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Populations and Evolution

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preprint2017arXiv

Misrepair mechanism: a mechanism essential for individual adaptation, species adaptation and species evolution

In Misrepair-accumulation theory, we have proposed a Misrepair mechanism for interpreting aging. However, Misrepair mechanism is also important in biological adaptation. Misrepair is a strategy of repair for increasing the surviving chance of an organism when it suffers from severe injuries. As a surviving strategy, Misrepair mechanism plays also an important role in individual adaptation, species survival, and species differentiation. Firstly, Misrepair of an injury is one of the manners of individual adaptation; and Misrepair mechanism gives an organism a great potential in adapting to changeable and destructive environment. Secondly, Misrepair mechanism is important in maintaining and enlarging the diversity of genome DNAs of a species; and a large diversity of genome DNAs is essential for the adaptation and the differentiation of a species in different environments. On one hand, somatic Misrepairs are essential for maintaining the sufficient number of individuals in a species, which are the vectors of different genome DNAs. On the other hand, Misrepair of DNA is a source of DNA mutations and the DNA Misrepairs in germ cells may contribute to the diversity of genome DNAs in a sp

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preprint2017arXiv

A nonautonomous epidemic model with general incidence and isolation

We obtain conditions for eradication and permanence of infection for a nonautonomous SIQR model with time-dependent parameters, that are not assumed to be periodic. The incidence is given by functions of all compartments and the threshold conditions are given by some numbers that play the role of the basic reproduction number. We obtain simple threshold conditions in the autonomous, asymptotically autonomous and periodic settings and show that our thresholds coincide with the ones already established. Additionally, we obtain threshold conditions for the general nonautonomous model with mass-action, standard and quarantine-adjusted incidence.

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preprint2016arXiv

Turbulence as a problem in non-equilibrium statistical mechanics

The transitional and well-developed regimes of turbulent shear flows exhibit a variety of remarkable scaling laws that are only now beginning to be systematically studied and understood. In the first part of this article, we summarize recent progress in understanding the friction factor of turbulent flows in rough pipes and quasi-two-dimensional soap films, showing how the data obey a two-parameter scaling law known as roughness-induced criticality, and exhibit power-law scaling of friction factor with Reynolds number that depends on the precise form of the nature of the turbulent cascade. These results hint at a non-equilibrium fluctuation-dissipation relation that applies to turbulent flows. The second part of this article concerns the lifetime statistics in smooth pipes around the transition, showing how the remarkable super-exponential scaling with Reynolds number reflects deep connections between large deviation theory, extreme value statistics, directed percolation and the onset of coexistence in predator-prey ecosystems. Both these phenomena reflect the way in which turbulence can be fruitfully approached as a problem in non-equilibrium statistical mechanics.

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preprint2017arXiv

Non-genetic diversity modulates population performance

Biological functions are typically performed by groups of cells that express predominantly the same genes, yet display a continuum of phenotypes. While it is known how one genotype can generate such non-genetic diversity, it remains unclear how different phenotypes contribute to the performance of biological function at the population level. We developed a microfluidic device to simultaneously measure the phenotype and chemotactic performance of tens of thousands of individual, freely-swimming Escherichia coli as they climbed a gradient of attractant. We discovered that spatial structure spontaneously emerged from initially well-mixed wild type populations due to non-genetic diversity. By manipulating the expression of key chemotaxis proteins, we established a causal relationship between protein expression, non- genetic diversity, and performance that was theoretically predicted. This approach generated a complete phenotype-to-performance map, in which we found a nonlinear regime. We used this map to demonstrate how changing the shape of a phenotypic distribution can have as large of an effect on collective performance as changing the mean phenotype, suggesting that selection could

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preprint2016arXiv

Random patterns in fish schooling enhance alertness: a hydrodynamic perspective

One of the most highly debated questions in the field of animal swarming and social behaviour, is the collective random patterns and chaotic behaviour formed by some animal species, in particular if there is a danger. Is such a behaviour beneficial or unfavourable for survival? Here we report on one of the most remarkable forms of animal swarming and social behaviour - fish schooling - from a hydrodynamic point of view. We found that some fish species do not have preferred orientation and they swarm in a random pattern mode, despite the excess of energy consumed. Our analyses, which includes calculations of the hydrodynamic forces between slender bodies, show that such a behaviour enhances the transfer of hydrodynamic information, and thus enhances the survivability of the school. These findings support the general hypothesis that a disordered and non-trivial collective behaviour of individuals within a nonlinear dynamical system is essential for optimising transfer of information - an optimisation that might be crucial for survival.

