Research

 

The aim of my research is to understand how natural selection and evolution shape the biological diversity seen in wild animal populations. Understanding the genetic basis of complex traits in wild populations depends on understanding the environment the population lives in, or the ecology of quantitative genetics. Work in my group has focused mainly on the the long-term studies of red deer on the Isle of Rum and Soay sheep on the St Kilda islands, both in NW Scotland, but has also involved several other vertebrate populations (see Publications); at the moment, I am working on an Australian cooperatively breeding passerine bird, the superb fairy wrens.

The following is a list of topics that we are currently interested in. Please click for more information on each.

 

Genetics of complex traits in wild populations

We can quantify the genetic basis of important phenotypic traits such as reproductive success, longevity or morphology, and the genetic correlations between them, by combining measurements of traits on individuals of known relatedness. We use data from long-term, individual-based studies of wild vertebrate populations to address a range of questions about the genetic component of phenotypic diversity, for example: Why is there so much genetic variance for traits under selection, when selection should favour a single optimal genotype? Why does consistent directional selection apparently fail to produce an evolutionary response? What constraints are imposed by genetic correlations between different traits? How do environmental conditions affect the expression of genetic variance?

Effects of climate change

Long-term studies of wild animal populations that have been the subject of detailed monitoring for many decades provide an unbeatable means of assessing the impact of climate change on wild populations. We are investigating the extent to which observed temporal trends in phenotype are due to responses to changing climate conditions, both via phenotypic plasticitiy and via the impact of the climate on the expression of genetic variation and the magnitude of natural selection.

Phenotypic plasticity

Phenotypic plasticity is the expression of different phenotypes by a single genotype under different environmental conditions, and is an important mechanism by which individuals in a population respond to changing environmental conditions such as climate change. However whilst many studies have shown evidence for plastic changes in a population’s mean trait value, we know less about differences between individuals in their plastic responses to climatic variation. Are some individuals more sensitive or responsive than others? If so, why? Is there a genetic basis to these differences between individuals?

Phenology: getting the timing right

The timing of different events in an animal's year can have a critical effect on its fitness: for example, breed too early and there may not be enough food available, breed too late and offspring may not have time to grow sufficiently before winter arrives. We know that changes in the weather cause changes in the timing of key events (an example of phenotypic plasticity described above), and that some individuals in a population may be more sensitive than others to the prevailing environmental conditions. We are exploring the evolutionary and ecological implications of this variation in timing in several ungulate and bird populations.

The evolutionary ecology of maternal effects

Maternal effects have the potential to generate crucial evolutionary trade-offs: what's best for the mother may not be best for an individual offspring. Furthermore, although we know that maternal effects are important in mammals, in natural populations we know very little about the relative impacts of genes versus environment in determining differences between mothers in their ability to invest in their offspring. Analyses of multigenerational pedigree data from wild populations provide an excellent opportunity to quantify the role that maternal effects play in evolutionary dynamics.

Sexually antagonistic effects

Genotypes that produce successful males may produce less successful females, and vice versa. This is because male and female deer need different attributes to succeed in the battle for survival and reproduction, and genes that work well in males don’t necessarily code for the best characteristics in females. Such sexually antagonistic effects could help explain the surprising persistence of biological diversity within populations despite expected erosion by natural selection.

Senescence

Although senescence is a nearly ubiquitous feature of multicellular organisms, the reasons for its evolution are not clear: why hasn’t natural selection prevented the decline in fitness observed in older individuals? We are currently investigating the environmental and genetic determinants of individual variation in ageing rates in natural populations using data on several long-lived species.

Evolution of behaviour

Current models of behavioral evolution often ignore the underlying genetic basis of behavioral variation and instead assume that selection produces the optimal expression of behavior for a given environment. This assumption is rarely tested because the difficulty of quantifying the genetic basis of behavioral traits has limited our ability to fully incorporate sources of behavioral variation into models of behavioral evolution. To address this problem, recent work in the group has explored the quantitative genetics of aggression of a wild bird population to investigate whether adaptive evolution is the basis for rapid changes in behavior during range expansions.

Quantitative genetics and the 'animal model' in wild populations

We can capitalise on the widespread availability of large-scale genotyping and hefty computer power to use complex pedigree analysis software to address a range of different questions about the genetic basis of complex traits in wild animals living in natural environments. The heritable basis of phenotypic variance can be estimated by looking at the similarity (covariance) between relatives. To do this, we first build a pedigree (family tree) for the individuals in a population using genotype information to determine who is related to whom. We then use restricted maximum likelihood (REML) or Bayesian mixed models, in particular 'animal models', to analyse this pedigree data, taking into account the fact relatives may share common environments as well as genes. In much of the work described above we are exploring different applications of animal models to data from wild populations.