213 research outputs found
Effects of Epistasis and Pleiotropy on Fitness Landscapes
The factors that influence genetic architecture shape the structure of the
fitness landscape, and therefore play a large role in the evolutionary
dynamics. Here the NK model is used to investigate how epistasis and pleiotropy
-- key components of genetic architecture -- affect the structure of the
fitness landscape, and how they affect the ability of evolving populations to
adapt despite the difficulty of crossing valleys present in rugged landscapes.
Populations are seen to make use of epistatic interactions and pleiotropy to
attain higher fitness, and are not inhibited by the fact that valleys have to
be crossed to reach peaks of higher fitness.Comment: 10 pages, 6 figures. To appear in "Origin of Life and Evolutionary
Mechanisms" (P. Pontarotti, ed.). Evolutionary Biology: 16th Meeting 2012,
Springer-Verla
Monte carlo simulations of parapatric speciation
Parapatric speciation is studied using an individual--based model with sexual
reproduction. We combine the theory of mutation accumulation for biological
ageing with an environmental selection pressure that varies according to the
individuals geographical positions and phenotypic traits. Fluctuations and
genetic diversity of large populations are crucial ingredients to model the
features of evolutionary branching and are intrinsic properties of the model.
Its implementation on a spatial lattice gives interesting insights into the
population dynamics of speciation on a geographical landscape and the
disruptive selection that leads to the divergence of phenotypes. Our results
suggest that assortative mating is not an obligatory ingredient to obtain
speciation in large populations at low gene flow.Comment: submitted to Phys.Rev.
Self-optimization, community stability, and fluctuations in two individual-based models of biological coevolution
We compare and contrast the long-time dynamical properties of two
individual-based models of biological coevolution. Selection occurs via
multispecies, stochastic population dynamics with reproduction probabilities
that depend nonlinearly on the population densities of all species resident in
the community. New species are introduced through mutation. Both models are
amenable to exact linear stability analysis, and we compare the analytic
results with large-scale kinetic Monte Carlo simulations, obtaining the
population size as a function of an average interspecies interaction strength.
Over time, the models self-optimize through mutation and selection to
approximately maximize a community fitness function, subject only to
constraints internal to the particular model. If the interspecies interactions
are randomly distributed on an interval including positive values, the system
evolves toward self-sustaining, mutualistic communities. In contrast, for the
predator-prey case the matrix of interactions is antisymmetric, and a nonzero
population size must be sustained by an external resource. Time series of the
diversity and population size for both models show approximate 1/f noise and
power-law distributions for the lifetimes of communities and species. For the
mutualistic model, these two lifetime distributions have the same exponent,
while their exponents are different for the predator-prey model. The difference
is probably due to greater resilience toward mass extinctions in the food-web
like communities produced by the predator-prey model.Comment: 26 pages, 12 figures. Discussion of early-time dynamics added. J.
Math. Biol., in pres
Phase transition in a mean-field model for sympatric speciation
We introduce an analytical model for population dynamics with intra-specific
competition, mutation and assortative mating as basic ingredients. The set of
equations that describes the time evolution of population size in a mean-field
approximation may be decoupled. We find a phase transition leading to sympatric
speciation as a parameter that quantifies competition strength is varied. This
transition, previously found in a computational model, occurs to be of first
order.Comment: accepted for Physica
Actuator Constrained Trajectory Generation and Control for Variable-Pitch Quadrotors
Control and trajectory generation algorithms for a quadrotor helicopter with
variable-pitch propellers are presented. The control law is not based on near-hover assumptions, allowing for large attitude deviations from hover. The trajectory generation algorithm ts a time-parametrized polynomial through any number of way points in R3, with a closed-form solution if the corresponding way point arrival times are known a priori. When time is not specifi ed, an algorithm for fi nding minimum-time paths subject to hardware actuator saturation limitations is presented. Attitude-specifi c constraints are easily embedded in the polynomial path formulation, allowing for aerobatic maneuvers to be performed using a single controller and trajectory generation algorithm. Experimental results on a variable pitch quadrotor demonstrate the control design and example trajectories.National Science Foundation (U.S.) (Graduate Research Fellowship under Grant No. 0645960
Comparison of Fixed and Variable Pitch Actuators for Agile Quadrotors
This paper presents the design, analysis and experimental testing of a variable-
pitch quadrotor. A custom in-lab built quadrotor with on-board attitude stabi-
lization is developed and tested. An analysis of the dynamic di erences in thrust
output between a xed-pitch and variable-pitch propeller is given and validated
with simulation and experimental results. It is shown that variable-pitch actuation
has signi cant advantages over the conventional xed-pitch con guration, includ-
ing increased thrust rate of change, decreased control saturation, and the ability to quickly and e ciently reverse thrust. These advantages result in improved quadro-tor tracking of linear and angular acceleration command inputs in both simulation and hardware testing. The bene ts should enable more aggressive and aerobatic ying with the variable-pitch quadrotor than with standard xed-pitch actuation, while retaining much of the mechanical simplicity and robustness of the xed-pitch quadrotor.Aurora Flight Sciences Corp.National Science Foundation (U.S.) (Graduate Research Fellowship Grant 0645960
