Genetic variation in within-individual variance: is it important in the wild?
Most model of evolution consider that intra-individual variance,
once corrected for environmental variation, is essentially random noise
and is similar across individuals. However, recent studies in captivity
showed that within-individual variance could
in fact have a genetic basis. In addition, several studies on captive
animal have shown the evolutionary importance of the genetic variance in
individual variation. For examples, animal breeding try to select for
milking cows with low daily variation in milk
production to facilitate stock prediction and management. So if we
start to understand the importance and the interest of the genetic basis
of within-individual variation in breeding programs, the evolutionary
importance of this genetic component remain relatively
unknown in the wild. Consequently, to better understand evolution in
the wild it is key to evaluate the existence and quantify the amount of
genetic variance in the intra-individual variance of traits and how it
correlates with other traits including fitness.
Ideally to get a wider understanding of the phenomenon, such study
would need to look at multiple type of traits and across multiple
species. Since this has rarely been done, to get a better understanding
this needs to be evaluated across multiple traits and
species. The aim of this project is to used new quantitative genetic
models, a statistical approach allowing to estimate the genetic variance
in a trait in wild population, to quantify the genetic variation in
within-individual variance in multiple traits
across at least 5 species using long-term pedigreed natural populations
including yellow-bellied marmots, alpine swifts, eastern chipmunks,
bighorn sheep and red squirrels. The project will thus be based on over
150 years of field work (combined across all
species). This project will offer opportunity to learn a variety of
important methods in evolutionary biology and to participate in the
field work on the marmot system. The student will be given a thorough
training in field skills and in statistical modelling
to tease apart the amount of trait variance explained by genetic and
environmental effects.
Relevant publications
Prentice PM, Houslay TM, Martin JGA, Wilson AJ. 2020 Genetic
variance for behavioural ‘predictability’ of stress response. Journal of
Evolutionary Biology 33, 642–652.
Martin JGA et al. 2017. Genetic basis of between- and
within-individual variance of docility. Journal of Evolutionary Biology,
30(4):796-805.
Westneat DF, Wright J, Dingemanse NJ. 2015 The biology hidden
inside residual within-individual phenotypic variation. Biological
Reviews 90, 729–743.
The project will be supervised by Pr. Julien Martin (uOttawa). The
project will be done in collaborations with the project leaders of
participating long-term studies. The student will be based at the
Biology department of the University of Ottawa. He/she
will have the opportunity to perform field work over the summer in
Colorado on the yellow-bellied marmot long-term study and to visit
project leaders in Canada (Ottawa, Montreal, Sherbrooke, Edmonton),
United-States (Los-Angeles, Boulder) and United-Kingdom
(Aberdeen).
Ottawa consistently ranks among the best Canadian cities. You’ll
love an easy-going lifestyle that appeals to urban adventurers and
nature lovers alike. Enjoy a revitalized city that is bursting with
energy. Gigs, festivals, theatre and art are all close
by in a walkable downtown core. And, having the 2nd highest
concentration of scientists and engineers in North America, you’ll have
lots of opportunities to build up your network and kick-start your
career.
Financial support
Financial support is available for 4 years. The student is expected to complete two teaching assistantship per year.
Candidate Profile
For this PhD project our ideal candidate:
• has a MSc in biology
• is creative, highly motivated and can work alone or in teams
• has strong interest in evolutionary biology and quantitative genetics
• has strong interest for statistical analyses and past experience with R programming
How to apply
Students that are interested should send a writing sample (thesis,
paper or scientific article), a CV, a motivation letter, and the contact
of two references to Pr. Martin (julien.martin@uottawa.ca). We will
start interviewing candidates in early July and continue to consider applications until the position is filled.