows bimodal nascent rotational distributions of OH products with low- and high-N" components with a ratio of 2.4:1. No spin-orbit propensities were observed, and the averaged ratios of Π(A('))∕Π(A") were determined to be 1.66 ± 0.27. On the basis of computations at the CBS-QB3 theory level and comparison with prior theory, the microscopic mechanisms responsible for the nascent populations can be understood in terms of two competing dynamical pathways: a direct abstraction process in the low-N" regime as the major pathway and an addition-complex forming process in the high-N" regime as the minor pathway. Particularly, during the bond cleavage process of the weakly bound van der Waals complex C(2)H(2)-OH, the characteristic pathway from the low dihedral-angle geometry was consistent with the observed preferential population of the Π(A') component in the nascent OH products. A molecular-level discussion of the reactivity, mechanism, and dynamical features of the title reaction are presented together with a comparison to gas-phase oxidation reactions of a series of prototypical hydrocarbon radicals.

Molecular population dynamics of DNA structures in a bcl-2 promoter sequence is regulated by small molecules and the transcription factor hnRNP LL.

PubMed

Cui, Yunxi; Koirala, Deepak; Kang, HyunJin; Dhakal, Soma; Yangyuoru, Philip; Hurley, Laurence H; Mao, Hanbin

2014-05-01

Minute difference in free energy change of unfolding among structures in an oligonucleotide sequence can lead to a complex population equilibrium, which is rather challenging for ensemble techniques to decipher. Herein, we introduce a new method, molecular population dynamics (MPD), to describe the intricate equilibrium among non-B deoxyribonucleic acid (DNA) structures. Using mechanical unfolding in laser tweezers, we identified six DNA species in a cytosine (C)-rich bcl-2 promoter sequence. Population patterns of these species with and without a small molecule (IMC-76 or IMC-48) or the transcription factor hnRNP LL are compared to reveal the MPD of different species. With a pattern recognition algorithm, we found that IMC-48 and hnRNP LL share 80% similarity in stabilizing i-motifs with 60 s incubation. In contrast, IMC-76 demonstrates an opposite behavior, preferring flexible DNA hairpins. With 120-180 s incubation, IMC-48 and hnRNP LL destabilize i-motifs, which has been previously proposed to activate bcl-2 transcriptions. These results provide strong support, from the population equilibrium perspective, that small molecules and hnRNP LL can modulate bcl-2 transcription through interaction with i-motifs. The excellent agreement with biochemical results firmly validates the MPD analyses, which, we expect, can be widely applicable to investigate complex equilibrium of biomacromolecules. © 2014 The Author(s). Published by Oxford University Press [on behalf of Nucleic Acids Research].

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

USGS Publications Warehouse

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

2016-01-01

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

Coevolutionary dynamics in large, but finite populations

NASA Astrophysics Data System (ADS)

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

2006-07-01

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

Trees wanted--dead or alive! Host selection and population dynamics in tree-killing bark beetles.

PubMed

Kausrud, Kyrre L; Grégoire, Jean-Claude; Skarpaas, Olav; Erbilgin, Nadir; Gilbert, Marius; Økland, Bjørn; Stenseth, Nils Chr

2011-01-01

Bark beetles (Coleoptera: Curculionidae, Scolytinae) feed and breed in dead or severely weakened host trees. When their population densities are high, some species aggregate on healthy host trees so that their defences may be exhausted and the inner bark successfully colonized, killing the tree in the process. Here we investigate under what conditions participating with unrelated conspecifics in risky mass attacks on living trees is an adaptive strategy, and what this can tell us about bark beetle outbreak dynamics. We find that the outcome of individual host selection may deviate from the ideal free distribution in a way that facilitates the emergence of tree-killing (aggressive) behavior, and that any heritability on traits governing aggressiveness seems likely to exist in a state of flux or cycles consistent with variability observed in natural populations. This may have implications for how economically and ecologically important species respond to environmental changes in climate and landscape (forest) structure. The population dynamics emerging from individual behavior are complex, capable of switching between "endemic" and "epidemic" regimes spontaneously or following changes in host availability or resistance. Model predictions are compared to empirical observations, and we identify some factors determining the occurrence and self-limitation of epidemics.

[Modelling of selection acting upon the pleioptropic locus in an asynchronous population].

PubMed

Zhdanov, O L; Frisman, E Ia

2014-08-01

We created and examined a mathematical model describing the size and genetic composition dynamics in a population with two age classes, where the survival of both zygotes and adult individuals is determined by one pleioptropic locus. Even under present limitations, as the outside effects of a complex multigenic system are reduced to the case of single locus, our model demonstrates a wide range of different evolutionary scenarios for possible changes in the population dynamics. An increase in the reproductive potential and survival is accompanied by a transition from stable to oscillating population numbers. However, the evolutionary growth of these parameters may be nonmonotonic and may fluctuate significantly. In the case of antagonistic pleioptropy, an increase in one of these parameters usually leads to a predictable decrease in the other. This, in turn, may even stabilize the numbers and genetic compositions of the age groups. We demonstrated that selection acting on later stages of the life cycle is accompanied by destabilization of the Hardy-Weinberg equilibriums that link allele and genotype frequencies. We obtained a balance ratio, which allowed us to compare the combined fitness of the genotypes and to demonstrate that selection leads to the exclusion of the least adapted genotypes. Initial conditionsmay in some cases determine the genetic composition and pattern of population size dynamics.

Economic Analysis of Biological Invasions in Forests

Treesearch

Tomas P. Holmes; Julian Aukema; Jeffrey Englin; Robert G. Haight; Kent Kovacs; Brian Leung

2014-01-01

Biological invasions of native forests by nonnative pests result from complex stochastic processes that are difficult to predict. Although economic optimization models describe efficient controls across the stages of an invasion, the ability to calibrate such models is constrained by lack of information on pest population dynamics and consequent economic damages. Here...

First Principles Dynamics and Coarse-Grained Characterization of Photoisomerization in Complex Environments

ERIC Educational Resources Information Center

Virshup, Aaron Michael

2009-01-01

Photoisomerization of conjugated systems is a common pathway for photomechanical energy conversion in biological chromophores. Such reactions are mediated by conical intersections (CIs)--points of degeneracy between different potential energy surfaces, which efficiently funnel population between electronic states. There are many examples of a…

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.

Interrogation of inhibitor of nuclear factor κB α/nuclear factor κB (IκBα/NF-κB) negative feedback loop dynamics: from single cells to live animals in vivo.

PubMed

Moss, Britney L; Elhammali, Adnan; Fowlkes, Tiffanie; Gross, Shimon; Vinjamoori, Anant; Contag, Christopher H; Piwnica-Worms, David

2012-09-07

Full understanding of the biological significance of negative feedback processes requires interrogation at multiple scales as follows: in single cells, cell populations, and live animals in vivo. The transcriptionally coupled IκBα/NF-κB negative feedback loop, a pivotal regulatory node of innate immunity and inflammation, represents a model system for multiscalar reporters. Using a κB(5)→IκBα-FLuc bioluminescent reporter, we rigorously evaluated the dynamics of ΙκBα degradation and subsequent NF-κB transcriptional activity in response to diverse modes of TNFα stimulation. Modulating TNFα concentration or pulse duration yielded complex, reproducible, and differential ΙκBα dynamics in both cell populations and live single cells. Tremendous heterogeneity in the transcriptional amplitudes of individual responding cells was observed, which was greater than the heterogeneity in the transcriptional kinetics of responsive cells. Furthermore, administration of various TNFα doses in vivo generated ΙκBα dynamic profiles in the liver resembling those observed in single cells and populations of cells stimulated with TNFα pulses. This suggested that dose modulation of circulating TNFα was perceived by hepatocytes in vivo as pulses of increasing duration. Thus, a robust bioluminescent reporter strategy enabled rigorous quantitation of NF-κB/ΙκBα dynamics in both live single cells and cell populations and furthermore, revealed reproducible behaviors that informed interpretation of in vivo studies.

Dynamic feature analysis of vector-based images for neuropsychological testing

NASA Astrophysics Data System (ADS)

Smith, Stephen L.; Cervantes, Basilio R.

1998-07-01

The dynamic properties of human motor activities, such as those observed in the course of drawing simple geometric shapes, are considerably more complex and often more informative than the goal to be achieved; in this case a static line drawing. This paper demonstrates how these dynamic properties may be used to provide a means of assessing a patient's visuo-spatial ability -- an important component of neuropsychological testing. The work described here provides a quantitative assessment of visuo-spatial ability, whilst preserving the conventional test environment. Results will be presented for a clinical population of long-term haemodialysis patients and test population comprises three groups of children (1) 7-8 years, (2) 9-10 years and (3) 11-12 years, all of which have no known neurological dysfunction. Ten new dynamic measurements extracted from patient responses in conjunction with one static feature deduced from earlier work describe a patient's visuo-spatial ability in a quantitative manner with sensitivity not previously attainable. The dynamic feature measurements in isolation provide a unique means of tracking a patient's approach to motor activities and could prove useful in monitoring a child' visuo-motor development.

Sinks without borders: Snowshoe hare dynamics in a complex landscape

USGS Publications Warehouse

Griffin, Paul C.; Mills, L. Scott

2009-01-01

A full understanding of population dynamics of wide-ranging animals should account for the effects that movement and habitat use have on individual contributions to population growth or decline. Quantifying the per-capita, habitat-specific contribution to population growth can clarify the value of different patch types, and help to differentiate population sources from population sinks. Snowshoe hares, Lepus americanus, routinely use various habitat types in the landscapes they inhabit in the contiguous US, where managing forests for high snowshoe hare density is a priority for conservation of Canada lynx, Lynx canadensis. We estimated density and demographic rates via mark–recapture live trapping and radio-telemetry within four forest stand structure (FSS) types at three study areas within heterogeneous managed forests in western Montana. We found support for known fate survival models with time-varying individual covariates representing the proportion of locations in each of the FSS types, with survival rates decreasing as use of open young and open mature FSS types increased. The per-capita contribution to overall population growth increased with use of the dense mature or dense young FSS types and decreased with use of the open young or open mature FSS types, and relatively high levels of immigration appear to be necessary to sustain hares in the open FSS types. Our results support a conceptual model for snowshoe hares in the southern range in which sink habitats (open areas) prevent the buildup of high hare densities. More broadly, we use this system to develop a novel approach to quantify demographic sources and sinks for animals making routine movements through complex fragmented landscapes.

Habitat fragmentation effects depend on complex interactions between population size and dispersal ability: Modeling influences of roads, agriculture and residential development across a range of life-history characteristics [chapter 20

Treesearch

Samuel A. Cushman; Bradley W. Compton; Kevin McGarigal

2010-01-01

Habitat loss and fragmentation are widely believed to be the most important drivers of extinction (Leakey and Lewin 1995). The habitats in which organisms live are spatially structured at a number of scales, and these patterns interact with organism perception and behavior to drive population dynamics and community structure (Johnson et al. 1992). Anthropogenic habitat...

Metastability and Inter-Band Frequency Modulation in Networks of Oscillating Spiking Neuron Populations

PubMed Central

Bhowmik, David; Shanahan, Murray

2013-01-01

Groups of neurons firing synchronously are hypothesized to underlie many cognitive functions such as attention, associative learning, memory, and sensory selection. Recent theories suggest that transient periods of synchronization and desynchronization provide a mechanism for dynamically integrating and forming coalitions of functionally related neural areas, and that at these times conditions are optimal for information transfer. Oscillating neural populations display a great amount of spectral complexity, with several rhythms temporally coexisting in different structures and interacting with each other. This paper explores inter-band frequency modulation between neural oscillators using models of quadratic integrate-and-fire neurons and Hodgkin-Huxley neurons. We vary the structural connectivity in a network of neural oscillators, assess the spectral complexity, and correlate the inter-band frequency modulation. We contrast this correlation against measures of metastable coalition entropy and synchrony. Our results show that oscillations in different neural populations modulate each other so as to change frequency, and that the interaction of these fluctuating frequencies in the network as a whole is able to drive different neural populations towards episodes of synchrony. Further to this, we locate an area in the connectivity space in which the system directs itself in this way so as to explore a large repertoire of synchronous coalitions. We suggest that such dynamics facilitate versatile exploration, integration, and communication between functionally related neural areas, and thereby supports sophisticated cognitive processing in the brain. PMID:23614040

Complexities, Catastrophes and Cities: Emergency Dynamics in Varying Scenarios and Urban Topologies

NASA Astrophysics Data System (ADS)

Narzisi, Giuseppe; Mysore, Venkatesh; Byeon, Jeewoong; Mishra, Bud

Complex Systems are often characterized by agents capable of interacting with each other dynamically, often in non-linear and non-intuitive ways. Trying to characterize their dynamics often results in partial differential equations that are difficult, if not impossible, to solve. A large city or a city-state is an example of such an evolving and self-organizing complex environment that efficiently adapts to different and numerous incremental changes to its social, cultural and technological infrastructure [1]. One powerful technique for analyzing such complex systems is Agent-Based Modeling (ABM) [9], which has seen an increasing number of applications in social science, economics and also biology. The agent-based paradigm facilitates easier transfer of domain specific knowledge into a model. ABM provides a natural way to describe systems in which the overall dynamics can be described as the result of the behavior of populations of autonomous components: agents, with a fixed set of rules based on local information and possible central control. As part of the NYU Center for Catastrophe Preparedness and Response (CCPR1), we have been exploring how ABM can serve as a powerful simulation technique for analyzing large-scale urban disasters. The central problem in Disaster Management is that it is not immediately apparent whether the current emergency plans are robust against such sudden, rare and punctuated catastrophic events.

Border Malaria Associated with Multidrug Resistance on Thailand-Myanmar and Thailand-Cambodia Borders: Transmission Dynamic, Vulnerability, and Surveillance

PubMed Central

Bhumiratana, Adisak; Intarapuk, Apiradee; Sorosjinda-Nunthawarasilp, Prapa; Maneekan, Pannamas; Koyadun, Surachart

2013-01-01

This systematic review elaborates the concepts and impacts of border malaria, particularly on the emergence and spread of Plasmodium falciparum and Plasmodium vivax multidrug resistance (MDR) malaria on Thailand-Myanmar and Thailand-Cambodia borders. Border malaria encompasses any complex epidemiological settings of forest-related and forest fringe-related malaria, both regularly occurring in certain transmission areas and manifesting a trend of increased incidence in transmission prone areas along these borders, as the result of interconnections of human settlements and movement activities, cross-border population migrations, ecological changes, vector population dynamics, and multidrug resistance. For regional and global perspectives, this review analyzes and synthesizes the rationales pertaining to transmission dynamics and the vulnerabilities of border malaria that constrain surveillance and control of the world's most MDR falciparum and vivax malaria on these chaotic borders. PMID:23865048

Narrative dynamics in social groups: A discrete choice model

NASA Astrophysics Data System (ADS)

Antoci, A.; Bellanca, N.; Galdi, G.; Sodini, M.

2018-05-01

Individuals follow different rules for action: they react swiftly, grasping the short-term advantages in sight, or they waste cognitive resources to complete otherwise easy tasks, but they are able to plan ahead future complex decisions. Scholars from different disciplines studied the conditions under which either decision rule may enhance the fitness of its adopters, with a focus on the environmental features. However, we here propose that a crucial feature of the evolution of populations and their decision rules is rather inter-group interactions. Indeed, we study what happens when two groups support different decision rules, encapsulated in narratives, and their populations interact with each other. In particular, we assume that the payoff of each rule depends on the share of both social groups which adopt such rules. We then describe the most salient dynamics scenarios and identify the conditions which lead to chaotic dynamics and multistability regimes.

Obesity prevention: Comparison of techniques and potential solution

NASA Astrophysics Data System (ADS)

Zulkepli, Jafri; Abidin, Norhaslinda Zainal; Zaibidi, Nerda Zura

2014-12-01

Over the years, obesity prevention has been a broadly studied subject by both academicians and practitioners. It is one of the most serious public health issue as it can cause numerous chronic health and psychosocial problems. Research is needed to suggest a population-based strategy for obesity prevention. In the academic environment, the importance of obesity prevention has triggered various problem solving approaches. A good obesity prevention model, should comprehend and cater all complex and dynamics issues. Hence, the main purpose of this paper is to discuss the qualitative and quantitative approaches on obesity prevention study and to provide an extensive literature review on various recent modelling techniques for obesity prevention. Based on these literatures, the comparison of both quantitative and qualitative approahes are highlighted and the justification on the used of system dynamics technique to solve the population of obesity is discussed. Lastly, a potential framework solution based on system dynamics modelling is proposed.

Modeling mechanical interactions in growing populations of rod-shaped bacteria

NASA Astrophysics Data System (ADS)

Winkle, James J.; Igoshin, Oleg A.; Bennett, Matthew R.; Josić, Krešimir; Ott, William

2017-10-01

Advances in synthetic biology allow us to engineer bacterial collectives with pre-specified characteristics. However, the behavior of these collectives is difficult to understand, as cellular growth and division as well as extra-cellular fluid flow lead to complex, changing arrangements of cells within the population. To rationally engineer and control the behavior of cell collectives we need theoretical and computational tools to understand their emergent spatiotemporal dynamics. Here, we present an agent-based model that allows growing cells to detect and respond to mechanical interactions. Crucially, our model couples the dynamics of cell growth to the cell’s environment: Mechanical constraints can affect cellular growth rate and a cell may alter its behavior in response to these constraints. This coupling links the mechanical forces that influence cell growth and emergent behaviors in cell assemblies. We illustrate our approach by showing how mechanical interactions can impact the dynamics of bacterial collectives growing in microfluidic traps.

Mathematical Models of the Impact of IL2 Modulation Therapies on T Cell Dynamics

PubMed Central

León, Kalet; García-Martínez, Karina; Carmenate, Tania

2013-01-01

Several reports in the literature have drawn a complex picture of the effect of treatments aiming to modulate IL2 activity in vivo. They seem to promote either immunity or tolerance, probably depending on the specific context, dose, and timing of their application. Such complexity might derive from the pleiotropic role of IL2 in T cell dynamics. To theoretically address the latter possibility, our group has developed several mathematical models for Helper, Regulatory, and Memory T cell population dynamics, which account for most well-known facts concerning their relationship with IL2. We have simulated the effect of several types of therapies, including the injection of: IL2; antibodies anti-IL2; IL2/anti-IL2 immune-complexes; and mutant variants of IL2. We studied the qualitative and quantitative conditions of dose and timing for these treatments which allow them to potentiate either immunity or tolerance. Our results provide reasonable explanations for the existent pre-clinical and clinical data, predict some novel treatments, and further provide interesting practical guidelines to optimize the future application of these types of treatments. PMID:24376444

cAMP-dependent protein kinase (PKA) complexes probed by complementary differential scanning fluorimetry and ion mobility–mass spectrometry

PubMed Central

Byrne, Dominic P.; Vonderach, Matthias; Ferries, Samantha; Brownridge, Philip J.; Eyers, Claire E.; Eyers, Patrick A.

2016-01-01

cAMP-dependent protein kinase (PKA) is an archetypal biological signaling module and a model for understanding the regulation of protein kinases. In the present study, we combine biochemistry with differential scanning fluorimetry (DSF) and ion mobility–mass spectrometry (IM–MS) to evaluate effects of phosphorylation and structure on the ligand binding, dynamics and stability of components of heteromeric PKA protein complexes in vitro. We uncover dynamic, conformationally distinct populations of the PKA catalytic subunit with distinct structural stability and susceptibility to the physiological protein inhibitor PKI. Native MS of reconstituted PKA R2C2 holoenzymes reveals variable subunit stoichiometry and holoenzyme ablation by PKI binding. Finally, we find that although a ‘kinase-dead’ PKA catalytic domain cannot bind to ATP in solution, it interacts with several prominent chemical kinase inhibitors. These data demonstrate the combined power of IM–MS and DSF to probe PKA dynamics and regulation, techniques that can be employed to evaluate other protein-ligand complexes, with broad implications for cellular signaling. PMID:27444646

Dynamics of Fos-Jun-NFAT1 complexes

PubMed Central

Ramirez-Carrozzi, Vladimir R.; Kerppola, Tom K.

2001-01-01

Transcription initiation in eukaryotes is controlled by nucleoprotein complexes formed through cooperative interactions among multiple transcription regulatory proteins. These complexes may be assembled via stochastic collisions or defined pathways. We investigated the dynamics of Fos-Jun-NFAT1 complexes by using a multicolor fluorescence resonance energy transfer assay. Fos-Jun heterodimers can bind to AP-1 sites in two opposite orientations, only one of which is populated in mature Fos-Jun-NFAT1 complexes. We studied the reversal of Fos-Jun binding orientation in response to NFAT1 by measuring the efficiencies of energy transfer from donor fluorophores linked to opposite ends of an oligonucleotide to an acceptor fluorophore linked to one subunit of the heterodimer. The reorientation of Fos-Jun by NFAT1 was not inhibited by competitor oligonucleotides or heterodimers. The rate of Fos-Jun reorientation was faster than the rate of heterodimer dissociation at some binding sites. The facilitated reorientation of Fos-Jun heterodimers therefore can enhance the efficiency of Fos-Jun-NFAT1 complex formation. We also examined the influence of the preferred orientation of Fos-Jun binding on the stability and transcriptional activity of Fos-Jun-NFAT1 complexes. Complexes formed at sites where Fos-Jun favored the same binding orientation in the presence and absence of NFAT1 exhibited an 8-fold slower dissociation rate than complexes formed at sites where Fos-Jun favored the opposite binding orientation. Fos-Jun-NFAT1 complexes also exhibited greater transcription activation at promoter elements that favored the same orientation of Fos-Jun binding in the presence and absence of NFAT1. Thus, the orientation of heterodimer binding can influence both the dynamics and promoter selectivity of multiprotein transcription regulatory complexes. PMID:11320240

Dynamics of Fos-Jun-NFAT1 complexes.

PubMed

Ramirez-Carrozzi, V R; Kerppola, T K

2001-04-24

Transcription initiation in eukaryotes is controlled by nucleoprotein complexes formed through cooperative interactions among multiple transcription regulatory proteins. These complexes may be assembled via stochastic collisions or defined pathways. We investigated the dynamics of Fos-Jun-NFAT1 complexes by using a multicolor fluorescence resonance energy transfer assay. Fos-Jun heterodimers can bind to AP-1 sites in two opposite orientations, only one of which is populated in mature Fos-Jun-NFAT1 complexes. We studied the reversal of Fos-Jun binding orientation in response to NFAT1 by measuring the efficiencies of energy transfer from donor fluorophores linked to opposite ends of an oligonucleotide to an acceptor fluorophore linked to one subunit of the heterodimer. The reorientation of Fos-Jun by NFAT1 was not inhibited by competitor oligonucleotides or heterodimers. The rate of Fos-Jun reorientation was faster than the rate of heterodimer dissociation at some binding sites. The facilitated reorientation of Fos-Jun heterodimers therefore can enhance the efficiency of Fos-Jun-NFAT1 complex formation. We also examined the influence of the preferred orientation of Fos-Jun binding on the stability and transcriptional activity of Fos-Jun-NFAT1 complexes. Complexes formed at sites where Fos-Jun favored the same binding orientation in the presence and absence of NFAT1 exhibited an 8-fold slower dissociation rate than complexes formed at sites where Fos-Jun favored the opposite binding orientation. Fos-Jun-NFAT1 complexes also exhibited greater transcription activation at promoter elements that favored the same orientation of Fos-Jun binding in the presence and absence of NFAT1. Thus, the orientation of heterodimer binding can influence both the dynamics and promoter selectivity of multiprotein transcription regulatory complexes.

Cognitive algorithms: dynamic logic, working of the mind, evolution of consciousness and cultures

NASA Astrophysics Data System (ADS)

Perlovsky, Leonid I.

2007-04-01

The paper discusses evolution of consciousness driven by the knowledge instinct, a fundamental mechanism of the mind which determines its higher cognitive functions. Dynamic logic mathematically describes the knowledge instinct. It overcomes past mathematical difficulties encountered in modeling intelligence and relates it to mechanisms of concepts, emotions, instincts, consciousness and unconscious. The two main aspects of the knowledge instinct are differentiation and synthesis. Differentiation is driven by dynamic logic and proceeds from vague and unconscious states to more crisp and conscious states, from less knowledge to more knowledge at each hierarchical level of the mind. Synthesis is driven by dynamic logic operating in a hierarchical organization of the mind; it strives to achieve unity and meaning of knowledge: every concept finds its deeper and more general meaning at a higher level. These mechanisms are in complex relationship of symbiosis and opposition, which leads to complex dynamics of evolution of consciousness and cultures. Modeling this dynamics in a population leads to predictions for the evolution of consciousness, and cultures. Cultural predictive models can be compared to experimental data and used for improvement of human conditions. We discuss existing evidence and future research directions.

Calls reveal population structure of blue whales across the southeast Indian Ocean and the southwest Pacific Ocean.

PubMed

Balcazar, Naysa E; Tripovich, Joy S; Klinck, Holger; Nieukirk, Sharon L; Mellinger, David K; Dziak, Robert P; Rogers, Tracey L

2015-11-24

For effective species management, understanding population structure and distribution is critical. However, quantifying population structure is not always straightforward. Within the Southern Hemisphere, the blue whale ( Balaenoptera musculus ) complex is extremely diverse but difficult to study. Using automated detector methods, we identified "acoustic populations" of whales producing region-specific call types. We examined blue whale call types in passive acoustic data at sites spanning over 7,370 km across the southeast Indian Ocean and southwest Pacific Ocean (SWPO) from 2009 to 2012. In the absence of genetic resolution, these acoustic populations offer unique information about the blue whale population complex. We found that the Australian continent acts as a geographic boundary, separating Australia and New Zealand blue whale acoustic populations at the junction of the Indian and Pacific Ocean basins. We located blue whales in previously undocumented locations, including the far SWPO, in the Tasman Sea off the east coast of Australia, and along the Lau Basin near Tonga. Our understanding of population dynamics across this broad scale has significant implications to recovery and conservation management for this endangered species, at a regional and global scale.

Transmission of biology and culture among post-contact Native Americans on the western Great Plains.

PubMed

Lycett, Stephen J; von Cramon-Taubadel, Noreen

2016-08-12

The transmission of genes and culture between human populations has major implications for understanding potential correlations between history, biological, and cultural variation. Understanding such dynamics in 19th century, post-contact Native Americans on the western Great Plains is especially challenging given passage of time, complexity of known dynamics, and difficulties of determining genetic patterns in historical populations for whom, even today, genetic data for their descendants are rare. Here, biometric data collected under the direction of Franz Boas from communities penecontemporaneous with the classic bison-hunting societies, were used as a proxy for genetic variation and analyzed together with cultural data. We show that both gene flow and "culture flow" among populations on the High Plains were mediated by geography, fitting a model of isolation-by-distance. Moreover, demographic and cultural exchange among these communities largely overrode the visible signal of the prior millennia of cultural and genetic histories of these populations.

Population dynamics in the presence of quasispecies effects and changing environments

NASA Astrophysics Data System (ADS)

Forster, Robert Burke

2006-12-01

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

Climate, invasive species and land use drive population dynamics of a cold-water specialist

USGS Publications Warehouse

Kovach, Ryan P.; Al-Chokhachy, Robert K.; Whited, Diane C.; Schmetterling, David A.; Dux, Andrew M; Muhlfeld, Clint C.

2017-01-01

Climate change is an additional stressor in a complex suite of threats facing freshwater biodiversity, particularly for cold-water fishes. Research addressing the consequences of climate change on cold-water fish has generally focused on temperature limits defining spatial distributions, largely ignoring how climatic variation influences population dynamics in the context of other existing stressors.We used long-term data from 92 populations of bull trout Salvelinus confluentus – one of North America's most cold-adapted fishes – to quantify additive and interactive effects of climate, invasive species and land use on population dynamics (abundance, variability and growth rate).Populations were generally depressed, more variable and declining where spawning and rearing stream habitat was limited, invasive species and land use were prevalent and stream temperatures were highest. Increasing stream temperature acted additively and independently, whereas land use and invasive species had additive and interactive effects (i.e. the impact of one stressor depended on exposure to the other stressor).Most (58%–78%) of the explained variation in population dynamics was attributed to the presence of invasive species, differences in life history and management actions in foraging habitats in rivers, lakes and reservoirs. Although invasive fishes had strong negative effects on populations in foraging habitats, proactive control programmes appeared to effectively temper their negative impact.Synthesis and applications. Long-term demographic data emphasize that climate warming will exacerbate imperilment of cold-water specialists like bull trout, yet other stressors – especially invasive fishes – are immediate threats that can be addressed by proactive management actions. Therefore, climate-adaptation strategies for freshwater biodiversity should consider existing abiotic and biotic stressors, some of which provide potential and realized opportunity for conservation of freshwater biodiversity in a warming world.

Insights into the Vitis complex in the Danube floodplain (Austria).

PubMed

Arnold, Claire; Bachmann, Olivier; Schnitzler, Annik

2017-10-01

European grapevine populations quickly disappeared from most of their range, massively killed by the spread of North American grapevine pests and diseases. Nowadays taxonomic pollution represents a new threat. A large Vitis complex involves escaped cultivars, rootstocks, and wild grapevines. The study aimed to provide insight into the Vitis complex in the Danube region through field and genetic analyses. Among the five other major rivers in Europe which still host wild grapevine populations, the Danube floodplain is the only one benefiting from an extensive protected forest area (93 km²) and an relatively active dynamic flood pulse. The Donau-Auen National Park also regroups the largest wild grapevine population in Europe. Ninety-two percent of the individuals collected in the park were true wild grapevines, and 8% were hybrids and introgressed individuals of rootstocks, wild grapevines, and cultivars. These three groups are interfertile acting either as pollen donor or receiver. Hybrids were established within and outside the dykes, mostly in anthropized forest edges. The best-developed individuals imply rootstock genes. They establish in the most erosive parts of the floodplain. 42% of the true wild grapevines lived at the edges of forest/meadow, 33.3% at the edges forest/channels, and 23.9% in forest gaps. DBH (Diameter Breast Height) varied significantly with the occurrence of flooding. Clones were found in both true wild and hybrids/introgressed grapevines. The process of cloning seemed to be prevented in places where flooding dynamics is reduced. The current global distribution of true wild grapevines shows a strong tendency toward clustering, in sites where forestry practices were the most extensive. However, the reduced flooding activity is a danger for long-term sustainability of the natural wild grapevine population.

Phenotypic plasticity despite source-sink population dynamics in a long-lived perennial plant.

PubMed

Anderson, Jill T; Sparks, Jed P; Geber, Monica A

2010-11-01

• Species that exhibit adaptive plasticity alter their phenotypes in response to environmental conditions, thereby maximizing fitness in heterogeneous landscapes. However, under demographic source-sink dynamics, selection should favor traits that enhance fitness in the source habitat at the expense of fitness in the marginal habitat. Consistent with source-sink dynamics, the perennial blueberry, Vaccinium elliottii (Ericaceae), shows substantially higher fitness and population sizes in dry upland forests than in flood-prone bottomland forests, and asymmetrical gene flow occurs from upland populations into bottomland populations. Here, we examined whether this species expresses plasticity to these distinct environments despite source-sink dynamics. • We assessed phenotypic responses to a complex environmental gradient in the field and to water stress in the glasshouse. • Contrary to expectations, V. elliottii exhibited a high degree of plasticity in foliar and root traits (specific leaf area, carbon isotope ratios, foliar nitrogen content, root : shoot ratio, root porosity and root architecture). • We propose that plasticity can be maintained in source-sink systems if it is favored within the source habitat and/or a phylogenetic artifact that is not costly. Additionally, plasticity could be advantageous if habitat-based differences in fitness result from incipient niche expansion. Our results illuminate the importance of evaluating phenotypic traits and fitness components across heterogeneous landscapes. © The Authors (2010). Journal compilation © New Phytologist Trust (2010).

VCGDB: a dynamic genome database of the Chinese population

PubMed Central

2014-01-01

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

Relative host body condition and food availability influence epidemic dynamics: a Poecilia reticulata-Gyrodactylus turnbulli host-parasite model.

PubMed

Tadiri, Christina P; Dargent, Felipe; Scott, Marilyn E

2013-03-01

Understanding disease transmission is important to species management and human health. Host body condition, nutrition and disease susceptibility interact in a complex manner, and while the individual effects of these variables are well known, our understanding of how they interact and translate to population dynamics is limited. Our objective was to determine whether host relative body condition influences epidemic dynamics, and how this relationship is affected by food availability. Poecilia reticulata (guppies) of roughly similar size were selected and assembled randomly into populations of 10 guppies assigned to 3 different food availability treatments, and the relative condition index (Kn) of each fish was calculated. We infected 1 individual per group ('source' fish) with Gyrodactyus turnbulli and counted parasites on each fish every other day for 10 days. Epidemic parameters for each population were analysed using generalized linear models. High host Kn-particularly that of the 'source' fish-exerted a positive effect on incidence, peak parasite burden, and the degree of parasite aggregation. Low food availability increased the strength of the associations with peak burden and aggregation. Our findings suggest that host Kn and food availability interact to influence epidemic dynamics, and that the condition of the individual that brings the parasite into the host population has a profound impact on the spread of infection.

Policy choices in dementia care-An exploratory analysis of the Alberta continuing care system (ACCS) using system dynamics.

PubMed

Cepoiu-Martin, Monica; Bischak, Diane P

2018-02-01

The increase in the incidence of dementia in the aging population and the decrease in the availability of informal caregivers put pressure on continuing care systems to care for a growing number of people with disabilities. Policy changes in the continuing care system need to address this shift in the population structure. One of the most effective tools for assessing policies in complex systems is system dynamics. Nevertheless, this method is underused in continuing care capacity planning. A system dynamics model of the Alberta Continuing Care System was developed using stylized data. Sensitivity analyses and policy evaluations were conducted to demonstrate the use of system dynamics modelling in this area of public health planning. We focused our policy exploration on introducing staff/resident benchmarks in both supportive living and long-term care (LTC). The sensitivity analyses presented in this paper help identify leverage points in the system that need to be acknowledged when policy decisions are made. Our policy explorations showed that the deficits of staff increase dramatically when benchmarks are introduced, as expected, but at the end of the simulation period, the difference in deficits of both nurses and health care aids are similar between the 2 scenarios tested. Modifying the benchmarks in LTC only versus in both supportive living and LTC has similar effects on staff deficits in long term, under the assumptions of this particular model. The continuing care system dynamics model can be used to test various policy scenarios, allowing decision makers to visualize the effect of a certain policy choice on different system variables and to compare different policy options. Our exploration illustrates the use of system dynamics models for policy making in complex health care systems. © 2017 John Wiley & Sons, Ltd.

Memory and obesity affect the population dynamics of asexual freshwater planarians

NASA Astrophysics Data System (ADS)

Dunkel, Jörn; Talbot, Jared; Schötz, Eva-Maria

2011-04-01

Asexual reproduction in multicellular organisms is a complex biophysical process that is not yet well understood quantitatively. Here, we report a detailed population study for the asexual freshwater planarian Schmidtea mediterranea, which can reproduce via transverse fission due to a large stem cell contingent. Our long-term observations of isolated non-interacting planarian populations reveal that the characteristic fission waiting time distributions for head and tail fragments differ significantly from each other. The stochastic fission dynamics of tail fragments exhibits non-negligible memory effects, implying that an accurate mathematical description of future data should be based on non-Markovian tree models. By comparing the effective growth of non-interacting planarian populations with those of self-interacting populations, we are able to quantify the influence of interactions between flatworms and physical conditions on the population growth. A surprising result is the non-monotonic relationship between effective population growth rate and nutrient supply: planarians exhibit a tendency to become 'obese' if the feeding frequency exceeds a critical level, resulting in a decreased reproduction activity. This suggests that these flatworms, which possess many genes homologous to those of humans, could become a new model system for studying dietary effects on reproduction and regeneration in multicellular organisms.

Dynamic social networks based on movement

USGS Publications Warehouse

Scharf, Henry; Hooten, Mevin B.; Fosdick, Bailey K.; Johnson, Devin S.; London, Joshua M.; Durban, John W.

2016-01-01

Network modeling techniques provide a means for quantifying social structure in populations of individuals. Data used to define social connectivity are often expensive to collect and based on case-specific, ad hoc criteria. Moreover, in applications involving animal social networks, collection of these data is often opportunistic and can be invasive. Frequently, the social network of interest for a given population is closely related to the way individuals move. Thus, telemetry data, which are minimally invasive and relatively inexpensive to collect, present an alternative source of information. We develop a framework for using telemetry data to infer social relationships among animals. To achieve this, we propose a Bayesian hierarchical model with an underlying dynamic social network controlling movement of individuals via two mechanisms: an attractive effect and an aligning effect. We demonstrate the model and its ability to accurately identify complex social behavior in simulation, and apply our model to telemetry data arising from killer whales. Using auxiliary information about the study population, we investigate model validity and find the inferred dynamic social network is consistent with killer whale ecology and expert knowledge.

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.

Asia on the move: research challenges for population geography.

PubMed

Hugo, G

1996-06-01

This paper "summarises some of the major changes which have occurred in international migration to, from, and within Asia in the last two decades....A number of theoretical challenges are put forward regarding the complex interrelationships between international population movements, economic development and social change. The employment of systems approaches, neoclassical economic theory, social networks and institutional approaches, and the potential role of population geography in developing a more comprehensive explanation of the changing dynamics of international migration in the region, are discussed. Also considered are the gender dimension in migration, remittance flows and their consequences, and policy issues." excerpt

Capture-recapture methodology

USGS Publications Warehouse

Gould, William R.; Kendall, William L.

2013-01-01

Capture-recapture methods were initially developed to estimate human population abundance, but since that time have seen widespread use for fish and wildlife populations to estimate and model various parameters of population, metapopulation, and disease dynamics. Repeated sampling of marked animals provides information for estimating abundance and tracking the fate of individuals in the face of imperfect detection. Mark types have evolved from clipping or tagging to use of noninvasive methods such as photography of natural markings and DNA collection from feces. Survival estimation has been emphasized more recently as have transition probabilities between life history states and/or geographical locations, even where some states are unobservable or uncertain. Sophisticated software has been developed to handle highly parameterized models, including environmental and individual covariates, to conduct model selection, and to employ various estimation approaches such as maximum likelihood and Bayesian approaches. With these user-friendly tools, complex statistical models for studying population dynamics have been made available to ecologists. The future will include a continuing trend toward integrating data types, both for tagged and untagged individuals, to produce more precise and robust population models.

A high-resolution genetic signature of demographic and spatial expansion in epizootic rabies virus

PubMed Central

Biek, Roman; Henderson, J. Caroline; Waller, Lance A.; Rupprecht, Charles E.; Real, Leslie A.

2007-01-01

Emerging pathogens potentially undergo rapid evolution while expanding in population size and geographic range during the course of invasion, yet it is generally difficult to demonstrate how these processes interact. Our analysis of a 30-yr data set covering a large-scale rabies virus outbreak among North American raccoons reveals the long lasting effect of the initial infection wave in determining how viral populations are genetically structured in space. We further find that coalescent-based estimates derived from the genetic data yielded an amazingly accurate reconstruction of the known spatial and demographic dynamics of the virus over time. Our study demonstrates the combined evolutionary and population dynamic processes characterizing the spread of pathogen after its introduction into a fully susceptible host population. Furthermore, the results provide important insights regarding the spatial scale of rabies persistence and validate the use of coalescent approaches for uncovering even relatively complex population histories. Such approaches will be of increasing relevance for understanding the epidemiology of emerging zoonotic diseases in a landscape context. PMID:17470818

Disentangling polydispersity in the PCNA−p15PAF complex, a disordered, transient and multivalent macromolecular assembly

PubMed Central

Cordeiro, Tiago N.; Chen, Po-chia; De Biasio, Alfredo; Sibille, Nathalie; Blanco, Francisco J.; Hub, Jochen S.; Crehuet, Ramon

2017-01-01

Abstract The intrinsically disordered p15PAF regulates DNA replication and repair when interacting with the Proliferating Cell Nuclear Antigen (PCNA) sliding clamp. As many interactions between disordered proteins and globular partners involved in signaling and regulation, the complex between p15PAF and trimeric PCNA is of low affinity, forming a transient complex that is difficult to characterize at a structural level due to its inherent polydispersity. We have determined the structure, conformational fluctuations, and relative population of the five species that coexist in solution by combining small-angle X-ray scattering (SAXS) with molecular modelling. By using explicit ensemble descriptions for the individual species, built using integrative approaches and molecular dynamics (MD) simulations, we collectively interpreted multiple SAXS profiles as population-weighted thermodynamic mixtures. The analysis demonstrates that the N-terminus of p15PAF penetrates the PCNA ring and emerges on the back face. This observation substantiates the role of p15PAF as a drag regulating PCNA processivity during DNA repair. Our study reveals the power of ensemble-based approaches to decode structural, dynamic, and thermodynamic information from SAXS data. This strategy paves the way for deciphering the structural bases of flexible, transient and multivalent macromolecular assemblies involved in pivotal biological processes. PMID:28180305

Ecophysiology meets conservation: understanding the role of disease in amphibian population declines

PubMed Central

Blaustein, Andrew R.; Gervasi, Stephanie S.; Johnson, Pieter T. J.; Hoverman, Jason T.; Belden, Lisa K.; Bradley, Paul W.; Xie, Gisselle Y.

2012-01-01

Infectious diseases are intimately associated with the dynamics of biodiversity. However, the role that infectious disease plays within ecological communities is complex. The complex effects of infectious disease at the scale of communities and ecosystems are driven by the interaction between host and pathogen. Whether or not a given host–pathogen interaction results in progression from infection to disease is largely dependent on the physiological characteristics of the host within the context of the external environment. Here, we highlight the importance of understanding the outcome of infection and disease in the context of host ecophysiology using amphibians as a model system. Amphibians are ideal for such a discussion because many of their populations are experiencing declines and extinctions, with disease as an important factor implicated in many declines and extinctions. Exposure to pathogens and the host's responses to infection can be influenced by many factors related to physiology such as host life history, immunology, endocrinology, resource acquisition, behaviour and changing climates. In our review, we discuss the relationship between disease and biodiversity. We highlight the dynamics of three amphibian host–pathogen systems that induce different effects on hosts and life stages and illustrate the complexity of amphibian–host–parasite systems. We then review links between environmental stress, endocrine–immune interactions, disease and climate change. PMID:22566676

Tigers in the Terai: Strong evidence for meta-population dynamics contributing to tiger recovery and conservation in the Terai Arc Landscape.