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preprint2016arXiv

Proto-Cooperation: group hunting sailfish improve hunting success by alternating attacks on grouping prey

We present evidence of a novel form of group hunting. Individual sailfish (Istiophorus platypterus) alternate attacks with other group members on their schooling prey (Sardinella aurita). While only 24% of attacks result in prey capture, multiple prey are injured in 95% of attacks, resulting in an increase of injured fish in the school with the number of attacks. How quickly prey are captured is positively correlated with the level of injury of the school, suggesting that hunters can benefit from other conspecifics' attacks on the prey. To explore this, we built a mathematical model capturing the dynamics of the hunt. We show that group hunting provides major efficiency gains (prey caught per unit time) for individuals in groups of up to 70 members. We also demonstrate that a free riding strategy, where some individuals wait until the prey are sufficiently injured before attacking, is only beneficial if the cost of attacking is high, and only then when waiting times are short. Our findings provide evidence that cooperative benefits can be realised through the facilitative effects of individuals' hunting actions without spatial coordination of attacks. Such "proto-cooper

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preprint2016arXiv

Complimentary Phylogenetic Signals for Morphological Characters and Quantitative 3D Shape Data within genus Homo

Estimating the phylogeny of the genus Homo is entering a new phase of vastly improved data and methodology. There is increasing evidence of 6 to 10 competing species/lineages at any point in the last half million years, making the elucidation of the relationships of individual specimens particularly important. Recent estimates of the phylogeny of key specimens include Waddell (2013, 2014, 2015, 2016), and Mounier et al. (2016). These are made with quite different data (3D skull shapes and discrete morphological characters, respectively) and methods of analysis (unweighted least squares fitting of distances, OLS+, and reweighted maximum parsimony, respectively). Initial inspection of the trees in these articles might leave the impression of a great deal of disagreement and confused results. Here it is shown this need not be the case, and that these two types of data and analysis may be indicating a very similar tree, one that is in good agreement also with subjective current wisdom/expert opinions on particular parts of the phylogeny. The precise location of the African LH18 specimen arises as key to a better understanding of the likely form of the last common ancestors of H. sapien

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preprint2016arXiv

Split scores: a tool to quantify phylogenetic signal in genome-scale data

Detecting variation in the evolutionary process along chromosomes is increasingly important as whole-genome data becomes more widely available. For example, factors such as incomplete lineage sorting, horizontal gene transfer, and chromosomal inversion are expected to result in changes in the underlying gene trees along a chromosome, while changes in selective pressure and mutational rates for different genomic regions may lead to shifts in the underlying mutational process. We propose the split score as a general method for quantifying support for a particular phylogenetic relationship within a genomic data set. Because the split score is based on algebraic properties of a matrix of site pattern frequencies, it can be rapidly computed, even for data sets that are large in the number of taxa and/or in the length of the alignment, providing an advantage over other methods (e.g., maximum likelihood) that are often used to assess such support. Using simulation we explore the properties of the split score, including its dependence on sequence length, branch length, size of a split and its ability to detect true splits in the underlying tree. Using a sliding window analysis, we show tha

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preprint2017arXiv

Global Properties of Nested Network Model with Application to Multi-Epitope HIV/CTL Dynamics

Mathematical modeling and analysis can provide insight on the dynamics of ecosystems which maintain biodiversity in the face of competitive and prey-predator interactions. Of primary interests are the underlying structure and features which stabilize diverse ecological networks. Recently Korytowski and Smith [17] proved that a perfectly nested infection network, along with appropriate life history trade-offs, leads to coexistence and persistence of bacteria-phage communities in a chemostat model. In this article, we generalize their model in order to apply it to the within-host dynamics virus and immune response, in particular HIV and CTL (Cytotoxic T Lymphocyte) cells. Our model can produce a diverse hierarchy of viral and immune populations, built through sequential viral escape from dominant immune responses and rise in subdominant immune responses, consistent with observed patterns of HIV/CTL evolution. We find a Lyapunov function for the system which leads to rigorous characterization of persistent viral and immune variants, and informs upon equilibria stability and global dynamics. Results are interpreted in the context of within-host HIV/CTL evolution and numerical simulatio

