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Research
The research theme at MaBS is the mathematical biology of
evolution. Evolution is the unifying theory of the biological
sciences, and our aim is to design advanced mathematical methods and
models that account for the biological complexity involved in most
evolutionary processes. Complexity arises on all levels of biological
organization: molecular, organismal, and ecological. The key issues of
evolutionary research, such as adaptation and speciation, are usually
addressed in special sub-disciplines for each of these levels, i.e.
molecular population genetics, quantitative genetics, and evolutionary
ecology. We work on all three fields with the special goal to create
an integrative approach, with a combination of models, concepts, and
methods.
Topics
Population genetics of adaptation
Tempo and mode of the adaptive process
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Which factors determine the rate of the adaptive process? How does
the adaptive architecture of quantitative traits look like? We derive
approximations for basic properties like fixation probabilities and
-times of beneficial alleles; and we analyse the distribution of
allelic effects of adaptations under various model assumptions.
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Hermisson J. and Pennings P.S. (2005)
Soft sweeps: Molecular population genetics of adaptation from standing genetic variation.
Genetics 169: 235-2352.
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(pdf)
This article analyses the fixation probability
for alleles that segregate in a population in mutation-selection-drift
balance and become beneficial after an environmental change and
compares it to the fixation probability for single new mutations.
Various demographic scenarios (bottlenecks) are considered. There is
also a new analytical approximation for the fixation time of
beneficial alleles.
In a series of papers, we use the so-called moving optimum model
to investigate the process of adaptation under gradual environmental
change:
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Kopp M. and Hermisson J. (2007)
Adaptation of a quantitative trait to a moving optimum.
Genetics 176: 715-719.
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(pdf)
This article provides an
initial analysis of the phenotypic effect sizes of adaptations that
contribute to adaptation of a simple two-locus trait under stabilizing
selection with a moving optimum. We identify key factors that
determine whether adaptations with small or large effect are
favored.
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Kopp M. and Hermisson J. (2009a)
The genetics of phenotypic adaptation I: Fixation of
beneficial mutations in the moving optimum model.
Genetics: 182: 233-249.
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(pdf)
This article extends the
analysis of the previous paper by, first, providing an
highly accurate approximation for the fixation time of a
single beneficial allele under moving optimum selection
and, second, by investigating the order of fixations in
simulations of a full multilocus model. We find that
the fastest time to fixation is for alleles with
intermediate effect, for which fixation depends equally
strong on genetic and environmental factors.
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Kopp M. and Hermisson J. (2009b)
The genetics of phenotypic adaptation II: The distribution
of adaptive substitutions in the moving optimum model.
Genetics 183: 1453-1476.
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(pdf)
Here, we use the moving
optimum model to calculate the distribution of phenotypic
effect sizes of fixations over a longer bout of
adaptation. We show that the mean size of fixed mutations
depens on a composite parameter that integrates over both
ecological and genetic factors.
Molecular signature of selection
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How many adaptive events have happened in the recent past of a
population? And which are the adaptive genes? Taking advantage of data
generated by new sequencing technologies, we design tests and methods
to detect positive selection from genome-wide polymorphism data.
The goal of this project is to describe the footprint of selection in
biologically realistic - complex - scenarios (time-, space-, and
frequency-dependent selection, recurrent mutation, standing genetic
variation, adaptation at multiple loci, etc.).
We call it a soft selective sweep if a beneficial allele does not
trace back to a common ancestor at the time when positive selection
first started. This can either happen if adaptation occurs from
standing genetic variation or if the beneficial allele is
introduced repeatedly into the population by recurrent mutation or
migration. The phenomenon is discussed in a series of three
articles:
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Hermisson J. and Pennings P.S. (2005)
Soft sweeps: Molecular population genetics of adaptation from standing genetic
variation.
Genetics 169: 235-2352.
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(pdf)
The first article discusses the consequences
on the footprint of positive selection on linked neutral variation if
adaptation occurs from standing genetic variation.
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Pennings P.S. and Hermisson J. (2006a)
Soft sweeps II - Molecular population genetics of adaptation from recurrent mutation or
migration.
Mol. Biol. Evol. 23: 1076-1084.
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(pdf)
Here we use coalescent
theory to derive the probability that multiple independent origins of
a beneficial allele are involved in its fixation and show that this is
a realistic biological scenario.
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Pennings P.S. and Hermisson J. (2006b)
Soft sweeps III - The signature of positive selection from
recurrent mutation.
PLoS Genetics: e186.