PubMed

Thapa, Kanchan; Wikramanayake, Eric; Malla, Sabita; Acharya, Krishna Prasad; Lamichhane, Babu Ram; Subedi, Naresh; Pokharel, Chiranjivi Prasad; Thapa, Gokarna Jung; Dhakal, Maheshwar; Bista, Ashish; Borah, Jimmy; Gupta, Mudit; Maurya, Kamlesh K; Gurung, Ghana Shyam; Jnawali, Shant Raj; Pradhan, Narendra Man Babu; Bhata, Shiv Raj; Koirala, Saroj; Ghose, Dipankar; Vattakaven, Joseph

2017-01-01

The source populations of tigers are mostly confined to protected areas, which are now becoming isolated. A landscape scale conservation strategy should strive to facilitate dispersal and survival of dispersing tigers by managing habitat corridors that enable tigers to traverse the matrix with minimal conflict. We present evidence for tiger dispersal along transboundary protected areas complexes in the Terai Arc Landscape, a priority tiger landscape in Nepal and India, by comparing camera trap data, and through population models applied to the long term camera trap data sets. The former showed that 11 individual tigers used the corridors that connected the transboundary protected areas. The estimated population growth rates using the minimum observed population size in two protected areas in Nepal, Bardia National Park and Suklaphanta National Park showed that the increases were higher than expected from growth rates due to in situ reproduction alone. These lines of evidence suggests that tigers are recolonizing Nepal's protected areas from India, after a period of population decline, and that the tiger populations in the transboundary protected areas complexes may be maintained as meta-population. Our results demonstrate the importance of adopting a landscape-scale approach to tiger conservation, especially to improve population recovery and long term population persistence.

Tigers in the Terai: Strong evidence for meta-population dynamics contributing to tiger recovery and conservation in the Terai Arc Landscape

PubMed Central

Wikramanayake, Eric; Malla, Sabita; Acharya, Krishna Prasad; Lamichhane, Babu Ram; Subedi, Naresh; Pokharel, Chiranjivi Prasad; Thapa, Gokarna Jung; Dhakal, Maheshwar; Bista, Ashish; Borah, Jimmy; Gupta, Mudit; Maurya, Kamlesh K.; Gurung, Ghana Shyam; Jnawali, Shant Raj; Pradhan, Narendra Man Babu; Bhata, Shiv Raj; Koirala, Saroj; Ghose, Dipankar; Vattakaven, Joseph

2017-01-01

The source populations of tigers are mostly confined to protected areas, which are now becoming isolated. A landscape scale conservation strategy should strive to facilitate dispersal and survival of dispersing tigers by managing habitat corridors that enable tigers to traverse the matrix with minimal conflict. We present evidence for tiger dispersal along transboundary protected areas complexes in the Terai Arc Landscape, a priority tiger landscape in Nepal and India, by comparing camera trap data, and through population models applied to the long term camera trap data sets. The former showed that 11 individual tigers used the corridors that connected the transboundary protected areas. The estimated population growth rates using the minimum observed population size in two protected areas in Nepal, Bardia National Park and Suklaphanta National Park showed that the increases were higher than expected from growth rates due to in situ reproduction alone. These lines of evidence suggests that tigers are recolonizing Nepal’s protected areas from India, after a period of population decline, and that the tiger populations in the transboundary protected areas complexes may be maintained as meta-population. Our results demonstrate the importance of adopting a landscape-scale approach to tiger conservation, especially to improve population recovery and long term population persistence. PMID:28591175

How spatio-temporal habitat connectivity affects amphibian genetic structure

PubMed Central

Watts, Alexander G.; Schlichting, Peter E.; Billerman, Shawn M.; Jesmer, Brett R.; Micheletti, Steven; Fortin, Marie-Josée; Funk, W. Chris; Hapeman, Paul; Muths, Erin; Murphy, Melanie A.

2015-01-01

Heterogeneous landscapes and fluctuating environmental conditions can affect species dispersal, population genetics, and genetic structure, yet understanding how biotic and abiotic factors affect population dynamics in a fluctuating environment is critical for species management. We evaluated how spatio-temporal habitat connectivity influences dispersal and genetic structure in a population of boreal chorus frogs (Pseudacris maculata) using a landscape genetics approach. We developed gravity models to assess the contribution of various factors to the observed genetic distance as a measure of functional connectivity. We selected (a) wetland (within-site) and (b) landscape matrix (between-site) characteristics; and (c) wetland connectivity metrics using a unique methodology. Specifically, we developed three networks that quantify wetland connectivity based on: (i) P. maculata dispersal ability, (ii) temporal variation in wetland quality, and (iii) contribution of wetland stepping-stones to frog dispersal. We examined 18 wetlands in Colorado, and quantified 12 microsatellite loci from 322 individual frogs. We found that genetic connectivity was related to topographic complexity, within- and between-wetland differences in moisture, and wetland functional connectivity as contributed by stepping-stone wetlands. Our results highlight the role that dynamic environmental factors have on dispersal-limited species and illustrate how complex asynchronous interactions contribute to the structure of spatially-explicit metapopulations. PMID:26442094

Dissemination, Implementation, and Improvement Science Research in Population Health: Opportunities for Public Health and CTSAs.

PubMed

Kuo, Tony; Gase, Lauren N; Inkelas, Moira

2015-12-01

The complex, dynamic nature of health systems requires dissemination, implementation, and improvement (DII) sciences to effectively translate emerging knowledge into practice. Although they hold great promise for informing multisector policies and system-level changes, these methods are often not strategically used by public health. More than 120 stakeholders from Southern California, including the community, federal and local government, university, and health services were convened to identify key priorities and opportunities for public health departments and Clinical and Translational Science Awards programs (CTSAs) to advance DII sciences in population health. Participants identified challenges (mismatch of practice realities with narrowly focused research questions; lack of iterative learning) and solutions (using methods that fit the dynamic nature of the real world; aligning theories of change across sectors) for applying DII science research to public health problems. Pragmatic steps that public health and CTSAs can take to facilitate DII science research include: employing appropriate study designs; training scientists and practicing professionals in these methods; securing resources to advance this work; and supporting team science to solve complex-systems issues. Public health and CTSAs represent a unique model of practice for advancing DII research in population health. The partnership can inform policy and program development in local communities. © 2015 Wiley Periodicals, Inc.

How spatio-temporal habitat connectivity affects amphibian genetic structure

USGS Publications Warehouse

Watts, Alexander G.; Schlichting, P; Billerman, S; Jesmer, B; Micheletti, S; Fortin, M.-J.; Funk, W.C.; Hapeman, P; Muths, Erin L.; Murphy, M.A.

2015-01-01

Heterogeneous landscapes and fluctuating environmental conditions can affect species dispersal, population genetics, and genetic structure, yet understanding how biotic and abiotic factors affect population dynamics in a fluctuating environment is critical for species management. We evaluated how spatio-temporal habitat connectivity influences dispersal and genetic structure in a population of boreal chorus frogs (Pseudacris maculata) using a landscape genetics approach. We developed gravity models to assess the contribution of various factors to the observed genetic distance as a measure of functional connectivity. We selected (a) wetland (within-site) and (b) landscape matrix (between-site) characteristics; and (c) wetland connectivity metrics using a unique methodology. Specifically, we developed three networks that quantify wetland connectivity based on: (i) P. maculata dispersal ability, (ii) temporal variation in wetland quality, and (iii) contribution of wetland stepping-stones to frog dispersal. We examined 18 wetlands in Colorado, and quantified 12 microsatellite loci from 322 individual frogs. We found that genetic connectivity was related to topographic complexity, within- and between-wetland differences in moisture, and wetland functional connectivity as contributed by stepping-stone wetlands. Our results highlight the role that dynamic environmental factors have on dispersal-limited species and illustrate how complex asynchronous interactions contribute to the structure of spatially-explicit metapopulations.

Caring for Student-Athletes following a Concussion

ERIC Educational Resources Information Center

Piebes, Sarah K.; Gourley, Meganne; Valovich McLeod, Tamara C.

2009-01-01

The school nurse plays a dynamic role in the care and treatment of a concussed athlete. Concussions in the adolescent populations are of special concern due to their potential impact on mental development and cognitive function, as well as an increased risk of serious complications including second impact syndrome. The complexity of a concussion…

EVALUATING EFFECTS OF LOW QUALITY HABITATS ON REGIONAL GROWTH IN PEOMYCUS LEUCOPUS: INSIGHTS FROM FIELD-PARAMETERIZED SPATIAL MATRIX MODELS.

EPA Science Inventory

Due to complex population dynamics and source-sink metapopulation processes, animal fitness sometimes varies across landscapes in ways that cannot be deduced from simple density patterns. In this study, we examine spatial patterns in fitness using a combination of intensive fiel...

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

Gentry, T.; Schadt, C.; Zhou, J.

Microarray technology has the unparalleled potential tosimultaneously determine the dynamics and/or activities of most, if notall, of the microbial populations in complex environments such as soilsand sediments. Researchers have developed several types of arrays thatcharacterize the microbial populations in these samples based on theirphylogenetic relatedness or functional genomic content. Several recentstudies have used these microarrays to investigate ecological issues;however, most have only analyzed a limited number of samples withrelatively few experiments utilizing the full high-throughput potentialof microarray analysis. This is due in part to the unique analyticalchallenges that these samples present with regard to sensitivity,specificity, quantitation, and data analysis. Thismore » review discussesspecific applications of microarrays to microbial ecology research alongwith some of the latest studies addressing the difficulties encounteredduring analysis of complex microbial communities within environmentalsamples. With continued development, microarray technology may ultimatelyachieve its potential for comprehensive, high-throughput characterizationof microbial populations in near real-time.« less

Response of single bacterial cells to stress gives rise to complex history dependence at the population level

PubMed Central

Mathis, Roland; Ackermann, Martin

2016-01-01

Most bacteria live in ever-changing environments where periods of stress are common. One fundamental question is whether individual bacterial cells have an increased tolerance to stress if they recently have been exposed to lower levels of the same stressor. To address this question, we worked with the bacterium Caulobacter crescentus and asked whether exposure to a moderate concentration of sodium chloride would affect survival during later exposure to a higher concentration. We found that the effects measured at the population level depended in a surprising and complex way on the time interval between the two exposure events: The effect of the first exposure on survival of the second exposure was positive for some time intervals but negative for others. We hypothesized that the complex pattern of history dependence at the population level was a consequence of the responses of individual cells to sodium chloride that we observed: (i) exposure to moderate concentrations of sodium chloride caused delays in cell division and led to cell-cycle synchronization, and (ii) whether a bacterium would survive subsequent exposure to higher concentrations was dependent on the cell-cycle state. Using computational modeling, we demonstrated that indeed the combination of these two effects could explain the complex patterns of history dependence observed at the population level. Our insight into how the behavior of single cells scales up to processes at the population level provides a perspective on how organisms operate in dynamic environments with fluctuating stress exposure. PMID:26960998

Thaumarchaeal amoA and nirK Gene Abundance Patterns Reveal Spatiotemporal Dynamics of Ammonia-oxidizing Archaeal Populations in Monterey Bay, CA

NASA Astrophysics Data System (ADS)

Tolar, B. B.; Reji, L.; Smith, J. M.; Chavez, F.; Francis, C.

2016-12-01

Thaumarchaeaota are among the most abundant microorganisms on the planet, and are significant players in the global nitrogen cycle. All cultivated members of the phylum are capable of performing the first and rate-limiting step of nitrification - the aerobic oxidation of ammonia to nitrite. In marine environments, ammonia-oxidizing archaea (AOA) have been found to greatly outnumber their bacterial counterparts. However, much about their ecology remains largely unknown. Monterey Bay, a non-estuarine embayment on the central California coast, is an ideal site for studying the dynamics of natural thaumarchaeal assemblages, given the highly dynamic nature of the Bay waters with seasonal upwelling episodes and the associated steep gradients in environmental variables. In the present study, we examined thaumarchaeal population dynamics in the upper Monterey Bay water column (0-500 m) using multiple molecular markers. Following high-resolution spatiotemporal sampling (i.e., up to 10 depths sampled monthly over a period of 2 years) at two stations in the Bay, we quantified thaumarchaeal functional genes - the ammonia monooxygenase (amoA) gene and its `shallow' and `deep' marine ecotypes, and variants of the marine nitrite reductase (nirK) gene. The abundances of both genes were regressed against environmental variables to gain insights into factors shaping their spatiotemporal dynamics in the Bay. Gene abundances at both stations varied with depth and season, with winter months generally having several orders of magnitude greater abundances. Statistical analyses point to differential controls on the gene abundances, with depth and temperature potentially being the major environmental determinants of thaumarchaeal population size. Our results also highlight the importance of employing multiple marker genes to gain a more highly resolved picture of thaumarchaeal population dynamics in complex environmental systems such as the coastal ocean.

Invasion complexity at large spatial scales is an emergent property of interactions among landscape characteristics and invader traits

PubMed Central

Jordan, Nicholas R.; Forester, James D.

2018-01-01

Invasion potential should be part of the evaluation of candidate species for any species introduction. However, estimating invasion risks remains a challenging problem, particularly in complex landscapes. Certain plant traits are generally considered to increase invasive potential and there is an understanding that landscapes influence invasions dynamics, but little research has been done to explore how those drivers of invasions interact. We evaluate the relative roles of, and potential interactions between, plant invasiveness traits and landscape characteristics on invasions with a case study using a model parameterized for the potentially invasive biomass crop, Miscanthus × giganteus. Using that model we simulate invasions on 1000 real landscapes to evaluate how landscape characteristics, including both composition and spatial structure, affect invasion outcomes. We conducted replicate simulations with differing strengths of plant invasiveness traits (dispersal ability, establishment ability, population growth rate, and the ability to utilize dispersal corridors) to evaluate how the importance of landscape characteristics for predicting invasion patterns changes depending on the invader details. Analysis of simulations showed that the presence of highly suitable habitat (e.g., grasslands) is generally the strongest determinant of invasion dynamics but that there are also more subtle interactions between landscapes and invader traits. These effects can also vary between different aspects of invasion dynamics (short vs. long time scales and population size vs. spatial extent). These results illustrate that invasions are complex emergent processes with multiple drivers and effective management needs to reflect the ecology of the species of interest and the particular goals or risks for which efforts need to be optimized. PMID:29771923

Dynamics of newly established elk populations

USGS Publications Warehouse

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

2007-01-01

The dynamics of newly established elk (Cervus elaphus) populations can provide insights about maximum sustainable rates of reproduction, survival, and increase. However, data used to estimate rates of increase typically have been limited to counts and rarely have included complementary estimates of vital rates. Complexities of population dynamics cannot be understood without considering population processes as well as population states. We estimated pregnancy rates, survival rates, age ratios, and sex ratios for reintroduced elk at Theodore Roosevelt National Park, North Dakota, USA; combined vital rates in a population projection model; and compared model projections with observed elk numbers and population ratios. Pregnancy rates in January (early in the second trimester of pregnancy) averaged 54.1% (SE = 5.4%) for subadults and 91.0% (SE = 1.7%) for adults, and 91.6% of pregnancies resulted in recruitment at 8 months. Annual survival rates of adult females averaged 0.96 (95% CI = 0.94-0.98) with hunting included and 0.99 (95% CI = 0.97-0.99) with hunting excluded from calculations. Our fitted model explained 99.8% of past variation in population estimates and represents a useful new tool for short-term management planning. Although we found no evidence of temporal variation in vital rates, variation in population composition caused substantial variation in projected rates of increase (??=1.20-1.36). Restoring documented hunter harvests and removals of elk by the National Park Service led to a potential rate of ?? = 1.26. Greater rates of increase substantiated elsewhere were within the expected range of chance variation, given our model and estimates of vital rates. Rates of increase realized by small elk populations are too variable to support inferences about habitat quality or density dependence.

Mixed-mode oscillations and population bursting in the pre-Bötzinger complex

PubMed Central

Bacak, Bartholomew J; Kim, Taegyo; Smith, Jeffrey C; Rubin, Jonathan E; Rybak, Ilya A

2016-01-01

This study focuses on computational and theoretical investigations of neuronal activity arising in the pre-Bötzinger complex (pre-BötC), a medullary region generating the inspiratory phase of breathing in mammals. A progressive increase of neuronal excitability in medullary slices containing the pre-BötC produces mixed-mode oscillations (MMOs) characterized by large amplitude population bursts alternating with a series of small amplitude bursts. Using two different computational models, we demonstrate that MMOs emerge within a heterogeneous excitatory neural network because of progressive neuronal recruitment and synchronization. The MMO pattern depends on the distributed neuronal excitability, the density and weights of network interconnections, and the cellular properties underlying endogenous bursting. Critically, the latter should provide a reduction of spiking frequency within neuronal bursts with increasing burst frequency and a dependence of the after-burst recovery period on burst amplitude. Our study highlights a novel mechanism by which heterogeneity naturally leads to complex dynamics in rhythmic neuronal populations. DOI: http://dx.doi.org/10.7554/eLife.13403.001 PMID:26974345

Modeling dynamic interactions and coherence between marine zooplankton and fishes linked to environmental variability

NASA Astrophysics Data System (ADS)

Liu, Hui; Fogarty, Michael J.; Hare, Jonathan A.; Hsieh, Chih-hao; Glaser, Sarah M.; Ye, Hao; Deyle, Ethan; Sugihara, George

2014-03-01

The dynamics of marine fishes are closely related to lower trophic levels and the environment. Quantitatively understanding ecosystem dynamics linking environmental variability and prey resources to exploited fishes is crucial for ecosystem-based management of marine living resources. However, standard statistical models typically grounded in the concept of linear system may fail to capture the complexity of ecological processes. We have attempted to model ecosystem dynamics using a flexible, nonparametric class of nonlinear forecasting models. We analyzed annual time series of four environmental indices, 22 marine copepod taxa, and four ecologically and commercially important fish species during 1977 to 2009 on Georges Bank, a highly productive and intensively studied area of the northeast U.S. continental shelf ecosystem. We examined the underlying dynamic features of environmental indices and copepods, quantified the dynamic interactions and coherence with fishes, and explored the potential control mechanisms of ecosystem dynamics from a nonlinear perspective. We found: (1) the dynamics of marine copepods and environmental indices exhibiting clear nonlinearity; (2) little evidence of complex dynamics across taxonomic levels of copepods; (3) strong dynamic interactions and coherence between copepods and fishes; and (4) the bottom-up forcing of fishes and top-down control of copepods coexisting as target trophic levels vary. These findings highlight the nonlinear interactions among ecosystem components and the importance of marine zooplankton to fish populations which point to two forcing mechanisms likely interactively regulating the ecosystem dynamics on Georges Bank under a changing environment.

Quantifying humpback whale song sequences to understand the dynamics of song exchange at the ocean basin scale.

PubMed

Garland, Ellen C; Noad, Michael J; Goldizen, Anne W; Lilley, Matthew S; Rekdahl, Melinda L; Garrigue, Claire; Constantine, Rochelle; Daeschler Hauser, Nan; Poole, M Michael; Robbins, Jooke

2013-01-01

Humpback whales have a continually evolving vocal sexual display, or "song," that appears to undergo both evolutionary and "revolutionary" change. All males within a population adhere to the current content and arrangement of the song. Populations within an ocean basin share similarities in their songs; this sharing is complex as multiple variations of the song (song types) may be present within a region at any one time. To quantitatively investigate the similarity of song types, songs were compared at both the individual singer and population level using the Levenshtein distance technique and cluster analysis. The highly stereotyped sequences of themes from the songs of 211 individuals from populations within the western and central South Pacific region from 1998 through 2008 were grouped together based on the percentage of song similarity, and compared to qualitatively assigned song types. The analysis produced clusters of highly similar songs that agreed with previous qualitative assignments. Each cluster contained songs from multiple populations and years, confirming the eastward spread of song types and their progressive evolution through the study region. Quantifying song similarity and exchange will assist in understanding broader song dynamics and contribute to the use of vocal displays as population identifiers.

Nutrition, fertility and steady-state population dynamics in a pre-industrial community in Penrith, northern England.

PubMed

Scott, S; Duncan, C J

1999-10-01

The effect of nutrition on fertility and its contribution thereby to population dynamics are assessed in three social groups (elite, tradesmen and subsistence) in a marginal, pre-industrial population in northern England. This community was particularly susceptible to fluctuations in the price of grains, which formed their basic foodstuff. The subsistence class, who formed the largest part of the population, had low levels of fertility and small family sizes, but women from all social groups had a characteristic and marked subfecundity in the early part of their reproductive lives. The health and nutrition of the mother during pregnancy was the most important factor in determining fertility and neonatal mortality. Inadequate nutrition had many subtle effects on reproduction which interacted to produce a complex web of events. A population boom occurred during the second half of the 18th century; fertility did not change but there was a marked improvement in infant mortality and it is suggested that the steadily improving nutritional standards of the population, particularly during crucial periods in pregnancy (i.e. the last trimester), probably made the biggest contribution to the improvement in infant mortality and so was probably the major factor in triggering the boom.

Parallel paleogenomic transects reveal complex genetic history of early European farmers

PubMed Central

Lipson, Mark; Szécsényi-Nagy, Anna; Mallick, Swapan; Pósa, Annamária; Stégmár, Balázs; Keerl, Victoria; Rohland, Nadin; Stewardson, Kristin; Ferry, Matthew; Michel, Megan; Oppenheimer, Jonas; Broomandkhoshbacht, Nasreen; Harney, Eadaoin; Nordenfelt, Susanne; Llamas, Bastien; Mende, Balázs Gusztáv; Köhler, Kitti; Oross, Krisztián; Bondár, Mária; Marton, Tibor; Osztás, Anett; Jakucs, János; Paluch, Tibor; Horváth, Ferenc; Csengeri, Piroska; Koós, Judit; Sebők, Katalin; Anders, Alexandra; Raczky, Pál; Regenye, Judit; Barna, Judit P.; Fábián, Szilvia; Serlegi, Gábor; Toldi, Zoltán; Nagy, Emese Gyöngyvér; Dani, János; Molnár, Erika; Pálfi, György; Márk, László; Melegh, Béla; Bánfai, Zsolt; Domboróczki, László; Fernández-Eraso, Javier; Mujika-Alustiza, José Antonio; Fernández, Carmen Alonso; Echevarría, Javier Jiménez; Bollongino, Ruth; Orschiedt, Jörg; Schierhold, Kerstin; Meller, Harald; Cooper, Alan; Burger, Joachim; Bánffy, Eszter; Alt, Kurt W.; Lalueza-Fox, Carles; Haak, Wolfgang; Reich, David

2017-01-01

Ancient DNA studies have established that Neolithic European populations were descended from Anatolian migrants1–8 who received a limited amount of admixture from resident hunter-gatherers3–5,9. Many open questions remain, however, about the spatial and temporal dynamics of population interactions and admixture during the Neolithic period. Using the highest-resolution genome-wide ancient DNA data set assembled to date—a total of 180 samples, 130 newly reported here, from the Neolithic and Chalcolithic of Hungary (6000–2900 BCE, n = 100), Germany (5500–3000 BCE, n = 42), and Spain (5500–2200 BCE, n = 38)—we investigate the population dynamics of Neolithization across Europe. We find that genetic diversity was shaped predominantly by local processes, with varied sources and proportions of hunter-gatherer ancestry among the three regions and through time. Admixture between groups with different ancestry profiles was pervasive and resulted in observable population transformation across almost all cultural transitions. Our results shed new light on the ways that gene flow reshaped European populations throughout the Neolithic period and demonstrate the potential of time-series-based sampling and modeling approaches to elucidate multiple dimensions of historical population interactions. PMID:29144465

Quantifying selection in evolving populations using time-resolved genetic data

NASA Astrophysics Data System (ADS)

Illingworth, Christopher J. R.; Mustonen, Ville

2013-01-01

Methods which uncover the molecular basis of the adaptive evolution of a population address some important biological questions. For example, the problem of identifying genetic variants which underlie drug resistance, a question of importance for the treatment of pathogens, and of cancer, can be understood as a matter of inferring selection. One difficulty in the inference of variants under positive selection is the potential complexity of the underlying evolutionary dynamics, which may involve an interplay between several contributing processes, including mutation, recombination and genetic drift. A source of progress may be found in modern sequencing technologies, which confer an increasing ability to gather information about evolving populations, granting a window into these complex processes. One particularly interesting development is the ability to follow evolution as it happens, by whole-genome sequencing of an evolving population at multiple time points. We here discuss how to use time-resolved sequence data to draw inferences about the evolutionary dynamics of a population under study. We begin by reviewing our earlier analysis of a yeast selection experiment, in which we used a deterministic evolutionary framework to identify alleles under selection for heat tolerance, and to quantify the selection acting upon them. Considering further the use of advanced intercross lines to measure selection, we here extend this framework to cover scenarios of simultaneous recombination and selection, and of two driver alleles with multiple linked neutral, or passenger, alleles, where the driver pair evolves under an epistatic fitness landscape. We conclude by discussing the limitations of the approach presented and outlining future challenges for such methodologies.

Controlling range expansion in habitat networks by adaptively targeting source populations.

PubMed

Hock, Karlo; Wolff, Nicholas H; Beeden, Roger; Hoey, Jessica; Condie, Scott A; Anthony, Kenneth R N; Possingham, Hugh P; Mumby, Peter J

2016-08-01

Controlling the spread of invasive species, pests, and pathogens is often logistically limited to interventions that target specific locations at specific periods. However, in complex, highly connected systems, such as marine environments connected by ocean currents, populations spread dynamically in both space and time via transient connectivity links. This results in nondeterministic future distributions of species in which local populations emerge dynamically and concurrently over a large area. The challenge, therefore, is to choose intervention locations that will maximize the effectiveness of the control efforts. We propose a novel method to manage dynamic species invasions and outbreaks that identifies the intervention locations most likely to curtail population expansion by selectively targeting local populations most likely to expand their future range. Critically, at any point during the development of the invasion or outbreak, the method identifies the local intervention that maximizes the long-term benefit across the ecosystem by restricting species' potential to spread. In so doing, the method adaptively selects the intervention targets under dynamically changing circumstances. To illustrate the effectiveness of the method we applied it to controlling the spread of crown-of-thorns starfish (Acanthaster sp.) outbreaks across Australia's Great Barrier Reef. Application of our method resulted in an 18-fold relative improvement in management outcomes compared with a random targeting of reefs in putative starfish control scenarios. Although we focused on applying the method to reducing the spread of an unwanted species, it can also be used to facilitate the spread of desirable species through connectivity networks. For example, the method could be used to select those fragments of habitat most likely to rebuild a population if they were sufficiently well protected. © 2016 Society for Conservation Biology.

Optimal control applied to a model for species augmentation.

PubMed

Bodine, Erin N; Gross, Louis J; Lenhart, Suzanne

2008-10-01

Species augmentation is a method of reducing species loss via augmenting declining or threatened populations with individuals from captive-bred or stable, wild populations. In this paper, we develop a differential equations model and optimal control formulation for a continuous time augmentation of a general declining population. We find a characterization for the optimal control and show numerical results for scenarios of different illustrative parameter sets. The numerical results provide considerably more detail about the exact dynamics of optimal augmentation than can be readily intuited. The work and results presented in this paper are a first step toward building a general theory of population augmentation, which accounts for the complexities inherent in many conservation biology applications.

Understanding the contribution of habitats and regional variation to long-term population trends in tricolored blackbirds

PubMed Central

Graves, Emily E; Holyoak, Marcel; Rodd Kelsey, T; Meese, Robert J

2013-01-01

Population trends represent a minimum amount of information required to assess the conservation status of a species. However, understanding and detecting trends can be complicated by variation among habitats and regions, and by dispersal connecting habitats through source-sink dynamics. We analyzed trends in breeding populations between habitats and regions to better understand the overall dynamics of a species' decline. Specifically, we analyzed historical trends in breeding populations of tricolored blackbirds (Agelaius tricolor) using breeding records from 1907 to 2009. The species breeds itinerantly and ephemerally uses multiple habitat types and breeding areas, which make interpretation of trends complex. We found overall abundance declines of 63% between 1935 and 1975. Since 1980 overall declines became nonsignificant and obscure despite large amounts of data from 1980 to 2009. Temporal trends differed between breeding habitat types and were associated with regional differences in population declines. A new habitat, triticale crops (a wheat-rye hybrid grain) produced colonies 40× larger, on average, than other breeding habitats, and contributed to a change in regional distribution since it primarily occurred in a single region. The mechanism for such an effect is not clear, but could represent the local availability of foodstuffs in the landscape rather than something specific to triticale crops. While variation in trends among habitats clearly occurred, they could not easily be ascribed to source-sink dynamics, ecological traps, habitat selection or other detailed ecological mechanisms. Nonetheless, such exchanges provide valuable information to guide management of dynamic systems. PMID:24101977

Critical dynamics in population vaccinating behavior.

PubMed

Pananos, A Demetri; Bury, Thomas M; Wang, Clara; Schonfeld, Justin; Mohanty, Sharada P; Nyhan, Brendan; Salathé, Marcel; Bauch, Chris T

2017-12-26

Vaccine refusal can lead to renewed outbreaks of previously eliminated diseases and even delay global eradication. Vaccinating decisions exemplify a complex, coupled system where vaccinating behavior and disease dynamics influence one another. Such systems often exhibit critical phenomena-special dynamics close to a tipping point leading to a new dynamical regime. For instance, critical slowing down (declining rate of recovery from small perturbations) may emerge as a tipping point is approached. Here, we collected and geocoded tweets about measles-mumps-rubella vaccine and classified their sentiment using machine-learning algorithms. We also extracted data on measles-related Google searches. We find critical slowing down in the data at the level of California and the United States in the years before and after the 2014-2015 Disneyland, California measles outbreak. Critical slowing down starts growing appreciably several years before the Disneyland outbreak as vaccine uptake declines and the population approaches the tipping point. However, due to the adaptive nature of coupled behavior-disease systems, the population responds to the outbreak by moving away from the tipping point, causing "critical speeding up" whereby resilience to perturbations increases. A mathematical model of measles transmission and vaccine sentiment predicts the same qualitative patterns in the neighborhood of a tipping point to greatly reduced vaccine uptake and large epidemics. These results support the hypothesis that population vaccinating behavior near the disease elimination threshold is a critical phenomenon. Developing new analytical tools to detect these patterns in digital social data might help us identify populations at heightened risk of widespread vaccine refusal. Copyright © 2017 the Author(s). Published by PNAS.

Critical dynamics in population vaccinating behavior

PubMed Central

Pananos, A. Demetri; Bury, Thomas M.; Wang, Clara; Schonfeld, Justin; Mohanty, Sharada P.; Nyhan, Brendan; Bauch, Chris T.

2017-01-01

Vaccine refusal can lead to renewed outbreaks of previously eliminated diseases and even delay global eradication. Vaccinating decisions exemplify a complex, coupled system where vaccinating behavior and disease dynamics influence one another. Such systems often exhibit critical phenomena—special dynamics close to a tipping point leading to a new dynamical regime. For instance, critical slowing down (declining rate of recovery from small perturbations) may emerge as a tipping point is approached. Here, we collected and geocoded tweets about measles–mumps–rubella vaccine and classified their sentiment using machine-learning algorithms. We also extracted data on measles-related Google searches. We find critical slowing down in the data at the level of California and the United States in the years before and after the 2014–2015 Disneyland, California measles outbreak. Critical slowing down starts growing appreciably several years before the Disneyland outbreak as vaccine uptake declines and the population approaches the tipping point. However, due to the adaptive nature of coupled behavior–disease systems, the population responds to the outbreak by moving away from the tipping point, causing “critical speeding up” whereby resilience to perturbations increases. A mathematical model of measles transmission and vaccine sentiment predicts the same qualitative patterns in the neighborhood of a tipping point to greatly reduced vaccine uptake and large epidemics. These results support the hypothesis that population vaccinating behavior near the disease elimination threshold is a critical phenomenon. Developing new analytical tools to detect these patterns in digital social data might help us identify populations at heightened risk of widespread vaccine refusal. PMID:29229821

Decreasing stochasticity through enhanced seasonality in measles epidemics.

PubMed

Mantilla-Beniers, N B; Bjørnstad, O N; Grenfell, B T; Rohani, P

2010-05-06

Seasonal changes in the environment are known to be important drivers of population dynamics, giving rise to sustained population cycles. However, it is often difficult to measure the strength and shape of seasonal forces affecting populations. In recent years, statistical time-series methods have been applied to the incidence records of childhood infectious diseases in an attempt to estimate seasonal variation in transmission rates, as driven by the pattern of school terms. In turn, school-term forcing was used to show how susceptible influx rates affect the interepidemic period. In this paper, we document the response of measles dynamics to distinct shifts in the parameter regime using previously unexplored records of measles mortality from the early decades of the twentieth century. We describe temporal patterns of measles epidemics using spectral analysis techniques, and point out a marked decrease in birth rates over time. Changes in host demography alone do not, however, suffice to explain epidemiological transitions. By fitting the time-series susceptible-infected-recovered model to measles mortality data, we obtain estimates of seasonal transmission in different eras, and find that seasonality increased over time. This analysis supports theoretical work linking complex population dynamics and the balance between stochastic and deterministic forces as determined by the strength of seasonality.

Integrative studies of cultural evolution: crossing disciplinary boundaries to produce new insights

PubMed Central

2018-01-01

Culture evolves according to dynamics on multiple temporal scales, from individuals' minute-by-minute behaviour to millennia of cultural accumulation that give rise to population-level differences. These dynamics act on a range of entities—including behavioural sequences, ideas and artefacts as well as individuals, populations and whole species—and involve mechanisms at multiple levels, from neurons in brains to inter-population interactions. Studying such complex phenomena requires an integration of perspectives from a diverse array of fields, as well as bridging gaps between traditionally disparate areas of study. In this article, which also serves as an introduction to the current special issue, we highlight some specific respects in which the study of cultural evolution has benefited and should continue to benefit from an integrative approach. We showcase a number of pioneering studies of cultural evolution that bring together numerous disciplines. These studies illustrate the value of perspectives from different fields for understanding cultural evolution, such as cognitive science and neuroanatomy, behavioural ecology, population dynamics, and evolutionary genetics. They also underscore the importance of understanding cultural processes when interpreting research about human genetics, neuroscience, behaviour and evolution. This article is part of the theme issue ‘Bridging cultural gaps: interdisciplinary studies in human cultural evolution’. PMID:29440515

Integrative studies of cultural evolution: crossing disciplinary boundaries to produce new insights.

PubMed

Kolodny, Oren; Feldman, Marcus W; Creanza, Nicole

2018-04-05

Culture evolves according to dynamics on multiple temporal scales, from individuals' minute-by-minute behaviour to millennia of cultural accumulation that give rise to population-level differences. These dynamics act on a range of entities-including behavioural sequences, ideas and artefacts as well as individuals, populations and whole species-and involve mechanisms at multiple levels, from neurons in brains to inter-population interactions. Studying such complex phenomena requires an integration of perspectives from a diverse array of fields, as well as bridging gaps between traditionally disparate areas of study. In this article, which also serves as an introduction to the current special issue, we highlight some specific respects in which the study of cultural evolution has benefited and should continue to benefit from an integrative approach. We showcase a number of pioneering studies of cultural evolution that bring together numerous disciplines. These studies illustrate the value of perspectives from different fields for understanding cultural evolution, such as cognitive science and neuroanatomy, behavioural ecology, population dynamics, and evolutionary genetics. They also underscore the importance of understanding cultural processes when interpreting research about human genetics, neuroscience, behaviour and evolution.This article is part of the theme issue 'Bridging cultural gaps: interdisciplinary studies in human cultural evolution'. © 2018 The Author(s).

Trees Wanted—Dead or Alive! Host Selection and Population Dynamics in Tree-Killing Bark Beetles

PubMed Central

Kausrud, Kyrre L.; Grégoire, Jean-Claude; Skarpaas, Olav; Erbilgin, Nadir; Gilbert, Marius; Økland, Bjørn; Stenseth, Nils Chr.

2011-01-01

Bark beetles (Coleoptera: Curculionidae, Scolytinae) feed and breed in dead or severely weakened host trees. When their population densities are high, some species aggregate on healthy host trees so that their defences may be exhausted and the inner bark successfully colonized, killing the tree in the process. Here we investigate under what conditions participating with unrelated conspecifics in risky mass attacks on living trees is an adaptive strategy, and what this can tell us about bark beetle outbreak dynamics. We find that the outcome of individual host selection may deviate from the ideal free distribution in a way that facilitates the emergence of tree-killing (aggressive) behavior, and that any heritability on traits governing aggressiveness seems likely to exist in a state of flux or cycles consistent with variability observed in natural populations. This may have implications for how economically and ecologically important species respond to environmental changes in climate and landscape (forest) structure. The population dynamics emerging from individual behavior are complex, capable of switching between “endemic” and “epidemic” regimes spontaneously or following changes in host availability or resistance. Model predictions are compared to empirical observations, and we identify some factors determining the occurrence and self-limitation of epidemics. PMID:21647433

Wild-captive interactions and economics drive dynamics of Asian elephants in Laos.

PubMed

Maurer, Gilles; Rashford, Benjamin S; Chanthavong, Vatsana; Mulot, Baptiste; Gimenez, Olivier

2017-11-01

The interactions between wild and captive populations of Asian elephants (Elephas maximus) persist in most countries of the species distribution, notably through the reproduction between captive females and wild males. However, these complex interactions have been poorly studied, despite their relevance for conservation of this endangered species. Laos has a centuries-long tradition of raising Asian elephants. Besides being cultural icons, captive elephants are inextricably linked to economics through their work in forestry. Using an ecological-economic model, we investigated the effect of socio-economic strategies on fecundity of the Lao population whose dynamics is shaped by human practices. We demonstrated that fecundity is impacted by: i) the dynamics of the wild elephant pool through mating of captive females by wild males, and ii) the financial incentive of elephant owners to breed their animals. As a result, we expect fecundity to rise in response to increases in elephant prices. The captive population will tend towards an asymptotic limit determined by the wild pool growth rate. However, the population will tend to extinction if exports continue. Our ecological-economic approach, by accounting for economic incentives, allows us to predict new equilibria that can serve as a baseline for designing sustainable management strategies for the species.

A quantitative evaluation of a qualitative risk assessment framework: Examining the assumptions and predictions of the Productivity Susceptibility Analysis (PSA)

PubMed Central

2018-01-01

Qualitative risk assessment frameworks, such as the Productivity Susceptibility Analysis (PSA), have been developed to rapidly evaluate the risks of fishing to marine populations and prioritize management and research among species. Despite being applied to over 1,000 fish populations, and an ongoing debate about the most appropriate method to convert biological and fishery characteristics into an overall measure of risk, the assumptions and predictive capacity of these approaches have not been evaluated. Several interpretations of the PSA were mapped to a conventional age-structured fisheries dynamics model to evaluate the performance of the approach under a range of assumptions regarding exploitation rates and measures of biological risk. The results demonstrate that the underlying assumptions of these qualitative risk-based approaches are inappropriate, and the expected performance is poor for a wide range of conditions. The information required to score a fishery using a PSA-type approach is comparable to that required to populate an operating model and evaluating the population dynamics within a simulation framework. In addition to providing a more credible characterization of complex system dynamics, the operating model approach is transparent, reproducible and can evaluate alternative management strategies over a range of plausible hypotheses for the system. PMID:29856869

Changes of population trends and mortality patterns in response to the reintroduction of large predators: The case study of African ungulates

NASA Astrophysics Data System (ADS)

Grange, Sophie; Owen-Smith, Norman; Gaillard, Jean-Michel; Druce, Dave J.; Moleón, Marcos; Mgobozi, Mandisa

2012-07-01

Large predators have been reintroduced to an increasing number of protected areas in South Africa. However, the conditions allowing both prey and predator populations to be sustained in enclosed areas are still unclear as there is a lack of understanding of the consequences of such reintroductions for ungulate population dynamics. Variation in lion numbers, two decades after their first release, offered a special opportunity to test the effects of predation pressure on the population dynamics of seven ungulate species in the 960 km2 Hluhluwe-iMfolozi Park (HiP), South Africa. We used two different approaches to examine predator-prey relationships: the population response of ungulates to predation pressure after accounting for possible confounding factors, and the pattern of ungulate adult mortality observed from carcass records. Rainfall patterns affected observed mortalities of several ungulate species in HiP. Although lion predation accounted for most ungulate mortality, it still had no detectable influence on ungulate population trends and mortality patterns, with one possible exception. This evidence suggests that the lion population had not yet attained the maximum abundance potentially supported by their ungulate prey; but following recent increases in lion numbers it will probably occur soon. It remains uncertain whether a quasi-stable balance will be reached between prey and predator populations, or whether favoured prey species will be depressed towards levels potentially generating oscillatory dynamics in this complex large mammal assemblage. We specifically recommend a continuous monitoring of predator and prey populations in HiP since lions are likely to show more impacts on their prey species in the next years.

Investigating effects of surrounding landscape composition and complexity on populations of two polyphagous insect pest groups in Iowa soybean

NASA Astrophysics Data System (ADS)

Kuntz, Cody Daniel

The composition and complexity of agro-ecosystems are important factors influencing the population dynamics of insect pests. Understanding these interactions may improve our ability to predict the spatial occurrence of pest outbreaks, thereby informing scouting and management decisions. In 2012 and 2013, two concurrent studies were conducted to examine the relationship between landscapes surrounding Iowa soybean, Glycine max [L.] Merrill, fields and two polyphagous pest groups; Japanese beetle, Popillia japonica Newman (Coleoptera: Scarabaeidae), and stink bugs (Hemiptera: Pentatomidae). Population densities were monitored in soybean within simple and complex agricultural landscapes to determine the response of these pests to landscape complexity. Results revealed P. japonica populations were significantly greater in soybean fields within complex landscapes and were positively associated with area of uncultivated land. The specific compositions of surrounding landscapes were also analyzed to determine the landscape features that explain the greatest variation in P. japonica and stink bug population densities. Results suggested that the area of wooded and grass habitat around fields accounted for the greatest variation in P. japonica populations; however, no discernable relationships were observed with stink bug populations. Sampling also sought to survey the community of stink bugs present in Iowa soybean. The community was predominantly comprised of stink bugs in the genus Euschistus, comprising a combined 91.04% of all captures. Additional species included the green stink bug, Acrosternum hilare (Say) (4.48%); spined soldier bug, Podisus maculiventris (Say) (2.99%); and red shouldered stink bug, Thyanta custator accerra (McAtee) (1.49%). Future work will be needed to determine if the landscape effects on P. japonica in soybean reported here are representative of other similar polyphagous pests of soybean and if they extend to other host plants as well. Furthermore, additional comprehensive surveys will be needed to better characterize the existing community of stink bug species present in Iowa field crops.