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preprint2016arXiv

Inference of Causal Information Flow in Collective Animal Behavior

Understanding and even defining what constitutes animal interactions remains a challenging problem. Correlational tools may be inappropriate for detecting communication between a set of many agents exhibiting nonlinear behavior. A different approach is to define coordinated motions in terms of an information theoretic channel of direct causal information flow. In this work, we consider time series data obtained by an experimental protocol of optical tracking of the insect species Chironomus riparius. The data constitute reconstructed 3-D spatial trajectories of the insects' flight trajectories and kinematics. We present an application of the optimal causation entropy (oCSE) principle to identify direct causal relationships or information channels among the insects. The collection of channels inferred by oCSE describes a network of information flow within the swarm. We find that information channels with a long spatial range are more common than expected under the assumption that causal information flows should be spatially localized. The tools developed herein are general and applicable to the inference and study of intercommunication networks in a wide variety of natural setti

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preprint2016arXiv

Population dynamics of synthetic Terraformation motifs

Ecosystems are complex systems, currently experiencing several threats associated with global warming, intensive exploitation, and human-driven habitat degradation. Such threats are pushing ecosystems to the brink of collapse. Because of a general presence of multiple stable states, including states involving population extinction, and due to intrinsic nonlinearities associated with feedback loops, collapse can occur in a catastrophic manner. Such catastrophic shifts have been suggested to pervade many of the future transitions affecting ecosystems at many different scales. Many studies have tried to delineate potential warning signals predicting such ongoing shifts but little is known about how such transitions might be effectively prevented. It has been recently suggested that a potential path to prevent or modify the outcome of these transitions would involve designing synthetic organisms and synthetic ecological interactions that could push these endangered systems out of the critical boundaries. Four classes of such ecological engineering designs or {\em Terraformation motifs} have been defined in a qualitative way. Here we develop the simplest mathematical models associated w

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preprint2016arXiv

Evolution of cooperation and costly incentives in the continuous snowdrift game

Game theory research on the snowdrift game has showed that gradual evolution of the continuously varying level of cooperation in joint enterprises can demonstrate evolutionary merging as well as evolutionary branching. However, little is known about the consequences of changes in diversity at the cooperation level. In the present study I consider effects of costly rewards on the continuous snowdrift game. I show that not evolutionary merging but evolutionary branching can promote the emergence of pool reward, which can then enhance social welfare.

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preprint2016arXiv

Controlling uncertainty in aptamer selection

The search for high-affinity aptamers for targets such as proteins, small molecules, or cancer cells remains a formidable endeavor. Systematic Evolution of Ligands by EXponential Enrichment (SELEX) offers an iterative process to discover these aptamers through evolutionary selection of high-affinity candidates from a highly diverse random pool. This randomness dictates an unknown population distribution of fitness parameters, encoded by the binding affinities, toward SELEX targets. Adding to this uncertainty, repeating SELEX under identical conditions may lead to variable outcomes. These uncertainties pose a challenge when tuning selection pressures to isolate high-affinity ligands. Here, we present a novel stochastic hybrid model that describes the evolutionary selection of aptamers in order to explore the impact of these unknowns. To our surprise, we find that even single copies of high-affinity ligands in a pool of billions can strongly influence population dynamics, yet their survival is highly dependent on chance. We perform Monte Carlo simulations to explore the impact of environmental parameters, such as the target concentration, on selection efficiency in SELEX and identify

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preprint2016arXiv

A Generalized Population Dynamics Model of a City and an Algorithm for Engineering Regime Shifts

Measures of wealth and production have been found to scale superlinearly with the population of a city. Therefore, it makes economic sense for humans to congregate together in dense settlements. A recent model of population dynamics showed that population growth can become superexponential due to the superlinear scaling of production with population in a city. Here, we generalize this population dynamics model and demonstrate the existence of multiple stable equilibrium points, showing how population growth can be stymied by a poor economic environment. This occurs when the goods and services produced by the city become less profitable due to a lack of diversification in the city's economy. Then, relying on critical slowing down signals related to the stability of an equilibrium point, we present an algorithm for engineering regime shifts such that a city at a stable equilibrium point may continue to grow again. The generality of the model and the algorithm used here implies that the model and algorithm need not be restricted to urban systems; they are easily applicable to other types of systems where the assumptions used are valid.