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(pdf)
The article describes how the footprint of positive
selection (site-frequency spectrum at linked neutral sites and LD
pattern) is changed if beneficial mutation is recurrent. We find that
statistical tests based on LD are much better suited to detect
positive selection under these conditions.
Population genetics of speciation
Sympatric speciation
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Is speciation without spatial separation of the incipient species
a plausible evolutionary scenario? We design and analyze genetically
explicit models for the evolution of assortative mating under
frequency-dependent disruptive selection.
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Pennings P.S., Kopp M., Meszena G., Dieckmann U. and Hermisson J. (2008).
An analytically tractable model for competitive speciation.
American Naturalist 171: E44-E71.
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(pdf)
In this paper, we study whether assortative mating can
evolve with respect to a trait that under
frequency-dependent disruptive selection that is
determined by one genetic locus with two alleles. This
simplification allows for an exhaustive analytical
treatment. Depending on the ecological and genetic
parameters, we describe five evolutionary regimes,
including evolution of complete reproductive
isolation from random mating in small steps.
We show how the results can be explained by the interplay of
natural and sexual selection.
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Kopp M. and Hermisson J. (2008).
Competitive speciation and costs of choosiness.
Journal of Evolutionary Biology 21: 1005-1023.
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(pdf)
In a follow-up to the previous paper, we
investigate how the likelihood of speciation is
affected by costs of female choosiness. We
study different types of costs and conclude that
speciation is still possible as long as costs are
moderate or weak.
Parapatric speciation
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Speciation in allopatric (spatially separated) populations can
easily occur by the accumulation of genetic "Dobzhansky-Muller"
incompatibilities. Under which conditions is this still possible in
populations that are not fully separated, but still exchange migrants?
We are interested in the emergence and maintenance of genetic
incompatibilities in structured populations.
Interspecific gene flow
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Even genetically diverged populations or incipient species may
still be linked by residual gene flow. We are particularly interested
under which conditions adaptations can still cross an emerging species
boundary. We also want to describe the genetic footprint of such
trans-specific adaptation.
Evolutionary consequences of gene interactions (epistasis)
Maintenance of expressed and hidden genetic variation
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The identification of mechanisms that are responsible for the
maintenance of genetic variation in natural population is a
classical problem in population genetics. In epistatic systems, we
need to distinguish expressed variation that is visible on the
phenotypic level (i.e., the heritable part of the phenotypic
variation) and hidden variation that is only expressed after
an environmental or genetic distortion. We study these quantities
in multilocus models of quantitative genetics.
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Hermisson J., Hansen T.F. and Wagner G.P. (2003).
Epistasis in polygenic traits and the evolution of genetic architecture under stabilizing selection.
American Naturalist 161:708-734.
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(pdf)
This article studies the so-called multilinear model of
epistasis. Analytical results show that epistasis
generally reduces the level of genetic variation that
is phenotypically expressed in mutation-selection
balance.
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Alvarez-Castro J.-M., Kopp M. and Hermisson J. (2009).
Effects of epistasis and the evolution of genetic
architecture: exact results for a 2-locus model.
Theoretical Population Biology 75: 109-122.
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(pdf)
For a two-locus model with epistasis, we
extend the results of the previous paper to
include genetic drift. We present analytical
results based on the "House of Gauss" and the
"Stochastic House of Gauss" approximations.
Individual-based computer simulations show
that these new predictions perform
considerably better than previous ones (based
on the Gaussian or House of Cards
approximation) for most parameter
combinations.
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Hermisson J. and Wagner G.P. (2004).
The Population Genetic Theory of Hidden Variation and Genetic Robustness.
Genetics 16 8:2271-2284.
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(pdf)
Featured in Nature Reviews Genetics Vol. 6 Feb 2005
(pdf)
We show that epistatic systems generically
harbor considerable amounts of hidden genetic
variation that can lead to large increases in
the phenotypically expressed genetic variation
after either a genetic or environmental
disturbance of the population. Mutational
robustness or canalization (see below) is not
needed to explain the release of genetic
variation under these circumstances.
Evolution of genetic architecture, canalization & mutational
robustness, evolution of evolvability
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How does selection shape the genetic architecture of phenotypic
traits and thus the boundary conditions for its own action? Are
certain features of the genetic architecture like mutational
robustness evolvable traits? And is evolvability itself an
evolvable trait? These questions of second-order evolution have
been heatedly debated in recent years.
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Hermisson J. and Wagner G.P. (2005).