What can forest managers learn from research on fossil insects? Linking forest ecological history, biodiversity and management

Treesearch

Nicki J. Whitehouse

2006-01-01

This paper outlines the usefulness of using fossil insects, particularly Coleoptera (beetles), preserved in waterlogged palaeoenvironmental and archaeological deposits in understanding the changing nature of forest ecosystems and their associated insect population dynamics over the last 10,000 years. Research in Europe has highlighted the complex nature of early forest...

Synthesis and Exciton Dynamics of Triplet Sensitized Conjugated Polymers.

PubMed

Andernach, Rolf; Utzat, Hendrik; Dimitrov, Stoichko D; McCulloch, Iain; Heeney, Martin; Durrant, James R; Bronstein, Hugo

2015-08-19

We report the synthesis of a novel polythiophene-based host-guest copolymer incorporating a Pt-porphyrin complex (TTP-Pt) into the backbone for efficient singlet to triplet polymer exciton sensitization. We elucidated the exciton dynamics in thin films of the material by means of Transient Absorption Spectrosopcy (TAS) on multiple time scales and investigated the mechanism of triplet exciton formation. During sensitization, singlet exciton diffusion is followed by exciton transfer from the polymer backbone to the complex where it undergoes intersystem crossing to the triplet state of the complex. We directly monitored the triplet exciton back transfer from the Pt-porphyrin to the polymer and found that 60% of the complex triplet excitons were transferred with a time constant of 1087 ps. We propose an equilibrium between polymer and porphyrin triplet states as a result of the low triplet diffusion length in the polymer backbone and hence an increased local triplet population resulting in increased triplet-triplet annihilation. This novel system has significant implications for the design of novel materials for triplet sensitized solar cells and upconversion layers.

Vector-virus interactions and transmission dynamics of West Nile virus.

PubMed

Ciota, Alexander T; Kramer, Laura D

2013-12-09

West Nile virus (WNV; Flavivirus; Flaviviridae) is the cause of the most widespread arthropod-borne viral disease in the world and the largest outbreak of neuroinvasive disease ever observed. Mosquito-borne outbreaks are influenced by intrinsic (e.g., vector and viral genetics, vector and host competence, vector life-history traits) and extrinsic (e.g., temperature, rainfall, human land use) factors that affect virus activity and mosquito biology in complex ways. The concept of vectorial capacity integrates these factors to address interactions of the virus with the arthropod host, leading to a clearer understanding of their complex interrelationships, how they affect transmission of vector-borne disease, and how they impact human health. Vertebrate factors including host competence, population dynamics, and immune status also affect transmission dynamics. The complexity of these interactions are further exacerbated by the fact that not only can divergent hosts differentially alter the virus, but the virus also can affect both vertebrate and invertebrate hosts in ways that significantly alter patterns of virus transmission. This chapter concentrates on selected components of the virus-vector-vertebrate interrelationship, focusing specifically on how interactions between vector, virus, and environment shape the patterns and intensity of WNV transmission.

Vector-Virus Interactions and Transmission Dynamics of West Nile Virus

PubMed Central

Ciota, Alexander T.; Kramer, Laura D.

2013-01-01

West Nile virus (WNV; Flavivirus; Flaviviridae) is the cause of the most widespread arthropod-borne viral disease in the world and the largest outbreak of neuroinvasive disease ever observed. Mosquito-borne outbreaks are influenced by intrinsic (e.g., vector and viral genetics, vector and host competence, vector life-history traits) and extrinsic (e.g., temperature, rainfall, human land use) factors that affect virus activity and mosquito biology in complex ways. The concept of vectorial capacity integrates these factors to address interactions of the virus with the arthropod host, leading to a clearer understanding of their complex interrelationships, how they affect transmission of vector-borne disease, and how they impact human health. Vertebrate factors including host competence, population dynamics, and immune status also affect transmission dynamics. The complexity of these interactions are further exacerbated by the fact that not only can divergent hosts differentially alter the virus, but the virus also can affect both vertebrate and invertebrate hosts in ways that significantly alter patterns of virus transmission. This chapter concentrates on selected components of the virus-vector-vertebrate interrelationship, focusing specifically on how interactions between vector, virus, and environment shape the patterns and intensity of WNV transmission. PMID:24351794

Single-virion sequencing of lamivudine-treated HBV populations reveal population evolution dynamics and demographic history.

PubMed

Zhu, Yuan O; Aw, Pauline P K; de Sessions, Paola Florez; Hong, Shuzhen; See, Lee Xian; Hong, Lewis Z; Wilm, Andreas; Li, Chen Hao; Hue, Stephane; Lim, Seng Gee; Nagarajan, Niranjan; Burkholder, William F; Hibberd, Martin

2017-10-27

Viral populations are complex, dynamic, and fast evolving. The evolution of groups of closely related viruses in a competitive environment is termed quasispecies. To fully understand the role that quasispecies play in viral evolution, characterizing the trajectories of viral genotypes in an evolving population is the key. In particular, long-range haplotype information for thousands of individual viruses is critical; yet generating this information is non-trivial. Popular deep sequencing methods generate relatively short reads that do not preserve linkage information, while third generation sequencing methods have higher error rates that make detection of low frequency mutations a bioinformatics challenge. Here we applied BAsE-Seq, an Illumina-based single-virion sequencing technology, to eight samples from four chronic hepatitis B (CHB) patients - once before antiviral treatment and once after viral rebound due to resistance. With single-virion sequencing, we obtained 248-8796 single-virion sequences per sample, which allowed us to find evidence for both hard and soft selective sweeps. We were able to reconstruct population demographic history that was independently verified by clinically collected data. We further verified four of the samples independently through PacBio SMRT and Illumina Pooled deep sequencing. Overall, we showed that single-virion sequencing yields insight into viral evolution and population dynamics in an efficient and high throughput manner. We believe that single-virion sequencing is widely applicable to the study of viral evolution in the context of drug resistance and host adaptation, allows differentiation between soft or hard selective sweeps, and may be useful in the reconstruction of intra-host viral population demographic history.

Parallel and Multivalued Logic by the Two-Dimensional Photon-Echo Response of a Rhodamine–DNA Complex

PubMed Central

2015-01-01

Implementing parallel and multivalued logic operations at the molecular scale has the potential to improve the miniaturization and efficiency of a new generation of nanoscale computing devices. Two-dimensional photon-echo spectroscopy is capable of resolving dynamical pathways on electronic and vibrational molecular states. We experimentally demonstrate the implementation of molecular decision trees, logic operations where all possible values of inputs are processed in parallel and the outputs are read simultaneously, by probing the laser-induced dynamics of populations and coherences in a rhodamine dye mounted on a short DNA duplex. The inputs are provided by the bilinear interactions between the molecule and the laser pulses, and the output values are read from the two-dimensional molecular response at specific frequencies. Our results highlights how ultrafast dynamics between multiple molecular states induced by light–matter interactions can be used as an advantage for performing complex logic operations in parallel, operations that are faster than electrical switching. PMID:25984269

Higher-order stochastic differential equations and the positive Wigner function

NASA Astrophysics Data System (ADS)

Drummond, P. D.

2017-12-01

General higher-order stochastic processes that correspond to any diffusion-type tensor of higher than second order are obtained. The relationship of multivariate higher-order stochastic differential equations with tensor decomposition theory and tensor rank is explained. Techniques for generating the requisite complex higher-order noise are proved to exist either using polar coordinates and γ distributions, or from products of Gaussian variates. This method is shown to allow the calculation of the dynamics of the Wigner function, after it is extended to a complex phase space. The results are illustrated physically through dynamical calculations of the positive Wigner distribution for three-mode parametric downconversion, widely used in quantum optics. The approach eliminates paradoxes arising from truncation of the higher derivative terms in Wigner function time evolution. Anomalous results of negative populations and vacuum scattering found in truncated Wigner quantum simulations in quantum optics and Bose-Einstein condensate dynamics are shown not to occur with this type of stochastic theory.

Atomistic non-adiabatic dynamics of the LH2 complex with a GPU-accelerated ab initio exciton model.

PubMed

Sisto, Aaron; Stross, Clem; van der Kamp, Marc W; O'Connor, Michael; McIntosh-Smith, Simon; Johnson, Graham T; Hohenstein, Edward G; Manby, Fred R; Glowacki, David R; Martinez, Todd J

2017-06-14

We recently outlined an efficient multi-tiered parallel ab initio excitonic framework that utilizes time dependent density functional theory (TDDFT) to calculate ground and excited state energies and gradients of large supramolecular complexes in atomistic detail - enabling us to undertake non-adiabatic simulations which explicitly account for the coupled anharmonic vibrational motion of all the constituent atoms in a supramolecular system. Here we apply that framework to the 27 coupled bacterio-chlorophyll-a chromophores which make up the LH2 complex, using it to compute an on-the-fly nonadiabatic surface-hopping (SH) trajectory of electronically excited LH2. Part one of this article is focussed on calibrating our ab initio exciton Hamiltonian using two key parameters: a shift δ, which corrects for the error in TDDFT vertical excitation energies; and an effective dielectric constant ε, which describes the average screening of the transition-dipole coupling between chromophores. Using snapshots obtained from equilibrium molecular dynamics simulations (MD) of LH2, we tune the values of both δ and ε through fitting to the thermally broadened experimental absorption spectrum, giving a linear absorption spectrum that agrees reasonably well with experiment. In part two of this article, we construct a time-resolved picture of the coupled vibrational and excitation energy transfer (EET) dynamics in the sub-picosecond regime following photo-excitation. Assuming Franck-Condon excitation of a narrow eigenstate band centred at 800 nm, we use surface hopping to follow a single nonadiabatic dynamics trajectory within the full eigenstate manifold. Consistent with experimental data, this trajectory gives timescales for B800→B850 population transfer (τ B800→B850 ) between 650-1050 fs, and B800 population decay (τ 800→ ) between 10-50 fs. The dynamical picture that emerges is one of rapidly fluctuating LH2 eigenstates that are delocalized over multiple chromophores and undergo frequent crossing on a femtosecond timescale as a result of the atomic vibrations of the constituent chromophores. The eigenstate fluctuations arise from disorder that is driven by vibrational dynamics with multiple characteristic timescales. The scalability of our ab initio excitonic computational framework across massively parallel architectures opens up the possibility of addressing a wide range of questions, including how specific dynamical motions impact both the pathways and efficiency of electronic energy-transfer within large supramolecular systems.

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

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

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

2015-11-01

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

Living in a network of scaling cities and finite resources.

PubMed

Qubbaj, Murad R; Shutters, Shade T; Muneepeerakul, Rachata

2015-02-01

Many urban phenomena exhibit remarkable regularity in the form of nonlinear scaling behaviors, but their implications on a system of networked cities has never been investigated. Such knowledge is crucial for our ability to harness the complexity of urban processes to further sustainability science. In this paper, we develop a dynamical modeling framework that embeds population-resource dynamics-a generalized Lotka-Volterra system with modifications to incorporate the urban scaling behaviors-in complex networks in which cities may be linked to the resources of other cities and people may migrate in pursuit of higher welfare. We find that isolated cities (i.e., no migration) are susceptible to collapse if they do not have access to adequate resources. Links to other cities may help cities that would otherwise collapse due to insufficient resources. The effects of inter-city links, however, can vary due to the interplay between the nonlinear scaling behaviors and network structure. The long-term population level of a city is, in many settings, largely a function of the city's access to resources over which the city has little or no competition. Nonetheless, careful investigation of dynamics is required to gain mechanistic understanding of a particular city-resource network because cities and resources may collapse and the scaling behaviors may influence the effects of inter-city links, thereby distorting what topological metrics really measure.

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

NASA Astrophysics Data System (ADS)

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

2015-11-01

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

Voids and the Cosmic Web: cosmic depression & spatial complexity

NASA Astrophysics Data System (ADS)

van de Weygaert, Rien

2016-10-01

Voids form a prominent aspect of the Megaparsec distribution of galaxies and matter. Not only do theyrepresent a key constituent of the Cosmic Web, they also are one of the cleanest probesand measures of global cosmological parameters. The shape and evolution of voids are highly sensitive tothe nature of dark energy, while their substructure and galaxy population provides a direct key to thenature of dark matter. Also, the pristine environment of void interiors is an important testing groundfor our understanding of environmental influences on galaxy formation and evolution. In this paper, we reviewthe key aspects of the structure and dynamics ofvoids, with a particular focus on the hierarchical evolution of the void population. We demonstratehow the rich structural pattern of the Cosmic Web is related to the complex evolution and buildupof voids.

Early signatures of regime shifts in gene expression dynamics

NASA Astrophysics Data System (ADS)

Pal, Mainak; Pal, Amit Kumar; Ghosh, Sayantari; Bose, Indrani

2013-06-01

Recently, a large number of studies have been carried out on the early signatures of sudden regime shifts in systems as diverse as ecosystems, financial markets, population biology and complex diseases. The signatures of regime shifts in gene expression dynamics are less systematically investigated. In this paper, we consider sudden regime shifts in the gene expression dynamics described by a fold-bifurcation model involving bistability and hysteresis. We consider two alternative models, models 1 and 2, of competence development in the bacterial population B. subtilis and determine some early signatures of the regime shifts between competence and noncompetence. We use both deterministic and stochastic formalisms for the purpose of our study. The early signatures studied include the critical slowing down as a transition point is approached, rising variance and the lag-1 autocorrelation function, skewness and a ratio of two mean first passage times. Some of the signatures could provide the experimental basis for distinguishing between bistability and excitability as the correct mechanism for the development of competence.

The importance of accurately modelling human interactions. Comment on "Coupled disease-behavior dynamics on complex networks: A review" by Z. Wang et al.

NASA Astrophysics Data System (ADS)

Rosati, Dora P.; Molina, Chai; Earn, David J. D.

2015-12-01

Human behaviour and disease dynamics can greatly influence each other. In particular, people often engage in self-protective behaviours that affect epidemic patterns (e.g., vaccination, use of barrier precautions, isolation, etc.). Self-protective measures usually have a mitigating effect on an epidemic [16], but can in principle have negative impacts at the population level [12,15,18]. The structure of underlying social and biological contact networks can significantly influence the specific ways in which population-level effects are manifested. Using a different contact network in a disease dynamics model-keeping all else equal-can yield very different epidemic patterns. For example, it has been shown that when individuals imitate their neighbours' vaccination decisions with some probability, this can lead to herd immunity in some networks [9], yet for other networks it can preserve clusters of susceptible individuals that can drive further outbreaks of infectious disease [12].

Statistical genetics and evolution of quantitative traits

NASA Astrophysics Data System (ADS)

Neher, Richard A.; Shraiman, Boris I.

2011-10-01

The distribution and heritability of many traits depends on numerous loci in the genome. In general, the astronomical number of possible genotypes makes the system with large numbers of loci difficult to describe. Multilocus evolution, however, greatly simplifies in the limit of weak selection and frequent recombination. In this limit, populations rapidly reach quasilinkage equilibrium (QLE) in which the dynamics of the full genotype distribution, including correlations between alleles at different loci, can be parametrized by the allele frequencies. This review provides a simplified exposition of the concept and mathematics of QLE which is central to the statistical description of genotypes in sexual populations. Key results of quantitative genetics such as the generalized Fisher’s “fundamental theorem,” along with Wright’s adaptive landscape, are shown to emerge within QLE from the dynamics of the genotype distribution. This is followed by a discussion under what circumstances QLE is applicable, and what the breakdown of QLE implies for the population structure and the dynamics of selection. Understanding the fundamental aspects of multilocus evolution obtained through simplified models may be helpful in providing conceptual and computational tools to address the challenges arising in the studies of complex quantitative phenotypes of practical interest.

Quantum cluster variational method and message passing algorithms revisited

NASA Astrophysics Data System (ADS)

Domínguez, E.; Mulet, Roberto

2018-02-01

We present a general framework to study quantum disordered systems in the context of the Kikuchi's cluster variational method (CVM). The method relies in the solution of message passing-like equations for single instances or in the iterative solution of complex population dynamic algorithms for an average case scenario. We first show how a standard application of the Kikuchi's CVM can be easily translated to message passing equations for specific instances of the disordered system. We then present an "ad hoc" extension of these equations to a population dynamic algorithm representing an average case scenario. At the Bethe level, these equations are equivalent to the dynamic population equations that can be derived from a proper cavity ansatz. However, at the plaquette approximation, the interpretation is more subtle and we discuss it taking also into account previous results in classical disordered models. Moreover, we develop a formalism to properly deal with the average case scenario using a replica-symmetric ansatz within this CVM for quantum disordered systems. Finally, we present and discuss numerical solutions of the different approximations for the quantum transverse Ising model and the quantum random field Ising model in two-dimensional lattices.

A system dynamics optimization framework to achieve population desired of average weight target

NASA Astrophysics Data System (ADS)

Abidin, Norhaslinda Zainal; Zulkepli, Jafri Haji; Zaibidi, Nerda Zura

2017-11-01

Obesity is becoming a serious problem in Malaysia as it has been rated as the highest among Asian countries. The aim of the paper is to propose a system dynamics (SD) optimization framework to achieve population desired weight target based on the changes in physical activity behavior and its association to weight and obesity. The system dynamics approach of stocks and flows diagram was used to quantitatively model the impact of both behavior on the population's weight and obesity trends. This work seems to bring this idea together and highlighting the interdependence of the various aspects of eating and physical activity behavior on the complex of human weight regulation system. The model was used as an experimentation vehicle to investigate the impacts of changes in physical activity on weight and prevalence of obesity implications. This framework paper provides evidence on the usefulness of SD optimization as a strategic decision making approach to assist in decision making related to obesity prevention. SD applied in this research is relatively new in Malaysia and has a high potential to apply to any feedback models that address the behavior cause to obesity.

A combined crossed-beam and theoretical study of the reaction dynamics of O(3P) + C2H3 → C2H2 + OH: Analysis of the nascent OH products with the preferential population of the Π(A') component

NASA Astrophysics Data System (ADS)

Park, Min-Jin; Jang, Su-Chan; Choi, Jong-Ho

2012-11-01

The gas-phase reaction dynamics of ground-state atomic oxygen [O(3P) from the photo-dissociation of NO2] with vinyl radicals [C2H3 from the supersonic flash pyrolysis of vinyl iodide, C2H3I] has been investigated using a combination of high-resolution laser-induced fluorescence spectroscopy in a crossed-beam configuration and ab initio calculations. Unlike the previous gas-phase bulk kinetic experiments by Baulch et al. [J. Phys. Chem. Ref. Data 34, 757 (2005)], 10.1063/1.1748524, a new exothermic channel of O(3P) + C2H3 → C2H2 + OH (X 2Π: υ″ = 0) has been identified for the first time, and the population analysis shows bimodal nascent rotational distributions of OH products with low- and high-N″ components with a ratio of 2.4:1. No spin-orbit propensities were observed, and the averaged ratios of Π(A')/Π(A″) were determined to be 1.66 ± 0.27. On the basis of computations at the CBS-QB3 theory level and comparison with prior theory, the microscopic mechanisms responsible for the nascent populations can be understood in terms of two competing dynamical pathways: a direct abstraction process in the low-N″ regime as the major pathway and an addition-complex forming process in the high-N″ regime as the minor pathway. Particularly, during the bond cleavage process of the weakly bound van der Waals complex C2H2—OH, the characteristic pathway from the low dihedral-angle geometry was consistent with the observed preferential population of the Π(A') component in the nascent OH products. A molecular-level discussion of the reactivity, mechanism, and dynamical features of the title reaction are presented together with a comparison to gas-phase oxidation reactions of a series of prototypical hydrocarbon radicals.

A meta-analysis of crop pest and natural enemy response to landscape complexity.

PubMed

Chaplin-Kramer, Rebecca; O'Rourke, Megan E; Blitzer, Eleanor J; Kremen, Claire

2011-09-01

Many studies in recent years have investigated the relationship between landscape complexity and pests, natural enemies and/or pest control. However, no quantitative synthesis of this literature beyond simple vote-count methods yet exists. We conducted a meta-analysis of 46 landscape-level studies, and found that natural enemies have a strong positive response to landscape complexity. Generalist enemies show consistent positive responses to landscape complexity across all scales measured, while specialist enemies respond more strongly to landscape complexity at smaller scales. Generalist enemy response to natural habitat also tends to occur at larger spatial scales than for specialist enemies, suggesting that land management strategies to enhance natural pest control should differ depending on whether the dominant enemies are generalists or specialists. The positive response of natural enemies does not necessarily translate into pest control, since pest abundances show no significant response to landscape complexity. Very few landscape-scale studies have estimated enemy impact on pest populations, however, limiting our understanding of the effects of landscape on pest control. We suggest focusing future research efforts on measuring population dynamics rather than static counts to better characterise the relationship between landscape complexity and pest control services from natural enemies. © 2011 Blackwell Publishing Ltd/CNRS.

Ecology and exploration of the rare biosphere.

PubMed

Lynch, Michael D J; Neufeld, Josh D

2015-04-01

The profound influence of microorganisms on human life and global biogeochemical cycles underlines the value of studying the biogeography of microorganisms, exploring microbial genomes and expanding our understanding of most microbial species on Earth: that is, those present at low relative abundance. The detection and subsequent analysis of low-abundance microbial populations—the 'rare biosphere'—have demonstrated the persistence, population dynamics, dispersion and predation of these microbial species. We discuss the ecology of rare microbial populations, and highlight molecular and computational methods for targeting taxonomic 'blind spots' within the rare biosphere of complex microbial communities.

Dynamical phases in a one-dimensional chain of heterospecies Rydberg atoms with next-nearest-neighbor interactions

NASA Astrophysics Data System (ADS)

Qian, Jing; Zhang, Lu; Zhai, Jingjing; Zhang, Weiping

2015-12-01

We theoretically investigate the dynamical phase diagram of a one-dimensional chain of laser-excited two-species Rydberg atoms. The existence of a variety of unique dynamical phases in the experimentally achievable parameter region is predicted under the mean-field approximation, and the change in those phases when the effect of the next-nearest-neighbor interaction is included is further discussed. In particular, we find that the com-petition of the strong Rydberg-Rydberg interactions and the optical excitation imbalance can lead to the presence of complex multiple chaotic phases, which are highly sensitive to the initial Rydberg-state population and the strength of the next-nearest-neighbor interactions.

Chemotaxis in densely populated tissue determines germinal center anatomy and cell motility: a new paradigm for the development of complex tissues.

PubMed

Hawkins, Jared B; Jones, Mark T; Plassmann, Paul E; Thorley-Lawson, David A

2011-01-01

Germinal centers (GCs) are complex dynamic structures that form within lymph nodes as an essential process in the humoral immune response. They represent a paradigm for studying the regulation of cell movement in the development of complex anatomical structures. We have developed a simulation of a modified cyclic re-entry model of GC dynamics which successfully employs chemotaxis to recapitulate the anatomy of the primary follicle and the development of a mature GC, including correctly structured mantle, dark and light zones. We then show that correct single cell movement dynamics (including persistent random walk and inter-zonal crossing) arise from this simulation as purely emergent properties. The major insight of our study is that chemotaxis can only achieve this when constrained by the known biological properties that cells are incompressible, exist in a densely packed environment, and must therefore compete for space. It is this interplay of chemotaxis and competition for limited space that generates all the complex and biologically accurate behaviors described here. Thus, from a single simple mechanism that is well documented in the biological literature, we can explain both higher level structure and single cell movement behaviors. To our knowledge this is the first GC model that is able to recapitulate both correctly detailed anatomy and single cell movement. This mechanism may have wide application for modeling other biological systems where cells undergo complex patterns of movement to produce defined anatomical structures with sharp tissue boundaries.

Effects of additional food in a delayed predator-prey model.

PubMed

Sahoo, Banshidhar; Poria, Swarup

2015-03-01

We examine the effects of supplying additional food to predator in a gestation delay induced predator-prey system with habitat complexity. Additional food works in favor of predator growth in our model. Presence of additional food reduces the predatory attack rate to prey in the model. Supplying additional food we can control predator population. Taking time delay as bifurcation parameter the stability of the coexisting equilibrium point is analyzed. Hopf bifurcation analysis is done with respect to time delay in presence of additional food. The direction of Hopf bifurcations and the stability of bifurcated periodic solutions are determined by applying the normal form theory and the center manifold theorem. The qualitative dynamical behavior of the model is simulated using experimental parameter values. It is observed that fluctuations of the population size can be controlled either by supplying additional food suitably or by increasing the degree of habitat complexity. It is pointed out that Hopf bifurcation occurs in the system when the delay crosses some critical value. This critical value of delay strongly depends on quality and quantity of supplied additional food. Therefore, the variation of predator population significantly effects the dynamics of the model. Model results are compared with experimental results and biological implications of the analytical findings are discussed in the conclusion section. Copyright © 2015 Elsevier Inc. All rights reserved.

Increased frequency of self-fertile isolates in Phytophthora infestans may attribute to their higher fitness relative to the A1 isolates

PubMed Central

Zhu, Wen; Shen, Lin-Lin; Fang, Zhi-Guo; Yang, Li-Na; Zhang, Jia-Feng; Sun, Dan-Li; Zhan, Jiasui

2016-01-01

Knowledge of population dynamics of mating types is important for better understanding pathogen’s evolutionary potential and sustainable management of natural and chemical resources such as host resistances and fungicides. In this study, 2250 Phytophthora infestans isolates sampled from 61 fields across China were assayed for spatiotemporal dynamics of mating type frequency. Self-fertile isolates dominated in ~50% of populations and all but one cropping region with an average frequency of 0.64 while no A2 isolates were detected. Analyses of 140 genotypes consisting of 82 self-fertile and 58 A1 isolates indicated that on average self-fertile isolates grew faster, demonstrated higher aggressiveness and were more tolerant to fungicides than A1 isolates; Furthermore, pattern of association between virulence complexity (defined as the number of differential cultivars on which an isolate can induce disease) and frequency was different in the two mating types. In A1 isolates, virulence complexity was negatively correlated (r = −0.515, p = 0.043) with frequency but this correlation was positive (r = 0.532, p = 0.037) in self-fertile isolates. Our results indicate a quick increase of self-fertile isolates possibly attributable to their higher fitness relative to A1 mating type counterpart in the field populations of P. infestans in China. PMID:27384813

Mouse Hair Cycle Expression Dynamics Modeled as Coupled Mesenchymal and Epithelial Oscillators

PubMed Central

Tasseff, Ryan; Bheda-Malge, Anjali; DiColandrea, Teresa; Bascom, Charles C.; Isfort, Robert J.; Gelinas, Richard

2014-01-01

The hair cycle is a dynamic process where follicles repeatedly move through phases of growth, retraction, and relative quiescence. This process is an example of temporal and spatial biological complexity. Understanding of the hair cycle and its regulation would shed light on many other complex systems relevant to biological and medical research. Currently, a systematic characterization of gene expression and summarization within the context of a mathematical model is not yet available. Given the cyclic nature of the hair cycle, we felt it was important to consider a subset of genes with periodic expression. To this end, we combined several mathematical approaches with high-throughput, whole mouse skin, mRNA expression data to characterize aspects of the dynamics and the possible cell populations corresponding to potentially periodic patterns. In particular two gene clusters, demonstrating properties of out-of-phase synchronized expression, were identified. A mean field, phase coupled oscillator model was shown to quantitatively recapitulate the synchronization observed in the data. Furthermore, we found only one configuration of positive-negative coupling to be dynamically stable, which provided insight on general features of the regulation. Subsequent bifurcation analysis was able to identify and describe alternate states based on perturbation of system parameters. A 2-population mixture model and cell type enrichment was used to associate the two gene clusters to features of background mesenchymal populations and rapidly expanding follicular epithelial cells. Distinct timing and localization of expression was also shown by RNA and protein imaging for representative genes. Taken together, the evidence suggests that synchronization between expanding epithelial and background mesenchymal cells may be maintained, in part, by inhibitory regulation, and potential mediators of this regulation were identified. Furthermore, the model suggests that impairing this negative regulation will drive a bifurcation which may represent transition into a pathological state such as hair miniaturization. PMID:25375120

Competition in a Social Structure

NASA Astrophysics Data System (ADS)

Legara, Erika Fille; Longjas, Anthony; Batac, Rene

Complex adaptive agents develop strategies in the presence of competition. In modern human societies, there is an inherent sense of locality when describing inter-agent dynamics because of its network structure. One then wonders whether the traditional advertising schemes that are globally publicized and target random individuals are as effective in attracting a larger portion of the population as those that take advantage of local neighborhoods, such as "word-of-mouth" marketing schemes. Here, we demonstrate using a differential equation model that schemes targeting local cliques within the network are more successful at gaining a larger share of the population than those that target users randomly at a global scale (e.g., television commercials, print ads, etc.). This suggests that success in the competition is dependent not only on the number of individuals in the population but also on how they are connected in the network. We further show that the model is general in nature by considering examples of competition dynamics, particularly those of business competition and language death.

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

PubMed Central

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

2008-01-01

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

Framework for Infectious Disease Analysis: A comprehensive and integrative multi-modeling approach to disease prediction and management.

PubMed

Erraguntla, Madhav; Zapletal, Josef; Lawley, Mark

2017-12-01

The impact of infectious disease on human populations is a function of many factors including environmental conditions, vector dynamics, transmission mechanics, social and cultural behaviors, and public policy. A comprehensive framework for disease management must fully connect the complete disease lifecycle, including emergence from reservoir populations, zoonotic vector transmission, and impact on human societies. The Framework for Infectious Disease Analysis is a software environment and conceptual architecture for data integration, situational awareness, visualization, prediction, and intervention assessment. Framework for Infectious Disease Analysis automatically collects biosurveillance data using natural language processing, integrates structured and unstructured data from multiple sources, applies advanced machine learning, and uses multi-modeling for analyzing disease dynamics and testing interventions in complex, heterogeneous populations. In the illustrative case studies, natural language processing from social media, news feeds, and websites was used for information extraction, biosurveillance, and situation awareness. Classification machine learning algorithms (support vector machines, random forests, and boosting) were used for disease predictions.

How many Coccolithovirus genotypes does it take to terminate an Emiliania huxleyi bloom?

PubMed

Highfield, Andrea; Evans, Claire; Walne, Anthony; Miller, Peter I; Schroeder, Declan C

2014-10-01

Giant viruses are known to be significant mortality agents of phytoplankton, often being implicated in the terminations of large Emiliania huxleyi blooms. We have previously shown the high temporal variability of E. huxleyi-infecting coccolithoviruses (EhVs) within a Norwegian fjord mesocosm. In the current study we investigated EhV dynamics within a naturally-occurring E. huxleyi bloom in the Western English Channel. Using denaturing gradient gel electrophoresis and marker gene sequencing, we uncovered a spatially highly dynamic Coccolithovirus population that was associated with a genetically stable E. huxleyi population as revealed by the major capsid protein gene (mcp) and coccolith morphology motif (CMM), respectively. Coccolithoviruses within the bloom were found to be variable with depth and unique virus populations were detected at different stations sampled indicating a complex network of EhV-host infections. This ultimately will have significant implications to the internal structure and longevity of ecologically important E. huxleyi blooms. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Single-cell resolution of intracellular T cell Ca2+ dynamics in response to frequency-based H2O2 stimulation.

PubMed

Kniss-James, Ariel S; Rivet, Catherine A; Chingozha, Loice; Lu, Hang; Kemp, Melissa L

2017-03-01

Adaptive immune cells, such as T cells, integrate information from their extracellular environment through complex signaling networks with exquisite sensitivity in order to direct decisions on proliferation, apoptosis, and cytokine production. These signaling networks are reliant on the interplay between finely tuned secondary messengers, such as Ca 2+ and H 2 O 2 . Frequency response analysis, originally developed in control engineering, is a tool used for discerning complex networks. This analytical technique has been shown to be useful for understanding biological systems and facilitates identification of the dominant behaviour of the system. We probed intracellular Ca 2+ dynamics in the frequency domain to investigate the complex relationship between two second messenger signaling molecules, H 2 O 2 and Ca 2+ , during T cell activation with single cell resolution. Single-cell analysis provides a unique platform for interrogating and monitoring cellular processes of interest. We utilized a previously developed microfluidic device to monitor individual T cells through time while applying a dynamic input to reveal a natural frequency of the system at approximately 2.78 mHz stimulation. Although our network was much larger with more unknown connections than previous applications, we are able to derive features from our data, observe forced oscillations associated with specific amplitudes and frequencies of stimuli, and arrive at conclusions about potential transfer function fits as well as the underlying population dynamics.

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

Genes, communities & invasive species: understanding the ecological and evolutionary dynamics of host-pathogen interactions.

PubMed

Burdon, J J; Thrall, P H; Ericson, L

2013-08-01

Reciprocal interactions between hosts and pathogens drive ecological, epidemiological and co-evolutionary trajectories, resulting in complex patterns of diversity at population, species and community levels. Recent results confirm the importance of negative frequency-dependent rather than 'arms-race' processes in the evolution of individual host-pathogen associations. At the community level, complex relationships between species abundance and diversity dampen or alter pathogen impacts. Invasive pathogens challenge these controls reflecting the earliest stages of evolutionary associations (akin to arms-race) where disease effects may be so great that they overwhelm the host's and community's ability to respond. Viewing these different stabilization/destabilization phases as a continuum provides a valuable perspective to assessment of the role of genetics and ecology in the dynamics of both natural and invasive host-pathogen associations. Copyright © 2013 Elsevier Ltd. All rights reserved.

Single-Molecule Sequencing Reveals Complex Genome Variation of Hepatitis B Virus during 15 Years of Chronic Infection following Liver Transplantation

PubMed Central

Betz-Stablein, B. D.; Töpfer, A.; Littlejohn, M.; Yuen, L.; Colledge, D.; Sozzi, V.; Angus, P.; Thompson, A.; Revill, P.; Beerenwinkel, N.; Warner, N.

2016-01-01

ABSTRACT Chronic hepatitis B (CHB) is prevalent worldwide. The infectious agent, hepatitis B virus (HBV), replicates via an RNA intermediate and is error prone, leading to the rapid generation of closely related but not identical viral variants, including those that can escape host immune responses and antiviral treatments. The complexity of CHB can be further enhanced by the presence of HBV variants with large deletions in the genome generated via splicing (spHBV variants). Although spHBV variants are incapable of autonomous replication, their replication is rescued by wild-type HBV. spHBV variants have been shown to enhance wild-type virus replication, and their prevalence increases with liver disease progression. Single-molecule deep sequencing was performed on whole HBV genomes extracted from samples, including the liver explant, longitudinally collected from a subject with CHB over a 15-year period after liver transplantation. By employing novel bioinformatics methods, this analysis showed that the dynamics of the viral population across a period of changing treatment regimens was complex. The spHBV variants detected in the liver explant remained present posttransplantation, and a highly diverse novel spHBV population as well as variants with multiple deletions in the pre-S genes emerged. The identification of novel mutations outside the HBV reverse transcriptase gene that co-occurred with known drug resistance-associated mutations highlights the relevance of using full-genome deep sequencing and supports the hypothesis that drug resistance involves interactions across the full length of the HBV genome. IMPORTANCE Single-molecule sequencing allowed the characterization, in unprecedented detail, of the evolution of HBV populations and offered unique insights into the dynamics of defective and spHBV variants following liver transplantation and complex treatment regimens. This analysis also showed the rapid adaptation of HBV populations to treatment regimens with evolving drug resistance phenotypes and evidence of purifying selection across the whole genome. Finally, the new open-source bioinformatics tools with the capacity to easily identify potential spliced variants from deep sequencing data are freely available. PMID:27252524

Population Dynamics of Early Human Migration in Britain

PubMed Central

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

2016-01-01

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

Magnetic storms and solar flares: can be analysed within similar mathematical framework with other extreme events?

NASA Astrophysics Data System (ADS)

Balasis, Georgios; Potirakis, Stelios M.; Papadimitriou, Constantinos; Zitis, Pavlos I.; Eftaxias, Konstantinos

2015-04-01

The field of study of complex systems considers that the dynamics of complex systems are founded on universal principles that may be used to describe a great variety of scientific and technological approaches of different types of natural, artificial, and social systems. We apply concepts of the nonextensive statistical physics, on time-series data of observable manifestations of the underlying complex processes ending up to different extreme events, in order to support the suggestion that a dynamical analogy characterizes the generation of a single magnetic storm, solar flare, earthquake (in terms of pre-seismic electromagnetic signals) , epileptic seizure, and economic crisis. The analysis reveals that all the above mentioned different extreme events can be analyzed within similar mathematical framework. More precisely, we show that the populations of magnitudes of fluctuations included in all the above mentioned pulse-like-type time series follow the traditional Gutenberg-Richter law as well as a nonextensive model for earthquake dynamics, with similar nonextensive q-parameter values. Moreover, based on a multidisciplinary statistical analysis we show that the extreme events are characterized by crucial common symptoms, namely: (i) high organization, high compressibility, low complexity, high information content; (ii) strong persistency; and (iii) existence of clear preferred direction of emerged activities. These symptoms clearly discriminate the appearance of the extreme events under study from the corresponding background noise.

Environmental change disrupts communication and sexual selection in a stickleback population.

PubMed

Candolin, Ulrika; Tukiainen, Iina; Bertell, Elina

2016-04-01

Environmental change that disrupts communication during mate choice and alters sexual selection could influence population dynamics. Yet little is known about such long-term effects. We investigated experimentally the consequences that disrupted visual communication during mate choice has for the quantity and viability of offspring produced in a threespine stickleback population (Gasterosteus aculeatus). We further related the results to long-term monitoring of population dynamics in the field to determine if changes are apparent under natural conditions. The results show that impaired visual communication because of algal blooms reduces reliability of male visual signals as indicators of offspring survival during their first weeks of life. This relaxes sexual selection but has no effect on the number of offspring hatching, as most males have a high hatching success in turbid water. Despite eutrophication and high turbidity levels that interfere with communication during mate choice, the population has grown during recent decades. Large numbers of offspring hatching, combined with high variation in juvenile fitness, has probably shifted selection to later life history stages and maintained a viable population. Together with reduced cost of sexual selection and ongoing ecosystem changes caused by human activities, this could have promoted population growth. These results point to the complexity of ecosystems and the necessity to consider all influencing factors when attempting to understand impacts of human activities on populations.

Understanding climate impacts on recruitment and spatial dynamics of Atlantic cod in the Gulf of Maine: Integration of observations and modeling

NASA Astrophysics Data System (ADS)

Runge, Jeffrey A.; Kovach, Adrienne I.; Churchill, James H.; Kerr, Lisa A.; Morrison, John R.; Beardsley, Robert C.; Berlinsky, David L.; Chen, Changsheng; Cadrin, Steven X.; Davis, Cabell S.; Ford, Kathryn H.; Grabowski, Jonathan H.; Howell, W. Huntting; Ji, Rubao; Jones, Rebecca J.; Pershing, Andrew J.; Record, Nicholas R.; Thomas, Andrew C.; Sherwood, Graham D.; Tallack, Shelly M. L.; Townsend, David W.

2010-10-01

We put forward a combined observing and modeling strategy for evaluating effects of environmental forcing on the dynamics of spatially structured cod populations spawning in the western Gulf of Maine. Recent work indicates at least two genetically differentiated complexes in this region: a late spring spawning, coastal population centered in Ipswich Bay, and a population that spawns in winter inshore and on nearshore banks in the Gulf of Maine and off southern New England. The two populations likely differ in trophic interactions and in physiological and behavioral responses to different winter and spring environments. Coupled physical-biological modeling has advanced to the point where within-decade forecasting of environmental conditions for recruitment to each of the two populations is feasible. However, the modeling needs to be supported by hydrographic, primary production and zooplankton data collected by buoys, and by data from remote sensing and fixed station sampling. Forecasts of environmentally driven dispersal and growth of planktonic early life stages, combined with an understanding of possible population-specific predator fields, usage of coastal habitat by juveniles and adult resident and migratory patterns, can be used to develop scenarios for spatially explicit population responses to multiple forcings, including climate change, anthropogenic impacts on nearshore juvenile habitat, connectivity among populations and management interventions such as regional fisheries closures.

Mathematical Modelling as a Tool to Understand Cell Self-renewal and Differentiation.

PubMed

Getto, Philipp; Marciniak-Czochra, Anna

2015-01-01

Mathematical modeling is a powerful technique to address key questions and paradigms in a variety of complex biological systems and can provide quantitative insights into cell kinetics, fate determination and development of cell populations. The chapter is devoted to a review of modeling of the dynamics of stem cell-initiated systems using mathematical methods of ordinary differential equations. Some basic concepts and tools for cell population dynamics are summarized and presented as a gentle introduction to non-mathematicians. The models take into account different plausible mechanisms regulating homeostasis. Two mathematical frameworks are proposed reflecting, respectively, a discrete (punctuated by division events) and a continuous character of transitions between differentiation stages. Advantages and constraints of the mathematical approaches are presented on examples of models of blood systems and compared to patients data on healthy hematopoiesis.

Controlled recovery of phylogenetic communities from an evolutionary model using a network approach

NASA Astrophysics Data System (ADS)

Sousa, Arthur M. Y. R.; Vieira, André P.; Prado, Carmen P. C.; Andrade, Roberto F. S.

2016-04-01

This works reports the use of a complex network approach to produce a phylogenetic classification tree of a simple evolutionary model. This approach has already been used to treat proteomic data of actual extant organisms, but an investigation of its reliability to retrieve a traceable evolutionary history is missing. The used evolutionary model includes key ingredients for the emergence of groups of related organisms by differentiation through random mutations and population growth, but purposefully omits other realistic ingredients that are not strictly necessary to originate an evolutionary history. This choice causes the model to depend only on a small set of parameters, controlling the mutation probability and the population of different species. Our results indicate that for a set of parameter values, the phylogenetic classification produced by the used framework reproduces the actual evolutionary history with a very high average degree of accuracy. This includes parameter values where the species originated by the evolutionary dynamics have modular structures. In the more general context of community identification in complex networks, our model offers a simple setting for evaluating the effects, on the efficiency of community formation and identification, of the underlying dynamics generating the network itself.

"Invisible" conformers of an antifungal disulfide protein revealed by constrained cold and heat unfolding, CEST-NMR experiments, and molecular dynamics calculations.