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preprint2016arXiv

Control of epidemics via social partnership adjustment

Epidemic control is of great importance for human society. Adjusting interacting partners is an effective individualized control strategy. Intuitively, it is done either by shortening the interaction time between susceptible and infected individuals or by increasing the opportunities for contact between susceptible individuals. Here, we provide a comparative study on these two control strategies by establishing an epidemic model with non-uniform stochastic interactions. It seems that the two strategies should be similar, since shortening the interaction time between susceptible and infected individuals somehow increases the chances for contact between susceptible individuals. However, analytical results indicate that the effectiveness of the former strategy sensitively depends on the infectious intensity and the combinations of different interaction rates, whereas the latter one is quite robust and efficient. Simulations are shown in comparison with our analytical predictions. Our work may shed light on the strategic choice of disease control.

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preprint2016arXiv

Elementary proof of convergence to the mean-field model for the SIR process

The susceptible-infected-recovered (SIR) model has been used extensively to model disease spread and other processes. Despite the widespread usage of this ordinary differential equation (ODE) based model which represents the mean-field approximation of the underlying stochastic SIR process on contact networks, only few rigorous approaches exist and these use complex semigroup and martingale techniques to prove that the expected fraction of the susceptible and infected nodes of the stochastic SIR process on a complete graph converges as the number of nodes increases to the solution of the mean-field ODE model. Extending the elementary proof of convergence for the SIS process introduced by Armbruster and Beck (2016) to the SIR process, we show convergence using only a system of three ODEs, simple probabilistic inequalities, and basic ODE theory. Our approach can also be generalized to many other types of compartmental models (e.g., susceptible-infected-recovered-susceptible (SIRS)) which are linear ODEs with the addition of quadratic terms for the number of new infections similar to the SI term in the SIR model.

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preprint2016arXiv

Speciation: Goldschmidt's Heresy, Once Supported by Gould and Dawkins, is Again Reinstated

The view that the initiation of branching into two sympatric species may not require natural selection emerged in Victorian times (Fleeming Jenkin, George Romanes, William Bateson). In the 1980s paleontologist Steven Jay Gould gave a theoretical underpinning of this non-genic "chromosomal" view, thus reinstating Richard Goldschmidt's "heresy" of the 1930s. From modelling studies with computer-generated "biomorphs," zoologist Richard Dawkins also affirmed Goldschmidt, proclaiming the "evolution of evolvability." However, in the 1990s, while Gould and Dawkins were recanting, bioinformatic, biochemical and cytological studies were providing a deeper underpinning. In 2001 this came under attack from leaders in the field who favored Dawkins' genic emphasis. Now, with growing evidence from multiple sources, we can reinstate again Goldschmidt's view and clarify its nineteenth century roots.

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preprint2016arXiv

Rényi entropy, abundance distribution and the equivalence of ensembles

Distributions of abundances or frequencies play an important role in many fields of science, from biology to sociology, as does the Rényi entropy, which measures the diversity of a statistical ensemble. We derive a mathematical relation between the abundance distribution and the Rényi entropy, by analogy with the equivalence of ensembles in thermodynamics. The abundance distribution is mapped onto the density of states, and the Rényi entropy to the free energy. The two quantities are related in the thermodynamic limit by a Legendre transform, by virtue of the equivalence between the micro-canonical and canonical ensembles. In this limit, we show how the Rényi entropy can be constructed geometrically from rank-frequency plots. This mapping predicts that non-concave regions of the rank-frequency curve should result in kinks in the Rényi entropy as a function of its order. We illustrate our results on simple examples, and emphasize the limitations of the equivalence of ensembles when a thermodynamic limit is not well defined. Our results help choose reliable diversity measures based on the experimental accuracy of the abundance distributions in particular frequency ranges.

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preprint2015arXiv

Diversity of immune strategies explained by adaptation to pathogen statistics

Biological organisms have evolved a wide range of immune mechanisms to defend themselves against pathogens. Beyond molecular details, these mechanisms differ in how protection is acquired, processed and passed on to subsequent generations -- differences that may be essential to long-term survival. Here, we introduce a mathematical framework to compare the long-term adaptation of populations as a function of the pathogen dynamics that they experience and of the immune strategy that they adopt. We find that the two key determinants of an optimal immune strategy are the frequency and the characteristic timescale of the pathogens. Depending on these two parameters, our framework identifies distinct modes of immunity, including adaptive, innate, bet-hedging and CRISPR-like immunities, which recapitulate the diversity of natural immune systems.

