University of Vienna
Faculty of Mathematics
A-1090 Vienna, Austria
Max F. Perutz Laboratories
Dr. Bohrgasse 9
A-1030 Vienna, Austria
Press & Public
Claus Rueffler - Senior Postdoc
Faculty of Mathematics
Oskar-Morgenstern-Platz 1, Room 9.138
T: +43 (0) 1 4277 - 50776
With October 2013 I have moved to Uppsala University, Sweden. My new homepage can be found here.
I am a theoretical biologist interested in ecology and evolution. More
specifically, I am interested in the evolution and maintenance of
phenotypic diversity and the responsible processes at the level of
genes, genotype-phenotype maps, species and communities. So far, I
have worked mostly on models that were designed to answer
rather general questions and that were not geared towards specific
systems. My main tools are mathematical models based on the "Adaptive dynamics" approach.
Mechanisms of Phenotype Determination
A current focus is the project "Multidimensional
adaptive dynamics and the evolution of phenotype determination" (link), which is financed by the WWTF. A description of the project in the online newspaper of the University of Vienna can be found here (in german).
Andreas Baumann, Helene Weigang and Hannes Svardal were part of the project.
The project originates from the observation that many heterogeneous
environments favor different phenotypes in different places or at
different times. Phenotypic diversity can either result from genetic
diversity or from a single genotype capable of producing different
phenotypes. A single genotype might produce different phenotypes, for
example in response to an environmental cue (phenotypic plasticity) or
through a randomisation mechanism (bet-hedging). A large part of the
existing theoretical literature attempts to give conditions under
which one of these specific mechanisms is favored over a
phenotypically monomorphic population. Recently, it has become clear
that in many circumstances different evolutionary responses are favored
simultaneously (Rueffler et al. 2006, TREE 21). The aim of this
project is twofold. First, we want to determine how selection pressures
arising from various ecological interactions determine which of the
possible phenotype determining mechanisms might evolve first and
possibly pre-empt any selection driving one of the alternative
responses. Second, the outcome of the evolutionary process does not
only depend on the selection pressure exerted by the environment but
also on the available phenotypic variation on which selection can act
upon. Hence, we want to explore how constraints on the level of the
genetic architecture and the developmental process affect the
evolutionary dynamics of phenotype determining mechanisms.
The Evolution of Division of Labor
Consider an organism which contains some kind of repeated module such as cells or iterated body segments. Assume furthermore that these modules were ancestrally identical and involved in more than one biological task. When do you expect that division of labor evolves such that different modules become specialized for alternative tasks and when do you expect that the modules stay undifferentiated and all keep executing the same set of tasks? This question has been addressed repeatedly in the context of specific systems such as germ-soma differentiation or caste formation in eusocial insects. However, there should also be general, non-system specific conditions that have to be fulfilled for functional differentiation between modules to be favored by natural selection.
One way to look at this problem is by means of fitness landscapes. Assume that the phenotype of each module can be described by a one-dimensional quantitative trait. As long as both modules are characterized by the same trait value functional differentiation between modules has not taken place (black curve). Functional differentiation is favored by natural selection if a combination of trait values that is a maximum in the constrained trait space (black dots) is a saddle point in the extended trait space (Figure a). Functional differentiation is not favored if such a point is a fitness maximum in the extended trait space (Figure b). Together with Günter Wagner and Joachim Hermisson I identified general system independent conditions leading to such saddle points and therefore to the evolution of function differentiation (Rueffler et al. 2012, PNAS). As part of her Diploma thesis Helene Weigang looked at this problem in a frequency-dependent context (Rueffler and Weigang, in prep.).
The evolutionary ecology of resource specialization
In the presence of different resources, when should we expect a
generalist phenotype and when specialized phenotypes? To answer this
question I studied a model of one evolving consumer feeding on two
resources. Based on this model, three different factors determine the
evolutionary dynamics of resource specialization. The first factor is
the quality of the trade-off that prevents consumers from being
specialized for different resources simultaneously. In accordance with
many previous models it appeared that strong trade-offs favor
specialists whereas weak trade-offs favor generalists. Second, the
final stop of evolution also depends on the foraging trait that is
considered to evolve. It appears that some traits are under
frequency-dependent selection while others are not
(Rueffler et al. 2006, Am. Nat. 167). In the first case, different specialized consumers
can coexist, and these types can emerge at an evolutionary branching
point, a scenario not possible in the second case. The third decisive
factor is whether consumers a capable of actively choosing which prey
type to attack. In this case, both the parameter space allowing for
coexistence and the likelihood for such a polymorphism to emerge
through a series of mutations of small effect is greatly increased
(Rueffler et al. 2007, Am. Nat. 169).
In the future, it will be interesting to incorporate diet choice
behavior into a wider range of models for the evolution of resource
Adaptive dynamics theory
Darwinian evolution is the process by which organisms adapt to their
ever-changing environment. In order to understand the principles
that govern evolutionary change, mathematical models play a vital
role. A relatively new and increasingly popular framework for the
study of long-term phenotypic evolution is 'adaptive dynamics'.
Mathematically, AD is related to dynamical systems theory and
evolutionary game theory. Biologically, AD is especially suited to
describe long-term evolution under frequency-dependent selection. A
defining feature of adaptive dynamics is that the fitness of a
specific phenotype is derived from an explicit ecological scenario
accounting for various interactions between the evolving population
under study and its (possibly coevolving) biotic and abiotic
environment. As part of my PhD thesis, I embedded Levins' classical
graphical fitness set approach for the study of evolutionary change of
two correlated traits into the adaptive dynamics framework. Levins'
theory was designed to study evolution on fixed fitness landscapes,
whereas most realistic ecological scenarios result in fitness
landscapes that change as the population evolves. It appeared that the
frequency-independent theory can be extended in a rather
straightforward way to incorporate scenarios where selection is
frequency-dependent, turning Levins_ idea into useful tool in adaptive
dynamics modeling (Rueffler et al. 2004, TPB 65).
The evolution of plant breeding systems
My interest in the evolution of plant breeding systems stems from
my master's thesis, for which I conducted empirical research on the
maintenance of gynodioecy in the Rock pink Dianthus sylvestris.
In this species (and many others), plants with pistillate (female) flowers
and with perfect (hermaphroditic) flowers coexist in many populations.
This breeding system is believed to represent a transitional state in
the evolution from hermaphroditic species to dioecious species. In
principle, individuals with only pistillate flowers have a
disadvantage compared to individuals with perfect flowers, because they
pass on their genes only via seeds and not via both pollen and seeds.
Hence, an explanation is needed for the maintenance of female
individuals. In the population of D. sylvestris that I investigated it
appeared that pistillate flowers suffer less from seed predation by
various insect species than perfect flowers, resulting in a higher per
flower seed set in pistillate flowers than in perfect flowers (Collin
et al. 2002, Oecologia 131).