Discussion with a dataset

Like many of you, I am always pleased to go out and observe nature and wildlife. As a child, I had the opportunity to grow up with the forest at the end of my backyard, and every summer our family spent weeks up North at our fishing cabin. These experiences forged my decision to become a wildlife biologist. At first, my main incentive to be a wildlife biologist was to spend months doing fieldwork in remote places. Now, with two energetic toddlers at home, I do not wish for long and remote fieldwork anymore. I nevertheless find my job at least as interesting, if not more.

As an undergrad, I feared statistics but over the years, my interest in statistics significantly increased! I now see statistics as a language that helps understand what the data want to tell us. Analyzing data is certainly not a linear process and can be viewed as a (sometimes challenging) discussion. Using a statistical analysis, you ask a question to a dataset and, depending on the results (the answer from the dataset), you may adjust your next questions by using different statistical tools, different combinations of variables, etc. After several attempts, taking usually weeks or months, you start to understand the main messages contained in your data.

After you sorted out what your dataset wants to tell you, it’s time to extend the discussion to new members. Lab mates and advisor(s) are perfect candidates to validate your findings or propose new analyses if the messages are still unclear. Those moments, thinking out loud, are what I find the most interesting of scientific research and collaborations. I always feel privileged when a lab mate wants to discuss their analyses or the results they just revealed.

My favourite parts of being a wildlife biologist has changed over the years. I still like going outside, but I now prefer small excursions with the kids to find some mushrooms in the forest or critters along beaches and streams.

By Martin Leclerc, Postdoctoral Fellow