PubMed

Fizil, Ádám; Gáspári, Zoltán; Barna, Terézia; Marx, Florentine; Batta, Gyula

2015-03-23

Transition between conformational states in proteins is being recognized as a possible key factor of function. In support of this, hidden dynamic NMR structures were detected in several cases up to populations of a few percent. Here, we show by two- and three-state analysis of thermal unfolding, that the population of hidden states may weight 20-40 % at 298 K in a disulfide-rich protein. In addition, sensitive (15) N-CEST NMR experiments identified a low populated (0.15 %) state that was in slow exchange with the folded PAF protein. Remarkably, other techniques failed to identify the rest of the NMR "dark matter". Comparison of the temperature dependence of chemical shifts from experiments and molecular dynamics calculations suggests that hidden conformers of PAF differ in the loop and terminal regions and are most similar in the evolutionary conserved core. Our observations point to the existence of a complex conformational landscape with multiple conformational states in dynamic equilibrium, with diverse exchange rates presumably responsible for the completely hidden nature of a considerable fraction. © 2015 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Transient recovery dynamics of a predator-prey system under press and pulse disturbances.

PubMed

Karakoç, Canan; Singer, Alexander; Johst, Karin; Harms, Hauke; Chatzinotas, Antonis

2017-04-04

Species recovery after disturbances depends on the strength and duration of disturbance, on the species traits and on the biotic interactions with other species. In order to understand these complex relationships, it is essential to understand mechanistically the transient dynamics of interacting species during and after disturbances. We combined microcosm experiments with simulation modelling and studied the transient recovery dynamics of a simple microbial food web under pulse and press disturbances and under different predator couplings to an alternative resource. Our results reveal that although the disturbances affected predator and prey populations by the same mortality, predator populations suffered for a longer time. The resulting diminished predation stress caused a temporary phase of high prey population sizes (i.e. prey release) during and even after disturbances. Increasing duration and strength of disturbances significantly slowed down the recovery time of the predator prolonging the phase of prey release. However, the additional coupling of the predator to an alternative resource allowed the predator to recover faster after the disturbances thus shortening the phase of prey release. Our findings are not limited to the studied system and can be used to understand the dynamic response and recovery potential of many natural predator-prey or host-pathogen systems. They can be applied, for instance, in epidemiological and conservational contexts to regulate prey release or to avoid extinction risk of the top trophic levels under different types of disturbances.

An application of the Caputo-Fabrizio operator to replicator-mutator dynamics: Bifurcation, chaotic limit cycles and control

NASA Astrophysics Data System (ADS)

Doungmo Goufo, Emile Franc

2018-02-01

The physical behaviors of replicator-mutator processes found in theoretical biophysics, physical chemistry, biochemistry and population biology remain complex with unlimited expressibility. People languages, for instance, have impressively and unpredictably changed over the time in human history. This is mainly due to the collection of small changes and collaboration with other languages. In this paper, the Caputo-Fabrizio operator is applied to a replicator-mutator dynamic taking place in midsts with movement. The model is fully analyzed and solved numerically via the Crank-Nicolson scheme. Stability and convergence results are provided. A concrete application to replicator-mutator dynamics for a population with three strategies is performed with numerical simulations provided for some fixed values of the physical position of the population symbolized by r and the grid points. Physically, it happens that limit cycles appear, not only in function of the mutation parameter μ but also in function of the values given to r . The amplitudes of limit cycles also appear to be proportional to r but the stability of the system remains unaffected. However, those limit cycles instead of disappearing as expected, are immediately followed by chaotic and unpredictable behaviors certainly due to the non-singular kernel used in the model and suitable to non-linear dynamics. Hence, the appearance and disappearance of limit cycles might be controlled by the position variable r which can also apprehend chaos.

Modeling oscillations and spiral waves in Dictyostelium populations

NASA Astrophysics Data System (ADS)

Noorbakhsh, Javad; Schwab, David J.; Sgro, Allyson E.; Gregor, Thomas; Mehta, Pankaj

2015-06-01

Unicellular organisms exhibit elaborate collective behaviors in response to environmental cues. These behaviors are controlled by complex biochemical networks within individual cells and coordinated through cell-to-cell communication. Describing these behaviors requires new mathematical models that can bridge scales—from biochemical networks within individual cells to spatially structured cellular populations. Here we present a family of "multiscale" models for the emergence of spiral waves in the social amoeba Dictyostelium discoideum. Our models exploit new experimental advances that allow for the direct measurement and manipulation of the small signaling molecule cyclic adenosine monophosphate (cAMP) used by Dictyostelium cells to coordinate behavior in cellular populations. Inspired by recent experiments, we model the Dictyostelium signaling network as an excitable system coupled to various preprocessing modules. We use this family of models to study spatially unstructured populations of "fixed" cells by constructing phase diagrams that relate the properties of population-level oscillations to parameters in the underlying biochemical network. We then briefly discuss an extension of our model that includes spatial structure and show how this naturally gives rise to spiral waves. Our models exhibit a wide range of novel phenomena. including a density-dependent frequency change, bistability, and dynamic death due to slow cAMP dynamics. Our modeling approach provides a powerful tool for bridging scales in modeling of Dictyostelium populations.

NEPTUNE'S WILD DAYS: CONSTRAINTS FROM THE ECCENTRICITY DISTRIBUTION OF THE CLASSICAL KUIPER BELT

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

Dawson, Rebekah I.; Murray-Clay, Ruth, E-mail: rdawson@cfa.harvard.edu

2012-05-01

Neptune's dynamical history shaped the current orbits of Kuiper Belt objects (KBOs), leaving clues to the planet's orbital evolution. In the 'classical' region, a population of dynamically 'hot' high-inclination KBOs overlies a flat 'cold' population with distinct physical properties. Simulations of qualitatively different histories for Neptune, including smooth migration on a circular orbit or scattering by other planets to a high eccentricity, have not simultaneously produced both populations. We explore a general Kuiper Belt assembly model that forms hot classical KBOs interior to Neptune and delivers them to the classical region, where the cold population forms in situ. First, wemore » present evidence that the cold population is confined to eccentricities well below the limit dictated by long-term survival. Therefore, Neptune must deliver hot KBOs into the long-term survival region without excessively exciting the eccentricities of the cold population. Imposing this constraint, we explore the parameter space of Neptune's eccentricity and eccentricity damping, migration, and apsidal precession. We rule out much of parameter space, except where Neptune is scattered to a moderately eccentric orbit (e > 0.15) and subsequently migrates a distance {Delta}a{sub N} = 1-6 AU. Neptune's moderate eccentricity must either damp quickly or be accompanied by fast apsidal precession. We find that Neptune's high eccentricity alone does not generate a chaotic sea in the classical region. Chaos can result from Neptune's interactions with Uranus, exciting the cold KBOs and placing additional constraints. Finally, we discuss how to interpret our constraints in the context of the full, complex dynamical history of the solar system.« less

A model of ecological and evolutionary consequences of color polymorphism.

PubMed

Forsman, Anders; Ahnesjö, Jonas; Caesar, Sofia; Karlsson, Magnus

2008-01-01

We summarize direct and indirect effects on fitness components of animal color pattern and present a synthesis of theories concerning the ecological and evolutionary dynamics of chromatic multiple niche polymorphisms. Previous endeavors have aimed primarily at identifying conditions that promote the evolution and maintenance of polymorphisms. We consider in a conceptual model also the reciprocal influence of color polymorphism on population processes and propose that polymorphism entails selective advantages that may promote the ecological success of polymorphic species. The model begins with an evolutionary branching event from mono- to polymorphic condition that, under the influence of correlational selection, is predicted to promote the evolution of physical integration of coloration and other traits (cf. multi-trait coevolution and complex phenotypes). We propose that the coexistence within a population of alternative ecomorphs with coadapted gene complexes promotes utilization of diverse environmental resources, population stability and persistence, colonization success, and range expansions, and enhances the evolutionary potential and speciation. Conversely, we predict polymorphic populations to be less vulnerable to environmental change and at lower risk of range contractions and extinctions compared with monomorphic populations. We offer brief suggestions as to how these falsifiable predictions may be tested.

A longitudinal cohort study of malaria exposure and changing serostatus in a malaria endemic area of rural Tanzania.

PubMed

Simmons, Ryan A; Mboera, Leonard; Miranda, Marie Lynn; Morris, Alison; Stresman, Gillian; Turner, Elizabeth L; Kramer, Randall; Drakeley, Chris; O'Meara, Wendy P

2017-08-02

Measurements of anti-malarial antibodies are increasingly used as a proxy of transmission intensity. Most serological surveys are based on the use of cross-sectional data that, when age-stratified, approximates historical patterns of transmission within a population. Comparatively few studies leverage longitudinal data to explicitly relate individual infection events with subsequent antibody responses. The occurrence of seroconversion and seroreversion events for two Plasmodium falciparum asexual stage antigens (MSP-1 and AMA-1) was examined using three annual measurements of 691 individuals from a cohort of individuals in a malaria-endemic area of rural east-central Tanzania. Mixed-effect logistic regression models were employed to determine factors associated with changes in serostatus over time. While the expected population-level relationship between seroprevalence and disease incidence was observed, on an individual level the relationship between individual infections and the antibody response was complex. MSP-1 antibody responses were more dynamic in response to the occurrence and resolution of infection events than AMA-1, while the latter was more correlated with consecutive infections. The MSP-1 antibody response to an observed infection seemed to decay faster over time than the corresponding AMA-1 response. Surprisingly, there was no evidence of an age effect on the occurrence of a conversion or reversion event. While the population-level results concur with previously published sero-epidemiological surveys, the individual-level results highlight the more complex relationship between detected infections and antibody dynamics than can be analysed using cross-sectional data. The longitudinal analysis of serological data may provide a powerful tool for teasing apart the complex relationship between infection events and the corresponding immune response, thereby improving the ability to rapidly assess the success or failure of malaria control programmes.

How Random Is Social Behaviour? Disentangling Social Complexity through the Study of a Wild House Mouse Population

PubMed Central

Perony, Nicolas; Tessone, Claudio J.; König, Barbara; Schweitzer, Frank

2012-01-01

Out of all the complex phenomena displayed in the behaviour of animal groups, many are thought to be emergent properties of rather simple decisions at the individual level. Some of these phenomena may also be explained by random processes only. Here we investigate to what extent the interaction dynamics of a population of wild house mice (Mus domesticus) in their natural environment can be explained by a simple stochastic model. We first introduce the notion of perceptual landscape, a novel tool used here to describe the utilisation of space by the mouse colony based on the sampling of individuals in discrete locations. We then implement the behavioural assumptions of the perceptual landscape in a multi-agent simulation to verify their accuracy in the reproduction of observed social patterns. We find that many high-level features – with the exception of territoriality – of our behavioural dataset can be accounted for at the population level through the use of this simplified representation. Our findings underline the potential importance of random factors in the apparent complexity of the mice's social structure. These results resonate in the general context of adaptive behaviour versus elementary environmental interactions. PMID:23209394

A method for evaluating cognitively informed micro-targeted campaign strategies: An agent-based model proof of principle

PubMed Central

Pilditch, Toby D.

2018-01-01

In political campaigns, perceived candidate credibility influences the persuasiveness of messages. In campaigns aiming to influence people’s beliefs, micro-targeted campaigns (MTCs) that target specific voters using their psychological profile have become increasingly prevalent. It remains open how effective MTCs are, notably in comparison to population-targeted campaign strategies. Using an agent-based model, the paper applies recent insights from cognitive models of persuasion, extending them to the societal level in a novel framework for exploring political campaigning. The paper provides an initial treatment of the complex dynamics of population level political campaigning in a psychologically informed manner. Model simulations show that MTCs can take advantage of the psychology of the electorate by targeting voters favourable disposed towards the candidate. Relative to broad campaigning, MTCs allow for efficient and adaptive management of complex campaigns. Findings show that disliked MTC candidates can beat liked population-targeting candidates, pointing to societal questions concerning campaign regulations. PMID:29634722

Origin, Spread and Demography of the Mycobacterium tuberculosis Complex

PubMed Central

Wirth, Thierry; Hildebrand, Falk; Allix-Béguec, Caroline; Wölbeling, Florian; Kubica, Tanja; Kremer, Kristin; van Soolingen, Dick; Rüsch-Gerdes, Sabine; Locht, Camille; Brisse, Sylvain; Meyer, Axel

2008-01-01

The evolutionary timing and spread of the Mycobacterium tuberculosis complex (MTBC), one of the most successful groups of bacterial pathogens, remains largely unknown. Here, using mycobacterial tandem repeat sequences as genetic markers, we show that the MTBC consists of two independent clades, one composed exclusively of M. tuberculosis lineages from humans and the other composed of both animal and human isolates. The latter also likely derived from a human pathogenic lineage, supporting the hypothesis of an original human host. Using Bayesian statistics and experimental data on the variability of the mycobacterial markers in infected patients, we estimated the age of the MTBC at 40,000 years, coinciding with the expansion of “modern” human populations out of Africa. Furthermore, coalescence analysis revealed a strong and recent demographic expansion in almost all M. tuberculosis lineages, which coincides with the human population explosion over the last two centuries. These findings thus unveil the dynamic dimension of the association between human host and pathogen populations. PMID:18802459

A method for evaluating cognitively informed micro-targeted campaign strategies: An agent-based model proof of principle.

PubMed

Madsen, Jens Koed; Pilditch, Toby D

2018-01-01

In political campaigns, perceived candidate credibility influences the persuasiveness of messages. In campaigns aiming to influence people's beliefs, micro-targeted campaigns (MTCs) that target specific voters using their psychological profile have become increasingly prevalent. It remains open how effective MTCs are, notably in comparison to population-targeted campaign strategies. Using an agent-based model, the paper applies recent insights from cognitive models of persuasion, extending them to the societal level in a novel framework for exploring political campaigning. The paper provides an initial treatment of the complex dynamics of population level political campaigning in a psychologically informed manner. Model simulations show that MTCs can take advantage of the psychology of the electorate by targeting voters favourable disposed towards the candidate. Relative to broad campaigning, MTCs allow for efficient and adaptive management of complex campaigns. Findings show that disliked MTC candidates can beat liked population-targeting candidates, pointing to societal questions concerning campaign regulations.

A framework for complexity in palliative care: A qualitative study with patients, family carers and professionals.

PubMed

Pask, Sophie; Pinto, Cathryn; Bristowe, Katherine; van Vliet, Liesbeth; Nicholson, Caroline; Evans, Catherine J; George, Rob; Bailey, Katharine; Davies, Joanna M; Guo, Ping; Daveson, Barbara A; Higginson, Irene J; Murtagh, Fliss Em

2018-06-01

Palliative care patients are often described as complex but evidence on complexity is limited. We need to understand complexity, including at individual patient-level, to define specialist palliative care, characterise palliative care populations and meaningfully compare interventions/outcomes. To explore palliative care stakeholders' views on what makes a patient more or less complex and insights on capturing complexity at patient-level. In-depth qualitative interviews, analysed using Framework analysis. Semi-structured interviews across six UK centres with patients, family, professionals, managers and senior leads, purposively sampled by experience, background, location and setting (hospital, hospice and community). 65 participants provided an understanding of complexity, which extended far beyond the commonly used physical, psychological, social and spiritual domains. Complexity included how patients interact with family/professionals, how services' respond to needs and societal perspectives on care. 'Pre-existing', 'cumulative' and 'invisible' complexity are further important dimensions to delivering effective palliative and end-of-life care. The dynamic nature of illness and needs over time was also profoundly influential. Adapting Bronfenbrenner's Ecological Systems Theory, we categorised findings into the microsystem (person, needs and characteristics), chronosystem (dynamic influences of time), mesosystem (interactions with family/health professionals), exosystem (palliative care services/systems) and macrosystem (societal influences). Stakeholders found it acceptable to capture complexity at the patient-level, with perceived benefits for improving palliative care resource allocation. Our conceptual framework encompasses additional elements beyond physical, psychological, social and spiritual domains and advances systematic understanding of complexity within the context of palliative care. This framework helps capture patient-level complexity and target resource provision in specialist palliative care.

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

PubMed Central

Lancelot, Renaud; Lesnoff, Matthieu

2016-01-01

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

A Gompertz population model with Allee effect and fuzzy initial values

NASA Astrophysics Data System (ADS)

Amarti, Zenia; Nurkholipah, Nenden Siti; Anggriani, Nursanti; Supriatna, Asep K.

2018-03-01

Growth and population dynamics models are important tools used in preparing a good management for society to predict the future of population or species. This has been done by various known methods, one among them is by developing a mathematical model that describes population growth. Models are usually formed into differential equations or systems of differential equations, depending on the complexity of the underlying properties of the population. One example of biological complexity is Allee effect. It is a phenomenon showing a high correlation between very small population size and the mean individual fitness of the population. In this paper the population growth model used is the Gompertz equation model by considering the Allee effect on the population. We explore the properties of the solution to the model numerically using the Runge-Kutta method. Further exploration is done via fuzzy theoretical approach to accommodate uncertainty of the initial values of the model. It is known that an initial value greater than the Allee threshold will cause the solution rises towards carrying capacity asymptotically. However, an initial value smaller than the Allee threshold will cause the solution decreases towards zero asymptotically, which means the population is eventually extinct. Numerical solutions show that modeling uncertain initial value of the critical point A (the Allee threshold) with a crisp initial value could cause the extinction of population of a certain possibilistic degree, depending on the predetermined membership function of the initial value.

Complex discrete dynamics from simple continuous population models.

PubMed

Gamarra, Javier G P; Solé, Ricard V

2002-05-01

Nonoverlapping generations have been classically modelled as difference equations in order to account for the discrete nature of reproductive events. However, other events such as resource consumption or mortality are continuous and take place in the within-generation time. We have realistically assumed a hybrid ODE bidimensional model of resources and consumers with discrete events for reproduction. Numerical and analytical approaches showed that the resulting dynamics resembles a Ricker map, including the doubling route to chaos. Stochastic simulations with a handling-time parameter for indirect competition of juveniles may affect the qualitative behaviour of the model.

The brain as a dynamic physical system.

PubMed

McKenna, T M; McMullen, T A; Shlesinger, M F

1994-06-01

The brain is a dynamic system that is non-linear at multiple levels of analysis. Characterization of its non-linear dynamics is fundamental to our understanding of brain function. Identifying families of attractors in phase space analysis, an approach which has proven valuable in describing non-linear mechanical and electrical systems, can prove valuable in describing a range of behaviors and associated neural activity including sensory and motor repertoires. Additionally, transitions between attractors may serve as useful descriptors for analysing state changes in neurons and neural ensembles. Recent observations of synchronous neural activity, and the emerging capability to record the spatiotemporal dynamics of neural activity by voltage-sensitive dyes and electrode arrays, provide opportunities for observing the population dynamics of neural ensembles within a dynamic systems context. New developments in the experimental physics of complex systems, such as the control of chaotic systems, selection of attractors, attractor switching and transient states, can be a source of powerful new analytical tools and insights into the dynamics of neural systems.

Analysis and prediction of pest dynamics in an agroforestry context using Tiko'n, a generic tool to develop food web models

NASA Astrophysics Data System (ADS)

Rojas, Marcela; Malard, Julien; Adamowski, Jan; Carrera, Jaime Luis; Maas, Raúl

2017-04-01

While it is known that climate change will impact future plant-pest population dynamics, potentially affecting crop damage, agroforestry with its enhanced biodiversity is said to reduce the outbreaks of pest insects by providing natural enemies for the control of pest populations. This premise is known in the literature as the natural enemy hypothesis and has been widely studied qualitatively. However, disagreement still exists on whether biodiversity enhancement reduces pest outbreaks, showing the need of quantitatively understanding the mechanisms behind the interactions between pests and natural enemies, also known as trophic interactions. Crop pest models that study insect population dynamics in agroforestry contexts are very rare, and pest models that take trophic interactions into account are even rarer. This may be due to the difficulty of representing complex food webs in a quantifiable model. There is therefore a need for validated food web models that allow users to predict the response of these webs to changes in climate in agroforestry systems. In this study we present Tiko'n, a Python-based software whose API allows users to rapidly build and validate trophic web models; the program uses a Bayesian inference approach to calibrate the models according to field data, allowing for the reuse of literature data from various sources and reducing the need for extensive field data collection. Tiko'n was run using coffee leaf miner (Leucoptera coffeella) and associated parasitoid data from a shaded coffee plantation, showing the mechanisms of insect population dynamics within a tri-trophic food web in an agroforestry system.

Dimensionality and entropy of spontaneous and evoked rate activity

NASA Astrophysics Data System (ADS)

Engelken, Rainer; Wolf, Fred

Cortical circuits exhibit complex activity patterns both spontaneously and evoked by external stimuli. Finding low-dimensional structure in population activity is a challenge. What is the diversity of the collective neural activity and how is it affected by an external stimulus? Using concepts from ergodic theory, we calculate the attractor dimensionality and dynamical entropy production of these networks. We obtain these two canonical measures of the collective network dynamics from the full set of Lyapunov exponents. We consider a randomly-wired firing-rate network that exhibits chaotic rate fluctuations for sufficiently strong synaptic weights. We show that dynamical entropy scales logarithmically with synaptic coupling strength, while the attractor dimensionality saturates. Thus, despite the increasing uncertainty, the diversity of collective activity saturates for strong coupling. We find that a time-varying external stimulus drastically reduces both entropy and dimensionality. Finally, we analytically approximate the full Lyapunov spectrum in several limiting cases by random matrix theory. Our study opens a novel avenue to characterize the complex dynamics of rate networks and the geometric structure of the corresponding high-dimensional chaotic attractor. received funding from Evangelisches Studienwerk Villigst, DFG through CRC 889 and Volkswagen Foundation.

New Mycobacterium tuberculosis Complex Sublineage, Brazzaville, Congo

PubMed Central

Malm, Sven; Linguissi, Laure S. Ghoma; Tekwu, Emmanuel M.; Vouvoungui, Jeannhey C.; Kohl, Thomas A.; Beckert, Patrick; Sidibe, Anissa; Rüsch-Gerdes, Sabine; Madzou-Laboum, Igor K.; Kwedi, Sylvie; Penlap Beng, Véronique; Frank, Matthias; Ntoumi, Francine

2017-01-01

Tuberculosis is a leading cause of illness and death in Congo. No data are available about the population structure and transmission dynamics of the Mycobacterium tuberculosis complex strains prevalent in this central Africa country. On the basis of single-nucleotide polymorphisms detected by whole-genome sequencing, we phylogenetically characterized 74 MTBC isolates from Brazzaville, the capital of Congo. The diversity of the study population was high; most strains belonged to the Euro-American lineage, which split into Latin American Mediterranean, Uganda I, Uganda II, Haarlem, X type, and a new dominant sublineage named Congo type (n = 26). Thirty strains were grouped in 5 clusters (each within 12 single-nucleotide polymorphisms), from which 23 belonged to the Congo type. High cluster rates and low genomic diversity indicate recent emergence and transmission of the Congo type, a new Euro-American sublineage of MTBC. PMID:28221129

New Mycobacterium tuberculosis Complex Sublineage, Brazzaville, Congo.

PubMed

Malm, Sven; Linguissi, Laure S Ghoma; Tekwu, Emmanuel M; Vouvoungui, Jeannhey C; Kohl, Thomas A; Beckert, Patrick; Sidibe, Anissa; Rüsch-Gerdes, Sabine; Madzou-Laboum, Igor K; Kwedi, Sylvie; Penlap Beng, Véronique; Frank, Matthias; Ntoumi, Francine; Niemann, Stefan

2017-03-01

Tuberculosis is a leading cause of illness and death in Congo. No data are available about the population structure and transmission dynamics of the Mycobacterium tuberculosis complex strains prevalent in this central Africa country. On the basis of single-nucleotide polymorphisms detected by whole-genome sequencing, we phylogenetically characterized 74 MTBC isolates from Brazzaville, the capital of Congo. The diversity of the study population was high; most strains belonged to the Euro-American lineage, which split into Latin American Mediterranean, Uganda I, Uganda II, Haarlem, X type, and a new dominant sublineage named Congo type (n = 26). Thirty strains were grouped in 5 clusters (each within 12 single-nucleotide polymorphisms), from which 23 belonged to the Congo type. High cluster rates and low genomic diversity indicate recent emergence and transmission of the Congo type, a new Euro-American sublineage of MTBC.

Greater than the sum of its parts? Modelling population contact and interaction of cultural repertoires

PubMed Central

Kolodny, Oren; Feldman, Marcus W.

2017-01-01

Evidence for interactions between populations plays a prominent role in the reconstruction of historical and prehistoric human dynamics; these interactions are usually interpreted to reflect cultural practices or demographic processes. The sharp increase in long-distance transportation of lithic material between the Middle and Upper Palaeolithic, for example, is seen as a manifestation of the cultural revolution that defined the transition between these epochs. Here, we propose that population interaction is not only a reflection of cultural change but also a potential driver of it. We explore the possible effects of inter-population migration on cultural evolution when migrating individuals possess core technological knowledge from their original population. Using a computational framework of cultural evolution that incorporates realistic aspects of human innovation processes, we show that migration can lead to a range of outcomes, including punctuated but transient increases in cultural complexity, an increase of cultural complexity to an elevated steady state and the emergence of a positive feedback loop that drives ongoing acceleration in cultural accumulation. Our findings suggest that population contact may have played a crucial role in the evolution of hominin cultures and propose explanations for observations of Palaeolithic cultural change whose interpretations have been hotly debated. PMID:28468920

A method for the direct measurement of electronic site populations in a molecular aggregate using two-dimensional electronic-vibrational spectroscopy

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

Lewis, Nicholas H. C.; Dong, Hui; Oliver, Thomas A. A.

2015-09-28

Two dimensional electronic spectroscopy has proven to be a valuable experimental technique to reveal electronic excitation dynamics in photosynthetic pigment-protein complexes, nanoscale semiconductors, organic photovoltaic materials, and many other types of systems. It does not, however, provide direct information concerning the spatial structure and dynamics of excitons. 2D infrared spectroscopy has become a widely used tool for studying structural dynamics but is incapable of directly providing information concerning electronic excited states. 2D electronic-vibrational (2DEV) spectroscopy provides a link between these domains, directly connecting the electronic excitation with the vibrational structure of the system under study. In this work, we derivemore » response functions for the 2DEV spectrum of a molecular dimer and propose a method by which 2DEV spectra could be used to directly measure the electronic site populations as a function of time following the initial electronic excitation. We present results from the response function simulations which show that our proposed approach is substantially valid. This method provides, to our knowledge, the first direct experimental method for measuring the electronic excited state dynamics in the spatial domain, on the molecular scale.« less

A method for the direct measurement of electronic site populations in a molecular aggregate using two-dimensional electronic-vibrational spectroscopy

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

Lewis, Nicholas H. C.; Dong, Hui; Oliver, Thomas A. A.

2015-09-28

Two dimensional electronic spectroscopy has proved to be a valuable experimental technique to reveal electronic excitation dynamics in photosynthetic pigment-protein complexes, nanoscale semiconductors, organic photovoltaic materials, and many other types of systems. It does not, however, provide direct information concerning the spatial structure and dynamics of excitons. 2D infrared spectroscopy has become a widely used tool for studying structural dynamics but is incapable of directly providing information concerning electronic excited states. 2D electronic-vibrational (2DEV) spectroscopy provides a link between these domains, directly connecting the electronic excitation with the vibrational structure of the system under study. In this work, we derivemore » response functions for the 2DEV spectrum of a molecular dimer and propose a method by which 2DEV spectra could be used to directly measure the electronic site populations as a function of time following the initial electronic excitation. We present results from the response function simulations which show that our proposed approach is substantially valid. This method provides, to our knowledge, the first direct experimental method for measuring the electronic excited state dynamics in the spatial domain, on the molecular scale.« less

A method for the direct measurement of electronic site populations in a molecular aggregate using two-dimensional electronic-vibrational spectroscopy.

PubMed

Lewis, Nicholas H C; Dong, Hui; Oliver, Thomas A A; Fleming, Graham R

2015-09-28

Two dimensional electronic spectroscopy has proved to be a valuable experimental technique to reveal electronic excitation dynamics in photosynthetic pigment-protein complexes, nanoscale semiconductors, organic photovoltaic materials, and many other types of systems. It does not, however, provide direct information concerning the spatial structure and dynamics of excitons. 2D infrared spectroscopy has become a widely used tool for studying structural dynamics but is incapable of directly providing information concerning electronic excited states. 2D electronic-vibrational (2DEV) spectroscopy provides a link between these domains, directly connecting the electronic excitation with the vibrational structure of the system under study. In this work, we derive response functions for the 2DEV spectrum of a molecular dimer and propose a method by which 2DEV spectra could be used to directly measure the electronic site populations as a function of time following the initial electronic excitation. We present results from the response function simulations which show that our proposed approach is substantially valid. This method provides, to our knowledge, the first direct experimental method for measuring the electronic excited state dynamics in the spatial domain, on the molecular scale.

Dynamic portrait of the region occupied by the Hungaria Asteroids: The influence of Mars

NASA Astrophysics Data System (ADS)

Correa-Otto, J. A.; Cañada-Assandri, M.

2018-06-01

The region occupied by the Hungaria asteroids has a high dynamical complexity. In this paper, we analyse the main dynamic structures and their influence on the known asteroids through the construction of maps of initial conditions. We evolve a set of test particles placed on a perfectly rectangular grid of initial conditions during 3 Myr under the gravitational influence of the Sun and eight planets, from Mercury to Neptune. Moreover, we use the method MEGNO in order to obtain a complete dynamical portrait of the region. A comparison of our maps with the distribution of real objects allows us to detect the main dynamical mechanisms acting in the domain under study such as mean-motion and secular resonances. Our main results is the existence of a small area inside a stable region where are placed the Hungaria asteroids. We found that the influence of Mars has an important role for the dynamic structure of the region, defining the limits for this population of asteroids. Our result is in agreement with previous studies, which have indicated the importance of the eccentricity of Mars for the stability of Hungaria asteroids. However, we found that the secular resonance resulting from the precession of perihelion due to a coupling with that of Jupiter proposed as limit for the Hungaria region could not be determinant for this population of asteroids.

Direct and indirect effects of climate change on amphibian populations

USGS Publications Warehouse

Blaustein, Andrew R.; Walls, Susan C.; Bancroft, Betsy A.; Lawler, Joshua J.; Searle, Catherine L.; Gervasi, Stephanie S.

2010-01-01

As part of an overall decline in biodiversity, populations of many organisms are declining and species are being lost at unprecedented rates around the world. This includes many populations and species of amphibians. Although numerous factors are affecting amphibian populations, we show potential direct and indirect effects of climate change on amphibians at the individual, population and community level. Shifts in amphibian ranges are predicted. Changes in climate may affect survival, growth, reproduction and dispersal capabilities. Moreover, climate change can alter amphibian habitats including vegetation, soil, and hydrology. Climate change can influence food availability, predator-prey relationships and competitive interactions which can alter community structure. Climate change can also alter pathogen-host dynamics and greatly influence how diseases are manifested. Changes in climate can interact with other stressors such as UV-B radiation and contaminants. The interactions among all these factors are complex and are probably driving some amphibian population declines and extinctions.

Identifying Reservoirs of Infection: A Conceptual and Practical Challenge

PubMed Central

2002-01-01

Many infectious agents, especially those that cause emerging diseases, infect more than one host species. Managing reservoirs of multihost pathogens often plays a crucial role in effective disease control. However, reservoirs remain variously and loosely defined. We propose that reservoirs can only be understood with reference to defined target populations. Therefore, we define a reservoir as one or more epidemiologically connected populations or environments in which the pathogen can be permanently maintained and from which infection is transmitted to the defined target population. Existence of a reservoir is confirmed when infection within the target population cannot be sustained after all transmission between target and nontarget populations has been eliminated. When disease can be controlled solely by interventions within target populations, little knowledge of potentially complex reservoir infection dynamics is necessary for effective control. We discuss the practical value of different approaches that may be used to identify reservoirs in the field. PMID:12498665

Noisy Oscillations in the Actin Cytoskeleton of Chemotactic Amoeba.

PubMed

Negrete, Jose; Pumir, Alain; Hsu, Hsin-Fang; Westendorf, Christian; Tarantola, Marco; Beta, Carsten; Bodenschatz, Eberhard

2016-09-30

Biological systems with their complex biochemical networks are known to be intrinsically noisy. Here we investigate the dynamics of actin polymerization of amoeboid cells, which are close to the onset of oscillations. We show that the large phenotypic variability in the polymerization dynamics can be accurately captured by a generic nonlinear oscillator model in the presence of noise. We determine the relative role of the noise with a single dimensionless, experimentally accessible parameter, thus providing a quantitative description of the variability in a population of cells. Our approach, which rests on a generic description of a system close to a Hopf bifurcation and includes the effect of noise, can characterize the dynamics of a large class of noisy systems close to an oscillatory instability.

Noisy Oscillations in the Actin Cytoskeleton of Chemotactic Amoeba

NASA Astrophysics Data System (ADS)

Negrete, Jose; Pumir, Alain; Hsu, Hsin-Fang; Westendorf, Christian; Tarantola, Marco; Beta, Carsten; Bodenschatz, Eberhard

2016-09-01

Biological systems with their complex biochemical networks are known to be intrinsically noisy. Here we investigate the dynamics of actin polymerization of amoeboid cells, which are close to the onset of oscillations. We show that the large phenotypic variability in the polymerization dynamics can be accurately captured by a generic nonlinear oscillator model in the presence of noise. We determine the relative role of the noise with a single dimensionless, experimentally accessible parameter, thus providing a quantitative description of the variability in a population of cells. Our approach, which rests on a generic description of a system close to a Hopf bifurcation and includes the effect of noise, can characterize the dynamics of a large class of noisy systems close to an oscillatory instability.

The effects of landscape modifications on the long-term persistence of animal populations.

PubMed

Nabe-Nielsen, Jacob; Sibly, Richard M; Forchhammer, Mads C; Forbes, Valery E; Topping, Christopher J

2010-01-28

The effects of landscape modifications on the long-term persistence of wild animal populations is of crucial importance to wildlife managers and conservation biologists, but obtaining experimental evidence using real landscapes is usually impossible. To circumvent this problem we used individual-based models (IBMs) of interacting animals in experimental modifications of a real Danish landscape. The models incorporate as much as possible of the behaviour and ecology of four species with contrasting life-history characteristics: skylark (Alauda arvensis), vole (Microtus agrestis), a ground beetle (Bembidion lampros) and a linyphiid spider (Erigone atra). This allows us to quantify the population implications of experimental modifications of landscape configuration and composition. Starting with a real agricultural landscape, we progressively reduced landscape complexity by (i) homogenizing habitat patch shapes, (ii) randomizing the locations of the patches, and (iii) randomizing the size of the patches. The first two steps increased landscape fragmentation. We assessed the effects of these manipulations on the long-term persistence of animal populations by measuring equilibrium population sizes and time to recovery after disturbance. Patch rearrangement and the presence of corridors had a large effect on the population dynamics of species whose local success depends on the surrounding terrain. Landscape modifications that reduced population sizes increased recovery times in the short-dispersing species, making small populations vulnerable to increasing disturbance. The species that were most strongly affected by large disturbances fluctuated little in population sizes in years when no perturbations took place. Traditional approaches to the management and conservation of populations use either classical methods of population analysis, which fail to adequately account for the spatial configurations of landscapes, or landscape ecology, which accounts for landscape structure but has difficulty predicting the dynamics of populations living in them. Here we show how realistic and replicable individual-based models can bridge the gap between non-spatial population theory and non-dynamic landscape ecology. A major strength of the approach is its ability to identify population vulnerabilities not detected by standard population viability analyses.

Complexity and Intermittent Turbulence in Space Plasmas

NASA Technical Reports Server (NTRS)

Chang, Tom; Tam, Sunny W. Y.; Wu, Cheng-Chin

2004-01-01

Sporadic and localized interactions of coherent structures arising from plasma resonances can be the origin of "complexity" of the coexistence of non- propagating spatiotemporal fluctuations and propagating modes in space plasmas. Numerical simulation results are presented to demonstrate the intermittent character of the non-propagating fluctuations. The technique of the dynamic renormalization-group is introduced and applied to the study of scale invariance of such type of multiscale fluctuations. We also demonstrate that the particle interactions with the intermittent turbulence can lead to the efficient energization of the plasma populations. An example related to the ion acceleration processes in the auroral zone is provided.

A white-box model of S-shaped and double S-shaped single-species population growth

PubMed Central

Kalmykov, Lev V.

2015-01-01

Complex systems may be mechanistically modelled by white-box modeling with using logical deterministic individual-based cellular automata. Mathematical models of complex systems are of three types: black-box (phenomenological), white-box (mechanistic, based on the first principles) and grey-box (mixtures of phenomenological and mechanistic models). Most basic ecological models are of black-box type, including Malthusian, Verhulst, Lotka–Volterra models. In black-box models, the individual-based (mechanistic) mechanisms of population dynamics remain hidden. Here we mechanistically model the S-shaped and double S-shaped population growth of vegetatively propagated rhizomatous lawn grasses. Using purely logical deterministic individual-based cellular automata we create a white-box model. From a general physical standpoint, the vegetative propagation of plants is an analogue of excitation propagation in excitable media. Using the Monte Carlo method, we investigate a role of different initial positioning of an individual in the habitat. We have investigated mechanisms of the single-species population growth limited by habitat size, intraspecific competition, regeneration time and fecundity of individuals in two types of boundary conditions and at two types of fecundity. Besides that, we have compared the S-shaped and J-shaped population growth. We consider this white-box modeling approach as a method of artificial intelligence which works as automatic hyper-logical inference from the first principles of the studied subject. This approach is perspective for direct mechanistic insights into nature of any complex systems. PMID:26038717

Copper(II) adsorption on the kaolinite(001) surface: Insights from first-principles calculations and molecular dynamics simulations

NASA Astrophysics Data System (ADS)

Kong, Xiang-Ping; Wang, Juan

2016-12-01

The adsorption behavior of Cu(II) on the basal hydroxylated kaolinite(001) surface in aqueous environment was investigated by first-principles calculations and molecular dynamics simulations. Structures of possible monodentate and bidentate inner-sphere adsorption complexes of Cu(II) were examined, and the charge transfer and bonding mechanism were analyzed. Combining the binding energy of complex, the radial distribution function of Cu(II) with oxygen and the extended X-ray absorption fine structure data, monodentate complex on site of surface oxygen with ;upright; hydrogen and bidentate complex on site of two oxygens (one with ;upright; hydrogen and one with ;lying; hydrogen) of single Al center have been found to be the major adsorption species of Cu(II). Both adsorption species are four-coordinated with a square planar geometry. The distribution of surface hydroxyls with ;lying; hydrogen around Cu(II) plays a key role in the structure and stability of adsorption complex. Upon the Mulliken population analysis and partial density of states, charge transfer occurs with Cu(II) accepting some electrons from both surface oxygens and aqua oxygens, and the bonding Cu 3d-O 2p state filling is primarily responsible for the strong covalent interaction of Cu(II) with surface oxygen.

Network complexity as a measure of information processing across resting-state networks: evidence from the Human Connectome Project

PubMed Central

McDonough, Ian M.; Nashiro, Kaoru

2014-01-01

An emerging field of research focused on fluctuations in brain signals has provided evidence that the complexity of those signals, as measured by entropy, conveys important information about network dynamics (e.g., local and distributed processing). While much research has focused on how neural complexity differs in populations with different age groups or clinical disorders, substantially less research has focused on the basic understanding of neural complexity in populations with young and healthy brain states. The present study used resting-state fMRI data from the Human Connectome Project (Van Essen et al., 2013) to test the extent that neural complexity in the BOLD signal, as measured by multiscale entropy (1) would differ from random noise, (2) would differ between four major resting-state networks previously associated with higher-order cognition, and (3) would be associated with the strength and extent of functional connectivity—a complementary method of estimating information processing. We found that complexity in the BOLD signal exhibited different patterns of complexity from white, pink, and red noise and that neural complexity was differentially expressed between resting-state networks, including the default mode, cingulo-opercular, left and right frontoparietal networks. Lastly, neural complexity across all networks was negatively associated with functional connectivity at fine scales, but was positively associated with functional connectivity at coarse scales. The present study is the first to characterize neural complexity in BOLD signals at a high temporal resolution and across different networks and might help clarify the inconsistencies between neural complexity and functional connectivity, thus informing the mechanisms underlying neural complexity. PMID:24959130

Information Complexity and Biology

NASA Astrophysics Data System (ADS)

Bagnoli, Franco; Bignone, Franco A.; Cecconi, Fabio; Politi, Antonio

Kolmogorov contributed directly to Biology in essentially three problems: the analysis of population dynamics (Lotka-Volterra equations), the reaction-diffusion formulation of gene spreading (FKPP equation), and some discussions about Mendel's laws. However, the widely recognized importance of his contribution arises from his work on algorithmic complexity. In fact, the limited direct intervention in Biology reflects the generally slow growth of interest of mathematicians towards biological issues. From the early work of Vito Volterra on species competition, to the slow growth of dynamical systems theory, contributions to the study of matter and the physiology of the nervous system, the first 50-60 years have witnessed important contributions, but as scattered pieces apparently uncorrelated, and in branches often far away from Biology. Up to the 40' it is hard to see the initial loose build up of a convergence, for those theories that will become mainstream research by the end of the century, and connected by the study of biological systems per-se.

Mapping the conformational landscape of a dynamic enzyme by multitemperature and XFEL crystallography

DOE PAGES

Keedy, Daniel A.; Kenner, Lillian R.; Warkentin, Matthew; ...