Evolution of phenotypic robustness.
Book chapter appeared in: Robust Design: A Repertoire from Biology, Ecology, and Engineering,
E. Jen (ed.), Oxford University Press, Oxford, pp 47-70.
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(pdf)
A review to clarify the concepts of canalization and genetic robustness.
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de Visser J.A.G.M., Hermisson J., Wagner G.P. et. al. (2003).
Perspective: evolution and detection of genetic robustness.
Evolution 57:1959-1972.
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(pdf)
This is a consensus paper that summarizes concepts,
results, and research issues that have been identified
at a workshop on phenotypic robustness at the Santa Fe
Institute (organized by JH and GPW).
A series of papers investigates how the genetic architecture
evolves under various selection regimes.
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Hermisson J., Hansen T.F. and Wagner, G.P. (2003).
Epistasis in polygenic traits and the evolution of genetic architecture under stabilizing selection.
American Naturalist 161:708-734.
(add/hide details)
(pdf)
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Alvarez-Castro J.-M., Kopp M. and Hermisson J. (2009).
Effects of epistasis and the evolution of genetic
architecture: exact results for a 2-locus model.
Theoretical Population Biology 75: 109-122.
(add/hide details)
(pdf)
The two above articles discuss the evolution of genetic
architecture under stabilizing selection. It is shown
that canalization (robustness) of a trait is not a
target of selection and usually not maximized at an
evolutionary equilibrium. Mutational robustness (i.e.
small mutational effects) primarily evolves for loci
with high mutation rates. We also stress the
importance of evolutionary inertia and stochastic
fluctuations for the evolution of genetic
architecture.
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Carter A.J.R., Hermisson J., and Hansen T.F. (2005).
The role of epistatic gene interactions in the response to selection and the evolution of
evolvability.
Theoretical Population Biology 68, 179-196.
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(pdf)
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Hansen T.F., Alvarez-Castro J.-M., Carter A.J.R., Hermisson J. and Wagner G.P. (2006).
Evolution of genetic architecture under directional selection
Evolution 60: 1523-1536.
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(pdf)
The two previous articles treat
the impact of directional selection on the genetic
architecture. It is shown that the outcome crucially
depends on the directionality of epistasis.
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Kopp M. and Hermisson J. (2006).
The evolution of genetic architecture under
frequency-dependent disruptive selection.
Evolution 60: 1537-1550.
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(pdf, online appendices)
Here, we show that selection pressures on the genetic
architecture can be much stronger under disruptive
selection (at so-called evolutionary branching points)
than under stabilizing selection. A genetic
architecture of a trait results where most genetic
variation is maintained at only few major loci.
Sequence space models and error thresholds
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Hermisson J., Wagner H. and Baake M. (2001).
Four-state quantum chain as a model for sequence evolution.
Journal of Statistical Physics 102: 315-343.
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(pdf)
We introduce a mapping of a four-letter
sequence space model to a quantum chain model in
physics and discuss error threshold phenomena in
relation to physical phase transitions. Results on the
equilibria and the evolutionary dynamics are
presented.
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Hermisson J., Redner 0., Wagner H. and Baake E. (2002).
Mutation-selection balance: ancestry, load, and maximum principle.
Theoretical Population Biology 62: 9-46.
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(pdf)
This article introduces concepts and tools based on ancestry to derive
and analyze equilibrium properties of sequence space models with
epistasis. In particular, we discuss how error threshold phenomena
depend on the epistasis of the fitness landscape.
Frequency-dependent selection and interspecific interactions
Sympatric speciation
(add/hide details)
Is speciation without spatial separation of the incipient species
a plausible evolutionary scenario? We design and analyze genetically
explicit models for the evolution of assortative mating under
frequency-dependent disruptive selection.
-
Pennings P.S., Kopp M., Meszena G., Dieckmann U. and Hermisson J. (2008).
An analytically tractable model for competitive speciation.
American Naturalist 171: E44-E71.
(add/hide details)
(pdf)
In this paper, we study whether assortative mating can
evolve with respect to a trait that is under
frequency-dependent disruptive selection and is
determined by one genetic locus with two alleles. This
simplification allows for an exhaustive analytical
treatment. Depending on the ecological and genetic
parameters, we describe five evolutionary regimes,
including evolution of complete reproductive
isolation from random mating in small steps.
The results can be explained by the interplay of
natural and sexual selection.
-
Kopp M. and Hermisson J. (2008).
Competitive speciation and costs of choosiness.