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preprint2016arXiv

Local equilibrium in bird flocks

The correlated motion of flocks is an instance of global order emerging from local interactions. An essential difference with analogous ferromagnetic systems is that flocks are active: animals move relative to each other, dynamically rearranging their interaction network. The effect of this off-equilibrium element is well studied theoretically, but its impact on actual biological groups deserves more experimental attention. Here, we introduce a novel dynamical inference technique, based on the principle of maximum entropy, which accodomates network rearrangements and overcomes the problem of slow experimental sampling rates. We use this method to infer the strength and range of alignment forces from data of starling flocks. We find that local bird alignment happens on a much faster timescale than neighbour rearrangement. Accordingly, equilibrium inference, which assumes a fixed interaction network, gives results consistent with dynamical inference. We conclude that bird orientations are in a state of local quasi-equilibrium over the interaction length scale, providing firm ground for the applicability of statistical physics in certain active systems.

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preprint2016arXiv

Darwinian Selection Induces Lamarckian Adaptation in a Holobiont Model

Current models of animal evolution focus on selection of individuals, ignoring the much faster selection of symbiotic bacteria. Here we take host-symbiont interactions into account by introducing a Population Genetics-like model of holobionts exposed to toxic stress. The stress can be alleviated by selection of resistant individuals (host and bacteria) and by secretion of a detoxification agent ("detox"). By defining a new measure, termed the Lamarckian, we show that selection of resistant bacteria over one generation of hosts leads to stress-dependent increase in the tolerance of the host's offspring. This benefit is mediated by co-alleviation of toxic and physiologic stress. Prolonged exposure leads to further adaptation by 'group selection' of bacterial communities with higher detox per bacterium. These findings show that Lamarckian adaptation can arise via interactions between two levels of Darwinian selection within a holobiont system. The conclusions and modelling framework are applicable to diverse types of holobiont systems.

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preprint2016arXiv

Robust permanence for ecological equations with internal and external feedbacks

Species experience both internal feedbacks with endogenous factors such as trait evolution and external feedbacks with exogenous factors such as weather. These feedbacks can play an important role in determining whether populations persist or communities of species coexist. To provide a general mathematical framework for studying these effects, we develop a theorem for coexistence for ecological models accounting for internal and external feedbacks. Specifically, we use average Lyapunov functions and Morse decompositions to develop sufficient and necessary conditions for robust permanence, a form of coexistence robust to large perturbations of the population densities and small structural perturbations of the models. We illustrate how our results can be applied to verify permanence in non-autonomous models, structured population models, including those with frequency-dependent feedbacks, and models of eco-evolutionary dynamics. In these applications, we discuss how our results relate to previous results for models with particular types of feedbacks.

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preprint2016arXiv

Stochastic epidemic dynamics on extremely heterogeneous networks

Networks of contacts capable of spreading infectious diseases are often observed to be highly heterogeneous, with the majority of individuals having fewer contacts than the mean, and a significant minority having relatively very many contacts. We derive a two-dimensional diffusion model for the full temporal behavior of the stochastic susceptible-infectious-recovered (SIR) model on such a network, by making use of a time-scale separation in the deterministic limit of the dynamics. This low-dimensional process is an accurate approximation to the full model in the limit of large populations, even for cases when the time-scale separation is not too pronounced, provided the maximum degree is not of the order of the population size.

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preprint2016arXiv

Rare events in stochastic populations under bursty reproduction

Recently, a first step was made by the authors towards a systematic investigation of the effect of reaction-step-size noise - uncertainty in the step size of the reaction - on the dynamics of stochastic populations. This was done by investigating the effect of bursty influx on the switching dynamics of stochastic populations. Here we extend this formalism to account for bursty reproduction processes, and improve the accuracy of the formalism to include subleading-order corrections. Bursty reproduction appears in various contexts, where notable examples include bursty viral production from infected cells, and reproduction of mammals involving varying number of offspring. The main question we quantitatively address is how bursty reproduction affects the overall fate of the population. We consider two complementary scenarios: population extinction and population survival; in the former a population gets extinct after maintaining a long-lived metastable state, whereas in the latter a population proliferates despite undergoing a deterministic drift towards extinction. In both models reproduction occurs in bursts, sampled from an arbitrary distribution. In the extinction problem, we show

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