2015-09-30

Determining the interconverting conformations of dynamic proteins in atomic detail is a major challenge for structural biology. Conformational heterogeneity in the active site of the dynamic enzyme cyclophilin A (CypA) has been previously linked to its catalytic function, but the extent to which the different conformations of these residues are correlated is unclear. Here we compare the conformational ensembles of CypA by multitemperature synchrotron crystallography and fixed-target X-ray free-electron laser (XFEL) crystallography. The diffraction-before-destruction nature of XFEL experiments provides a radiation-damage-free view of the functionally important alternative conformations of CypA, confirming earlier synchrotron-based results. We monitored the temperature dependences ofmore » these alternative conformations with eight synchrotron datasets spanning 100-310 K. Multiconformer models show that many alternative conformations in CypA are populated only at 240 K and above, yet others remain populated or become populated at 180 K and below. These results point to a complex evolution of conformational heterogeneity between 180-–240 K that involves both thermal deactivation and solvent-driven arrest of protein motions in the crystal. The lack of a single shared conformational response to temperature within the dynamic active-site network provides evidence for a conformation shuffling model, in which exchange between rotamer states of a large aromatic ring in the middle of the network shifts the conformational ensemble for the other residues in the network. Altogether, our multitemperature analyses and XFEL data motivate a new generation of temperature- and time-resolved experiments to structurally characterize the dynamic underpinnings of protein function.« less

Mapping the conformational landscape of a dynamic enzyme by multitemperature and XFEL crystallography

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

Keedy, Daniel A.; Kenner, Lillian R.; Warkentin, Matthew

Determining the interconverting conformations of dynamic proteins in atomic detail is a major challenge for structural biology. Conformational heterogeneity in the active site of the dynamic enzyme cyclophilin A (CypA) has been previously linked to its catalytic function, but the extent to which the different conformations of these residues are correlated is unclear. Here we compare the conformational ensembles of CypA by multitemperature synchrotron crystallography and fixed-target X-ray free-electron laser (XFEL) crystallography. The diffraction-before-destruction nature of XFEL experiments provides a radiation-damage-free view of the functionally important alternative conformations of CypA, confirming earlier synchrotron-based results. We monitored the temperature dependences ofmore » these alternative conformations with eight synchrotron datasets spanning 100-310 K. Multiconformer models show that many alternative conformations in CypA are populated only at 240 K and above, yet others remain populated or become populated at 180 K and below. These results point to a complex evolution of conformational heterogeneity between 180-–240 K that involves both thermal deactivation and solvent-driven arrest of protein motions in the crystal. The lack of a single shared conformational response to temperature within the dynamic active-site network provides evidence for a conformation shuffling model, in which exchange between rotamer states of a large aromatic ring in the middle of the network shifts the conformational ensemble for the other residues in the network. Together, our multitemperature analyses and XFEL data motivate a new generation of temperature- and time-resolved experiments to structurally characterize the dynamic underpinnings of protein function.« less

Mapping the conformational landscape of a dynamic enzyme by multitemperature and XFEL crystallography

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

Keedy, Daniel A.; Kenner, Lillian R.; Warkentin, Matthew

Determining the interconverting conformations of dynamic proteins in atomic detail is a major challenge for structural biology. Conformational heterogeneity in the active site of the dynamic enzyme cyclophilin A (CypA) has been previously linked to its catalytic function, but the extent to which the different conformations of these residues are correlated is unclear. Here we compare the conformational ensembles of CypA by multitemperature synchrotron crystallography and fixed-target X-ray free-electron laser (XFEL) crystallography. The diffraction-before-destruction nature of XFEL experiments provides a radiation-damage-free view of the functionally important alternative conformations of CypA, confirming earlier synchrotron-based results. We monitored the temperature dependences ofmore » these alternative conformations with eight synchrotron datasets spanning 100-310 K. Multiconformer models show that many alternative conformations in CypA are populated only at 240 K and above, yet others remain populated or become populated at 180 K and below. These results point to a complex evolution of conformational heterogeneity between 180-–240 K that involves both thermal deactivation and solvent-driven arrest of protein motions in the crystal. The lack of a single shared conformational response to temperature within the dynamic active-site network provides evidence for a conformation shuffling model, in which exchange between rotamer states of a large aromatic ring in the middle of the network shifts the conformational ensemble for the other residues in the network. Altogether, our multitemperature analyses and XFEL data motivate a new generation of temperature- and time-resolved experiments to structurally characterize the dynamic underpinnings of protein function.« less

Management of postural sensory conflict and dynamic balance control in late-stage Parkinson's disease.

PubMed

Colnat-Coulbois, S; Gauchard, G C; Maillard, L; Barroche, G; Vespignani, H; Auque, J; Perrin, P P

2011-10-13

Parkinson's disease (PD) is known to affect postural control, especially in situations needing a change in balance strategy or when a concurrent task is simultaneously performed. However, few studies assessing postural control in patients with PD included homogeneous population in late stage of the disease. Thus, this study aimed to analyse postural control and strategies in a homogeneous population of patients with idiopathic advanced (late-stage) PD, and to determine the contribution of peripheral inputs in simple and more complex postural tasks, such as sensory conflicting and dynamic tasks. Twenty-four subjects with advanced PD (duration: median (M)=11.0 years, interquartile range (IQR)=4.3 years; Unified Parkinson's Disease Rating Scale (UPDRS): M "on-dopa"=13.5, IQR=7.8; UPDRS: M "off-dopa"=48.5, IQR=16.8; Hoehn and Yahr stage IV in all patients) and 48 age-matched healthy controls underwent static (SPT) and dynamic posturographic (DPT) tests and a sensory organization test (SOT). In SPT, patients with PD showed reduced postural control precision with increased oscillations in both anterior-posterior and medial-lateral planes. In SOT, patients with PD displayed reduced postural performances especially in situations in which visual and vestibular cues became predominant to organize balance control, as was the ability to manage balance in situations for which visual or proprioceptive inputs are disrupted. In DPT, postural restabilization strategies were often inefficient to maintain equilibrium resulting in falls. Postural strategies were often precarious, postural regulation involving more hip joint than ankle joint in patients with advanced PD than in controls. Difficulties in managing complex postural situations, such as sensory conflicting and dynamic situations might reflect an inadequate sensory organization suggesting impairment in central information processing. Copyright © 2011. Published by Elsevier Ltd.

Coupled effects of vertical mixing and benthic grazing on phytoplankton populations in shallow, turbid estuaries

USGS Publications Warehouse

Koseff, Jeffrey R.; Holen, Jacqueline K.; Monismith, Stephen G.; Cloern, James E.

1993-01-01

Coastal ocean waters tend to have very different patterns of phytoplankton biomass variability from the open ocean, and the connections between physical variability and phytoplankton bloom dynamics are less well established for these shallow systems. Predictions of biological responses to physical variability in these environments is inherently difficult because the recurrent seasonal patterns of mixing are complicated by aperiodic fluctuations in river discharge and the high-frequency components of tidal variability. We might expect, then, less predictable and more complex bloom dynamics in these shallow coastal systems compared with the open ocean. Given this complex and dynamic physical environment, can we develop a quantitative framework to define the physical regimes necessary for bloom inception, and can we identify the important mechanisms of physical-biological coupling that lead to the initiation and termination of blooms in estuaries and shallow coastal waters? Numerical modeling provides one approach to address these questions. Here we present results of simulation experiments with a refined version of Cloern's (1991) model in which mixing processes are treated more realistically to reflect the dynamic nature of turbulence generation in estuaries. We investigated several simple models for the turbulent mixing coefficient. We found that the addition of diurnal tidal variation to Cloern's model greatly reduces biomass growth indicating that variations of mixing on the time scale of hours are crucial. Furthermore, we found that for conditions representative of South San Francisco Bay, numerical simulations only allowed for bloom development when the water column was stratified and when minimal mixing was prescribed in the upper layer. Stratification, however, itself is not sufficient to ensure that a bloom will develop: minimal wind stirring is a further prerequisite to bloom development in shallow turbid estuaries with abundant populations of benthic suspension feeders.

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

PubMed

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

2012-01-01

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

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.

Model-Based Phenotypic Signatures Governing the Dynamics of the Stem and Semi-differentiated Cell Populations in Dysplastic Colonic Crypts.

PubMed

Nikolov, Svetoslav; Santos, Guido; Wolkenhauer, Olaf; Vera, Julio

2018-02-01

Mathematical modeling of cell differentiated in colonic crypts can contribute to a better understanding of basic mechanisms underlying colonic tissue organization, but also its deregulation during carcinogenesis and tumor progression. Here, we combined bifurcation analysis to assess the effect that time delay has in the complex interplay of stem cells and semi-differentiated cells at the niche of colonic crypts, and systematic model perturbation and simulation to find model-based phenotypes linked to cancer progression. The models suggest that stem cell and semi-differentiated cell population dynamics in colonic crypts can display chaotic behavior. In addition, we found that clinical profiling of colorectal cancer correlates with the in silico phenotypes proposed by the mathematical model. Further, potential therapeutic targets for chemotherapy resistant phenotypes are proposed, which in any case will require experimental validation.

Synchronisation and stability in river metapopulation networks.

PubMed

Yeakel, J D; Moore, J W; Guimarães, P R; de Aguiar, M A M

2014-03-01

Spatial structure in landscapes impacts population stability. Two linked components of stability have large consequences for persistence: first, statistical stability as the lack of temporal fluctuations; second, synchronisation as an aspect of dynamic stability, which erodes metapopulation rescue effects. Here, we determine the influence of river network structure on the stability of riverine metapopulations. We introduce an approach that converts river networks to metapopulation networks, and analytically show how fluctuation magnitude is influenced by interaction structure. We show that river metapopulation complexity (in terms of branching prevalence) has nonlinear dampening effects on population fluctuations, and can also buffer against synchronisation. We conclude by showing that river transects generally increase synchronisation, while the spatial scale of interaction has nonlinear effects on synchronised dynamics. Our results indicate that this dual stability - conferred by fluctuation and synchronisation dampening - emerges from interaction structure in rivers, and this may strongly influence the persistence of river metapopulations. © 2013 John Wiley & Sons Ltd/CNRS.

Response of native insect communities to invasive plants.

PubMed

Bezemer, T Martijn; Harvey, Jeffrey A; Cronin, James T

2014-01-01

Invasive plants can disrupt a range of trophic interactions in native communities. As a novel resource they can affect the performance of native insect herbivores and their natural enemies such as parasitoids and predators, and this can lead to host shifts of these herbivores and natural enemies. Through the release of volatile compounds, and by changing the chemical complexity of the habitat, invasive plants can also affect the behavior of native insects such as herbivores, parasitoids, and pollinators. Studies that compare insects on related native and invasive plants in invaded habitats show that the abundance of insect herbivores is often lower on invasive plants, but that damage levels are similar. The impact of invasive plants on the population dynamics of resident insect species has been rarely examined, but invasive plants can influence the spatial and temporal dynamics of native insect (meta)populations and communities, ultimately leading to changes at the landscape level.

High-Redshift Astrophysics Using Every Photon

NASA Astrophysics Data System (ADS)

Breysse, Patrick; Kovetz, Ely; Rahman, Mubdi; Kamionkowski, Marc

2017-01-01

Large galaxy surveys have dramatically improved our understanding of the complex processes which govern gas dynamics and star formation in the nearby universe. However, we know far less about the most distant galaxies, as existing high-redshift observations can only detect the very brightest sources. Intensity mapping surveys provide a promising tool to access this poorly-studied population. By observing emission lines with low angular resolution, these surveys can make use of every photon in a target line to study faint emitters which are inaccessible using traditional techniques. With upcoming carbon monoxide experiments in mind, I will demonstrate how an intensity map can be used to measure the luminosity function of a galaxy population, and in turn how these measurements will allow us to place robust constraints on the cosmic star formation history. I will then show how cross-correlating CO isotopologue lines will make it possible to study gas dynamics within the earliest galaxies in unprecedented detail.

Synchronization in Random Pulse Oscillator Networks

NASA Astrophysics Data System (ADS)

Brown, Kevin; Hermundstad, Ann

Motivated by synchronization phenomena in neural systems, we study synchronization of random networks of coupled pulse oscillators. We begin by considering binomial random networks whose nodes have intrinsic linear dynamics. We quantify order in the network spiking dynamics using a new measure: the normalized Lev-Zimpel complexity (LZC) of the nodes' spike trains. Starting from a globally-synchronized state, we see two broad classes of behaviors. In one (''temporally random''), the LZC is high and nodes spike independently with no coherent pattern. In another (''temporally regular''), the network does not globally synchronize but instead forms coherent, repeating population firing patterns with low LZC. No topological feature of the network reliably predicts whether an individual network will show temporally random or regular behavior; however, we find evidence that degree heterogeneity in binomial networks has a strong effect on the resulting state. To confirm these findings, we generate random networks with independently-adjustable degree mean and variance. We find that the likelihood of temporally-random behavior increases as degree variance increases. Our results indicate the subtle and complex relationship between network structure and dynamics.

Biophysical model of prokaryotic diversity in geothermal hot springs.

PubMed

Klales, Anna; Duncan, James; Nett, Elizabeth Janus; Kane, Suzanne Amador

2012-02-01

Recent studies of photosynthetic bacteria living in geothermal hot spring environments have revealed surprisingly complex ecosystems with an unexpected level of genetic diversity. One case of particular interest involves the distribution along hot spring thermal gradients of genetically distinct bacterial strains that differ in their preferred temperatures for reproduction and photosynthesis. In such systems, a single variable, temperature, defines the relevant environmental variation. In spite of this, each region along the thermal gradient exhibits multiple strains of photosynthetic bacteria adapted to several distinct thermal optima, rather than a single thermal strain adapted to the local environmental temperature. Here we analyze microbiology data from several ecological studies to show that the thermal distribution data exhibit several universal features independent of location and specific bacterial strain. These include the distribution of optimal temperatures of different thermal strains and the functional dependence of the net population density on temperature. We present a simple population dynamics model of these systems that is highly constrained by biophysical data and by physical features of the environment. This model can explain in detail the observed thermal population distributions, as well as certain features of population dynamics observed in laboratory studies of the same organisms. © 2012 American Physical Society

Atomistic non-adiabatic dynamics of the LH2 complex with a GPU-accelerated ab initio exciton model

DOE PAGES

Sisto, Aaron; Stross, Clem; van der Kamp, Marc W.; ...

2017-03-28

We recently outlined an efficient multi-tiered parallel ab initio excitonic framework that utilizes time dependent density functional theory (TDDFT) to calculate ground and excited state energies and gradients of large supramolecular complexes in atomistic detail – enabling us to undertake non-adiabatic simulations which explicitly account for the coupled anharmonic vibrational motion of all the constituent atoms in a supramolecular system. Here we apply that framework to the 27 coupled bacterio-chlorophyll-a chromophores which make up the LH2 complex, using it to compute an on-the-fly nonadiabatic surface-hopping (SH) trajectory of electronically excited LH2. Part one of this article is focussed on calibratingmore » our ab initio exciton Hamiltonian using two key parameters: a shift δ, which corrects for the error in TDDFT vertical excitation energies; and an effective dielectric constant ε, which describes the average screening of the transition-dipole coupling between chromophores. Using snapshots obtained from equilibrium molecular dynamics simulations (MD) of LH2, we tune the values of both δ and ε through fitting to the thermally broadened experimental absorption spectrum, giving a linear absorption spectrum that agrees reasonably well with experiment. In part two of this article, we construct a time-resolved picture of the coupled vibrational and excitation energy transfer (EET) dynamics in the sub-picosecond regime following photo-excitation. Assuming Franck–Condon excitation of a narrow eigenstate band centred at 800 nm, we use surface hopping to follow a single nonadiabatic dynamics trajectory within the full eigenstate manifold. Consistent with experimental data, this trajectory gives timescales for B800→B850 population transfer (τ B800→B850) between 650–1050 fs, and B800 population decay (τ 800→) between 10–50 fs. The dynamical picture that emerges is one of rapidly fluctuating LH2 eigenstates that are delocalized over multiple chromophores and undergo frequent crossing on a femtosecond timescale as a result of the atomic vibrations of the constituent chromophores. The eigenstate fluctuations arise from disorder that is driven by vibrational dynamics with multiple characteristic timescales. The scalability of our ab initio excitonic computational framework across massively parallel architectures opens up the possibility of addressing a wide range of questions, including how specific dynamical motions impact both the pathways and efficiency of electronic energy-transfer within large supramolecular systems.« less

The genomic and epidemiological dynamics of human influenza A virus.

PubMed

Rambaut, Andrew; Pybus, Oliver G; Nelson, Martha I; Viboud, Cecile; Taubenberger, Jeffery K; Holmes, Edward C

2008-05-29

The evolutionary interaction between influenza A virus and the human immune system, manifest as 'antigenic drift' of the viral haemagglutinin, is one of the best described patterns in molecular evolution. However, little is known about the genome-scale evolutionary dynamics of this pathogen. Similarly, how genomic processes relate to global influenza epidemiology, in which the A/H3N2 and A/H1N1 subtypes co-circulate, is poorly understood. Here through an analysis of 1,302 complete viral genomes sampled from temperate populations in both hemispheres, we show that the genomic evolution of influenza A virus is characterized by a complex interplay between frequent reassortment and periodic selective sweeps. The A/H3N2 and A/H1N1 subtypes exhibit different evolutionary dynamics, with diverse lineages circulating in A/H1N1, indicative of weaker antigenic drift. These results suggest a sink-source model of viral ecology in which new lineages are seeded from a persistent influenza reservoir, which we hypothesize to be located in the tropics, to sink populations in temperate regions.

Excited state dynamics of the astaxanthin radical cation

NASA Astrophysics Data System (ADS)

Amarie, Sergiu; Förster, Ute; Gildenhoff, Nina; Dreuw, Andreas; Wachtveitl, Josef

2010-07-01

Femtosecond transient absorption spectroscopy in the visible and NIR and ultrafast fluorescence spectroscopy were used to examine the excited state dynamics of astaxanthin and its radical cation. For neutral astaxanthin, two kinetic components corresponding to time constants of 130 fs (decay of the S 2 excited state) and 5.2 ps (nonradiative decay of the S 1 excited state) were sufficient to describe the data. The dynamics of the radical cation proved to be more complex. The main absorption band was shifted to 880 nm (D 0 → D 3 transition), showing a weak additional band at 1320 nm (D 0 → D 1 transition). We found, that D 3 decays to the lower-lying D 2 within 100 fs, followed by a decay to D 1 with a time constant of 0.9 ps. The D 1 state itself exhibited a dual behavior, the majority of the population is transferred to the ground state in 4.9 ps, while a small population decays on a longer timescale of 40 ps. Both transitions from D 1 were found to be fluorescent.

Von Bertalanffy's dynamics under a polynomial correction: Allee effect and big bang bifurcation

NASA Astrophysics Data System (ADS)

Leonel Rocha, J.; Taha, A. K.; Fournier-Prunaret, D.

2016-02-01

In this work we consider new one-dimensional populational discrete dynamical systems in which the growth of the population is described by a family of von Bertalanffy's functions, as a dynamical approach to von Bertalanffy's growth equation. The purpose of introducing Allee effect in those models is satisfied under a correction factor of polynomial type. We study classes of von Bertalanffy's functions with different types of Allee effect: strong and weak Allee's functions. Dependent on the variation of four parameters, von Bertalanffy's functions also includes another class of important functions: functions with no Allee effect. The complex bifurcation structures of these von Bertalanffy's functions is investigated in detail. We verified that this family of functions has particular bifurcation structures: the big bang bifurcation of the so-called “box-within-a-box” type. The big bang bifurcation is associated to the asymptotic weight or carrying capacity. This work is a contribution to the study of the big bang bifurcation analysis for continuous maps and their relationship with explosion birth and extinction phenomena.

(A)biotic processes control soil carbon dynamics: quantitative assessment of model complexity, stability and response to perturbations for improving ESMs

NASA Astrophysics Data System (ADS)

Georgiou, K.; Abramoff, R. Z.; Harte, J.; Riley, W. J.; Torn, M. S.

2016-12-01

As global temperatures and atmospheric CO2 concentrations continue to increase, soil microbial activity and decomposition of soil organic matter (SOM) are expected to follow suit, potentially limiting soil carbon storage. Traditional global- and ecosystem-scale models simulate SOM decomposition using linear kinetics, which are inherently unable to reproduce carbon-concentration feedbacks, such as priming of native SOM at elevated CO2 concentrations. Recent studies using nonlinear microbial models of SOM decomposition seek to capture these interactions, and several groups are currently integrating these microbial models into Earth System Models (ESMs). However, despite their widespread ability to exhibit nonlinear responses, these models vary tremendously in complexity and, consequently, dynamics. In this study, we explore, both analytically and numerically, the emergent oscillatory behavior and insensitivity of SOM stocks to carbon inputs that have been deemed `unrealistic' in recent microbial models. We discuss the sources of instability in four models of varying complexity, by sequentially reducing complexity of a detailed model that includes microbial physiology, a mineral sorption isotherm, and enzyme dynamics. We also present an alternative representation of microbial turnover that limits population sizes and, thus, reduces oscillations. We compare these models to several long-term carbon input manipulations, including the Detritus Input and Removal Treatment (DIRT) experiments, to show that there are clear metrics that can be used to distinguish and validate the inherent dynamics of each model structure. We find that traditional linear and nonlinear models cannot readily capture the range of long-term responses observed across the DIRT experiments as a direct consequence of their model structures, and that modifying microbial turnover results in more realistic predictions. Finally, we discuss our findings in the context of improving microbial model behavior for inclusion in ESMs.

Functional complexity and ecosystem stability: an experimental approach

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

Van Voris, P.; O'Neill, R.V.; Shugart, H.H.

1978-01-01

The complexity-stability hypothesis was experimentally tested using intact terrestrial microcosms. Functional complexity was defined as the number and significance of component interactions (i.e., population interactions, physical-chemical reactions, biological turnover rates) influenced by nonlinearities, feedbacks, and time delays. It was postulated that functional complexity could be nondestructively measured through analysis of a signal generated from the system. Power spectral analysis of hourly CO/sub 2/ efflux, from eleven old-field microcosms, was analyzed for the number of low frequency peaks and used to rank the functional complexity of each system. Ranking of ecosystem stability was based on the capacity of the system tomore » retain essential nutrients and was measured by net loss of Ca after the system was stressed. Rank correlation supported the hypothesis that increasing ecosystem functional complexity leads to increasing ecosystem stability. The results indicated that complex functional dynamics can serve to stabilize the system. The results also demonstrated that microcosms are useful tools for system-level investigations.« less

Changes in the Russian Wheat Aphid (Hemiptera: Aphididae) Biotype Complex in South Africa.

PubMed

Jankielsohn, Astrid

2016-04-01

Russian wheat aphid Diuraphis noxia (Kurdjumov) has spread from its native area in central Asia to all the major wheat-producing countries in the world to become an international wheat pest. Because the Russian wheat aphid is a serious threat to the wheat industry in South Africa, it is important to investigate the key factors involved in the distribution of Russian wheat aphid biotypes and in the changes of the Russian wheat aphid biotype complex in South Africa. There are currently four known Russian wheat aphid biotypes occurring in South Africa. Russian wheat aphid samples were collected from 2011 to 2014 during the wheat-growing season in spring and summer and these samples were screened to determine the biotype status. RWASA1 occurred predominantly in the Western Cape, while RWASA2 and RWASA3 occurred predominantly in the Eastern Free State. Following the first record of RWASA4 in 2011, this biotype was restricted to the Eastern Free State. The surveys suggest that the Russian wheat aphid bioype complex was more diverse in the Eastern Free State than in the other wheat production areas. There was also a shift in Russian wheat aphid biotype composition over time. The Russian wheat aphid biotype complex is dynamic, influenced by environmental factors such as host plants, altitude, and climate, and it can change and diversify over time causing fluctuation in populations over sites and years. This dynamic nature of the Russian wheat aphid will continue to challenge the development of Russian wheat aphid-resistant wheat cultivars in South Africa, and the continued monitoring of the biotypic and genetic structure, to determine genetic relatedness and variation in different biotypes, of Russian wheat aphid populations is important for protecting wheat.

Emergence of microbial diversity due to cross-feeding interactions in a spatial model of gut microbial metabolism.

PubMed

Hoek, Milan J A van; Merks, Roeland M H

2017-05-16

The human gut contains approximately 10 14 bacteria, belonging to hundreds of different species. Together, these microbial species form a complex food web that can break down nutrient sources that our own digestive enzymes cannot handle, including complex polysaccharides, producing short chain fatty acids and additional metabolites, e.g., vitamin K. Microbial diversity is important for colonic health: Changes in the composition of the microbiota have been associated with inflammatory bowel disease, diabetes, obesity and Crohn's disease, and make the microbiota more vulnerable to infestation by harmful species, e.g., Clostridium difficile. To get a grip on the controlling factors of microbial diversity in the gut, we here propose a multi-scale, spatiotemporal dynamic flux-balance analysis model to study the emergence of metabolic diversity in a spatial gut-like, tubular environment. The model features genome-scale metabolic models (GEM) of microbial populations, resource sharing via extracellular metabolites, and spatial population dynamics and evolution. In this model, cross-feeding interactions emerge readily, despite the species' ability to metabolize sugars autonomously. Interestingly, the community requires cross-feeding for producing a realistic set of short-chain fatty acids from an input of glucose, If we let the composition of the microbial subpopulations change during invasion of adjacent space, a complex and stratified microbiota evolves, with subspecies specializing on cross-feeding interactions via a mechanism of compensated trait loss. The microbial diversity and stratification collapse if the flux through the gut is enhanced to mimic diarrhea. In conclusion, this in silico model is a helpful tool in systems biology to predict and explain the controlling factors of microbial diversity in the gut. It can be extended to include, e.g., complex nutrient sources, and host-microbiota interactions via the intestinal wall.

Physiological condition of bank voles (Myodes glareolus) during the increase and decline phases of the population cycle.

PubMed

Nieminen, Petteri; Huitu, Otso; Henttonen, Heikki; Finnilä, Mikko A J; Voutilainen, Liina; Itämies, Juhani; Kärjä, Vesa; Saarela, Seppo; Halonen, Toivo; Aho, Jari; Mustonen, Anne-Mari

2015-09-01

The dynamics of animal populations are greatly influenced by interactions with their natural enemies and food resources. However, quantifying the relative effects of these factors on demographic rates remains a perpetual challenge for animal population ecology. Food scarcity is assumed to limit the growth and to initiate the decline of cyclic herbivore populations, but this has not been verified with physiological health indices. We hypothesized that individuals in declining populations would exhibit signs of malnutrition-induced deterioration of physiological condition. We evaluated the association of body condition with population cycle phase in bank voles (Myodes glareolus) during the increase and decline phases of a population cycle. The bank voles had lower body masses, condition indices and absolute masses of particular organs during the decline. Simultaneously, they had lower femoral masses, mineral contents and densities. Hemoglobin and hematocrit values and several parameters known to respond to food deprivation were unaffected by the population phase. There were no signs of lymphopenia, eosinophilia, granulocytosis or monocytosis. Erythrocyte counts were higher and plasma total protein levels and tissue proportions of essential polyunsaturated fatty acids lower in the population decline. Ectoparasite load was lower and adrenal gland masses or catecholamine concentrations did not suggest higher stress levels. Food availability seems to limit the size of voles during the decline but they can adapt to the prevailing conditions without clear deleterious health effects. This highlights the importance of quantifying individual health state when evaluating the effects of complex trophic interactions on the dynamics of wild animal populations. Copyright © 2015 Elsevier Inc. All rights reserved.

Resolving the excited state equilibrium of peridinin in solution.

PubMed

Papagiannakis, Emmanouil; Larsen, Delmar S; van Stokkum, Ivo H M; Vengris, Mikas; Hiller, Roger G; van Grondelle, Rienk

2004-12-14

The carotenoid peridinin is abundant in the biosphere, as it is the main pigment bound by the light-harvesting complexes of dinoflagellates, where it collects blue and green sunlight and transfers energy to chlorophyll a with high efficiency. Its molecular structure is particularly complex, giving rise to an intricate excited state manifold, which includes a state with charge-transfer character. To disentangle the excited states of peridinin and understand their function in vivo, we applied dispersed pump-probe and pump-dump-probe spectroscopy. The preferential depletion of population from the intramolecular charge transfer state by the dump pulse demonstrates that the S(1) and this charge transfer state are distinct entities. The ensuing dump-induced dynamics illustrates the equilibration of the two states which occurs on the time scale of a few picoseconds. Additionally, the dump pulse populates a short-lived ground state intermediate, which is suggestive of a complex relaxation pathway, probably including structural reorientation or solvation of the ground state. These findings indicate that the unique intramolecular charge transfer state of peridinin is an efficient energy donor to chlorophyll a in the peridinin-chlorophyll-protein complex and thus plays a significant role in global light harvesting.

Designing and Undertaking a Health Economics Study of Digital Health Interventions.

PubMed

McNamee, Paul; Murray, Elizabeth; Kelly, Michael P; Bojke, Laura; Chilcott, Jim; Fischer, Alastair; West, Robert; Yardley, Lucy

2016-11-01

This paper introduces and discusses key issues in the economic evaluation of digital health interventions. The purpose is to stimulate debate so that existing economic techniques may be refined or new methods developed. The paper does not seek to provide definitive guidance on appropriate methods of economic analysis for digital health interventions. This paper describes existing guides and analytic frameworks that have been suggested for the economic evaluation of healthcare interventions. Using selected examples of digital health interventions, it assesses how well existing guides and frameworks align to digital health interventions. It shows that digital health interventions may be best characterized as complex interventions in complex systems. Key features of complexity relate to intervention complexity, outcome complexity, and causal pathway complexity, with much of this driven by iterative intervention development over time and uncertainty regarding likely reach of the interventions among the relevant population. These characteristics imply that more-complex methods of economic evaluation are likely to be better able to capture fully the impact of the intervention on costs and benefits over the appropriate time horizon. This complexity includes wider measurement of costs and benefits, and a modeling framework that is able to capture dynamic interactions among the intervention, the population of interest, and the environment. The authors recommend that future research should develop and apply more-flexible modeling techniques to allow better prediction of the interdependency between interventions and important environmental influences. Copyright © 2016 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.

The Radiation Belt Storm Probes (RBSP) Energetic Particle, Composition, and Thermal plasma (ECT) Suite: Upcoming Opportunties for Testing Radiation Belt Acceleration Mechanisms

NASA Astrophysics Data System (ADS)

Spence, Harlan; Reeves, Geoffrey

2012-07-01

The Radiation Belt Storm Probes (RBSP) mission will launch in late summer 2012 and begin its exploration of acceleration and dynamics of energetic particles in the inner magnetosphere. In this presentation, we discuss opportunities afforded by the RBSP Energetic Particle, Composition, and Thermal plasma (ECT) instrument suite to advance our understanding of acceleration processes in the radiation belts. The RBSP-ECT instrument suite comprehensively measures the electron and major ion populations of the inner magnetosphere, from the lowest thermal plasmas of the plasmasphere, to the hot plasma of the ring current, to the relativistic populations of the radiation belts. Collectively, the ECT measurements will reveal the complex cross-energy coupling of these colocated particle populations, which along with concurrent RBSP wave measurements, will permit various wave-particle acceleration mechanisms to be tested. We review the measurement capabilities of the RBSP-ECT instrument suite, and demonstrate several examples of how these measurements will be used to explore candidate acceleration mechanisms and dynamics of radiation belt particles.

Phylodynamics and movement of Phycodnaviruses among aquatic environments

PubMed Central

Gimenes, Manuela V; Zanotto, Paolo M de A; Suttle, Curtis A; da Cunha, Hillândia B; Mehnert, Dolores U

2012-01-01

Phycodnaviruses have a significant role in modulating the dynamics of phytoplankton, thereby influencing community structure and succession, nutrient cycles and potentially atmospheric composition because phytoplankton fix about half the carbon dioxide (CO2) on the planet, and some algae release dimethylsulphoniopropionate when lysed by viruses. Despite their ecological importance and widespread distribution, relatively little is known about the evolutionary history, phylogenetic relationships and phylodynamics of the Phycodnaviruses from freshwater environments. Herein we provide novel data on Phycodnaviruses from the largest river system on earth—the Amazon Basin—that were compared with samples from different aquatic systems from several places around the world. Based on phylogenetic inference using DNA polymerase (pol) sequences we show the presence of distinct populations of Phycodnaviridae. Preliminary coarse-grained phylodynamics and phylogeographic inferences revealed a complex dynamics characterized by long-term fluctuations in viral population sizes, with a remarkable worldwide reduction of the effective population around 400 thousand years before the present (KYBP), followed by a recovery near to the present time. Moreover, we present evidence for significant viral gene flow between freshwater environments, but crucially almost none between freshwater and marine environments. PMID:21796218

Internal Disequilibria and Phenotypic Diversification during Replication of Hepatitis C Virus in a Noncoevolving Cellular Environment

PubMed Central

Moreno, Elena; Gallego, Isabel; Gregori, Josep; Lucía-Sanz, Adriana; Soria, María Eugenia; Castro, Victoria; Beach, Nathan M.; Manrubia, Susanna; Quer, Josep; Esteban, Juan Ignacio; Rice, Charles M.; Gómez, Jordi; Gastaminza, Pablo

2017-01-01

ABSTRACT Viral quasispecies evolution upon long-term virus replication in a noncoevolving cellular environment raises relevant general issues, such as the attainment of population equilibrium, compliance with the molecular-clock hypothesis, or stability of the phenotypic profile. Here, we evaluate the adaptation, mutant spectrum dynamics, and phenotypic diversification of hepatitis C virus (HCV) in the course of 200 passages in human hepatoma cells in an experimental design that precluded coevolution of the cells with the virus. Adaptation to the cells was evidenced by increase in progeny production. The rate of accumulation of mutations in the genomic consensus sequence deviated slightly from linearity, and mutant spectrum analyses revealed a complex dynamic of mutational waves, which was sustained beyond passage 100. The virus underwent several phenotypic changes, some of which impacted the virus-host relationship, such as enhanced cell killing, a shift toward higher virion density, and increased shutoff of host cell protein synthesis. Fluctuations in progeny production and failure to reach population equilibrium at the genomic level suggest internal instabilities that anticipate an unpredictable HCV evolution in the complex liver environment. IMPORTANCE Long-term virus evolution in an unperturbed cellular environment can reveal features of virus evolution that cannot be explained by comparing natural viral isolates. In the present study, we investigate genetic and phenotypic changes that occur upon prolonged passage of hepatitis C virus (HCV) in human hepatoma cells in an experimental design in which host cell evolutionary change is prevented. Despite replication in a noncoevolving cellular environment, the virus exhibited internal population disequilibria that did not decline with increased adaptation to the host cells. The diversification of phenotypic traits suggests that disequilibria inherent to viral populations may provide a selective advantage to viruses that can be fully exploited in changing environments. PMID:28275194

Complex postglacial recolonization inferred from population genetic structure of mottled sculpin Cottus bairdii in tributaries of eastern Lake Michigan, U.S.A.

PubMed

Homola, J J; Ruetz, C R; Kohler, S L; Thum, R A

2016-11-01

This study used analyses of the genetic structure of a non-game fish species, the mottled sculpin Cottus bairdii to hypothesize probable recolonization routes used by cottids and possibly other Laurentian Great Lakes fishes following glacial recession. Based on samples from 16 small streams in five major Lake Michigan, U.S.A., tributary basins, significant interpopulation differentiation was documented (overall F ST = 0·235). Differentiation was complex, however, with unexpectedly high genetic similarity among basins as well as occasionally strong differentiation within basins, despite relatively close geographic proximity of populations. Genetic dissimilarities were identified between eastern and western populations within river basins, with similarities existing between eastern and western populations across basins. Given such patterns, recolonization is hypothesized to have occurred on three occasions from more than one glacial refugium, with a secondary vicariant event resulting from reduction in the water level of ancestral Lake Michigan. By studying the phylogeography of a small, non-game fish species, this study provides insight into recolonization dynamics of the region that could be difficult to infer from game species that are often broadly dispersed by humans. © 2016 The Fisheries Society of the British Isles.

Hybrid function projective synchronization in complex dynamical networks

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

Wei, Qiang; Wang, Xing-yuan, E-mail: wangxy@dlut.edu.cn; Hu, Xiao-peng

2014-02-15

This paper investigates hybrid function projective synchronization in complex dynamical networks. When the complex dynamical networks could be synchronized up to an equilibrium or periodic orbit, a hybrid feedback controller is designed to realize the different component of vector of node could be synchronized up to different desired scaling function in complex dynamical networks with time delay. Hybrid function projective synchronization (HFPS) in complex dynamical networks with constant delay and HFPS in complex dynamical networks with time-varying coupling delay are researched, respectively. Finally, the numerical simulations show the effectiveness of theoretical analysis.

Setting realistic recovery targets for two interacting endangered species, sea otter and northern abalone.

PubMed

Chadès, Iadine; Curtis, Janelle M R; Martin, Tara G

2012-12-01

Failure to account for interactions between endangered species may lead to unexpected population dynamics, inefficient management strategies, waste of scarce resources, and, at worst, increased extinction risk. The importance of species interactions is undisputed, yet recovery targets generally do not account for such interactions. This shortcoming is a consequence of species-centered legislation, but also of uncertainty surrounding the dynamics of species interactions and the complexity of modeling such interactions. The northern sea otter (Enhydra lutris kenyoni) and one of its preferred prey, northern abalone (Haliotis kamtschatkana), are endangered species for which recovery strategies have been developed without consideration of their strong predator-prey interactions. Using simulation-based optimization procedures from artificial intelligence, namely reinforcement learning and stochastic dynamic programming, we combined sea otter and northern abalone population models with functional-response models and examined how different management actions affect population dynamics and the likelihood of achieving recovery targets for each species through time. Recovery targets for these interacting species were difficult to achieve simultaneously in the absence of management. Although sea otters were predicted to recover, achieving abalone recovery targets failed even when threats to abalone such as predation and poaching were reduced. A management strategy entailing a 50% reduction in the poaching of northern abalone was a minimum requirement to reach short-term recovery goals for northern abalone when sea otters were present. Removing sea otters had a marginally positive effect on the abalone population but only when we assumed a functional response with strong predation pressure. Our optimization method could be applied more generally to any interacting threatened or invasive species for which there are multiple conservation objectives. © 2012 Society for Conservation Biology.

A systems theoretic approach to analysis and control of mammalian circadian dynamics

PubMed Central

Abel, John H.; Doyle, Francis J.

2016-01-01

The mammalian circadian clock is a complex multi-scale, multivariable biological control system. In the past two decades, methods from systems engineering have led to numerous insights into the architecture and functionality of this system. In this review, we examine the mammalian circadian system through a process systems lens. We present a mathematical framework for examining the cellular circadian oscillator, and show recent extensions for understanding population-scale dynamics. We provide an overview of the routes by which the circadian system can be systemically manipulated, and present in silico proof of concept results for phase resetting of the clock via model predictive control. PMID:28496287

Systems thinking in combating infectious diseases.

PubMed

Xia, Shang; Zhou, Xiao-Nong; Liu, Jiming

2017-09-11

The transmission of infectious diseases is a dynamic process determined by multiple factors originating from disease pathogens and/or parasites, vector species, and human populations. These factors interact with each other and demonstrate the intrinsic mechanisms of the disease transmission temporally, spatially, and socially. In this article, we provide a comprehensive perspective, named as systems thinking, for investigating disease dynamics and associated impact factors, by means of emphasizing the entirety of a system's components and the complexity of their interrelated behaviors. We further develop the general steps for performing systems approach to tackling infectious diseases in the real-world settings, so as to expand our abilities to understand, predict, and mitigate infectious diseases.

Scalable Entity-Based Modeling of Population-Based Systems, Final LDRD Report

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

Cleary, A J; Smith, S G; Vassilevska, T K

2005-01-27

The goal of this project has been to develop tools, capabilities and expertise in the modeling of complex population-based systems via scalable entity-based modeling (EBM). Our initial focal application domain has been the dynamics of large populations exposed to disease-causing agents, a topic of interest to the Department of Homeland Security in the context of bioterrorism. In the academic community, discrete simulation technology based on individual entities has shown initial success, but the technology has not been scaled to the problem sizes or computational resources of LLNL. Our developmental emphasis has been on the extension of this technology to parallelmore » computers and maturation of the technology from an academic to a lab setting.« less

Fixation of slightly beneficial mutations: effects of life history.

PubMed

Vindenes, Yngvild; Lee, Aline Magdalena; Engen, Steinar; Saether, Bernt-Erik

2010-04-01

Recent studies of rates of evolution have revealed large systematic differences among organisms with different life histories, both within and among taxa. Here, we consider how life history may affect the rate of evolution via its influence on the fixation probability of slightly beneficial mutations. Our approach is based on diffusion modeling for a finite, stage-structured population with stochastic population dynamics. The results, which are verified by computer simulations, demonstrate that even with complex population structure just two demographic parameters are sufficient to give an accurate approximation of the fixation probability of a slightly beneficial mutation. These are the reproductive value of the stage in which the mutation first occurs and the demographic variance of the population. The demographic variance also determines what influence population size has on the fixation probability. This model represents a substantial generalization of earlier models, covering a large range of life histories.

Social interaction in synthetic and natural microbial communities.

PubMed

Xavier, Joao B

2011-04-12

Social interaction among cells is essential for multicellular complexity. But how do molecular networks within individual cells confer the ability to interact? And how do those same networks evolve from the evolutionary conflict between individual- and population-level interests? Recent studies have dissected social interaction at the molecular level by analyzing both synthetic and natural microbial populations. These studies shed new light on the role of population structure for the evolution of cooperative interactions and revealed novel molecular mechanisms that stabilize cooperation among cells. New understanding of populations is changing our view of microbial processes, such as pathogenesis and antibiotic resistance, and suggests new ways to fight infection by exploiting social interaction. The study of social interaction is also challenging established paradigms in cancer evolution and immune system dynamics. Finding similar patterns in such diverse systems suggests that the same 'social interaction motifs' may be general to many cell populations.

Complex chimerism

PubMed Central

Ma, Kimberly K.; Petroff, Margaret G.; Coscia, Lisa A.; Armenti, Vincent T.; Adams Waldorf, Kristina M.

2013-01-01

Thousands of women with organ transplantation have undergone successful pregnancies, however little is known about how the profound immunologic changes associated with pregnancy might influence tolerance or rejection of the allograft. Pregnant women with a solid organ transplant are complex chimeras with multiple foreign cell populations from the donor organ, fetus, and mother of the pregnant woman. We consider the impact of complex chimerism and pregnancy-associated immunologic changes on tolerance of the allograft both during pregnancy and the postpartum period. Mechanisms of allograft tolerance are likely dynamic during pregnancy and affected by the influx of fetal microchimeric cells, HLA relationships (between the fetus, pregnant woman and/or donor), peripheral T cell tolerance to fetal cells, and fetal minor histocompatibility antigens. Further research is necessary to understand the complex immunology during pregnancy and the postpartum period of women with a solid organ transplant. PMID:23974274

Spatial and temporal optimization in habitat placement for a threatened plant: the case of the western prairie fringed orchid

Treesearch

John Hof; Carolyn Hull Sieg; Michael Bevers

1999-01-01

This paper investigates an optimization approach to determining the placement and timing of habitat protection for the western prairie fringed orchid. This plant’s population dynamics are complex, creating a challenging optimization problem. The sensitivity of the orchid to random climate conditions is handled probabilistically. The plant’s seed, protocorm and above-...

Impact of unexpected events, shocking news, and rumors on foreign exchange market dynamics

NASA Astrophysics Data System (ADS)

McDonald, Mark; Suleman, Omer; Williams, Stacy; Howison, Sam; Johnson, Neil F.

2008-04-01

The dynamical response of a population of interconnected objects, when exposed to external perturbations, is of great interest to physicists working on complex systems. Here we focus on human systems, by analyzing the dynamical response of the world’s financial community to various types of unexpected events—including the 9/11 terrorist attacks as they unfolded on a minute-by-minute basis. For the unfolding events of 9/11, our results show that there was a gradual collective understanding of what was happening, rather than an immediate realization. More generally, we find that for news items which are not simple economic statements—and hence whose implications for the market are not immediately obvious—there are periods of collective discovery during which opinions seem to vary in a remarkably synchronized way.