Journal of Evolutionary Biology 21: 1005-1023.
(add/hide details)
(pdf)
In a follow-up to the previous paper, we
investigate how the likelihood of speciation is
affected by costs of female choosiness. We
study different types of costs and conclude that
speciation is still possible as long as costs are
moderate or weak.
Intraspecific phenotypic variation
(add/hide details)
A key-phenomenon from the adaptive dynamics literature is
'evolutionary branching'. This term describes the adaptive split of a
single (clonal) lineage into two separate lineages through a series of
mutations of small effect. It occurs when disruptive selection is
generated by negatively frequency-dependent interactions. The
recognition of the ubiquity of evolutionary branching in mathematical
models has been very stimulating in sympatric speciation research.
However, recently it became clear that sympatric speciation is but one
possible response to negative frequency-dependent selection.
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Rueffler C., Van Dooren T.J.M., Leimar O. and Abrams P.A. (2006).
Disruptive selection and then what?
Trends in Ecology and Evolution 21: 238-245.
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(pdf)
In this review article we present an overview of
potential evolutionary consequences to disruptive
selection. It forms the basis of one or our research
focuses: Which path should we expect evolution to take
when alternative evolutionary responses exist to a
given selection pressure?
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Kopp M. and Hermisson J. (2006).
The evolution of genetic architecture under
frequency-dependent disruptive selection.
Evolution 60: 1537-1550.
(add/hide details)
(pdf, online appendices)
In this paper, we use modifier theory to study the
evolution of phenotypic effect sizes of loci
contributing to a trait under frequency-dependent
disruptive selection. We find that the phenotype
distribution of the population evolves to match the
available ecological niches. Typically, this is
achieved by the evolution of a higly asymmetric genetic
architecture where most of the genetic variation is
concentrated on a small number of major loci.
In the presence of several resources, when should we expect
consumers to be generalists that are relatively efficient foragers on
all resources and when should we expect consumers that are specialized
on one resource on the expense of being inefficient on other
resources? When consumers have a noticeable effect on the density of
their prey, frequency dependence arises naturally making adaptive
dynamics an attractive modelling framework.
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Rueffler C., Metz J.A.J. and Van Dooren T.J.M. (2006).
The evolution of resource specialization through
frequency-dependent and frequency-independent mechanims.
American Naturalist 167: 81-93.
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(pdf)
In this article we show that whether interactions are frequency-dependent or not depends on the foraging
traits considered evolvable. As a result, different traits involved in
the foraging process have qualitatively different evolutionary
dynamics.
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Rueffler C., Metz, J.A.J. and Van Dooren T.J.M. (2007).
The interplay between behavior and morphology in the evolutionary
dynamics of resource specialization.
American Naturalist 169: E34-E52.
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(pdf)
In the previous article it was
assumed that consumers attack all prey upon encounter, irrespective of
the consumers phenotype. In this article we relax this assumption by
introducing a behavioural component: consumers decide upon encounter
with a resource item whether or not to attack it in a way that
maximizes their overall resource uptake. This added feature
significantly facilitates the evolution of polymorphism in the
consumer population.
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Abrams, P.A., Rueffler C. and Kim, G. (2008).
Determinants of the strength of disruptive and/or divergent selection arising from resource competition.
Evolution 62: 1571-1586.
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(pdf upon request)
In this article we re-investigate a classical model of intraspecific competition for resources and show that, in contradiction with the traditional view, the strength of disruptive selection at a branching point can be a unimodal function of the intensity of competition. This new finding emerges when one includes the possibility that the consumer population can drive heavily utilized resources to extinction.
Phenotypic plasticity
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In heterogeneous environments, an alternative to genetic
polymorphisms is the evolution of phenotypic plasticity. For
example, phenotypic plasticity plays a large role in predator-prey
systems, both ecologically and evolutionarily. Plastic responses
of prey to predators are known as inducible defenses. Similarly,
plastic responses of predators to prey can be called inducible
offenses.
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Kopp M. and Tollrian R. (2003).
Trophic size polyphenism in Lembadion bullinum: costs and benefits of an inducible offense.
Ecology 84: 641-651.
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(pdf)
This empirical study shows that the protozoan predator
Lembadion bullinum plastically adjusts its cell
size to the size of the available prey.
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Kopp M. and Tollrian R. (2003).
Reciprocal phenotypic plasticity in a predator-prey system:
inducible offences against inducible defences?
Ecology Letters 6: 742-748.
