As a statistician at UNB in Saint John, Connie Stewart works with “pretty much anyone who needs help.” Like a superhero, she swoops in whenever fellow academics have a statistics puzzle to solve. In helping her colleagues, she’s also developing new statistical methods, and these days, most of the time that ground-breaking work happens in concert with ecology-based research. She first started working with ecologists while working on her PhD. She was working with Dalhousie University ecologists and statisticians who developed “quantitative fatty-acid signature analysis” (QFASA) in relation to grey seals. QFASA is a way to estimate seal diets — some fatty acids of the prey the seals ingest end up in the latter’s tissue with little change. QFASA involves statistical methods to match the predator with its prey’s fatty acids. The result — an estimate of the seal’s diet —includes the proportion of each prey species in the seal’s diet. “You get an estimate of diet that might, for example, contain 30 per cent herring, 20 per cent capelin, and so on,” Stewart says. “That’s an estimate. The biologists I’m working with are studying the grey seal population off the coast of Sable Island, but this can be used on a number of species, including polar bears, seabirds and sea lions.” But before she could come up with results for her colleagues, she had to solve a problem. Analyzing the diet estimates wasn’t straightforward because they are constrained to percentages that add up to 100, which means she could not apply standard statistical methods to them. She had to find a way to answer standard ecological questions in a non-standard way. When researchers such as Stewart develop new statistical methods, they run simulations to assess their efficacy. “We generate pseudo-predators, which we can do if we have a prey database,” she says. “You choose a diet of your choice and then you sample from the prey base proportionately. That gives you a pseudo fatty-acid signature.” She then takes that pretend seal fatty-acid signature and can estimate the diet and apply her methods to it. “Because we generated it with a specific diet, we know how good our answers are,” Stewart explains. “In practice, you have data and you can apply any method you want to it, but you don’t know what the true answer is. Here, we know the diets of the pseudo-predators and can see whether our methods are behaving correctly.” Running such simulations takes a long time, so Stewart uses high-powered computing through ACENET and Compute Canada to do her work. She used to use a cluster at Dalhousie University, but she migrated to ACENET’s digital infrastructure because it’s bigger and can accommodate more users working at the same time. Could she do her work without ACENET? “I’d be more limited in the different cases I could run and how long it would take me to get the research done.” As for the grey seals, knowing their diet is important because their population in the Northwest Atlantic has increased from about 15,000 in 1960 to 424,300 in 2016. Ecologists want to understand the impacts of that ballooning population on the overall ecosystem, particularly as it relates to fish populations that are commercially important to the local economy. Stewart’s statistical analyses are helping them get there.
Showcase Tag: Statistical Methods
The Physics of Fox Movement in Complex Landscapes
Sheldon Opps recalls watching a large silver fox from the window of his Prince Edward Island home last winter. The fox in question was navigating the urban sidewalk, maneuvering around high snowbanks, even pausing to check for traffic before crossing the street. “He was tracing a path just like a human would,” Opps says. “He was very comfortable in his urban environment.” Opps spends a lot of time thinking about urban foxes. The University of Prince Edward Island physics professor has been conducting an ongoing study of fox movement patterns within highly fragmented habitats such as urban Charlottetown. But Opps is not a biologist. He’s an expert in the field of soft condensed matter physics, where he applies the tools of statistical physics to study a variety of biologically relevant physical systems, including liquids, colloids, foams, gels and biological tissues. The interest in fox behaviour came via his wife Marina Silva-Opps, a biologist at UPEI, and from his interest in applying the methods of computational and statistical physics to study other complex systems – such as animal movement. The life of a fox in Charlottetown is fraught with challenges. Along with the typical dangers that a city presents – traffic, hostile dogs and homeowners, a lack of natural food sources – the animals must deal with ever increasing habitat fragmentation that breaks up their traditional hunting grounds. Opps is studying what that fragmentation means for both foxes and humans. Habitat fragmentation is having some unusual effects on the highly adaptive fox population. For one thing, the animals are quickly becoming semi-domesticated as homeowners feed them and even give them names in many cases. “We’re seeing the same patterns happening that we believe led to the domestication of dogs thousands of years ago,” says Opps. According to the current theory, wild wolves began living in close proximity to humans in the Palaeolithic age to take advantage of their hunting leftovers, eventually becoming domesticated by the process. “The conjecture is that in 50 or 100 years, if this continues, foxes could become domesticated here in Charlottetown as they have in other areas in the world, such as Russia”. Patrick Strongman is a physics undergraduate student at UPEI and an ACENET fellowship holder who is working with Opps on the fox project. As part of his research project, Strongman developed the algorithm used to track fox movements and identify cluster points where animals gathered. The algorithm compiled hundreds of data points including individual fox movements, distances travelled, velocity and GPS information, and used the data to run simulations of fox movements based on changing urban conditions. Strongman says the ACENET computer network was key to the project. “It cut down to a few hours what would have normally taken weeks to complete,” he says. Opps admits that fox habitat is an unusual subject for a physicist to be studying – particularly one trained in theoretical disciplines such as quantum mechanics and statistical physics. But he says it’s not really such a big stretch. “Like any physicist I’m a problem solver,” he says. “Physicists are usually busy looking across time and space or peering down into the realm of quantum mechanics. But just as a telescope looks back into time to study the beginnings of the universe, a study like this can unlock the secrets of how life evolved over time. Everything is interconnected. Humans and foxes are all a part of an evolving universe.”