The Complexity of Dynamics in Small Neural Circuits

PubMed Central

Panzeri, Stefano

2016-01-01

Mean-field approximations are a powerful tool for studying large neural networks. However, they do not describe well the behavior of networks composed of a small number of neurons. In this case, major differences between the mean-field approximation and the real behavior of the network can arise. Yet, many interesting problems in neuroscience involve the study of mesoscopic networks composed of a few tens of neurons. Nonetheless, mathematical methods that correctly describe networks of small size are still rare, and this prevents us to make progress in understanding neural dynamics at these intermediate scales. Here we develop a novel systematic analysis of the dynamics of arbitrarily small networks composed of homogeneous populations of excitatory and inhibitory firing-rate neurons. We study the local bifurcations of their neural activity with an approach that is largely analytically tractable, and we numerically determine the global bifurcations. We find that for strong inhibition these networks give rise to very complex dynamics, caused by the formation of multiple branching solutions of the neural dynamics equations that emerge through spontaneous symmetry-breaking. This qualitative change of the neural dynamics is a finite-size effect of the network, that reveals qualitative and previously unexplored differences between mesoscopic cortical circuits and their mean-field approximation. The most important consequence of spontaneous symmetry-breaking is the ability of mesoscopic networks to regulate their degree of functional heterogeneity, which is thought to help reducing the detrimental effect of noise correlations on cortical information processing. PMID:27494737

Conformational dynamics of bacterial trigger factor in apo and ribosome-bound states.

PubMed

Can, Mehmet Tarik; Kurkcuoglu, Zeynep; Ezeroglu, Gokce; Uyar, Arzu; Kurkcuoglu, Ozge; Doruker, Pemra

2017-01-01

The chaperone trigger factor (TF) binds to the ribosome exit tunnel and helps cotranslational folding of nascent chains (NC) in bacterial cells and chloroplasts. In this study, we aim to investigate the functional dynamics of fully-atomistic apo TF and its complex with 50S. As TF accomodates a high percentage of charged residues on its surface, the effect of ionic strength on TF dynamics is assessed here by performing five independent molecular dynamics (MD) simulations (total of 1.3 micro-second duration) at 29 mM and 150 mM ionic strengths. At both concentrations, TF exhibits high inter- and intra-domain flexibility related to its binding (BD), core (CD), and head (HD) domains. Even though large oscillations in gyration radius exist during each run, we do not detect the so-called 'fully collapsed' state with both HD and BD collapsed upon the core. In fact, the extended conformers with relatively open HD and BD are highly populated at the physiological concentration of 150 mM. More importantly, extended TF snapshots stand out in terms of favorable docking onto the 50S subunit. Elastic network modeling (ENM) indicates significant changes in TF's functional dynamics and domain decomposition depending on its conformation and positioning on the 50S. The most dominant slow motions are the lateral sweeping and vertical opening/closing of HD relative to 50S. Finally, our ENM-based efficient technique -ClustENM- is used to sample atomistic conformers starting with an extended TF-50S complex. Specifically, BD and CD motions are restricted near the tunnel exit, while HD is highly mobile. The atomistic conformers generated without an NC are in agreement with the cryo-EM maps available for TF-ribosome-NC complex.

Modeling Dynamics of Culex pipiens Complex Populations and Assessing Abatement Strategies for West Nile Virus

PubMed Central

Pawelek, Kasia A.; Hager, Elizabeth J.; Hunt, Gregg J.

2014-01-01

The primary mosquito species associated with underground stormwater systems in the United States are the Culex pipiens complex species. This group represents important vectors of West Nile virus (WNV) throughout regions of the continental U.S. In this study, we designed a mathematical model and compared it with surveillance data for the Cx. pipiens complex collected in Beaufort County, South Carolina. Based on the best fit of the model to the data, we estimated parameters associated with the effectiveness of public health insecticide (adulticide) treatments (primarily pyrethrin products) as well as the birth, maturation, and death rates of immature and adult Cx. pipiens complex mosquitoes. We used these estimates for modeling the spread of WNV to obtain more reliable disease outbreak predictions and performed numerical simulations to test various mosquito abatement strategies. We demonstrated that insecticide treatments produced significant reductions in the Cx. pipiens complex populations. However, abatement efforts were effective for approximately one day and the vector mosquitoes rebounded until the next treatment. These results suggest that frequent insecticide applications are necessary to control these mosquitoes. We derived the basic reproductive number (ℜ0) to predict the conditions under which disease outbreaks are likely to occur and to evaluate mosquito abatement strategies. We concluded that enhancing the mosquito death rate results in lower values of ℜ0, and if ℜ0<1, then an epidemic will not occur. Our modeling results provide insights about control strategies of the vector populations and, consequently, a potential decrease in the risk of a WNV outbreak. PMID:25268229

A Three-protein Charge Zipper Stabilizes a Complex Modulating Bacterial Gene Silencing*

PubMed Central

Cordeiro, Tiago N.; García, Jesús; Bernadó, Pau; Millet, Oscar; Pons, Miquel

2015-01-01

The Hha/YmoA nucleoid-associated proteins help selectively silence horizontally acquired genetic material, including pathogenicity and antibiotic resistance genes and their maintenance in the absence of selective pressure. Members of the Hha family contribute to gene silencing by binding to the N-terminal dimerization domain of H-NS and modifying its selectivity. Hha-like proteins and the H-NS N-terminal domain are unusually rich in charged residues, and their interaction is mostly electrostatic-driven but, nonetheless, highly selective. The NMR-based structural model of the complex between Hha/YmoA and the H-NS N-terminal dimerization domain reveals that the origin of the selectivity is the formation of a three-protein charge zipper with interdigitated complementary charged residues from Hha and the two units of the H-NS dimer. The free form of YmoA shows collective microsecond-millisecond dynamics that can by measured by NMR relaxation dispersion experiments and shows a linear dependence with the salt concentration. The number of residues sensing the collective dynamics and the population of the minor form increased in the presence of H-NS. Additionally, a single residue mutation in YmoA (D43N) abolished H-NS binding and the dynamics of the apo-form, suggesting the dynamics and binding are functionally related. PMID:26085102

Dynamics of photoionization from molecular electronic wavepacket states in intense pulse laser fields: A nonadiabatic electron wavepacket study.

PubMed

Matsuoka, Takahide; Takatsuka, Kazuo

2017-04-07

A theory for dynamics of molecular photoionization from nonadiabatic electron wavepackets driven by intense pulse lasers is proposed. Time evolution of photoelectron distribution is evaluated in terms of out-going electron flux (current of the probability density of electrons) that has kinetic energy high enough to recede from the molecular system. The relevant electron flux is in turn evaluated with the complex-valued electronic wavefunctions that are time evolved in nonadiabatic electron wavepacket dynamics in laser fields. To uniquely rebuild such wavefunctions with its electronic population being lost by ionization, we adopt the complex-valued natural orbitals emerging from the electron density as building blocks of the total wavefunction. The method has been implemented into a quantum chemistry code, which is based on configuration state mixing for polyatomic molecules. Some of the practical aspects needed for its application will be presented. As a first illustrative example, we show the results of hydrogen molecule and its isotope substitutes (HD and DD), which are photoionized by a two-cycle pulse laser. Photon emission spectrum associated with above threshold ionization is also shown. Another example is taken from photoionization dynamics from an excited state of a water molecule. Qualitatively significant effects of nonadiabatic interaction on the photoelectron spectrum are demonstrated.

Incorporating diverse data and realistic complexity into demographic estimation procedures for sea otters

USGS Publications Warehouse

Tinker, M. Timothy; Doak, Daniel F.; Estes, James A.; Hatfield, Brian B.; Staedler, Michelle M.; Gross, Arthur

2006-01-01

Reliable information on historical and current population dynamics is central to understanding patterns of growth and decline in animal populations. We developed a maximum likelihood-based analysis to estimate spatial and temporal trends in age/sex-specific survival rates for the threatened southern sea otter (Enhydra lutris nereis), using annual population censuses and the age structure of salvaged carcass collections. We evaluated a wide range of possible spatial and temporal effects and used model averaging to incorporate model uncertainty into the resulting estimates of key vital rates and their variances. We compared these results to current demographic parameters estimated in a telemetry-based study conducted between 2001 and 2004. These results show that survival has decreased substantially from the early 1990s to the present and is generally lowest in the north-central portion of the population's range. The greatest temporal decrease in survival was for adult females, and variation in the survival of this age/sex class is primarily responsible for regulating population growth and driving population trends. Our results can be used to focus future research on southern sea otters by highlighting the life history stages and mortality factors most relevant to conservation. More broadly, we have illustrated how the powerful and relatively straightforward tools of information-theoretic-based model fitting can be used to sort through and parameterize quite complex demographic modeling frameworks. ?? 2006 by the Ecological Society of America.

New Methods for Analysis of Spatial Distribution and Coaggregation of Microbial Populations in Complex Biofilms

PubMed Central

Almstrand, Robert; Daims, Holger; Persson, Frank; Sörensson, Fred

2013-01-01

In biofilms, microbial activities form gradients of substrates and electron acceptors, creating a complex landscape of microhabitats, often resulting in structured localization of the microbial populations present. To understand the dynamic interplay between and within these populations, quantitative measurements and statistical analysis of their localization patterns within the biofilms are necessary, and adequate automated tools for such analyses are needed. We have designed and applied new methods for fluorescence in situ hybridization (FISH) and digital image analysis of directionally dependent (anisotropic) multispecies biofilms. A sequential-FISH approach allowed multiple populations to be detected in a biofilm sample. This was combined with an automated tool for vertical-distribution analysis by generating in silico biofilm slices and the recently developed Inflate algorithm for coaggregation analysis of microbial populations in anisotropic biofilms. As a proof of principle, we show distinct stratification patterns of the ammonia oxidizers Nitrosomonas oligotropha subclusters I and II and the nitrite oxidizer Nitrospira sublineage I in three different types of wastewater biofilms, suggesting niche differentiation between the N. oligotropha subclusters, which could explain their coexistence in the same biofilms. Coaggregation analysis showed that N. oligotropha subcluster II aggregated closer to Nitrospira than did N. oligotropha subcluster I in a pilot plant nitrifying trickling filter (NTF) and a moving-bed biofilm reactor (MBBR), but not in a full-scale NTF, indicating important ecophysiological differences between these phylogenetically closely related subclusters. By using high-resolution quantitative methods applicable to any multispecies biofilm in general, the ecological interactions of these complex ecosystems can be understood in more detail. PMID:23892743

Dynamics of Marine Microbial Metabolism and Physiology at Station ALOHA

NASA Astrophysics Data System (ADS)

Casey, John R.

Marine microbial communities influence global biogeochemical cycles by coupling the transduction of free energy to the transformation of Earth's essential bio-elements: H, C, N, O, P, and S. The web of interactions between these processes is extraordinarily complex, though fundamental physical and thermodynamic principles should describe its dynamics. In this collection of 5 studies, aspects of the complexity of marine microbial metabolism and physiology were investigated as they interact with biogeochemical cycles and direct the flow of energy within the Station ALOHA surface layer microbial community. In Chapter 1, and at the broadest level of complexity discussed, a method to relate cell size to metabolic activity was developed to evaluate allometric power laws at fine scales within picoplankton populations. Although size was predictive of metabolic rates, within-population power laws deviated from the broader size spectrum, suggesting metabolic diversity as a key determinant of microbial activity. In Chapter 2, a set of guidelines was proposed by which organic substrates are selected and utilized by the heterotrophic community based on their nitrogen content, carbon content, and energy content. A hierarchical experimental design suggested that the heterotrophic microbial community prefers high nitrogen content but low energy density substrates, while carbon content was not important. In Chapter 3, a closer look at the light-dependent dynamics of growth on a single organic substrate, glycolate, suggested that growth yields were improved by photoheterotrophy. The remaining chapters were based on the development of a genome-scale metabolic network reconstruction of the cyanobacterium Prochlorococcus to probe its metabolic capabilities and quantify metabolic fluxes. Findings described in Chapter 4 pointed to evolution of the Prochlorococcus metabolic network to optimize growth at low phosphate concentrations. Finally, in Chapter 5 and at the finest scale of complexity, a method was developed to predict hourly changes in both physiology and metabolic fluxes in Prochlorococcus by incorporating gene expression time-series data within the metabolic network model. Growth rates predicted by this method more closely matched experimental data, and diel changes in elemental composition and the energy content of biomass were predicted. Collectively, these studies identify and quantify the potential impact of variations in metabolic and physiological traits on the melee of microbial community interactions.

Mapping the conformational landscape of a dynamic enzyme by multitemperature and XFEL crystallography

PubMed Central

Keedy, Daniel A; Kenner, Lillian R; Warkentin, Matthew; Woldeyes, Rahel A; Hopkins, Jesse B; Thompson, Michael C; Brewster, Aaron S; Van Benschoten, Andrew H; Baxter, Elizabeth L; Uervirojnangkoorn, Monarin; McPhillips, Scott E; Song, Jinhu; Alonso-Mori, Roberto; Holton, James M; Weis, William I; Brunger, Axel T; Soltis, S Michael; Lemke, Henrik; Gonzalez, Ana; Sauter, Nicholas K; Cohen, Aina E; van den Bedem, Henry; Thorne, Robert E; Fraser, James S

2015-01-01

Determining the interconverting conformations of dynamic proteins in atomic detail is a major challenge for structural biology. Conformational heterogeneity in the active site of the dynamic enzyme cyclophilin A (CypA) has been previously linked to its catalytic function, but the extent to which the different conformations of these residues are correlated is unclear. Here we compare the conformational ensembles of CypA by multitemperature synchrotron crystallography and fixed-target X-ray free-electron laser (XFEL) crystallography. The diffraction-before-destruction nature of XFEL experiments provides a radiation-damage-free view of the functionally important alternative conformations of CypA, confirming earlier synchrotron-based results. We monitored the temperature dependences of these alternative conformations with eight synchrotron datasets spanning 100-310 K. Multiconformer models show that many alternative conformations in CypA are populated only at 240 K and above, yet others remain populated or become populated at 180 K and below. These results point to a complex evolution of conformational heterogeneity between 180-–240 K that involves both thermal deactivation and solvent-driven arrest of protein motions in the crystal. The lack of a single shared conformational response to temperature within the dynamic active-site network provides evidence for a conformation shuffling model, in which exchange between rotamer states of a large aromatic ring in the middle of the network shifts the conformational ensemble for the other residues in the network. Together, our multitemperature analyses and XFEL data motivate a new generation of temperature- and time-resolved experiments to structurally characterize the dynamic underpinnings of protein function. DOI: http://dx.doi.org/10.7554/eLife.07574.001 PMID:26422513

Excitation energy transfer in photosynthetic protein-pigment complexes

NASA Astrophysics Data System (ADS)

Yeh, Shu-Hao

Quantum biology is a relatively new research area which investigates the rules that quantum mechanics plays in biology. One of the most intriguing systems in this field is the coherent excitation energy transport (EET) in photosynthesis. In this document I will discuss the theories that are suitable for describing the photosynthetic EET process and the corresponding numerical results on several photosynthetic protein-pigment complexes (PPCs). In some photosynthetic EET processes, because of the electronic coupling between the chromophores within the system is about the same order of magnitude as system-bath coupling (electron-phonon coupling), a non-perturbative method called hierarchy equation of motion (HEOM) is applied to study the EET dynamics. The first part of this thesis includes brief introduction and derivation to the HEOM approach. The second part of this thesis the HEOM method will be applied to investigate the EET process within the B850 ring of the light harvesting complex 2 (LH2) from purple bacteria, Rhodopseudomonas acidophila. The dynamics of the exciton population and coherence will be analyzed under different initial excitation configurations and temperatures. Finally, how HEOM can be implemented to simulate the two-dimensional electronic spectra of photosynthetic PPCs will be discussed. Two-dimensional electronic spectroscopy is a crucial experimental technique to probe EET dynamics in multi-chromophoric systems. The system we are interested in is the 7-chromophore Fenna-Matthews-Olson (FMO) complex from green sulfur bacteria, Prosthecochloris aestuarii. Recent crystallographic studies report the existence of an additional (eighth) chromophore in some of the FMO monomers. By applying HEOM we are able to calculate the two-dimensional electronic spectra of the 7-site and 8-site FMO complexes and investigate the functionality of the eighth chromophore.

Perspective: Maximum caliber is a general variational principle for dynamical systems

NASA Astrophysics Data System (ADS)

Dixit, Purushottam D.; Wagoner, Jason; Weistuch, Corey; Pressé, Steve; Ghosh, Kingshuk; Dill, Ken A.

2018-01-01

We review here Maximum Caliber (Max Cal), a general variational principle for inferring distributions of paths in dynamical processes and networks. Max Cal is to dynamical trajectories what the principle of maximum entropy is to equilibrium states or stationary populations. In Max Cal, you maximize a path entropy over all possible pathways, subject to dynamical constraints, in order to predict relative path weights. Many well-known relationships of non-equilibrium statistical physics—such as the Green-Kubo fluctuation-dissipation relations, Onsager's reciprocal relations, and Prigogine's minimum entropy production—are limited to near-equilibrium processes. Max Cal is more general. While it can readily derive these results under those limits, Max Cal is also applicable far from equilibrium. We give examples of Max Cal as a method of inference about trajectory distributions from limited data, finding reaction coordinates in bio-molecular simulations, and modeling the complex dynamics of non-thermal systems such as gene regulatory networks or the collective firing of neurons. We also survey its basis in principle and some limitations.

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

PubMed

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

2018-05-01

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

Noise facilitates transcriptional control under dynamic inputs.

PubMed

Kellogg, Ryan A; Tay, Savaş

2015-01-29

Cells must respond sensitively to time-varying inputs in complex signaling environments. To understand how signaling networks process dynamic inputs into gene expression outputs and the role of noise in cellular information processing, we studied the immune pathway NF-κB under periodic cytokine inputs using microfluidic single-cell measurements and stochastic modeling. We find that NF-κB dynamics in fibroblasts synchronize with oscillating TNF signal and become entrained, leading to significantly increased NF-κB oscillation amplitude and mRNA output compared to non-entrained response. Simulations show that intrinsic biochemical noise in individual cells improves NF-κB oscillation and entrainment, whereas cell-to-cell variability in NF-κB natural frequency creates population robustness, together enabling entrainment over a wider range of dynamic inputs. This wide range is confirmed by experiments where entrained cells were measured under all input periods. These results indicate that synergy between oscillation and noise allows cells to achieve efficient gene expression in dynamically changing signaling environments. Copyright © 2015 Elsevier Inc. All rights reserved.

Perspective: Maximum caliber is a general variational principle for dynamical systems.

PubMed

Dixit, Purushottam D; Wagoner, Jason; Weistuch, Corey; Pressé, Steve; Ghosh, Kingshuk; Dill, Ken A

2018-01-07

We review here Maximum Caliber (Max Cal), a general variational principle for inferring distributions of paths in dynamical processes and networks. Max Cal is to dynamical trajectories what the principle of maximum entropy is to equilibrium states or stationary populations. In Max Cal, you maximize a path entropy over all possible pathways, subject to dynamical constraints, in order to predict relative path weights. Many well-known relationships of non-equilibrium statistical physics-such as the Green-Kubo fluctuation-dissipation relations, Onsager's reciprocal relations, and Prigogine's minimum entropy production-are limited to near-equilibrium processes. Max Cal is more general. While it can readily derive these results under those limits, Max Cal is also applicable far from equilibrium. We give examples of Max Cal as a method of inference about trajectory distributions from limited data, finding reaction coordinates in bio-molecular simulations, and modeling the complex dynamics of non-thermal systems such as gene regulatory networks or the collective firing of neurons. We also survey its basis in principle and some limitations.

The big and intricate dreams of little organelles: Embracing complexity in the study of membrane traffic.

PubMed

Liu, Allen P; Botelho, Roberto J; Antonescu, Costin N

2017-09-01

Compartmentalization of eukaryotic cells into dynamic organelles that exchange material through regulated membrane traffic governs virtually every aspect of cellular physiology including signal transduction, metabolism and transcription. Much has been revealed about the molecular mechanisms that control organelle dynamics and membrane traffic and how these processes are regulated by metabolic, physical and chemical cues. From this emerges the understanding of the integration of specific organellar phenomena within complex, multiscale and nonlinear regulatory networks. In this review, we discuss systematic approaches that revealed remarkable insight into the complexity of these phenomena, including the use of proximity-based proteomics, high-throughput imaging, transcriptomics and computational modeling. We discuss how these methods offer insights to further understand molecular versatility and organelle heterogeneity, phenomena that allow a single organelle population to serve a range of physiological functions. We also detail on how transcriptional circuits drive organelle adaptation, such that organelles may shift their function to better serve distinct differentiation and stress conditions. Thus, organelle dynamics and membrane traffic are functionally heterogeneous and adaptable processes that coordinate with higher-order system behavior to optimize cell function under a range of contexts. Obtaining a comprehensive understanding of organellar phenomena will increasingly require combined use of reductionist and system-based approaches. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Computational complexity of ecological and evolutionary spatial dynamics

PubMed Central

Ibsen-Jensen, Rasmus; Chatterjee, Krishnendu; Nowak, Martin A.

2015-01-01

There are deep, yet largely unexplored, connections between computer science and biology. Both disciplines examine how information proliferates in time and space. Central results in computer science describe the complexity of algorithms that solve certain classes of problems. An algorithm is deemed efficient if it can solve a problem in polynomial time, which means the running time of the algorithm is a polynomial function of the length of the input. There are classes of harder problems for which the fastest possible algorithm requires exponential time. Another criterion is the space requirement of the algorithm. There is a crucial distinction between algorithms that can find a solution, verify a solution, or list several distinct solutions in given time and space. The complexity hierarchy that is generated in this way is the foundation of theoretical computer science. Precise complexity results can be notoriously difficult. The famous question whether polynomial time equals nondeterministic polynomial time (i.e., P = NP) is one of the hardest open problems in computer science and all of mathematics. Here, we consider simple processes of ecological and evolutionary spatial dynamics. The basic question is: What is the probability that a new invader (or a new mutant) will take over a resident population? We derive precise complexity results for a variety of scenarios. We therefore show that some fundamental questions in this area cannot be answered by simple equations (assuming that P is not equal to NP). PMID:26644569

Asteroid family dynamics in the inner main belt

NASA Astrophysics Data System (ADS)

Dykhuis, Melissa Joy

The inner main asteroid belt is an important source of near-Earth objects and terrestrial planet impactors; however, the dynamics and history of this region are challenging to understand, due to its high population density and the presence of multiple orbital resonances. This dissertation explores the properties of two of the most populous inner main belt family groups --- the Flora family and the Nysa-Polana complex --- investigating their memberships, ages, spin properties, collision dynamics, and range in orbital and reflectance parameters. Though diffuse, the family associated with asteroid (8) Flora dominates the inner main belt in terms of the extent of its members in orbital parameter space, resulting in its significant overlap with multiple neighboring families. This dissertation introduces a new method for membership determination (the core sample method) which enables the distinction of the Flora family from the background, permitting its further analysis. The Flora family is shown to have a signature in plots of semimajor axis vs. size consistent with that expected for a collisional family dispersed as a result of the Yarkovsky radiation effect. The family's age is determined from the Yarkovsky dispersion to be 950 My. Furthermore, a survey of the spin sense of 21 Flora-region asteroids, accomplished via a time-efficient modification of the epoch method for spin sense determination, confirms the single-collision Yarkovsky-dispersed model for the family's origin. The neighboring Nysa-Polana complex is the likely source region for many of the carbonaceous near-Earth asteroids, several of which are important targets for spacecraft reconnaissance and sample return missions. Family identification in the Nysa-Polana complex via the core sample method reveals two families associated with asteroid (135) Hertha, both with distinct age and reflectance properties. The larger of these two families demonstrates a correlation in semimajor axis and eccentricity indicating that its family-forming collision occurred near the parent body's aphelion. In addition, the Eulalia family is connected with a possible second component, suggesting an anisotropic distribution of ejecta from its collision event.

Self-organized instability in complex ecosystems.

PubMed

Solé, Ricard V; Alonso, David; McKane, Alan

2002-05-29

Why are some ecosystems so rich, yet contain so many rare species? High species diversity, together with rarity, is a general trend in neotropical forests and coral reefs. However, the origin of such diversity and the consequences of food web complexity in both species abundances and temporal fluctuations are not well understood. Several regularities are observed in complex, multispecies ecosystems that suggest that these ecologies might be organized close to points of instability. We explore, in greater depth, a recent stochastic model of population dynamics that is shown to reproduce: (i) the scaling law linking species number and connectivity; (ii) the observed distributions of species abundance reported from field studies (showing long tails and thus a predominance of rare species); (iii) the complex fluctuations displayed by natural communities (including chaotic dynamics); and (iv) the species-area relations displayed by rainforest plots. It is conjectured that the conflict between the natural tendency towards higher diversity due to immigration, and the ecosystem level constraints derived from an increasing number of links, leaves the system poised at a critical boundary separating stable from unstable communities, where large fluctuations are expected to occur. We suggest that the patterns displayed by species-rich communities, including rarity, would result from such a spontaneous tendency towards instability.

Computational Analysis of Hybrid Two-Photon Absorbers with Excited State Absorption

DTIC Science & Technology

2007-03-01

level. This hybrid arrangement creates a complex dynamical system in which the electron carrier concentration of every photo-activated energy level...spatiotemporal details of the electron population densities of each photo-activated energy level as well as the pulse shape in space and time. The main...experiments at low input energy . However, further additions must be done to the calculation of the optical path for high input energy . 1 15. SUBJECT TERM

Towards Computing the Battle for Hearts and Minds: Lessons from the Vendée

NASA Astrophysics Data System (ADS)

Hurwitz, Roger

We analyze the conditions and processes that spawned a historic case of insurgency in the context of regime change. The analysis is an early step in the development of formal models that capture the complex dynamics of insurgencies, resistance and other conflicts that are often characterized as "battles for hearts and minds" (henceforth BHAM). The characterization, however, flattens the complexities of the conflict. It suggests bloodless engagements where victories come from public relations and demonstration projects that foster positive attitudes among a subject population. Officials conducting these battles sometimes use the label to mask their ignorance of the complexities and sometimes with the intention of minimizing their difficulties in dealing with them. Modeling can therefore be a constructive step in overcoming their impoverished thinking.

Population viability of the Snake River chinook salmon (Oncorhynchus tshawytscha)

USGS Publications Warehouse

Emlen, John M.

1995-01-01

In the presence of historical data, population viability models of intermediate complexity can be parameterized and utilized to project the consequences of various management actions for endangered species. A general stochastic population dynamics model with density feedback, age structure, and autocorrelated environmental fluctuations was constructed and parameterized for best fit over 36 years of spring chinook salmon (Oncorhynchus tshawytscha) redd count data in five Idaho index streams. Simulations indicate that persistence of the Snake River spring chinook salmon population depends primarily on density-independent mortality. Improvement of rearing habitat, predator control, reduced fishing pressure, and improved dam passage all would alleviate density-independent mortality. The current value of the Ricker α should provide for a continuation of the status quo. A recovery of the population to 1957–1961 levels within 100 years would require an approximately 75% increase in survival and (or) fecundity. Manipulations of the Ricker β are likely to have little or no effect on persistence versus extinction, but considerable influence on population size.

Asynchronous Rate Chaos in Spiking Neuronal Circuits

PubMed Central

Harish, Omri; Hansel, David

2015-01-01

The brain exhibits temporally complex patterns of activity with features similar to those of chaotic systems. Theoretical studies over the last twenty years have described various computational advantages for such regimes in neuronal systems. Nevertheless, it still remains unclear whether chaos requires specific cellular properties or network architectures, or whether it is a generic property of neuronal circuits. We investigate the dynamics of networks of excitatory-inhibitory (EI) spiking neurons with random sparse connectivity operating in the regime of balance of excitation and inhibition. Combining Dynamical Mean-Field Theory with numerical simulations, we show that chaotic, asynchronous firing rate fluctuations emerge generically for sufficiently strong synapses. Two different mechanisms can lead to these chaotic fluctuations. One mechanism relies on slow I-I inhibition which gives rise to slow subthreshold voltage and rate fluctuations. The decorrelation time of these fluctuations is proportional to the time constant of the inhibition. The second mechanism relies on the recurrent E-I-E feedback loop. It requires slow excitation but the inhibition can be fast. In the corresponding dynamical regime all neurons exhibit rate fluctuations on the time scale of the excitation. Another feature of this regime is that the population-averaged firing rate is substantially smaller in the excitatory population than in the inhibitory population. This is not necessarily the case in the I-I mechanism. Finally, we discuss the neurophysiological and computational significance of our results. PMID:26230679

Move-by-move dynamics of the advantage in chess matches reveals population-level learning of the game.

PubMed

Ribeiro, Haroldo V; Mendes, Renio S; Lenzi, Ervin K; del Castillo-Mussot, Marcelo; Amaral, Luís A N

2013-01-01

The complexity of chess matches has attracted broad interest since its invention. This complexity and the availability of large number of recorded matches make chess an ideal model systems for the study of population-level learning of a complex system. We systematically investigate the move-by-move dynamics of the white player's advantage from over seventy thousand high level chess matches spanning over 150 years. We find that the average advantage of the white player is positive and that it has been increasing over time. Currently, the average advantage of the white player is 0.17 pawns but it is exponentially approaching a value of 0.23 pawns with a characteristic time scale of 67 years. We also study the diffusion of the move dependence of the white player's advantage and find that it is non-Gaussian, has long-ranged anti-correlations and that after an initial period with no diffusion it becomes super-diffusive. We find that the duration of the non-diffusive period, corresponding to the opening stage of a match, is increasing in length and exponentially approaching a value of 15.6 moves with a characteristic time scale of 130 years. We interpret these two trends as a resulting from learning of the features of the game. Additionally, we find that the exponent [Formula: see text] characterizing the super-diffusive regime is increasing toward a value of 1.9, close to the ballistic regime. We suggest that this trend is due to the increased broadening of the range of abilities of chess players participating in major tournaments.

Move-by-Move Dynamics of the Advantage in Chess Matches Reveals Population-Level Learning of the Game

PubMed Central

Ribeiro, Haroldo V.; Mendes, Renio S.; Lenzi, Ervin K.; del Castillo-Mussot, Marcelo; Amaral, Luís A. N.

2013-01-01

The complexity of chess matches has attracted broad interest since its invention. This complexity and the availability of large number of recorded matches make chess an ideal model systems for the study of population-level learning of a complex system. We systematically investigate the move-by-move dynamics of the white player’s advantage from over seventy thousand high level chess matches spanning over 150 years. We find that the average advantage of the white player is positive and that it has been increasing over time. Currently, the average advantage of the white player is 0.17 pawns but it is exponentially approaching a value of 0.23 pawns with a characteristic time scale of 67 years. We also study the diffusion of the move dependence of the white player’s advantage and find that it is non-Gaussian, has long-ranged anti-correlations and that after an initial period with no diffusion it becomes super-diffusive. We find that the duration of the non-diffusive period, corresponding to the opening stage of a match, is increasing in length and exponentially approaching a value of 15.6 moves with a characteristic time scale of 130 years. We interpret these two trends as a resulting from learning of the features of the game. Additionally, we find that the exponent characterizing the super-diffusive regime is increasing toward a value of 1.9, close to the ballistic regime. We suggest that this trend is due to the increased broadening of the range of abilities of chess players participating in major tournaments. PMID:23382876

Predicting the effects of ocean acidification on predator-prey interactions: a conceptual framework based on coastal molluscs.

PubMed

Kroeker, Kristy J; Sanford, Eric; Jellison, Brittany M; Gaylord, Brian

2014-06-01

The influence of environmental change on species interactions will affect population dynamics and community structure in the future, but our current understanding of the outcomes of species interactions in a high-CO2 world is limited. Here, we draw upon emerging experimental research examining the effects of ocean acidification on coastal molluscs to provide hypotheses of the potential impacts of high-CO2 on predator-prey interactions. Coastal molluscs, such as oysters, mussels, and snails, allocate energy among defenses, growth, and reproduction. Ocean acidification increases the energetic costs of physiological processes such as acid-base regulation and calcification. Impacted molluscs can display complex and divergent patterns of energy allocation to defenses and growth that may influence predator-prey interactions; these include changes in shell properties, body size, tissue mass, immune function, or reproductive output. Ocean acidification has also been shown to induce complex changes in chemoreception, behavior, and inducible defenses, including altered cue detection and predator avoidance behaviors. Each of these responses may ultimately alter the susceptibility of coastal molluscs to predation through effects on predator handling time, satiation, and search time. While many of these effects may manifest as increases in per capita predation rates on coastal molluscs, the ultimate outcome of predator-prey interactions will also depend on how ocean acidification affects the specified predators, which also exhibit complex responses to ocean acidification. Changes in predator-prey interactions could have profound and unexplored consequences for the population dynamics of coastal molluscs in a high-CO2 ocean. © 2014 Marine Biological Laboratory.

Energy transfer dynamics in trimers and aggregates of light-harvesting complex II probed by 2D electronic spectroscopy

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

Enriquez, Miriam M.; Zhang, Cheng; Tan, Howe-Siang, E-mail: howesiang@ntu.edu.sg

2015-06-07

The pathways and dynamics of excitation energy transfer between the chlorophyll (Chl) domains in solubilized trimeric and aggregated light-harvesting complex II (LHCII) are examined using two-dimensional electronic spectroscopy (2DES). The LHCII trimers and aggregates exhibit the unquenched and quenched excitonic states of Chl a, respectively. 2DES allows direct correlation of excitation and emission energies of coupled states over population time delays, hence enabling mapping of the energy flow between Chls. By the excitation of the entire Chl b Q{sub y} band, energy transfer from Chl b to Chl a states is monitored in the LHCII trimers and aggregates. Global analysismore » of the two-dimensional (2D) spectra reveals that energy transfer from Chl b to Chl a occurs on fast and slow time scales of 240–270 fs and 2.8 ps for both forms of LHCII. 2D decay-associated spectra resulting from the global analysis identify the correlation between Chl states involved in the energy transfer and decay at a given lifetime. The contribution of singlet–singlet annihilation on the kinetics of Chl energy transfer and decay is also modelled and discussed. The results show a marked change in the energy transfer kinetics in the time range of a few picoseconds. Owing to slow energy equilibration processes, long-lived intermediate Chl a states are present in solubilized trimers, while in aggregates, the population decay of these excited states is significantly accelerated, suggesting that, overall, the energy transfer within the LHCII complexes is faster in the aggregated state.« less

The Anthropocene Generalized: Evolution of Exo-Civilizations and Their Planetary Feedback.

PubMed

Frank, A; Carroll-Nellenback, Jonathan; Alberti, M; Kleidon, A

2018-05-01

We present a framework for studying generic behaviors possible in the interaction between a resource-harvesting technological civilization (an exo-civilization) and the planetary environment in which it evolves. Using methods from dynamical systems theory, we introduce and analyze a suite of simple equations modeling a population which consumes resources for the purpose of running a technological civilization and the feedback those resources drive on the state of the host planet. The feedbacks can drive the planet away from the initial state the civilization originated in and into domains that are detrimental to its sustainability. Our models conceptualize the problem primarily in terms of feedbacks from the resource use onto the coupled planetary systems. In addition, we also model the population growth advantages gained via the harvesting of these resources. We present three models of increasing complexity: (1) Civilization-planetary interaction with a single resource; (2) Civilization-planetary interaction with two resources each of which has a different level of planetary system feedback; (3) Civilization-planetary interaction with two resources and nonlinear planetary feedback (i.e., runaways). All three models show distinct classes of exo-civilization trajectories. We find smooth entries into long-term, "sustainable" steady states. We also find population booms followed by various levels of "die-off." Finally, we also observe rapid "collapse" trajectories for which the population approaches n = 0. Our results are part of a program for developing an "Astrobiology of the Anthropocene" in which questions of sustainability, centered on the coupled Earth-system, can be seen in their proper astronomical/planetary context. We conclude by discussing the implications of our results for both the coupled Earth system and for the consideration of exo-civilizations across cosmic history. Key Words: Anthropocene-Astrobiology-Civilization-Dynamical system theory-Exoplanets-Population dynamics. Astrobiology 18, 503-518.

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

PubMed

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

2016-06-01

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

Long-term dynamics of Mycoplasma conjunctivae at the wildlife-livestock interface in the Pyrenees

PubMed Central

Cabezón, Oscar; Frey, Joachim; Velarde, Roser; Serrano, Emmanuel; Colom-Cadena, Andreu; Gelormini, Giuseppina; Marco, Ignasi; Mentaberre, Gregorio; Lavín, Santiago; López-Olvera, Jorge Ramón

2017-01-01

Functional roles of domestic and wild host populations in infectious keratoconjunctivitis (IKC) epidemiology have been extensively discussed claiming a domestic reservoir for the more susceptible wild hosts, however, based on limited data. With the aim to better assess IKC epidemiology in complex host-pathogen alpine systems, the long-term infectious dynamics and molecular epidemiology of Mycoplasma conjunctivae was investigated in all host populations from six study areas in the Pyrenees and one in the Cantabrian Mountains (Northern Spain). Detection of M. conjunctivae was performed by qPCR on 3600 eye swabs collected during seven years from hunted wild ungulates and sympatric domestic sheep (n = 1800 animals), and cluster analyses of the strains were performed including previous reported local strains. Mycoplasma conjunctivae was consistently detected in three Pyrenean chamois (Rupicapra p. pyrenaica) populations, as well as in sheep flocks (17.0% of sheep) and occasionally in mouflon (Ovis aries musimon) from the Pyrenees (22.2% in one year/area); statistically associated with ocular clinical signs only in chamois. Chamois populations showed different infection dynamics with low but steady prevalence (4.9%) and significant yearly fluctuations (0.0%– 40.0%). Persistence of specific M. conjunctivae strain clusters in wild host populations is demonstrated for six and nine years. Cross-species transmission between chamois and sheep and chamois and mouflon were also sporadically evidenced. Overall, independent M. conjunctivae sylvatic and domestic cycles occurred at the wildlife-livestock interface in the alpine ecosystems from the Pyrenees with sheep and chamois as the key host species for each cycle, and mouflon as a spill-over host. Host population characteristics and M. conjunctivae strains resulted in different epidemiological scenarios in chamois, ranging from the fading out of the mycoplasma to the epidemic and endemic long-term persistence. These findings highlight the capacity of M. conjunctivae to establish diverse interactions and persist in host populations, also with different transmission conditions. PMID:29016676

Cryptic herbivores mediate the strength and form of ungulate impacts on a long-lived savanna tree.

PubMed

Maclean, Janet E; Goheen, Jacob R; Doak, Daniel F; Palmer, Todd M; Young, Truman P

2011-08-01

Plant populations are regulated by a diverse array of herbivores that impose demographic filters throughout their life cycle. Few studies, however, simultaneously quantify the impacts of multiple herbivore guilds on the lifetime performance or population growth rate of plants. In African savannas, large ungulates (such as elephants) are widely regarded as important drivers of woody plant population dynamics, while the potential impacts of smaller, more cryptic herbivores (such as rodents) have largely been ignored. We combined a large-scale ungulate exclusion experiment with a five-year manipulation of rodent densities to quantify the impacts of three herbivore guilds (wild ungulates, domestic cattle, and rodents) on all life stages of a widespread savanna tree. We utilized demographic modeling to reveal the overall role of each guild in regulating tree population dynamics, and to elucidate the importance of different demographic hurdles in driving population growth under contrasting consumer communities. We found that wild ungulates dramatically reduced population growth, shifting the population trajectory from increase to decline, but that the mechanisms driving these effects were strongly mediated by rodents. The impact of wild ungulates on population growth was predominantly driven by their negative effect on tree reproduction when rodents were excluded, and on adult tree survival when rodents were present. By limiting seedling survival, rodents also reduced population growth; however, this effect was strongly dampened where wild ungulates were present. We suggest that these complex interactions between disparate consumer guilds can have important consequences for the population demography of long-lived species, and that the effects of a single consumer group are often likely to vary dramatically depending on the larger community in which interactions are embedded.

Multistate matrix population model to assess the contributions and impacts on population abundance of domestic cats in urban areas including owned cats, unowned cats, and cats in shelters

PubMed Central

Coe, Jason B.

2018-01-01

Concerns over cat homelessness, over-taxed animal shelters, public health risks, and environmental impacts has raised attention on urban-cat populations. To truly understand cat population dynamics, the collective population of owned cats, unowned cats, and cats in the shelter system must be considered simultaneously because each subpopulation contributes differently to the overall population of cats in a community (e.g., differences in neuter rates, differences in impacts on wildlife) and cats move among categories through human interventions (e.g., adoption, abandonment). To assess this complex socio-ecological system, we developed a multistate matrix model of cats in urban areas that include owned cats, unowned cats (free-roaming and feral), and cats that move through the shelter system. Our model requires three inputs—location, number of human dwellings, and urban area—to provide testable predictions of cat abundance for any city in North America. Model-predicted population size of unowned cats in seven Canadian cities were not significantly different than published estimates (p = 0.23). Model-predicted proportions of sterile feral cats did not match observed sterile cat proportions for six USA cities (p = 0.001). Using a case study from Guelph, Ontario, Canada, we compared model-predicted to empirical estimates of cat abundance in each subpopulation and used perturbation analysis to calculate relative sensitivity of vital rates to cat abundance to demonstrate how management or mismanagement in one portion of the population could have repercussions across all portions of the network. Our study provides a general framework to consider cat population abundance in urban areas and, with refinement that includes city-specific parameter estimates and modeling, could provide a better understanding of population dynamics of cats in our communities. PMID:29489854

Multistate matrix population model to assess the contributions and impacts on population abundance of domestic cats in urban areas including owned cats, unowned cats, and cats in shelters.