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(pdf)
Here, we describe the one of the first examples of
reciprocal phentypic plasticity. The ciliate
Euplotes octocarinatus responds to the
presence of its predator, Lembadion
bullinum by developing an inducible defense.
Lembadion reacts to this defense by increasing
its mean cell size, that is, by an inducible
offense. We speculate whether this reciprocal
plasticity might be the result of (diffuse)
coevolution.
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Kopp M. and Gabriel W. (2006).
The effect of an inducible defense in the Nicholson-Bailey model.
Theoretical Population Biology 70: 43-55.
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(pdf)
In this paper we study how inducible prey defenses
affect predator-prey population dynamics. Typically,
inducible defenses increase stability and persistence,
but there are exceptions to this rule.
Coevolution
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Ecological interactions between species can lead to indirect
frequency-dependent selection (for example, if predators adapt to
exploiting the most common type of prey). Possible results are
coevolutionary arms races or Red Queen dynamics.
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Kopp M. and Gavrilets S. (2006).
Multilocus genetics and the coevolution of quantitative traits.
Evolution 60: 1321-1336.
(add/hide details)
(pdf , online appendices
1,
2,
3)
Predator-prey coevolution can lead to
persistent coevolutionary cycles ('Red Queen dynamics').
Here, we investigate how these dynamics are
influenced by the genetic architecture of the
traits under reciprocal selection. We find that,
with a large number of loci contributing, the
dynacmis tend to be destabilized and the genetic
variances of prey and predator are highly
different.
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Kopp M. and Tollrian R. (2003).
Reciprocal phenotypic plasticity in a predator-prey system:
inducible offences against inducible defences?
Ecology Letters 6: 742-748.
(add/hide details)
(pdf)
Here, we describe the one of the first examples of
reciprocal phentypic plasticity. The ciliate
Euplotes octocarinatus responds to the
presence of its predator, Lembadion
bullinum by developing an inducible defense.
Lembadion reacts to this defense by increasing
its mean cell size, that is, by an inducible
offense. We speculate whether this reciprocal
plasticity might be the result of (diffuse)
coevolution.
Adaptive dynamics methodology
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Adaptive dynamics is a relatively new toolbox to model the
evolution of phenotypic traits under complex ecological
scenarios (see section on methods).
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Rueffler C., Metz J.A.J. and Van Dooren T.J.M. (2004).
Adaptive walks on changing landscapes: Levins' approach
extended.
Theoretical Population Biology 65: 165-178.
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(pdf)
The article extends Levins' classical and influential geometrical
approach to determine the optimal phenotype when two evolving traits
are coupled by a trade-off. In our article we relax Levins' assumption
that frequency dependence is absent.
Methods
Our mathematical methods are quite diverse and follow the needs of
the biological problem that is addressed. Often techniques from
various mathematical fields are combined.
Stochastics
In molecular population genetics, evolution is modelled as a
stochastic process. We use time-forward approaches based on branching
processes
(e.g. Hermisson et al. 2002)
and diffusions
(e.g. Hermisson and
Pennings 2005) and
time-backward approaches, which use the coalescent
(e.g. Hermisson and Pennings 2006a
,b).
Differential equations
The deterministic models in quantitative genetics and evolutionary
ecology are formalized as systems of differential and difference
equations. We use various techniques from these fields to analyse the
equilibrium structure (existence, stability, domains of attraction) of
biological models
(e.g. Hermisson et al. 2003).
Adaptive dynamics
Adaptive dynamics is an increasingly popular toolbox to model
phenotypic evolution under realistic ecololgical scenarios (Metz
et al. 1996; Dieckmann and Law 1996: J. Math. Biol. 34:
579-612; Geritz et al. 1998: Evol. Ecol. 12: 35-57). It combines
elements from evolutionary game theory, the theories of dynamical
systems and stochastic processes. For an exhaustive literature survey
on adaptive dynamics see here.
Statistical methods
Statistical tests and methods link empirical data to patterns that
are predicted from theoretical models. In the context of molecular
data, we have used statistical analysis
(Stoletzki et al. 2005).
and have developed tests
(Pennings and Hermisson
2006b).
Computer simulations
In complex biological situations, computer simulations are always
needed to complement and validate the analytical analysis. Our
simulation tools use various different techniques, including time
forward ('Wright-Fisher') simulations using multinomial sampling
(e.g. Kopp and Hermisson
2007), individual based simulations (e.g.
Carter et al. 2005),
and time-backward simulations using the coalescent
(Pennings and Hermisson
2006b).
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