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Feature: Advances with wolves – Professor Tim Coulson

10 Apr, 2012

Professor Tim Coulson, Imperial College London.

Professor Tim Coulson, Imperial College London.

When the testing of his model of environmental change was delayed by ethical issues about using human data, Professor Tim Coulson from Imperial College London turned to wild wolves as a model population. He tells us about the Science paper that resulted, and how he’s now applying his model to people.

How did this work come about?

I took a sabbatical in the USA, funded by the Wellcome Trust, to develop demographic methods in human populations. I wanted to link the dynamics of body size (obesity) in humans with the population growth rate. People are interested in the consequences of increasing obesity levels on fertility rates, survival rates etc., and how they are likely to affect things like food consumption and demands on healthcare. I started to write a paper about how this could be done in theory, but had difficulties getting access to human data to test the model.

Why wolves?

I started casting around for another system to work on. I had done quite a lot of work on animal populations in the past, so I wanted to work on a US population that had been quite well studied. I contacted the researchers at Yellowstone National Park, met them, and we hit it off. We’re delighted that it has led to a Science paper, and hopefully we’ll be able to get some follow-up papers on humans in due course. I thought it was rather ironic that it was easier to get access to data from a wild animal population than from humans!

What data did you use?

Wolves. Credit: ucumari on Flickr.

Wolves. Credit: ucumari on Flickr.

As well as being a fantastic place to work, Yellowstone has a wonderful dataset on wolves, which were reintroduced there in the mid-1990s. Researchers have been collecting the kind of information we needed to run our models: the weight of individual animals, how long they live, and details of their offspring. Obviously, obesity isn’t a problem in wolves but animal body sizes do fluctuate quite a lot from year to year as things like prey availability vary. Changes in body size can influence population size, and they can go up and down together. And these joint fluctuations can influence ‘life histories’ – the timing of events in individuals’ lives, such as their life expectancy at birth and the age at which they reach sexual maturity.

How does the model work?

You can consider any population as consisting of individuals, each with many attributes, in terms of both phenotype (e.g. body size, hair colour) and genotype (the particular version of a gene present). What this means is that, at any one point in time, you can construct a distribution of those characters. This distribution can change over time. You can visualise populations as character distributions fluctuating from year to year. As long as we can identify how these characters are associated with survival, reproduction and development (e.g. are wolves of a certain size more likely to have big offspring?), it’s possible to write a model of dynamics with these distributions. You can then ask things like: ‘What would happen to survival at old age if we continued to see an increase in human obesity levels?’ Our model gives a relatively simple way to measure so-called eco-evolutionary consequences of environmental change, where simultaneous changes occur in ecological factors (e.g. population size) and evolutionary factors (e.g. phenotype frequency).

What are you doing now?

One of the nice things about the theory is that it’s very general. In my group there are people applying it to insect and plant populations, work that could ultimately feed into things like conservation and population management. We’re also applying it to human populations, working with a collaborator in Stanford who has access to data from the Framingham Heart Study.

Image: A group of wolves in Wolf Park in the USA. Credit: ucumari on Flickr.

Further reading

Coulson T et al. Modeling effects of environmental change on wolf population dynamics, trait evolution, and life history. Science 2011;334(6060):1275-8.

This feature also appears in issue 70 of Wellcome News.

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