PubMed

Flockhart, D T Tyler; Coe, Jason B

2018-01-01

Concerns over cat homelessness, over-taxed animal shelters, public health risks, and environmental impacts has raised attention on urban-cat populations. To truly understand cat population dynamics, the collective population of owned cats, unowned cats, and cats in the shelter system must be considered simultaneously because each subpopulation contributes differently to the overall population of cats in a community (e.g., differences in neuter rates, differences in impacts on wildlife) and cats move among categories through human interventions (e.g., adoption, abandonment). To assess this complex socio-ecological system, we developed a multistate matrix model of cats in urban areas that include owned cats, unowned cats (free-roaming and feral), and cats that move through the shelter system. Our model requires three inputs-location, number of human dwellings, and urban area-to provide testable predictions of cat abundance for any city in North America. Model-predicted population size of unowned cats in seven Canadian cities were not significantly different than published estimates (p = 0.23). Model-predicted proportions of sterile feral cats did not match observed sterile cat proportions for six USA cities (p = 0.001). Using a case study from Guelph, Ontario, Canada, we compared model-predicted to empirical estimates of cat abundance in each subpopulation and used perturbation analysis to calculate relative sensitivity of vital rates to cat abundance to demonstrate how management or mismanagement in one portion of the population could have repercussions across all portions of the network. Our study provides a general framework to consider cat population abundance in urban areas and, with refinement that includes city-specific parameter estimates and modeling, could provide a better understanding of population dynamics of cats in our communities.

Modeling the Pre-Industrial Roots of Modern Super-Exponential Population Growth

PubMed Central

Stutz, Aaron Jonas

2014-01-01

To Malthus, rapid human population growth—so evident in 18th Century Europe—was obviously unsustainable. In his Essay on the Principle of Population, Malthus cogently argued that environmental and socioeconomic constraints on population rise were inevitable. Yet, he penned his essay on the eve of the global census size reaching one billion, as nearly two centuries of super-exponential increase were taking off. Introducing a novel extension of J. E. Cohen's hallmark coupled difference equation model of human population dynamics and carrying capacity, this article examines just how elastic population growth limits may be in response to demographic change. The revised model involves a simple formalization of how consumption costs influence carrying capacity elasticity over time. Recognizing that complex social resource-extraction networks support ongoing consumption-based investment in family formation and intergenerational resource transfers, it is important to consider how consumption has impacted the human environment and demography—especially as global population has become very large. Sensitivity analysis of the consumption-cost model's fit to historical population estimates, modern census data, and 21st Century demographic projections supports a critical conclusion. The recent population explosion was systemically determined by long-term, distinctly pre-industrial cultural evolution. It is suggested that modern globalizing transitions in technology, susceptibility to infectious disease, information flows and accumulation, and economic complexity were endogenous products of much earlier biocultural evolution of family formation's embeddedness in larger, hierarchically self-organizing cultural systems, which could potentially support high population elasticity of carrying capacity. Modern super-exponential population growth cannot be considered separately from long-term change in the multi-scalar political economy that connects family formation and intergenerational resource transfers to wider institutions and social networks. PMID:25141019

Potassium conductance dynamics confer robust spike-time precision in a neuromorphic model of the auditory brain stem

PubMed Central

Boahen, Kwabena

2013-01-01

A fundamental question in neuroscience is how neurons perform precise operations despite inherent variability. This question also applies to neuromorphic engineering, where low-power microchips emulate the brain using large populations of diverse silicon neurons. Biological neurons in the auditory pathway display precise spike timing, critical for sound localization and interpretation of complex waveforms such as speech, even though they are a heterogeneous population. Silicon neurons are also heterogeneous, due to a key design constraint in neuromorphic engineering: smaller transistors offer lower power consumption and more neurons per unit area of silicon, but also more variability between transistors and thus between silicon neurons. Utilizing this variability in a neuromorphic model of the auditory brain stem with 1,080 silicon neurons, we found that a low-voltage-activated potassium conductance (gKL) enables precise spike timing via two mechanisms: statically reducing the resting membrane time constant and dynamically suppressing late synaptic inputs. The relative contribution of these two mechanisms is unknown because blocking gKL in vitro eliminates dynamic adaptation but also lengthens the membrane time constant. We replaced gKL with a static leak in silico to recover the short membrane time constant and found that silicon neurons could mimic the spike-time precision of their biological counterparts, but only over a narrow range of stimulus intensities and biophysical parameters. The dynamics of gKL were required for precise spike timing robust to stimulus variation across a heterogeneous population of silicon neurons, thus explaining how neural and neuromorphic systems may perform precise operations despite inherent variability. PMID:23554436

A decision-support tool to inform Australian strategies for preventing suicide and suicidal behaviour.

PubMed

Page, Andrew; Atkinson, Jo-An; Heffernan, Mark; McDonnell, Geoff; Hickie, Ian

2017-04-27

Dynamic simulation modelling is increasingly being recognised as a valuable decision-support tool to help guide investments and actions to address complex public health issues such as suicide. In particular, participatory system dynamics (SD) modelling provides a useful tool for asking high-level 'what if' questions, and testing the likely impacts of different combinations of policies and interventions at an aggregate level before they are implemented in the real world. We developed an SD model for suicide prevention in Australia, and investigated the hypothesised impacts over the next 10 years (2015-2025) of a combination of current intervention strategies proposed for population interventions in Australia: 1) general practitioner (GP) training, 2) coordinated aftercare in those who have attempted suicide, 3) school-based mental health literacy programs, 4) brief-contact interventions in hospital settings, and 5) psychosocial treatment approaches. Findings suggest that the largest reductions in suicide were associated with GP training (6%) and coordinated aftercare approaches (4%), with total reductions of 12% for all interventions combined. This paper highlights the value of dynamic modelling methods for managing complexity and uncertainty, and demonstrates their potential use as a decision-support tool for policy makers and program planners for community suicide prevention actions.

Human Disturbance Influences Reproductive Success and Growth Rate in California Sea Lions (Zalophus californianus)

PubMed Central

French, Susannah S.; González-Suárez, Manuela; Young, Julie K.; Durham, Susan; Gerber, Leah R.

2011-01-01

The environment is currently undergoing changes at both global (e.g., climate change) and local (e.g., tourism, pollution, habitat modification) scales that have the capacity to affect the viability of animal and plant populations. Many of these changes, such as human disturbance, have an anthropogenic origin and therefore may be mitigated by management action. To do so requires an understanding of the impact of human activities and changing environmental conditions on population dynamics. We investigated the influence of human activity on important life history parameters (reproductive rate, and body condition, and growth rate of neonate pups) for California sea lions (Zalophus californianus) in the Gulf of California, Mexico. Increased human presence was associated with lower reproductive rates, which translated into reduced long-term population growth rates and suggested that human activities are a disturbance that could lead to population declines. We also observed higher body growth rates in pups with increased exposure to humans. Increased growth rates in pups may reflect a density dependent response to declining reproductive rates (e.g., decreased competition for resources). Our results highlight the potentially complex changes in life history parameters that may result from human disturbance, and their implication for population dynamics. We recommend careful monitoring of human activities in the Gulf of California and emphasize the importance of management strategies that explicitly consider the potential impact of human activities such as ecotourism on vertebrate populations. PMID:21436887

Complex dynamics at the interface between wild and domestic viruses of finfish

USGS Publications Warehouse

Kurath, G.; Winton, J.

2011-01-01

Viral traffic occurs readily between wild and domesticated stocks of finfish because aquatic environments have greater connectivity than their terrestrial counterparts and because the global expansion and dynamic nature of intensive aquaculture provide multiple pathways of transmission and unique drivers of virus adaptation. Supported by examples from the literature, we provide reasons why viruses move from wild fish reservoirs to infect domestic fish in aquaculture more readily than 'domestic' viruses move across the interface to infect wild stocks. We also hypothesize that 'wild' viruses moving across the interface to domestic populations of finfish are more frequently associated with disease outbreaks and host switches compared to domestic viruses that cross the interface to infect wild fish.

A robust and tunable mitotic oscillator in artificial cells

PubMed Central

Wang, Shiyuan; Barnes, Patrick M; Liu, Xuwen; Xu, Haotian; Jin, Minjun; Liu, Allen P

2018-01-01

Single-cell analysis is pivotal to deciphering complex phenomena like heterogeneity, bistability, and asynchronous oscillations, where a population ensemble cannot represent individual behaviors. Bulk cell-free systems, despite having unique advantages of manipulation and characterization of biochemical networks, lack the essential single-cell information to understand a class of out-of-steady-state dynamics including cell cycles. Here, by encapsulating Xenopus egg extracts in water-in-oil microemulsions, we developed artificial cells that are adjustable in sizes and periods, sustain mitotic oscillations for over 30 cycles, and function in forms from the simplest cytoplasmic-only to the more complicated ones involving nuclear dynamics, mimicking real cells. Such innate flexibility and robustness make it key to studying clock properties like tunability and stochasticity. Our results also highlight energy as an important regulator of cell cycles. We demonstrate a simple, powerful, and likely generalizable strategy of integrating strengths of single-cell approaches into conventional in vitro systems to study complex clock functions. PMID:29620527

Cloud Model-Based Artificial Immune Network for Complex Optimization Problem

PubMed Central

Wang, Mingan; Li, Jianming; Guo, Dongliang

2017-01-01

This paper proposes an artificial immune network based on cloud model (AINet-CM) for complex function optimization problems. Three key immune operators—cloning, mutation, and suppression—are redesigned with the help of the cloud model. To be specific, an increasing half cloud-based cloning operator is used to adjust the dynamic clone multipliers of antibodies, an asymmetrical cloud-based mutation operator is used to control the adaptive evolution of antibodies, and a normal similarity cloud-based suppressor is used to keep the diversity of the antibody population. To quicken the searching convergence, a dynamic searching step length strategy is adopted. For comparative study, a series of numerical simulations are arranged between AINet-CM and the other three artificial immune systems, that is, opt-aiNet, IA-AIS, and AAIS-2S. Furthermore, two industrial applications—finite impulse response (FIR) filter design and proportional-integral-differential (PID) controller tuning—are investigated and the results demonstrate the potential searching capability and practical value of the proposed AINet-CM algorithm. PMID:28630620

The complex nature of storm-time ion dynamics: Transport and local acceleration

DOE PAGES

Denton, M. H.; Reeves, G. D.; Thomsen, M. F.; ...

2016-09-29

Data from the Van Allen Probes Helium, Oxygen, Proton, and Electron (HOPE) spectrometers reveal hitherto unresolved spatial structure and dynamics in ion populations. Complex regions of O + dominance, at energies from a few eV to >10 keV, are observed throughout the magnetosphere. Isolated regions on the dayside that are rich in energetic O + might easily be interpreted as strong energization of ionospheric plasma. In this paper, we demonstrate, however, that both the energy spectrum and the limited magnetic local time extent of these features can be explained by energy-dependent drift of particles injected on the nightside 24 hmore » earlier. Particle tracing simulations show that the energetic O + can originate in the magnetotail, not in the ionosphere. Finally, enhanced wave activity is colocated with the heavy ion-rich plasma, and we further conclude that the waves were not a source of free energy for accelerating ionospheric plasma but rather the consequence of the arrival of substorm-injected plasma.« less

Cloud Model-Based Artificial Immune Network for Complex Optimization Problem.

PubMed

Wang, Mingan; Feng, Shuo; Li, Jianming; Li, Zhonghua; Xue, Yu; Guo, Dongliang

2017-01-01

This paper proposes an artificial immune network based on cloud model (AINet-CM) for complex function optimization problems. Three key immune operators-cloning, mutation, and suppression-are redesigned with the help of the cloud model. To be specific, an increasing half cloud-based cloning operator is used to adjust the dynamic clone multipliers of antibodies, an asymmetrical cloud-based mutation operator is used to control the adaptive evolution of antibodies, and a normal similarity cloud-based suppressor is used to keep the diversity of the antibody population. To quicken the searching convergence, a dynamic searching step length strategy is adopted. For comparative study, a series of numerical simulations are arranged between AINet-CM and the other three artificial immune systems, that is, opt-aiNet, IA-AIS, and AAIS-2S. Furthermore, two industrial applications-finite impulse response (FIR) filter design and proportional-integral-differential (PID) controller tuning-are investigated and the results demonstrate the potential searching capability and practical value of the proposed AINet-CM algorithm.

Dynamical complexity in a mean-field model of human EEG

NASA Astrophysics Data System (ADS)

Frascoli, Federico; Dafilis, Mathew P.; van Veen, Lennaert; Bojak, Ingo; Liley, David T. J.

2008-12-01

A recently proposed mean-field theory of mammalian cortex rhythmogenesis describes the salient features of electrical activity in the cerebral macrocolumn, with the use of inhibitory and excitatory neuronal populations (Liley et al 2002). This model is capable of producing a range of important human EEG (electroencephalogram) features such as the alpha rhythm, the 40 Hz activity thought to be associated with conscious awareness (Bojak & Liley 2007) and the changes in EEG spectral power associated with general anesthetic effect (Bojak & Liley 2005). From the point of view of nonlinear dynamics, the model entails a vast parameter space within which multistability, pseudoperiodic regimes, various routes to chaos, fat fractals and rich bifurcation scenarios occur for physiologically relevant parameter values (van Veen & Liley 2006). The origin and the character of this complex behaviour, and its relevance for EEG activity will be illustrated. The existence of short-lived unstable brain states will also be discussed in terms of the available theoretical and experimental results. A perspective on future analysis will conclude the presentation.

Effect of flow and peristaltic mixing on bacterial growth in a gut-like channel

PubMed Central

Cremer, Jonas; Segota, Igor; Yang, Chih-yu; Arnoldini, Markus; Sauls, John T.; Zhang, Zhongge; Gutierrez, Edgar; Groisman, Alex; Hwa, Terence

2016-01-01

The ecology of microbes in the gut has been shown to play important roles in the health of the host. To better understand microbial growth and population dynamics in the proximal colon, the primary region of bacterial growth in the gut, we built and applied a fluidic channel that we call the “minigut.” This is a channel with an array of membrane valves along its length, which allows mimicking active contractions of the colonic wall. Repeated contraction is shown to be crucial in maintaining a steady-state bacterial population in the device despite strong flow along the channel that would otherwise cause bacterial washout. Depending on the flow rate and the frequency of contractions, the bacterial density profile exhibits varying spatial dependencies. For a synthetic cross-feeding community, the species abundance ratio is also strongly affected by mixing and flow along the length of the device. Complex mixing dynamics due to contractions is described well by an effective diffusion term. Bacterial dynamics is captured by a simple reaction–diffusion model without adjustable parameters. Our results suggest that flow and mixing play a major role in shaping the microbiota of the colon. PMID:27681630

Multi-scale individual-based model of microbial and bioconversion dynamics in aerobic granular sludge.

PubMed

Xavier, Joao B; De Kreuk, Merle K; Picioreanu, Cristian; Van Loosdrecht, Mark C M

2007-09-15

Aerobic granular sludge is a novel compact biological wastewater treatment technology for integrated removal of COD (chemical oxygen demand), nitrogen, and phosphate charges. We present here a multiscale model of aerobic granular sludge sequencing batch reactors (GSBR) describing the complex dynamics of populations and nutrient removal. The macro scale describes bulk concentrations and effluent composition in six solutes (oxygen, acetate, ammonium, nitrite, nitrate, and phosphate). A finer scale, the scale of one granule (1.1 mm of diameter), describes the two-dimensional spatial arrangement of four bacterial groups--heterotrophs, ammonium oxidizers, nitrite oxidizers, and phosphate accumulating organisms (PAO)--using individual based modeling (IbM) with species-specific kinetic models. The model for PAO includes three internal storage compounds: polyhydroxyalkanoates (PHA), poly phosphate, and glycogen. Simulations of long-term reactor operation show how the microbial population and activity depends on the operating conditions. Short-term dynamics of solute bulk concentrations are also generated with results comparable to experimental data from lab scale reactors. Our results suggest that N-removal in GSBR occurs mostly via alternating nitrification/denitrification rather than simultaneous nitrification/denitrification, supporting an alternative strategy to improve N-removal in this promising wastewater treatment process.

Consumption, supply and transport: self-organization without direct communication

NASA Technical Reports Server (NTRS)

Kessler, J. O.

1996-01-01

Swimming bacteria of the species Bacillus subtilis require and consume oxygen. In static liquid cultures the cells' swimming behaviour leads them to accumulate up oxygen concentration gradients generated by consumption and supply. Since the density of bacterial cells exceeds that of the fluid in which they live, fluid regions where cells have accumulated are denser than depleted regions. These density variations cause convection. The fluid motion is dynamically maintained by the swimming of the cells toward regions of attraction: the air-fluid interface and the fluctuating advecting attractors, gradients of oxygen concentration that are embedded in the convecting fluid. Because of the fluid dynamical conservation laws, these complex physical and biological factors generate patterns ordered over distances > 10000 bacterial cell diameters. The convection enhances long-range transport and mixing of oxygen, cells and extracellular products by orders of magnitude. Thus, through the interplay of physical and biological factors, a population of undifferentiated selfish cells creates functional dynamic patterns. Populations of bacteria that have organised themselves into regularly patterned regions of vigorous convection and varying cell concentration interact with their environment as if they were one purposeful, coherent multicellular individual. The mathematical and experimental ingredients of these remarkable phenomena are presented here.

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

Deng, Ye; Zhang, Ping; Qin, Yujia

When trying to discern network interactions among different species/populations in microbial communities interests have been evoked in recent years, but little information is available about temporal dynamics of microbial network interactions in response to environmental perturbations. We modified the random matrix theory-based network approach to discern network succession in groundwater microbial communities in response to emulsified vegetable oil (EVO) amendment for uranium bioremediation. Groundwater microbial communities from one control and seven monitor wells were analysed with a functional gene array (GeoChip 3.0), and functional molecular ecological networks (fMENs) at different time points were reconstructed. Our results showed that the networkmore » interactions were dramatically altered by EVO amendment. Dynamic and resilient succession was evident: fairly simple at the initial stage (Day 0), increasingly complex at the middle period (Days 4, 17, 31), most complex at Day 80, and then decreasingly complex at a later stage (140–269 days). Unlike previous studies in other habitats, negative interactions predominated in a time-series fMEN, suggesting strong competition among different microbial species in the groundwater systems after EVO injection. In particular, several keystone sulfate-reducing bacteria showed strong negative interactions with their network neighbours. These results provide mechanistic understanding of the decreased phylogenetic diversity during environmental perturbations.« less

A Systems Approach to Vaccine Decision Making

PubMed Central

Lee, Bruce Y.; Mueller, Leslie E.; Tilchin, Carla G.

2016-01-01

Vaccines reside in a complex multiscale system that includes biological, clinical, behavioral, social, operational, environmental, and economical relationships. Not accounting for these systems when making decisions about vaccines can result in changes that have little effect rather than solutions, lead to unsustainable solutions, miss indirect (e.g., secondary, tertiary, and beyond) effects, cause unintended consequences, and lead to wasted time, effort, and resources. Mathematical and computational modeling can help better understand and address complex systems by representing all or most of the components, relationships, and processes. Such models can serve as “virtual laboratories” to examine how a system operates and test the effects of different changes within the system. Here are ten lessons learned from using computational models to bring more of a systems approach to vaccine decision making: (i) traditional single measure approaches may overlook opportunities; (ii) there is complex interplay among many vaccine, population, and disease characteristics; (iii) accounting for perspective can identify synergies; (iv) the distribution system should not be overlooked; (v) target population choice can have secondary and tertiary effects; (vi) potentially overlooked characteristics can be important; (vii) characteristics of one vaccine can affect other vaccines; (viii) the broader impact of vaccines is complex; (ix) vaccine administration extends beyond the provider level; (x) and the value of vaccines is dynamic. PMID:28017430

A systems approach to vaccine decision making.

PubMed

Lee, Bruce Y; Mueller, Leslie E; Tilchin, Carla G

2017-01-20

Vaccines reside in a complex multiscale system that includes biological, clinical, behavioral, social, operational, environmental, and economical relationships. Not accounting for these systems when making decisions about vaccines can result in changes that have little effect rather than solutions, lead to unsustainable solutions, miss indirect (e.g., secondary, tertiary, and beyond) effects, cause unintended consequences, and lead to wasted time, effort, and resources. Mathematical and computational modeling can help better understand and address complex systems by representing all or most of the components, relationships, and processes. Such models can serve as "virtual laboratories" to examine how a system operates and test the effects of different changes within the system. Here are ten lessons learned from using computational models to bring more of a systems approach to vaccine decision making: (i) traditional single measure approaches may overlook opportunities; (ii) there is complex interplay among many vaccine, population, and disease characteristics; (iii) accounting for perspective can identify synergies; (iv) the distribution system should not be overlooked; (v) target population choice can have secondary and tertiary effects; (vi) potentially overlooked characteristics can be important; (vii) characteristics of one vaccine can affect other vaccines; (viii) the broader impact of vaccines is complex; (ix) vaccine administration extends beyond the provider level; and (x) the value of vaccines is dynamic. Copyright © 2016 Elsevier Ltd. All rights reserved.

Elastic Multi-scale Mechanisms: Computation and Biological Evolution.

PubMed

Diaz Ochoa, Juan G

2018-01-01

Explanations based on low-level interacting elements are valuable and powerful since they contribute to identify the key mechanisms of biological functions. However, many dynamic systems based on low-level interacting elements with unambiguous, finite, and complete information of initial states generate future states that cannot be predicted, implying an increase of complexity and open-ended evolution. Such systems are like Turing machines, that overlap with dynamical systems that cannot halt. We argue that organisms find halting conditions by distorting these mechanisms, creating conditions for a constant creativity that drives evolution. We introduce a modulus of elasticity to measure the changes in these mechanisms in response to changes in the computed environment. We test this concept in a population of predators and predated cells with chemotactic mechanisms and demonstrate how the selection of a given mechanism depends on the entire population. We finally explore this concept in different frameworks and postulate that the identification of predictive mechanisms is only successful with small elasticity modulus.

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

PubMed

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

2015-01-01

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

Three-dimensional confocal morphometry – a new approach for studying dynamic changes in cell morphology in brain slices

PubMed Central

Chvátal, Alexandr; Anděrová, Miroslava; Kirchhoff, Frank

2007-01-01

Pathological states in the central nervous system lead to dramatic changes in the activity of neuroactive substances in the extracellular space, to changes in ionic homeostasis and often to cell swelling. To quantify changes in cell morphology over a certain period of time, we employed a new technique, three-dimensional confocal morphometry. In our experiments, performed on enhanced green fluorescent protein/glial fibrillary acidic protein astrocytes in brain slices in situ and thus preserving the extracellular microenvironment, confocal morphometry revealed that the application of hypotonic solution evoked two types of volume change. In one population of astrocytes, hypotonic stress evoked small cell volume changes followed by a regulatory volume decrease, while in the second population volume changes were significantly larger without subsequent volume regulation. Three-dimensional cell reconstruction revealed that even though the total astrocyte volume increased during hypotonic stress, the morphological changes in various cell compartments and processes were more complex than have been previously shown, including swelling, shrinking and structural rearrangement. Our data show that astrocytes in brain slices in situ during hypotonic stress display complex behaviour. One population of astrocytes is highly capable of cell volume regulation, while the second population is characterized by prominent cell swelling, accompanied by plastic changes in morphology. It is possible to speculate that these two astrocyte populations play different roles during physiological and pathological states. PMID:17488344

Ecology of zoonotic infectious diseases in bats: current knowledge and future directions

USGS Publications Warehouse

Hayman, D.T.; Bowen, R.A.; Cryan, P.M.; McCracken, G.F.; O'Shea, T.J.; Peel, A.J.; Gilbert, A.; Webb, C.T.; Wood, J.L.

2013-01-01

Bats are hosts to a range of zoonotic and potentially zoonotic pathogens. Human activities that increase exposure to bats will likely increase the opportunity for infections to spill over in the future. Ecological drivers of pathogen spillover and emergence in novel hosts, including humans, involve a complex mixture of processes, and understanding these complexities may aid in predicting spillover. In particular, only once the pathogen and host ecologies are known can the impacts of anthropogenic changes be fully appreciated. Cross-disciplinary approaches are required to understand how host and pathogen ecology interact. Bats differ from other sylvatic disease reservoirs because of their unique and diverse lifestyles, including their ability to fly, often highly gregarious social structures, long lifespans and low fecundity rates. We highlight how these traits may affect infection dynamics and how both host and pathogen traits may interact to affect infection dynamics. We identify key questions relating to the ecology of infectious diseases in bats and propose that a combination of field and laboratory studies are needed to create data-driven mechanistic models to elucidate those aspects of bat ecology that are most critical to the dynamics of emerging bat viruses. If commonalities can be found, then predicting the dynamics of newly emerging diseases may be possible. This modelling approach will be particularly important in scenarios when population surveillance data are unavailable and when it is unclear which aspects of host ecology are driving infection dynamics.

Ecology of Zoonotic Infectious Diseases in Bats: Current Knowledge and Future Directions

PubMed Central

Hayman, D T S; Bowen, R A; Cryan, P M; McCracken, G F; O’Shea, T J; Peel, A J; Gilbert, A; Webb, C T; Wood, J L N

2013-01-01

Bats are hosts to a range of zoonotic and potentially zoonotic pathogens. Human activities that increase exposure to bats will likely increase the opportunity for infections to spill over in the future. Ecological drivers of pathogen spillover and emergence in novel hosts, including humans, involve a complex mixture of processes, and understanding these complexities may aid in predicting spillover. In particular, only once the pathogen and host ecologies are known can the impacts of anthropogenic changes be fully appreciated. Cross-disciplinary approaches are required to understand how host and pathogen ecology interact. Bats differ from other sylvatic disease reservoirs because of their unique and diverse lifestyles, including their ability to fly, often highly gregarious social structures, long lifespans and low fecundity rates. We highlight how these traits may affect infection dynamics and how both host and pathogen traits may interact to affect infection dynamics. We identify key questions relating to the ecology of infectious diseases in bats and propose that a combination of field and laboratory studies are needed to create data-driven mechanistic models to elucidate those aspects of bat ecology that are most critical to the dynamics of emerging bat viruses. If commonalities can be found, then predicting the dynamics of newly emerging diseases may be possible. This modelling approach will be particularly important in scenarios when population surveillance data are unavailable and when it is unclear which aspects of host ecology are driving infection dynamics. PMID:22958281

Predation Risk Shapes Social Networks in Fission-Fusion Populations

PubMed Central

Kelley, Jennifer L.; Morrell, Lesley J.; Inskip, Chloe; Krause, Jens; Croft, Darren P.

2011-01-01

Predation risk is often associated with group formation in prey, but recent advances in methods for analysing the social structure of animal societies make it possible to quantify the effects of risk on the complex dynamics of spatial and temporal organisation. In this paper we use social network analysis to investigate the impact of variation in predation risk on the social structure of guppy shoals and the frequency and duration of shoal splitting (fission) and merging (fusion) events. Our analyses revealed that variation in the level of predation risk was associated with divergent social dynamics, with fish in high-risk populations displaying a greater number of associations with overall greater strength and connectedness than those from low-risk sites. Temporal patterns of organisation also differed according to predation risk, with fission events more likely to occur over two short time periods (5 minutes and 20 minutes) in low-predation fish and over longer time scales (>1.5 hours) in high-predation fish. Our findings suggest that predation risk influences the fine-scale social structure of prey populations and that the temporal aspects of organisation play a key role in defining social systems. PMID:21912627

Effects of paternal phenotype and environmental variability on age and size at maturity in a male dimorphic mite

NASA Astrophysics Data System (ADS)

Smallegange, Isabel M.

2011-04-01

Investigating how the environment affects age and size at maturity of individuals is crucial to understanding how changes in the environment affect population dynamics through the biology of a species. Paternal phenotype, maternal, and offspring environment may crucially influence these traits, but to my knowledge, their combined effects have not yet been tested. Here, I found that in bulb mites ( Rhizoglyphus robini), maternal nutrition, offspring nutrition, and paternal phenotype (males are fighters, able to kill other mites, or benign scramblers) interactively affected offspring age and size at maturity. The largest effect occurred when both maternal and offspring nutrition was poor: in that case offspring from fighter sires required a significantly longer development time than offspring from scrambler sires. Investigating parental effects on the relationship between age and size at maturity revealed no paternal effects, and only for females was its shape influenced by maternal nutrition. Overall, this reaction norm was nonlinear. These non-genetic intergenerational effects may play a complex, yet unexplored role in influencing population fluctuations—possibly explaining why results from field studies often do not match theoretical predictions on maternal effects on population dynamics.

A standardized tritrophic small-scale system (TriCosm) for the assessment of stressor-induced effects on aquatic community dynamics.

PubMed

Riedl, Verena; Agatz, Annika; Benstead, Rachel; Ashauer, Roman

2018-04-01

Chemical impacts on the environment are routinely assessed in single-species tests. They are employed to measure direct effects on nontarget organisms, but indirect effects on ecological interactions can only be detected in multispecies tests. Micro- and mesocosms are more complex and environmentally realistic, yet they are less frequently used for environmental risk assessment because resource demand is high, whereas repeatability and statistical power are often low. Test systems fulfilling regulatory needs (i.e., standardization, repeatability, and replication) and the assessment of impacts on species interactions and indirect effects are lacking. In the present study we describe the development of the TriCosm, a repeatable aquatic multispecies test with 3 trophic levels and increased statistical power. High repeatability of community dynamics of 3 interacting aquatic populations (algae, Ceriodaphnia, and Hydra) was found with an average coefficient of variation of 19.5% and the ability to determine small effect sizes. The TriCosm combines benefits of both single-species tests (fulfillment of regulatory requirements) and complex multispecies tests (ecological relevance) and can be used, for instance, at an intermediate tier in environmental risk assessment. Furthermore, comparatively quickly generated population and community toxicity data can be useful for the development and testing of mechanistic effect models. Environ Toxicol Chem 2018;37:1051-1060. © 2017 SETAC. © 2017 SETAC.

Evolutionary divergence in sexual signals: Insights from within and among barn swallow populations

NASA Astrophysics Data System (ADS)

Wilkins, Matthew Reed

A wealth of studies across diverse animal groups indicate the importance of sexual selection in shaping phenotypes within and across breeding populations. In recent decades, much research has focused on how divergent sexual selection pressures among populations may lead to speciation. For my first dissertation chapter, I performed a literature review on the causes and consequences of evolutionary divergence in acoustic signals and developed the acoustic window conceptual framework for understanding the contributions of selection, genetic drift, and evolutionary constraint to signal divergence. Further, I found that sexual selection explains acoustic differences between recently diverged populations of the best-studied taxa. However, the relative contributions of ecological selection, sexual selection, and drift to acoustic divergence have not typically been considered within the same study systems. The remainder of my dissertation used the Northern Hemisphere-distributed barn swallow ( Hirundo rustica) species complex as a model system to study sender-receiver dynamics, intra- and intersexual selection pressures, and visual and acoustic signal interactions at the local scale, and signal divergence across populations at the global scale. From song recordings taken across 19 sampling sites, spanning five of six described subspecies, I demonstrated considerable conservation in song structure. However, temporal traits were highly divergent across subspecies, and in particular, the speed of the terminal trill of songs. In a detailed study of the multimodal communication system of the barn swallow (including visual and acoustic traits), I demonstrated that males and females use different types of signals to mediate competition and mate choice. One of the only exceptions to this rule was trill rate, which was also implicated in song divergence across populations. In order to test the function of trill rate in communication, I performed a two-year playback study within the North American subspecies, H. r. erythrogaster. Contrary to expectations, males did not have stronger responses to faster trilling (high performance) simulated intruders. Instead, resident males had stronger responses to the high performance stimulus only when the intruder was also darker than the resident. Collectively, my dissertation offers novel insight into the evolutionary dynamics of complex sexual signaling at multiple spatial scales.

Evolution and Conservation on Top of the World: Phylogeography of the Marbled Water Frog (Telmatobius marmoratus Species Complex; Anura, Telmatobiidae) in Protected Areas of Chile.

PubMed

Victoriano, Pedro F; Muñoz-Mendoza, Carla; Sáez, Paola A; Salinas, Hugo F; Muñoz-Ramírez, Carlos; Sallaberry, Michel; Fibla, Pablo; Méndez, Marco A

2015-01-01

The Andean Altiplano has served as a complex setting throughout its history, driving dynamic processes of diversification in several taxa. We investigated phylogeographic processes in the Telmatobius marmoratus species complex occurring in this region by studying the geographic patterns of genetic variability, genealogies, and historical migration, using the cytochrome b (cyt-b) gene as a marker. DNA sequences from Telmatobius gigas and Telmatobius culeus, Bolivian species with an uncertain taxonomic status, were also included. Additionally, we evaluated the phylogenetic diversity (PD) represented within Chilean protected areas and the complementary contribution from unprotected populations. Phylogenetic reconstructions from 148 cyt-b sequences revealed 4 main clades, one of which corresponded to T. culeus. T. gigas was part of T. marmoratus clade indicating paraphyletic relationships. Haplotypes from Chilean and Bolivian sites were not reciprocally monophyletic. Geographic distribution of lineages, spatial Bayesian analysis, and migration patterns indicated that T. marmoratus displays a weaker geographic structure than expected based on habitat distribution and physiological requirements. Demographic and statistical phylogeography analyses pointed out to a scenario of recent population expansion and high connectivity events of a more recent age than the post Last Glacial Maximum, probably associated to more humid events in Altiplano. PD of T. marmoratus populations within protected areas represents 55.6% of the total estimated PD. The unprotected populations that would contribute the most to PD are Caquena and Quebe (21%). Recent evolutionary processes and paleoclimatic changes, potentially driving shifts in habitat connectivity levels and population sizes, could explain the phylogeographic patterns recovered herein. © The American Genetic Association 2015. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Dynamics of change in local physician supply: an ecological perspective.

PubMed

Jiang, H Joanna; Begun, James W

2002-05-01

The purpose of this study is to employ an ecological framework to identify factors that have an impact on change in local physician supply within the USA. A particular specialty type of patient care physicians in a local market is defined as a physician population. Four physician populations are identified: generalists, medical specialists, surgical specialists, and hospital-based specialists. Based on population ecology theory, the proposed framework explains the growth of a particular physician population by four mechanisms: the intrinsic properties of this physician population; the local market's carrying capacity, which is determined by three environmental dimensions (munificence, concentration, diversity); competition within the same physician population; and interdependence between different physician populations. Data at the level of Metropolitan Statistical Areas (MSAs) were compiled from the US Area Resources File, the American Hospital Association Annual Surveys of Hospitals, the American Medical Association Census of Medical Groups, the InterStudy National HMO Census, and the US County Business Patterns. Changes in the number and percentage of physicians in a particular specialty population from 1985 to 1994 were regressed, respectively, on 1985-94 changes in the explanatory variables as well as their levels in 1985. The results indicate that the population ecology framework is useful in explaining dynamics of change in the local physician workforce. Variables measuring the three environmental dimensions were found to have significant, and in some cases, differential effects on change in the size of different specialty populations. For example, both hospital consolidation and managed care penetration showed significant positive eflects on growth of the generalist population but suppressing effects on growth of the specialist population. The percentage of physicians in a particular specialty population in 1985 was negatively related to change in the size of that specialty population between 1985 and 1994, suggesting the existence of competition. Overall, the findings of this study facilitate a better understanding of the complexity of physician workforce supply.

Creating virtual humans for simulation-based training and planning

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

Stansfield, S.; Sobel, A.

1998-05-12

Sandia National Laboratories has developed a distributed, high fidelity simulation system for training and planning small team Operations. The system provides an immersive environment populated by virtual objects and humans capable of displaying complex behaviors. The work has focused on developing the behaviors required to carry out complex tasks and decision making under stress. Central to this work are techniques for creating behaviors for virtual humans and for dynamically assigning behaviors to CGF to allow scenarios without fixed outcomes. Two prototype systems have been developed that illustrate these capabilities: MediSim, a trainer for battlefield medics and VRaptor, a system formore » planning, rehearsing and training assault operations.« less

Climate change can alter predator-prey dynamics and population viability of prey.

PubMed

Bastille-Rousseau, Guillaume; Schaefer, James A; Peers, Michael J L; Ellington, E Hance; Mumma, Matthew A; Rayl, Nathaniel D; Mahoney, Shane P; Murray, Dennis L

2018-01-01

For many organisms, climate change can directly drive population declines, but it is less clear how such variation may influence populations indirectly through modified biotic interactions. For instance, how will climate change alter complex, multi-species relationships that are modulated by climatic variation and that underlie ecosystem-level processes? Caribou (Rangifer tarandus), a keystone species in Newfoundland, Canada, provides a useful model for unravelling potential and complex long-term implications of climate change on biotic interactions and population change. We measured cause-specific caribou calf predation (1990-2013) in Newfoundland relative to seasonal weather patterns. We show that black bear (Ursus americanus) predation is facilitated by time-lagged higher summer growing degree days, whereas coyote (Canis latrans) predation increases with current precipitation and winter temperature. Based on future climate forecasts for the region, we illustrate that, through time, coyote predation on caribou calves could become increasingly important, whereas the influence of black bear would remain unchanged. From these predictions, demographic projections for caribou suggest long-term population limitation specifically through indirect effects of climate change on calf predation rates by coyotes. While our work assumes limited impact of climate change on other processes, it illustrates the range of impact that climate change can have on predator-prey interactions. We conclude that future efforts to predict potential effects of climate change on populations and ecosystems should include assessment of both direct and indirect effects, including climate-predator interactions.

Sparse dynamical Boltzmann machine for reconstructing complex networks with binary dynamics

NASA Astrophysics Data System (ADS)

Chen, Yu-Zhong; Lai, Ying-Cheng

2018-03-01

Revealing the structure and dynamics of complex networked systems from observed data is a problem of current interest. Is it possible to develop a completely data-driven framework to decipher the network structure and different types of dynamical processes on complex networks? We develop a model named sparse dynamical Boltzmann machine (SDBM) as a structural estimator for complex networks that host binary dynamical processes. The SDBM attains its topology according to that of the original system and is capable of simulating the original binary dynamical process. We develop a fully automated method based on compressive sensing and a clustering algorithm to construct the SDBM. We demonstrate, for a variety of representative dynamical processes on model and real world complex networks, that the equivalent SDBM can recover the network structure of the original system and simulates its dynamical behavior with high precision.

Sparse dynamical Boltzmann machine for reconstructing complex networks with binary dynamics.

PubMed

Chen, Yu-Zhong; Lai, Ying-Cheng

2018-03-01

Revealing the structure and dynamics of complex networked systems from observed data is a problem of current interest. Is it possible to develop a completely data-driven framework to decipher the network structure and different types of dynamical processes on complex networks? We develop a model named sparse dynamical Boltzmann machine (SDBM) as a structural estimator for complex networks that host binary dynamical processes. The SDBM attains its topology according to that of the original system and is capable of simulating the original binary dynamical process. We develop a fully automated method based on compressive sensing and a clustering algorithm to construct the SDBM. We demonstrate, for a variety of representative dynamical processes on model and real world complex networks, that the equivalent SDBM can recover the network structure of the original system and simulates its dynamical behavior with high precision.

Density dependence in demography and dispersal generates fluctuating invasion speeds

PubMed Central

Li, Bingtuan; Miller, Tom E. X.

2017-01-01

Density dependence plays an important role in population regulation and is known to generate temporal fluctuations in population density. However, the ways in which density dependence affects spatial population processes, such as species invasions, are less understood. Although classical ecological theory suggests that invasions should advance at a constant speed, empirical work is illuminating the highly variable nature of biological invasions, which often exhibit nonconstant spreading speeds, even in simple, controlled settings. Here, we explore endogenous density dependence as a mechanism for inducing variability in biological invasions with a set of population models that incorporate density dependence in demographic and dispersal parameters. We show that density dependence in demography at low population densities—i.e., an Allee effect—combined with spatiotemporal variability in population density behind the invasion front can produce fluctuations in spreading speed. The density fluctuations behind the front can arise from either overcompensatory population growth or density-dependent dispersal, both of which are common in nature. Our results show that simple rules can generate complex spread dynamics and highlight a source of variability in biological invasions that may aid in ecological forecasting. PMID:28442569

Food provisioning alters infection dynamics in populations of a wild rodent

PubMed Central

Forbes, Kristian M.; Henttonen, Heikki; Hirvelä-Koski, Varpu; Kipar, Anja; Mappes, Tapio; Stuart, Peter; Huitu, Otso

2015-01-01

While pathogens are often assumed to limit the growth of wildlife populations, experimental evidence for their effects is rare. A lack of food resources has been suggested to enhance the negative effects of pathogen infection on host populations, but this theory has received little investigation. We conducted a replicated two-factor enclosure experiment, with introduction of the bacterium Bordetella bronchiseptica and food supplementation, to evaluate the individual and interactive effects of pathogen infection and food availability on vole populations during a boreal winter. We show that prior to bacteria introduction, vole populations were limited by food availability. Bordetella bronchiseptica introduction then reduced population growth and abundance, but contrary to predictions, primarily in food supplemented populations. Infection prevalence and pathological changes in vole lungs were most common in food supplemented populations, and are likely to have resulted from increased congregation and bacteria transmission around feeding stations. Bordetella bronchiseptica-infected lungs often showed protozoan co-infection (consistent with Hepatozoon erhardovae), together with more severe inflammatory changes. Using a multidisciplinary approach, this study demonstrates a complex picture of interactions and underlying mechanisms, leading to population-level effects. Our results highlight the potential for food provisioning to markedly influence disease processes in wildlife mammal populations. PMID:26446813

Fixation Probability in a Haploid-Diploid Population

PubMed Central

Bessho, Kazuhiro; Otto, Sarah P.

2017-01-01

Classical population genetic theory generally assumes either a fully haploid or fully diploid life cycle. However, many organisms exhibit more complex life cycles, with both free-living haploid and diploid stages. Here we ask what the probability of fixation is for selected alleles in organisms with haploid-diploid life cycles. We develop a genetic model that considers the population dynamics using both the Moran model and Wright–Fisher model. Applying a branching process approximation, we obtain an accurate fixation probability assuming that the population is large and the net effect of the mutation is beneficial. We also find the diffusion approximation for the fixation probability, which is accurate even in small populations and for deleterious alleles, as long as selection is weak. These fixation probabilities from branching process and diffusion approximations are similar when selection is weak for beneficial mutations that are not fully recessive. In many cases, particularly when one phase predominates, the fixation probability differs substantially for haploid-diploid organisms compared to either fully haploid or diploid species. PMID:27866168

Selection, adaptation, and predictive information in changing environments

NASA Astrophysics Data System (ADS)

Feltgen, Quentin; Nemenman, Ilya

2014-03-01

Adaptation by means of natural selection is a key concept in evolutionary biology. Individuals better matched to the surrounding environment outcompete the others. This increases the fraction of the better adapted individuals in the population, and hence increases its collective fitness. Adaptation is also prominent on the physiological scale in neuroscience and cell biology. There each individual infers properties of the environment and changes to become individually better, improving the overall population as well. Traditionally, these two notions of adaption have been considered distinct. Here we argue that both types of adaptation result in the same population growth in a broad class of analytically tractable population dynamics models in temporally changing environments. In particular, both types of adaptation lead to subextensive corrections to the population growth rates. These corrections are nearly universal and are equal to the predictive information in the environment time series, which is also the characterization of the time series complexity. This work has been supported by the James S. McDonnell Foundation.

