Marie Auger-Methe: Assistant Professor at Department of Statistics, Institute for the Oceans and Fisheries, UBC Faculty of Science

Each year graduate students are encouraged to give kudos to their supervisors through social media and our website as part of #GreatSupervisorWeek. Below are students who mentioned this supervisor since the initiative was started in 2017.

Fun amongst the Gentoo colony with @AugerMethe. Much learned, hilarious field moments had, and all the penguins tagged! Cheers to a #GreatSupervisor at #UBC @UBCoceans

Sarah (2018)

Graduate Student Supervision

Doctoral Student Supervision (Jan 2008 - May 2021)

Accounting for preferential sampling in the statistical analysis of spatio-temporal data (2021)

Spatio-temporal statistical methods are widely used to model natural phenomena across both space and time. Example phenomena include the concentrations of airborne pollutants and the distributions of endangered species. A spatio-temporal process is said to have been preferentially sampled when the locations and/or times chosen to observe it depend stochastically on the values of the process at the chosen locations and/or times. When standard statistical methodologies are used, predictions of a preferentially sampled spatio-temporal process into unsampled regions and times may be severely biased. Preferential sampling within spatio-temporal data may be the rule rather than the exception in practice. The work demonstrated in this dissertation addresses the issue of preferential sampling. We develop the first general framework for modelling preferential sampling in spatio-temporal data and apply it to historical UK black smoke measurements. We demonstrate that existing estimates of population-level black smoke exposures may be highly inaccurate due to preferential sampling. By leveraging the information contained in the chosen sampling locations, we can adjust estimates of black smoke exposure to the presence of preferential sampling. Next, we develop a fast, intuitive, powerful, and general test for preferential sampling. A user-friendly R-package we wrote performs the test. We demonstrate its utility in both a thorough simulation study and by successfully replicating previously-published results on preferential sampling. Finally, we adapt our ideas on preferential sampling to the setting of spatio-temporal point patterns. By considering the observed point pattern as a spatio-temporal thinned, marked log-Gaussian Cox process, we show that preferential sampling can be directly accounted for within the model. Under certain assumptions, the true distribution of locations can then be attained. Using these ideas, we develop a framework for combining multiple data sources to estimate the spatio-temporal distribution of an animal. We then apply our framework to estimate effort-corrected space-use of an endangered ecotype of killer whales. Ultimately, we hope that investigations into preferential sampling will become an essential component within spatio-temporal analyses, akin to model diagnostics. The methods developed in this dissertation are widely applicable, allowing researchers to routinely perform such investigations.

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Master's Student Supervision (2010 - 2020)

Diving into the cold: individual variation in the winter foraging behaviour of the gentoo penguin (2020)

Within any population, certain individuals outperform other members of their species. However, the precise basis for their advantage largely remains a mystery in ecology. In the last decade, research on the variability in foraging behaviour and diet between individuals has become a focus for ecologists as a potential mechanism for individual advantage. The numbers of breeding pairs of gentoo penguins in the Falkland Islands fluctuate annually, and while the precise cause of deferred breeding is unknown, carryover effects from the previous winter period are likely an important factor. Blood oxygen-carrying capacity and body mass are proposed to be critical carryover effects from winter influencing the reproductive trade-off of participating in breeding in the following spring, given their proposed influence on the diving ability and hence foraging capacity of penguins. In this thesis, I investigate (1) if interindividual variation in diving efficiency is associated with the condition of oxygen stores through i) blood oxygen-carrying capacity, using blood hemoglobin (Hb) and hematocrit (Hct) as indicators, and ii) body mass, and (2) if pre-breeding foraging effort differs between individuals based on their condition of oxygen stores and breeding status. Through monitoring penguins with time-depth recorders, I explored how Hb, Hct, and body mass influenced a penguin’s ability to dive efficiently (maximize bottom time) over their natural range of foraging depths. Subsequently, I monitored breeding participation and egg lay date to assess the reproductive status of individuals. Reduced blood oxygen-carrying capacity was found to negatively impact dive efficiency, and the effect was most influential during deeper dives. Penguins with higher Hb and an apparent optimum Hct of 52 % performed best. Pre-breeding foraging effort was predictive of reproductive status, as early laying penguins exhibited lower foraging effort and spent less time at sea than non-breeding penguins. How diving behaviour corresponds to breeding participation is essential to understand the effects ecosystem changes have on populations, and knowledge gained here could have broad implications for the conservation of this genus and many diving species.

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