Predicting evolution and visualizing high-dimensional fitness landscapes
The tempo and mode of an adaptive process is strongly determined by the
structure of the fitness landscape that underlies it. In order to be able to
predict evolutionary outcomes (even on the short term), we must know more about
the nature of realistic fitness landscapes than we do today. For example, in
order to know whether evolution is predominantly taking paths that move upwards
in fitness and along neutral ridges, or else entails a significant number of
valley crossings, we need to be able to visualize these landscapes: we must
determine whether there are peaks in the landscape, where these peaks are
located with respect to one another, and whether evolutionary paths can connect
them. This is a difficult task because genetic fitness landscapes (as opposed
to those based on traits) are high-dimensional, and tools for visualizing such
landscapes are lacking. In this contribution, we focus on the predictability of
evolution on rugged genetic fitness landscapes, and determine that peaks in
such landscapes are highly clustered: high peaks are predominantly close to
other high peaks. As a consequence, the valleys separating such peaks are
shallow and narrow, such that evolutionary trajectories towards the highest
peak in the landscape can be achieved via a series of valley crossingsComment: 12 pages, 7 figures. To appear in "Recent Advances in the Theory and
Application of Fitness Landscapes" (A. Engelbrecht and H. Richter, eds.).
Springer Series in Emergence, Complexity, and Computation, 201
Topological reversibility and causality in feed-forward networks
Systems whose organization displays causal asymmetry constraints, from
evolutionary trees to river basins or transport networks, can be often
described in terms of directed paths (causal flows) on a discrete state space.
Such a set of paths defines a feed-forward, acyclic network. A key problem
associated with these systems involves characterizing their intrinsic degree of
path reversibility: given an end node in the graph, what is the uncertainty of
recovering the process backwards until the origin? Here we propose a novel
concept, \textit{topological reversibility}, which rigorously weigths such
uncertainty in path dependency quantified as the minimum amount of information
required to successfully revert a causal path. Within the proposed framework we
also analytically characterize limit cases for both topologically reversible
and maximally entropic structures. The relevance of these measures within the
context of evolutionary dynamics is highlighted.Comment: 9 pages, 3 figure
Isolation-by-Distance and Outbreeding Depression Are Sufficient to Drive Parapatric Speciation in the Absence of Environmental Influences
A commonly held view in evolutionary biology is that speciation (the emergence of genetically distinct and reproductively incompatible subpopulations) is driven by external environmental constraints, such as localized barriers to dispersal or habitat-based variation in selection pressures. We have developed a spatially explicit model of a biological population to study the emergence of spatial and temporal patterns of genetic diversity in the absence of predetermined subpopulation boundaries. We propose a 2-D cellular automata model showing that an initially homogeneous population might spontaneously subdivide into reproductively incompatible species through sheer isolation-by-distance when the viability of offspring decreases as the genomes of parental gametes become increasingly different. This simple implementation of the Dobzhansky-Muller model provides the basis for assessing the process and completion of speciation, which is deemed to occur when there is complete postzygotic isolation between two subpopulations. The model shows an inherent tendency toward spatial self-organization, as has been the case with other spatially explicit models of evolution. A well-mixed version of the model exhibits a relatively stable and unimodal distribution of genetic differences as has been shown with previous models. A much more interesting pattern of temporal waves, however, emerges when the dispersal of individuals is limited to short distances. Each wave represents a subset of comparisons between members of emergent subpopulations diverging from one another, and a subset of these divergences proceeds to the point of speciation. The long-term persistence of diverging subpopulations is the essence of speciation in biological populations, so the rhythmic diversity waves that we have observed suggest an inherent disposition for a population experiencing isolation-by-distance to generate new species
Rapid Transition towards the Division of Labor via Evolution of Developmental Plasticity
A crucial step in several major evolutionary transitions is the division of labor between components of the emerging higher-level evolutionary unit. Examples include the separation of germ and soma in simple multicellular organisms, appearance of multiple cell types and organs in more complex organisms, and emergence of casts in eusocial insects. How the division of labor was achieved in the face of selfishness of lower-level units is controversial. I present a simple mathematical model describing the evolutionary emergence of the division of labor via developmental plasticity starting with a colony of undifferentiated cells and ending with completely differentiated multicellular organisms. I explore how the plausibility and the dynamics of the division of labor depend on its fitness advantage, mutation rate, costs of developmental plasticity, and the colony size. The model shows that the transition to differentiated multicellularity, which has happened many times in the history of life, can be achieved relatively easily. My approach is expandable in a number of directions including the emergence of multiple cell types, complex organs, or casts of eusocial insects
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