Effects of Human-Nature Interactions on Wildlife Habitat Dynamics: The Case of Wolong Nature Reserve for Giant Pandas

NASA Astrophysics Data System (ADS)

Vina, A.; Tuanmu, M.; Yang, W.; Liu, J.

2012-12-01

Human activities continue to induce the degradation of natural ecosystems, thus threatening not only the long-term survival of many wildlife species around the world, but also the resilience of natural ecosystems to global environmental changes. In response, many conservation efforts are emerging as adaptive strategies for coping with the degradation of natural ecosystems. Among them, the establishment of nature reserves is considered to be the most effective. However the effectiveness of nature reserves depends on the type and intensity of human activities occurring within their boundaries. But many of these activities constitute important livelihood systems for local human populations. Therefore, to enhance the effectiveness of conservation actions without significantly affecting local livelihood systems, it is essential to understand the complexity of human-nature interactions and their effects on the spatio-temporal dynamics of natural ecosystems. In this study, we evaluated the relation between giant panda habitat dynamics, conservation efforts and human activities in Wolong Nature Reserve for Giant Pandas, Sichuan Province, China. This reserve supports ca. 10% of the entire wild giant panda population but is also home to ca. 4,900 local residents. The spatio-temporal dynamics of giant panda habitat over the last four decades were analyzed using a time series of remotely sensed imagery acquired by different satellite sensor systems, including the Landsat Multi-Spectral Scanner, the Landsat Thematic Mapper and the Moderate Resolution Imaging Spectroradiometer (MODIS). Our assessment suggests that when local residents were actively involved in conservation efforts (through a payment for ecosystem services scheme established since around 2000) panda habitat started to recover, thus enhancing the resilience capacity of natural ecosystems in the Reserve. This reversed a long-term (> 30 years) trend of panda habitat degradation. The study not only has direct implications for wildlife habitat conservation but also increases our understanding of the complexity of human-nature interactions and their effects on the resilience of natural ecosystems.

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

Rameau, J. D.; Freutel, S.; Kemper, A. F.

We report that in complex materials various interactions have important roles in determining electronic properties. Angle-resolved photoelectron spectroscopy (ARPES) is used to study these processes by resolving the complex single-particle self-energy and quantifying how quantum interactions modify bare electronic states. However, ambiguities in the measurement of the real part of the self-energy and an intrinsic inability to disentangle various contributions to the imaginary part of the self-energy can leave the implications of such measurements open to debate. Here we employ a combined theoretical and experimental treatment of femtosecond time-resolved ARPES (tr-ARPES) show how population dynamics measured using tr-ARPES can bemore » used to separate electron–boson interactions from electron–electron interactions. In conclusion, we demonstrate a quantitative analysis of a well-defined electron–boson interaction in the unoccupied spectrum of the cuprate Bi 2Sr 2CaCu 2O 8+x characterized by an excited population decay time that maps directly to a discrete component of the equilibrium self-energy not readily isolated by static ARPES experiments.« less

The Influence of Mean Trophic Level on Biomass and Production in Marine Ecosystems

NASA Astrophysics Data System (ADS)

Woodson, C. B.; Schramski, J.

2016-02-01

The oceans have faced rapid removal of top predators causing a reduction in the mean trophic level of many marine ecosystems due to fishing down the food web. However, estimating the pre-exploitation biomass of the ocean has been difficult. Historical population sizes have been estimated using population dynamics models, archaeological or historical records, fisheries data, living memory, ecological monitoring data, genetics, and metabolic theory. In this talk, we expand on the use of metabolic theory by including complex trophic webs to estimate pre-exploitation levels of marine biomass. Our results suggest that historical marine biomass could be as much as 10 times higher than current estimates and that the total carrying capacity of the ocean is sensitive to mean trophic level and trophic web complexity. We further show that the production levels needed to support the added biomass are possible due to biomass accumulation and predator-prey overlap in regions such as fronts. These results have important implications for marine biogeochemical cycling, fisheries management, and conservation efforts.

Models of Eucalypt phenology predict bat population flux.

PubMed

Giles, John R; Plowright, Raina K; Eby, Peggy; Peel, Alison J; McCallum, Hamish

2016-10-01

Fruit bats (Pteropodidae) have received increased attention after the recent emergence of notable viral pathogens of bat origin. Their vagility hinders data collection on abundance and distribution, which constrains modeling efforts and our understanding of bat ecology, viral dynamics, and spillover. We addressed this knowledge gap with models and data on the occurrence and abundance of nectarivorous fruit bat populations at 3 day roosts in southeast Queensland. We used environmental drivers of nectar production as predictors and explored relationships between bat abundance and virus spillover. Specifically, we developed several novel modeling tools motivated by complexities of fruit bat foraging ecology, including: (1) a dataset of spatial variables comprising Eucalypt-focused vegetation indices, cumulative precipitation, and temperature anomaly; (2) an algorithm that associated bat population response with spatial covariates in a spatially and temporally relevant way given our current understanding of bat foraging behavior; and (3) a thorough statistical learning approach to finding optimal covariate combinations. We identified covariates that classify fruit bat occupancy at each of our three study roosts with 86-93% accuracy. Negative binomial models explained 43-53% of the variation in observed abundance across roosts. Our models suggest that spatiotemporal heterogeneity in Eucalypt-based food resources could drive at least 50% of bat population behavior at the landscape scale. We found that 13 spillover events were observed within the foraging range of our study roosts, and they occurred during times when models predicted low population abundance. Our results suggest that, in southeast Queensland, spillover may not be driven by large aggregations of fruit bats attracted by nectar-based resources, but rather by behavior of smaller resident subpopulations. Our models and data integrated remote sensing and statistical learning to make inferences on bat ecology and disease dynamics. This work provides a foundation for further studies on landscape-scale population movement and spatiotemporal disease dynamics.

a System Dynamics Approach for Looking at the Human and Environmental Interactions of Community-Based Irrigation Systems in New Mexico

NASA Astrophysics Data System (ADS)

Ochoa, C. G.; Tidwell, V. C.

2012-12-01

In the arid southwestern United States community water management systems have adapted to cope with climate variability and with socio-cultural and economic changes that have occurred since the establishment of these systems more than 300 years ago. In New Mexico, the community-based irrigation systems were established by Spanish settlers and have endured climate variability in the form of low levels of precipitation and have prevailed over important socio-political changes including the transfer of territory between Spain and Mexico, and between Mexico and the United States. Because of their inherent nature of integrating land and water use with society involvement these community-based systems have multiple and complex economic, ecological, and cultural interactions. Current urban population growth and more variable climate conditions are adding pressure to the survival of these systems. We are conducting a multi-disciplinary research project that focuses on characterizing these intrinsically complex human and natural interactions in three community-based irrigation systems in northern New Mexico. We are using a system dynamics approach to integrate different hydrological, ecological, socio-cultural and economic aspects of these three irrigation systems. Coupled with intensive field data collection, we are building a system dynamics model that will enable us to simulate important linkages and interactions between environmental and human elements occurring in each of these water management systems. We will test different climate variability and population growth scenarios and the expectation is that we will be able to identify critical tipping points of these systems. Results from this model can be used to inform policy recommendations relevant to the environment and to urban and agricultural land use planning in the arid southwestern United States.

Graceful Failure and Societal Resilience Analysis Via Agent-Based Modeling and Simulation

NASA Astrophysics Data System (ADS)

Schopf, P. S.; Cioffi-Revilla, C.; Rogers, J. D.; Bassett, J.; Hailegiorgis, A. B.

2014-12-01

Agent-based social modeling is opening up new methodologies for the study of societal response to weather and climate hazards, and providing measures of resiliency that can be studied in many contexts, particularly in coupled human and natural-technological systems (CHANTS). Since CHANTS are complex adaptive systems, societal resiliency may or may not occur, depending on dynamics that lack closed form solutions. Agent-based modeling has been shown to provide a viable theoretical and methodological approach for analyzing and understanding disasters and societal resiliency in CHANTS. Our approach advances the science of societal resilience through computational modeling and simulation methods that complement earlier statistical and mathematical approaches. We present three case studies of social dynamics modeling that demonstrate the use of these agent based models. In Central Asia, we exmaine mutltiple ensemble simulations with varying climate statistics to see how droughts and zuds affect populations, transmission of wealth across generations, and the overall structure of the social system. In Eastern Africa, we explore how successive episodes of drought events affect the adaptive capacity of rural households. Human displacement, mainly, rural to urban migration, and livelihood transition particularly from pastoral to farming are observed as rural households interacting dynamically with the biophysical environment and continually adjust their behavior to accommodate changes in climate. In the far north case we demonstrate one of the first successful attempts to model the complete climate-permafrost-infrastructure-societal interaction network as a complex adaptive system/CHANTS implemented as a ``federated'' agent-based model using evolutionary computation. Analysis of population changes resulting from extreme weather across these and other cases provides evidence for the emergence of new steady states and shifting patterns of resilience.

The Earth's Population Can Reach 14 Billion in the 23rd Century without Significant Adverse Effects on Survivability.

PubMed

Krapivin, Vladimir F; Varotsos, Costas A; Soldatov, Vladimir Yu

2017-08-07

This paper presents the results obtained from the study of the sustainable state between nature and human society on a global scale, focusing on the most critical interactions between the natural and anthropogenic processes. Apart from the conventional global models, the basic tool employed herein is the newly proposed complex model entitled "nature-society system (NSS) model", through which a reliable modeling of the processes taking place in the global climate-nature-society system (CNSS) is achieved. This universal tool is mainly based on the information technology that allows the adaptive conformance of the parametric and functional space of this model. The structure of this model includes the global biogeochemical cycles, the hydrological cycle, the demographic processes and a simple climate model. In this model, the survivability indicator is used as a criterion for the survival of humanity, which defines a trend in the dynamics of the total biomass of the biosphere, taking into account the trends of the biocomplexity dynamics of the land and hydrosphere ecosystems. It should be stressed that there are no other complex global models comparable to those of the CNSS model developed here. The potential of this global model is demonstrated through specific examples in which the classification of the terrestrial ecosystem is accomplished by separating 30 soil-plant formations for geographic pixels 4° × 5°. In addition, humanity is considered to be represented by three groups of economic development status (high, transition, developing) and the World Ocean is parameterized by three latitude zones (low, middle, high). The modelling results obtained show the dynamics of the CNSS at the beginning of the 23rd century, according to which the world population can reach the level of 14 billion without the occurrence of major negative impacts.

Social and economic influences on human behavioural response in an emerging epidemic

NASA Astrophysics Data System (ADS)

Phang, P.; Wiwatanapataphee, B.; Wu, Y. H.

2017-10-01

The human behavioural changes have been recognized as an important key in shaping the disease spreading and determining the success of control measures in the course of epidemic outbreaks. However, apart from cost-benefit considerations, in reality, people are heterogeneous in their preferences towards adopting certain protective actions to reduce their risk of infection, and social norms have a function in individuals’ decision making. Here, we studied the interplay between the epidemic dynamics, imitation dynamics and the heterogeneity of individual protective behavioural response under the considerations of both economic and social factors, with a simple mathematical compartmental model and multi-population game dynamical replicator equations. We assume that susceptibles in different subpopulations have different preferences in adopting either normal or altered behaviour. By incorporating both intra- and inter-group social pressure, the outcome of the strategy distribution depends on the initial proportion of susceptible with normal and altered strategies in both subpopulations. The increase of additional cost to susceptible with altered behaviour will discourage people to take up protective actions and hence results in higher epidemic final size. For a specific cost of altered behaviour, the social group pressure could be a “double edge sword”, though. We conclude that the interplays between individual protective behaviour adoption, imitation and epidemic dynamics are necessarily complex if both economic and social factors act on populations with existing preferences.

Evolutionary dynamics of a smoothed war of attrition game.

PubMed

Iyer, Swami; Killingback, Timothy

2016-05-07

In evolutionary game theory the War of Attrition game is intended to model animal contests which are decided by non-aggressive behavior, such as the length of time that a participant will persist in the contest. The classical War of Attrition game assumes that no errors are made in the implementation of an animal׳s strategy. However, it is inevitable in reality that such errors must sometimes occur. Here we introduce an extension of the classical War of Attrition game which includes the effect of errors in the implementation of an individual׳s strategy. This extension of the classical game has the important feature that the payoff is continuous, and as a consequence admits evolutionary behavior that is fundamentally different from that possible in the original game. We study the evolutionary dynamics of this new game in well-mixed populations both analytically using adaptive dynamics and through individual-based simulations, and show that there are a variety of possible outcomes, including simple monomorphic or dimorphic configurations which are evolutionarily stable and cannot occur in the classical War of Attrition game. In addition, we study the evolutionary dynamics of this extended game in a variety of spatially and socially structured populations, as represented by different complex network topologies, and show that similar outcomes can also occur in these situations. Copyright © 2016 Elsevier Ltd. All rights reserved.

Communication: Broad manifold of excitonic states in light-harvesting complex 1 promotes efficient unidirectional energy transfer in vivo

NASA Astrophysics Data System (ADS)

Sohail, Sara H.; Dahlberg, Peter D.; Allodi, Marco A.; Massey, Sara C.; Ting, Po-Chieh; Martin, Elizabeth C.; Hunter, C. Neil; Engel, Gregory S.

2017-10-01

In photosynthetic organisms, the pigment-protein complexes that comprise the light-harvesting antenna exhibit complex electronic structures and ultrafast dynamics due to the coupling among the chromophores. Here, we present absorptive two-dimensional (2D) electronic spectra from living cultures of the purple bacterium, Rhodobacter sphaeroides, acquired using gradient assisted photon echo spectroscopy. Diagonal slices through the 2D lineshape of the LH1 stimulated emission/ground state bleach feature reveal a resolvable higher energy population within the B875 manifold. The waiting time evolution of diagonal, horizontal, and vertical slices through the 2D lineshape shows a sub-100 fs intra-complex relaxation as this higher energy population red shifts. The absorption (855 nm) of this higher lying sub-population of B875 before it has red shifted optimizes spectral overlap between the LH1 B875 band and the B850 band of LH2. Access to an energetically broad distribution of excitonic states within B875 offers a mechanism for efficient energy transfer from LH2 to LH1 during photosynthesis while limiting back transfer. Two-dimensional lineshapes reveal a rapid decay in the ground-state bleach/stimulated emission of B875. This signal, identified as a decrease in the dipole strength of a strong transition in LH1 on the red side of the B875 band, is assigned to the rapid localization of an initially delocalized exciton state, a dephasing process that frustrates back transfer from LH1 to LH2.

Dynamics of major histocompatibility complex class I association with the human peptide-loading complex.

PubMed

Panter, Michaela S; Jain, Ankur; Leonhardt, Ralf M; Ha, Taekjip; Cresswell, Peter

2012-09-07

Although the human peptide-loading complex (PLC) is required for optimal major histocompatibility complex class I (MHC I) antigen presentation, its composition is still incompletely understood. The ratio of the transporter associated with antigen processing (TAP) and MHC I to tapasin, which is responsible for MHC I recruitment and peptide binding optimization, is particularly critical for modeling of the PLC. Here, we characterized the stoichiometry of the human PLC using both biophysical and biochemical approaches. By means of single-molecule pulldown (SiMPull), we determined a TAP/tapasin ratio of 1:2, consistent with previous studies of insect-cell microsomes, rat-human chimeric cells, and HeLa cells expressing truncated TAP subunits. We also report that the tapasin/MHC I ratio varies, with the PLC population comprising both 2:1 and 2:2 complexes, based on mutational and co-precipitation studies. The MHC I-saturated PLC may be particularly prevalent among peptide-selective alleles, such as HLA-C4. Additionally, MHC I association with the PLC increases when its peptide supply is reduced by inhibiting the proteasome or by blocking TAP-mediated peptide transport using viral inhibitors. Taken together, our results indicate that the composition of the human PLC varies under normal conditions and dynamically adapts to alterations in peptide supply that may arise during viral infection. These findings improve our understanding of the quality control of MHC I peptide loading and may aid the structural and functional modeling of the human PLC.

The evolutionary dynamics of language.

PubMed

Steels, Luc; Szathmáry, Eörs

2018-02-01

The well-established framework of evolutionary dynamics can be applied to the fascinating open problems how human brains are able to acquire and adapt language and how languages change in a population. Schemas for handling grammatical constructions are the replicating unit. They emerge and multiply with variation in the brains of individuals and undergo selection based on their contribution to needed expressive power, communicative success and the reduction of cognitive effort. Adopting this perspective has two major benefits. (i) It makes a bridge to neurobiological models of the brain that have also adopted an evolutionary dynamics point of view, thus opening a new horizon for studying how human brains achieve the remarkably complex competence for language. And (ii) it suggests a new foundation for studying cultural language change as an evolutionary dynamics process. The paper sketches this novel perspective, provides references to empirical data and computational experiments, and points to open problems. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

A prototypic mathematical model of the human hair cycle.

PubMed

Al-Nuaimi, Yusur; Goodfellow, Marc; Paus, Ralf; Baier, Gerold

2012-10-07

The human hair cycle is a complex, dynamic organ-transformation process during which the hair follicle repetitively progresses from a growth phase (anagen) to a rapid apoptosis-driven involution (catagen) and finally a relative quiescent phase (telogen) before returning to anagen. At present no theory satisfactorily explains the origin of the hair cycle rhythm. Based on experimental evidence we propose a prototypic model that focuses on the dynamics of hair matrix keratinocytes. We argue that a plausible feedback-control structure between two key compartments (matrix keratinocytes and dermal papilla) leads to dynamic instabilities in the population dynamics resulting in rhythmic hair growth. The underlying oscillation consists of an autonomous switching between two quasi-steady states. Additional features of the model, namely bistability and excitability, lead to new hypotheses about the impact of interventions on hair growth. We show how in silico testing may facilitate testing of candidate hair growth modulatory agents in human HF organ culture or in clinical trials. Copyright © 2012 Elsevier Ltd. All rights reserved.

Dynamical ion transfer between coupled Coulomb crystals in a double-well potential.

PubMed

Klumpp, Andrea; Zampetaki, Alexandra; Schmelcher, Peter

2017-09-01

We investigate the nonequilibrium dynamics of coupled Coulomb crystals of different sizes trapped in a double well potential. The dynamics is induced by an instantaneous quench of the potential barrier separating the two crystals. Due to the intra- and intercrystal Coulomb interactions and the asymmetric population of the potential wells, we observe a complex reordering of ions within the two crystals as well as ion transfer processes from one well to the other. The study and analysis of the latter processes constitutes the main focus of this work. In particular, we examine the dependence of the observed ion transfers on the quench amplitude performing an analysis for different crystalline configurations ranging from one-dimensional ion chains via two-dimensional zigzag chains and ring structures to three-dimensional spherical structures. Such an analysis provides us with the means to extract the general principles governing the ion transfer dynamics and we gain some insight on the structural disorder caused by the quench of the barrier height.

Dynamic Network Drivers of Seizure Generation, Propagation and Termination in Human Neocortical Epilepsy

PubMed Central

Khambhati, Ankit N.; Davis, Kathryn A.; Oommen, Brian S.; Chen, Stephanie H.; Lucas, Timothy H.; Litt, Brian; Bassett, Danielle S.

2015-01-01

The epileptic network is characterized by pathologic, seizure-generating ‘foci’ embedded in a web of structural and functional connections. Clinically, seizure foci are considered optimal targets for surgery. However, poor surgical outcome suggests a complex relationship between foci and the surrounding network that drives seizure dynamics. We developed a novel technique to objectively track seizure states from dynamic functional networks constructed from intracranial recordings. Each dynamical state captures unique patterns of network connections that indicate synchronized and desynchronized hubs of neural populations. Our approach suggests that seizures are generated when synchronous relationships near foci work in tandem with rapidly changing desynchronous relationships from the surrounding epileptic network. As seizures progress, topographical and geometrical changes in network connectivity strengthen and tighten synchronous connectivity near foci—a mechanism that may aid seizure termination. Collectively, our observations implicate distributed cortical structures in seizure generation, propagation and termination, and may have practical significance in determining which circuits to modulate with implantable devices. PMID:26680762

Complexity and dynamics of topological and community structure in complex networks

NASA Astrophysics Data System (ADS)

Berec, Vesna

2017-07-01

Complexity is highly susceptible to variations in the network dynamics, reflected on its underlying architecture where topological organization of cohesive subsets into clusters, system's modular structure and resulting hierarchical patterns, are cross-linked with functional dynamics of the system. Here we study connection between hierarchical topological scales of the simplicial complexes and the organization of functional clusters - communities in complex networks. The analysis reveals the full dynamics of different combinatorial structures of q-th-dimensional simplicial complexes and their Laplacian spectra, presenting spectral properties of resulting symmetric and positive semidefinite matrices. The emergence of system's collective behavior from inhomogeneous statistical distribution is induced by hierarchically ordered topological structure, which is mapped to simplicial complex where local interactions between the nodes clustered into subcomplexes generate flow of information that characterizes complexity and dynamics of the full system.

Duplication and population dynamics shape historic patterns of selection and genetic variation at the major histocompatibility complex in rodents

PubMed Central

Winternitz, Jamie C; Wares, John P

2013-01-01

Genetic variation at the major histocompatibility complex (MHC) is vitally important for wildlife populations to respond to pathogen threats. As natural populations can fluctuate greatly in size, a key issue concerns how population cycles and bottlenecks that could reduce genetic diversity will influence MHC genes. Using 454 sequencing, we characterized genetic diversity at the DRB Class II locus in montane voles (Microtus montanus), a North American rodent that regularly undergoes high-amplitude fluctuations in population size. We tested for evidence of historic balancing selection, recombination, and gene duplication to identify mechanisms maintaining allelic diversity. Counter to our expectations, we found strong evidence of purifying selection acting on the DRB locus in montane voles. We speculate that the interplay between population fluctuations and gene duplication might be responsible for the weak evidence of historic balancing selection and strong evidence of purifying selection detected. To further explore this idea, we conducted a phylogenetically controlled comparative analysis across 16 rodent species with varying demographic histories and MHC duplication events (based on the maximum number of alleles detected per individual). On the basis of phylogenetic generalized linear model-averaging, we found evidence that the estimated number of duplicated loci was positively related to allelic diversity and, surprisingly, to the strength of purifying selection at the DRB locus. Our analyses also revealed that species that had undergone population bottlenecks had lower allelic richness than stable species. This study highlights the need to consider demographic history and genetic structure alongside patterns of natural selection to understand resulting patterns of genetic variation at the MHC. PMID:23789067

Predator-prey dynamics stabilised by nonlinearity explain oscillations in dust-forming plasmas

NASA Astrophysics Data System (ADS)

Ross, A. E.; McKenzie, D. R.

2016-04-01

Dust-forming plasmas are ionised gases that generate particles from a precursor. In nature, dust-forming plasmas are found in flames, the interstellar medium and comet tails. In the laboratory, they are valuable in generating nanoparticles for medicine and electronics. Dust-forming plasmas exhibit a bizarre, even puzzling behaviour in which they oscillate with timescales of seconds to minutes. Here we show how the problem of understanding these oscillations may be cast as a predator-prey problem, with electrons as prey and particles as predators. The addition of a nonlinear loss term to the classic Lotka-Volterra equations used for describing the predator-prey problem in ecology not only stabilises the oscillations in the solutions for the populations of electrons and particles in the plasma but also explains the behaviour in more detail. The model explains the relative phase difference of the two populations, the way in which the frequency of the oscillations varies with the concentration of the precursor gas, and the oscillations of the light emission, determined by the populations of both species. Our results demonstrate the value of adopting an approach to a complex physical science problem that has been found successful in ecology, where complexity is always present.

Modelling and mapping tick dynamics using volunteered observations.

PubMed

Garcia-Martí, Irene; Zurita-Milla, Raúl; van Vliet, Arnold J H; Takken, Willem

2017-11-14

Tick populations and tick-borne infections have steadily increased since the mid-1990s posing an ever-increasing risk to public health. Yet, modelling tick dynamics remains challenging because of the lack of data and knowledge on this complex phenomenon. Here we present an approach to model and map tick dynamics using volunteered data. This approach is illustrated with 9 years of data collected by a group of trained volunteers who sampled active questing ticks (AQT) on a monthly basis and for 15 locations in the Netherlands. We aimed at finding the main environmental drivers of AQT at multiple time-scales, and to devise daily AQT maps at the national level for 2014. Tick dynamics is a complex ecological problem driven by biotic (e.g. pathogens, wildlife, humans) and abiotic (e.g. weather, landscape) factors. We enriched the volunteered AQT collection with six types of weather variables (aggregated at 11 temporal scales), three types of satellite-derived vegetation indices, land cover, and mast years. Then, we applied a feature engineering process to derive a set of 101 features to characterize the conditions that yielded a particular count of AQT on a date and location. To devise models predicting the AQT, we use a time-aware Random Forest regression method, which is suitable to find non-linear relationships in complex ecological problems, and provides an estimation of the most important features to predict the AQT. We trained a model capable of fitting AQT with reduced statistical metrics. The multi-temporal study on the feature importance indicates that variables linked to water levels in the atmosphere (i.e. evapotranspiration, relative humidity) consistently showed a higher explanatory power than previous works using temperature. As a product of this study, we are able of mapping daily tick dynamics at the national level. This study paves the way towards the design of new applications in the fields of environmental research, nature management, and public health. It also illustrates how Citizen Science initiatives produce geospatial data collections that can support scientific analysis, thus enabling the monitoring of complex environmental phenomena.

SYNTHETIC BIOLOGY. Emergent genetic oscillations in a synthetic microbial consortium.

PubMed

Chen, Ye; Kim, Jae Kyoung; Hirning, Andrew J; Josić, Krešimir; Bennett, Matthew R

2015-08-28

A challenge of synthetic biology is the creation of cooperative microbial systems that exhibit population-level behaviors. Such systems use cellular signaling mechanisms to regulate gene expression across multiple cell types. We describe the construction of a synthetic microbial consortium consisting of two distinct cell types—an "activator" strain and a "repressor" strain. These strains produced two orthogonal cell-signaling molecules that regulate gene expression within a synthetic circuit spanning both strains. The two strains generated emergent, population-level oscillations only when cultured together. Certain network topologies of the two-strain circuit were better at maintaining robust oscillations than others. The ability to program population-level dynamics through the genetic engineering of multiple cooperative strains points the way toward engineering complex synthetic tissues and organs with multiple cell types. Copyright © 2015, American Association for the Advancement of Science.

Epigenetics: relevance and implications for public health.

PubMed

Rozek, Laura S; Dolinoy, Dana C; Sartor, Maureen A; Omenn, Gilbert S

2014-01-01

Improved understanding of the multilayer regulation of the human genome has led to a greater appreciation of environmental, nutritional, and epigenetic risk factors for human disease. Chromatin remodeling, histone tail modifications, and DNA methylation are dynamic epigenetic changes responsive to external stimuli. Careful interpretation can provide insights for actionable public health through collaboration between population and basic scientists and through integration of multiple data sources. We review key findings in environmental epigenetics both in human population studies and in animal models, and discuss the implications of these results for risk assessment and public health protection. To ultimately succeed in identifying epigenetic mechanisms leading to complex phenotypes and disease, researchers must integrate the various animal models, human clinical approaches, and human population approaches while paying attention to life-stage sensitivity, to generate effective prescriptions for human health evaluation and disease prevention.

Propagation, cascades, and agreement dynamics in complex communication and social networks

NASA Astrophysics Data System (ADS)

Lu, Qiming

Many modern and important technological, social, information and infrastructure systems can be viewed as complex systems with a large number of interacting components. Models of complex networks and dynamical interactions, as well as their applications are of fundamental interests in many aspects. Here, several stylized models of multiplex propagation and opinion dynamics are investigated on complex and empirical social networks. We first investigate cascade dynamics in threshold-controlled (multiplex) propagation on random geometric networks. We find that such local dynamics can serve as an efficient, robust, and reliable prototypical activation protocol in sensor networks in responding to various alarm scenarios. We also consider the same dynamics on a modified network by adding a few long-range communication links, resulting in a small-world network. We find that such construction can further enhance and optimize the speed of the network's response, while keeping energy consumption at a manageable level. We also investigate a prototypical agent-based model, the Naming Game, on two-dimensional random geometric networks. The Naming Game [A. Baronchelli et al., J. Stat. Mech.: Theory Exp. (2006) P06014.] is a minimal model, employing local communications that captures the emergence of shared communication schemes (languages) in a population of autonomous semiotic agents. Implementing the Naming Games with local broadcasts on random geometric graphs, serves as a model for agreement dynamics in large-scale, autonomously operating wireless sensor networks. Further, it captures essential features of the scaling properties of the agreement process for spatially-embedded autonomous agents. Among the relevant observables capturing the temporal properties of the agreement process, we investigate the cluster-size distribution and the distribution of the agreement times, both exhibiting dynamic scaling. We also present results for the case when a small density of long-range communication links are added on top of the random geometric graph, resulting in a "small-world"-like network and yielding a significantly reduced time to reach global agreement. We construct a finite-size scaling analysis for the agreement times in this case. When applying the model of Naming Game on empirical social networks, this stylized agent-based model captures essential features of agreement dynamics in a network of autonomous agents, corresponding to the development of shared classification schemes in a network of artificial agents or opinion spreading and social dynamics in social networks. Our study focuses on the impact that communities in the underlying social graphs have on the outcome of the agreement process. We find that networks with strong community structure hinder the system from reaching global agreement; the evolution of the Naming Game in these networks maintains clusters of coexisting opinions indefinitely. Further, we investigate agent-based network strategies to facilitate convergence to global consensus.

Isolation mediates persistent founder effects on zooplankton colonisation in new temporary ponds

PubMed Central

Badosa, Anna; Frisch, Dagmar; Green, Andy J.; Rico, Ciro; Gómez, Africa

2017-01-01

Understanding the colonisation process in zooplankton is crucial for successful restoration of aquatic ecosystems. Here, we analyzed the clonal and genetic structure of the cyclical parthenogenetic rotifer Brachionus plicatilis by following populations established in new temporary ponds during the first three hydroperiods. Rotifer populations established rapidly after first flooding, although colonisation was ongoing throughout the study. Multilocus genotypes from 7 microsatellite loci suggested that most populations (10 of 14) were founded by few clones. The exception was one of the four populations that persisted throughout the studied hydroperiods, where high genetic diversity in the first hydroperiod suggested colonisation from a historical egg bank, and no increase in allelic diversity was detected with time. In contrast, in another of these four populations, we observed a progressive increase of allelic diversity. This population became less differentiated from the other populations suggesting effective gene flow soon after its foundation. Allelic diversity and richness remained low in the remaining two, more isolated, populations, suggesting little gene flow. Our results highlight the complexity of colonisation dynamics, with evidence for persistent founder effects in some ponds, but not in others, and with early immigration both from external source populations, and from residual, historical diapausing egg banks. PMID:28276459

Isolation mediates persistent founder effects on zooplankton colonisation in new temporary ponds

NASA Astrophysics Data System (ADS)

Badosa, Anna; Frisch, Dagmar; Green, Andy J.; Rico, Ciro; Gómez, Africa

2017-03-01

Understanding the colonisation process in zooplankton is crucial for successful restoration of aquatic ecosystems. Here, we analyzed the clonal and genetic structure of the cyclical parthenogenetic rotifer Brachionus plicatilis by following populations established in new temporary ponds during the first three hydroperiods. Rotifer populations established rapidly after first flooding, although colonisation was ongoing throughout the study. Multilocus genotypes from 7 microsatellite loci suggested that most populations (10 of 14) were founded by few clones. The exception was one of the four populations that persisted throughout the studied hydroperiods, where high genetic diversity in the first hydroperiod suggested colonisation from a historical egg bank, and no increase in allelic diversity was detected with time. In contrast, in another of these four populations, we observed a progressive increase of allelic diversity. This population became less differentiated from the other populations suggesting effective gene flow soon after its foundation. Allelic diversity and richness remained low in the remaining two, more isolated, populations, suggesting little gene flow. Our results highlight the complexity of colonisation dynamics, with evidence for persistent founder effects in some ponds, but not in others, and with early immigration both from external source populations, and from residual, historical diapausing egg banks.

Spiraling patterns in evolutionary models inspired by bacterial games with cyclic dominance

NASA Astrophysics Data System (ADS)

Mobilia, Mauro

2015-03-01

Understanding the mechanisms allowing the maintenance of biodiversity is a central issue in biology. Evolutionary game theory, where the success of one species depends on what the others are doing, provides a promising framework to investigate this complex problem. Experiments on microbial populations have shown that cyclic local interactions promote species coexistence. In this context, rock-paper-scissors games - in which rock crushes scissors, scissors cut paper, and paper wraps rock - are often used to model the dynamics of populations in cyclic competition. After a brief survey of some inspiring experiments, I will discuss the subtle interplay between individuals' mobility and their local interactions in two-dimensional rock-paper-scissors systems. This leads to the loss of biodiversity above a certain mobility threshold, and to the formation of spiraling patterns below the critical mobility rate. I will then study a generic rock-paper-scissors metapopulation model formulated on a two-dimensional grid of patches. When these have a large carrying capacity, the model's dynamics is faithfully described in terms of the system's complex Ginzburg-Landau equation properly derived from a multiscale expansion. The properties of the ensuing complex Ginzburg-Landau equation are exploited to derive the system's phase diagram and to characterize the spatio-temporal properties of the spiraling patterns in each phase. This enables us to analyze the spiral waves stability, how these are influenced by linear and nonlinear diffusion, and to discuss phenomena such as far-field breakup. Presentation mainy based on joint work with B. Szczesny and A. M. Rucklidge. Fruitful earlier collaborations with E. Frey, Q. He, T. Reichenbach, and U. C. Täuber are also acknowledged. Work supported by the UK EPSRC (Grant No. EP/P505593/1).

Dark-Bright Soliton Dynamics Beyond the Mean-Field Approximation

NASA Astrophysics Data System (ADS)

Katsimiga, Garyfallia; Koutentakis, Georgios; Mistakidis, Simeon; Kevrekidis, Panagiotis; Schmelcher, Peter; Theory Group of Fundamental Processes in Quantum Physics Team

2017-04-01

The dynamics of dark bright solitons beyond the mean-field approximation is investigated. We first examine the case of a single dark-bright soliton and its oscillations within a parabolic trap. Subsequently, we move to the setting of collisions, comparing the mean-field approximation to that involving multiple orbitals in both the dark and the bright component. Fragmentation is present and significantly affects the dynamics, especially in the case of slower solitons and in that of lower atom numbers. It is shown that the presence of fragmentation allows for bipartite entanglement between the distinguishable species. Most importantly the interplay between fragmentation and entanglement leads to the decay of each of the initial mean-field dark-bright solitons into fast and slow fragmented dark-bright structures. A variety of excitations including dark-bright solitons in multiple (concurrently populated) orbitals is observed. Dark-antidark states and domain-wall-bright soliton complexes can also be observed to arise spontaneously in the beyond mean-field dynamics. Deutsche Forschungsgemeinschaft (DFG) in the framework of the SFB 925 ``Light induced dynamics and control of correlated quantum systems''.

Mapping the Complete Reaction Path of a Complex Photochemical Reaction.

PubMed

Smith, Adam D; Warne, Emily M; Bellshaw, Darren; Horke, Daniel A; Tudorovskya, Maria; Springate, Emma; Jones, Alfred J H; Cacho, Cephise; Chapman, Richard T; Kirrander, Adam; Minns, Russell S

2018-05-04

We probe the dynamics of dissociating CS_{2} molecules across the entire reaction pathway upon excitation. Photoelectron spectroscopy measurements using laboratory-generated femtosecond extreme ultraviolet pulses monitor the competing dissociation, internal conversion, and intersystem crossing dynamics. Dissociation occurs either in the initially excited singlet manifold or, via intersystem crossing, in the triplet manifold. Both product channels are monitored and show that, despite being more rapid, the singlet dissociation is the minor product and that triplet state products dominate the final yield. We explain this by a consideration of accurate potential energy curves for both the singlet and triplet states. We propose that rapid internal conversion stabilizes the singlet population dynamically, allowing for singlet-triplet relaxation via intersystem crossing and the efficient formation of spin-forbidden dissociation products on longer timescales. The study demonstrates the importance of measuring the full reaction pathway for defining accurate reaction mechanisms.

Mapping the Complete Reaction Path of a Complex Photochemical Reaction

NASA Astrophysics Data System (ADS)

Smith, Adam D.; Warne, Emily M.; Bellshaw, Darren; Horke, Daniel A.; Tudorovskya, Maria; Springate, Emma; Jones, Alfred J. H.; Cacho, Cephise; Chapman, Richard T.; Kirrander, Adam; Minns, Russell S.

2018-05-01

We probe the dynamics of dissociating CS2 molecules across the entire reaction pathway upon excitation. Photoelectron spectroscopy measurements using laboratory-generated femtosecond extreme ultraviolet pulses monitor the competing dissociation, internal conversion, and intersystem crossing dynamics. Dissociation occurs either in the initially excited singlet manifold or, via intersystem crossing, in the triplet manifold. Both product channels are monitored and show that, despite being more rapid, the singlet dissociation is the minor product and that triplet state products dominate the final yield. We explain this by a consideration of accurate potential energy curves for both the singlet and triplet states. We propose that rapid internal conversion stabilizes the singlet population dynamically, allowing for singlet-triplet relaxation via intersystem crossing and the efficient formation of spin-forbidden dissociation products on longer timescales. The study demonstrates the importance of measuring the full reaction pathway for defining accurate reaction mechanisms.

Self-amplified photo-induced gap quenching in a correlated electron material

PubMed Central

Mathias, S.; Eich, S.; Urbancic, J.; Michael, S.; Carr, A. V.; Emmerich, S.; Stange, A.; Popmintchev, T.; Rohwer, T.; Wiesenmayer, M.; Ruffing, A.; Jakobs, S.; Hellmann, S.; Matyba, P.; Chen, C.; Kipp, L.; Bauer, M.; Kapteyn, H. C.; Schneider, H. C.; Rossnagel, K.; Murnane, M. M.; Aeschlimann, M.

2016-01-01

Capturing the dynamic electronic band structure of a correlated material presents a powerful capability for uncovering the complex couplings between the electronic and structural degrees of freedom. When combined with ultrafast laser excitation, new phases of matter can result, since far-from-equilibrium excited states are instantaneously populated. Here, we elucidate a general relation between ultrafast non-equilibrium electron dynamics and the size of the characteristic energy gap in a correlated electron material. We show that carrier multiplication via impact ionization can be one of the most important processes in a gapped material, and that the speed of carrier multiplication critically depends on the size of the energy gap. In the case of the charge-density wave material 1T-TiSe2, our data indicate that carrier multiplication and gap dynamics mutually amplify each other, which explains—on a microscopic level—the extremely fast response of this material to ultrafast optical excitation. PMID:27698341

Host-parasite oscillation dynamics and evolution in a compartmentalized RNA replication system.

PubMed

Bansho, Yohsuke; Furubayashi, Taro; Ichihashi, Norikazu; Yomo, Tetsuya

2016-04-12

To date, various cellular functions have been reconstituted in vitro such as self-replication systems using DNA, RNA, and proteins. The next important challenges include the reconstitution of the interactive networks of self-replicating species and investigating how such interactions generate complex ecological behaviors observed in nature. Here, we synthesized a simple replication system composed of two self-replicating host and parasitic RNA species. We found that the parasitic RNA eradicates the host RNA under bulk conditions; however, when the system is compartmentalized, a continuous oscillation pattern in the population dynamics of the two RNAs emerges. The oscillation pattern changed as replication proceeded mainly owing to the evolution of the host RNA. These results demonstrate that a cell-like compartment plays an important role in host-parasite ecological dynamics and suggest that the origin of the host-parasite coevolution might date back to the very early stages of the evolution of life.

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

PubMed Central

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

2013-01-01

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

Inversion for Refractivity Parameters Using a Dynamic Adaptive Cuckoo Search with Crossover Operator Algorithm

PubMed Central

Zhang, Zhihua; Sheng, Zheng; Shi, Hanqing; Fan, Zhiqiang

2016-01-01

Using the RFC technique to estimate refractivity parameters is a complex nonlinear optimization problem. In this paper, an improved cuckoo search (CS) algorithm is proposed to deal with this problem. To enhance the performance of the CS algorithm, a parameter dynamic adaptive operation and crossover operation were integrated into the standard CS (DACS-CO). Rechenberg's 1/5 criteria combined with learning factor were used to control the parameter dynamic adaptive adjusting process. The crossover operation of genetic algorithm was utilized to guarantee the population diversity. The new hybrid algorithm has better local search ability and contributes to superior performance. To verify the ability of the DACS-CO algorithm to estimate atmospheric refractivity parameters, the simulation data and real radar clutter data are both implemented. The numerical experiments demonstrate that the DACS-CO algorithm can provide an effective method for near-real-time estimation of the atmospheric refractivity profile from radar clutter. PMID:27212938

Ubiquitin in Motion: Structural Studies of the Ubiquitin-Conjugating Enzyme~Ubiquitin Conjugate

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

Pruneda, Jonathan N.; Stoll, Kate E.; Bolton, Laura J.

2011-03-15

Ubiquitination of proteins provides a powerful and versatile post-translational signal in the eukaryotic cell. The formation of a thioester bond between ubiquitin (Ub) and the active site of a ubiquitin-conjugating enzyme (E2) is critical for the transfer of Ub to substrates. Assembly of a functional ubiquitin ligase (E3) complex poised for Ub transfer involves recognition and binding of an E2~Ub conjugate. Therefore, full characterization of the structure and dynamics of E2~Ub conjugates is required for further mechanistic understanding of Ub transfer reactions. Here we present characterization of the dynamic behavior of E2~Ub conjugates of two human enzymes, UbcH5c~Ub and Ubc13~Ub,more » in solution as determined by nuclear magnetic resonance and small-angle X-ray scattering. Within each conjugate, Ub retains great flexibility with respect to the E2, indicative of highly dynamic species that adopt manifold orientations. The population distribution of Ub conformations is dictated by the identity of the E2: the UbcH5c~Ub conjugate populates an array of extended conformations, and the population of Ubc13~Ub conjugates favors a closed conformation in which the hydrophobic surface of Ub faces helix 2 of Ubc13. Finally, we propose that the varied conformations adopted by Ub represent available binding modes of the E2~Ub species and thus provide insight into the diverse E2~Ub protein interactome, particularly with regard to interaction with Ub ligases.« less