scholarly journals From stochastic, individual-based models to the canonical equation of adaptive dynamics in one step

2017 ◽  
Vol 27 (2) ◽  
pp. 1093-1170 ◽  
Author(s):  
Martina Baar ◽  
Anton Bovier ◽  
Nicolas Champagnat
2015 ◽  
Vol 25 (07) ◽  
pp. 1540001 ◽  
Author(s):  
Fabio Della Rossa ◽  
Fabio Dercole ◽  
Pietro Landi

We unfold the bifurcation involving the loss of evolutionary stability of an equilibrium of the canonical equation of Adaptive Dynamics (AD). The equation deterministically describes the expected long-term evolution of inheritable traits — phenotypes or strategies — of coevolving populations, in the limit of rare and small mutations. In the vicinity of a stable equilibrium of the AD canonical equation, a mutant type can invade and coexist with the present — resident — types, whereas the fittest always win far from equilibrium. After coexistence, residents and mutants effectively diversify, according to the enlarged canonical equation, only if natural selection favors outer rather than intermediate traits — the equilibrium being evolutionarily unstable, rather than stable. Though the conditions for evolutionary branching — the joint effect of resident-mutant coexistence and evolutionary instability — have been known for long, the unfolding of the bifurcation has remained a missing tile of AD, the reason being related to the nonsmoothness of the mutant invasion fitness after branching. In this paper, we develop a methodology that allows the approximation of the invasion fitness after branching in terms of the expansion of the (smooth) fitness before branching. We then derive a canonical model for the branching bifurcation and perform its unfolding around the loss of evolutionary stability. We cast our analysis in the simplest (but classical) setting of asexual, unstructured populations living in an isolated, homogeneous, and constant abiotic environment; individual traits are one-dimensional; intra- as well as inter-specific ecological interactions are described in the vicinity of a stationary regime.


Author(s):  
Michael Doebeli

This chapter discusses adaptive diversification due to predator–prey interactions. It has long been recognized that consumption, that is, predation, can not only exert strong selection pressure on the consumer, but also on the consumed species. However, predation has traditionally received much less attention than competition as a cause for the origin and maintenance of diversity. By using adaptive dynamics theory as well as individual-based models, the chapter then illustrates that adaptive diversification in prey species due to frequency-dependent predator–prey interactions is a theoretically plausible scenario. It also describes conditions for diversification due to predator–prey interactions in classical Lotka–Volterra models, which requires analysis of coevolutionary dynamics between two interacting species, and hence of adaptive dynamics in two-dimensional phenotype spaces.


2013 ◽  
Vol 3 (6) ◽  
pp. 20130025 ◽  
Author(s):  
Johan A. J. Metz ◽  
Carolien G. F. de Kovel

One of the powerful tools of adaptive dynamics is its so-called canonical equation (CE), a differential equation describing how the prevailing trait vector changes over evolutionary time. The derivation of the CE is based on two simplifying assumptions, separation of population dynamical and mutational time scales and small mutational steps. (It may appear that these two conditions rarely go together. However, for small step sizes the time-scale separation need not be very strict.) The CE was derived in 1996, with mathematical rigour being added in 2003. Both papers consider only well-mixed clonal populations with the simplest possible life histories. In 2008, the CE's reach was heuristically extended to locally well-mixed populations with general life histories. We, again heuristically, extend it further to Mendelian diploids and haplo-diploids. Away from strict time-scale separation the CE does an even better approximation job in the Mendelian than in the clonal case owing to gene substitutions occurring effectively in parallel, which obviates slowing down by clonal interference.


2018 ◽  
Vol 11 (8) ◽  
pp. 1283-1292 ◽  
Author(s):  
Guim Aguadé-Gorgorió ◽  
Ricard Solé

2017 ◽  
Author(s):  
Guim Aguadé-Gorgorió ◽  
Ricard Solé

In most instances of tumour development, genetic instability plays a role in allowing cancer cell populations to respond to selection barriers, such as physical constraints or immune responses, and rapidly adapt to an always changing environment. Modelling instability is a nontrivial task, since by definition evolving changing instability leads to changes in the underlying landscape. In this paper we explore mathematically a simple version of unstable tumor progression using the formalism of Adaptive Dynamics (AD) where selection and mutation are explicitly coupled. Using a set of basic fitness landscapes, the so called canonical equation for the evolution of genetic instability on a minimal scenario associated to a population of unstable cells is derived. The implications and potential extensions of this model are discussed.


Selection ◽  
2002 ◽  
Vol 2 (1-2) ◽  
pp. 73-83 ◽  
Author(s):  
N. Champagnat ◽  
R. Ferričre ◽  
G. Ben Arous4

Author(s):  
R.P. Goehner ◽  
W.T. Hatfield ◽  
Prakash Rao

Computer programs are now available in various laboratories for the indexing and simulation of transmission electron diffraction patterns. Although these programs address themselves to the solution of various aspects of the indexing and simulation process, the ultimate goal is to perform real time diffraction pattern analysis directly off of the imaging screen of the transmission electron microscope. The program to be described in this paper represents one step prior to real time analysis. It involves the combination of two programs, described in an earlier paper(l), into a single program for use on an interactive basis with a minicomputer. In our case, the minicomputer is an INTERDATA 70 equipped with a Tektronix 4010-1 graphical display terminal and hard copy unit.A simplified flow diagram of the combined program, written in Fortran IV, is shown in Figure 1. It consists of two programs INDEX and TEDP which index and simulate electron diffraction patterns respectively. The user has the option of choosing either the indexing or simulating aspects of the combined program.


2006 ◽  
Vol 73 ◽  
pp. 85-96 ◽  
Author(s):  
Richard J. Reece ◽  
Laila Beynon ◽  
Stacey Holden ◽  
Amanda D. Hughes ◽  
Karine Rébora ◽  
...  

The recognition of changes in environmental conditions, and the ability to adapt to these changes, is essential for the viability of cells. There are numerous well characterized systems by which the presence or absence of an individual metabolite may be recognized by a cell. However, the recognition of a metabolite is just one step in a process that often results in changes in the expression of whole sets of genes required to respond to that metabolite. In higher eukaryotes, the signalling pathway between metabolite recognition and transcriptional control can be complex. Recent evidence from the relatively simple eukaryote yeast suggests that complex signalling pathways may be circumvented through the direct interaction between individual metabolites and regulators of RNA polymerase II-mediated transcription. Biochemical and structural analyses are beginning to unravel these elegant genetic control elements.


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