It's debatable whether the actual work in the field or the necessary preparation for field work is more draining. But I think many will agree that no matter how severe a poison ivy rash or how many tsetse fly bites you get, you'd rather be scratching them in the field than when dealing with the prerequisite logistics. Luckily here in RECaP, my fellow students are ahead of the game. Tutilo Mudumba is currently joined by our PI (Bob Montgomery) and new research assistant Sophia Jingo in Murchison Falls National Park, where they are setting things up for his field work focusing on lion conservation, and kicking off the Snares to Wares Initiative. Steve Gray is getting ready to again conquer the hoary frosts of Northern Michigan until and beyond when that frost no longer comes. Last year, Steve made it through a very mentally exhausting field season – I think he’s due for some better fortune this time around. I know Arthur Muneza must be feeling some serious relaxation, as he doesn't have the same load of field work, but has just successfully defended his master's thesis. However, given that he is starting his Ph.D. this January, field work is right around the corner for him. Remington Moll and Waldemar Ortiz have been busy preparing and communicating with personnel at the Cleveland Metroparks, eagerly awaiting another field season in which they will set up even more camera traps throughout the Emerald Necklace this summer. As for me, I couldn't be more excited for my first field season in my new "field" - the RECaP offices.
My work here in RECaP is characterized by two broad roles; that of i) quantitative ecologist and ii) statistician. As a quantitative ecologist I help investigate questions that require sophisticated quantitative methods or custom programing to assess. In this capacity I can apply my skills in a variety of ways, from assisting a colleague with modeling expertise for a component of their overall research project, to pursuing my own projects! In both scenarios, it is often the case that I will work with data that has already been collected. For example, in my current project I am part of a large team interested in exploring the relationship between moose movement and ambient temperature. This general idea is of interest because many have suggested that rising ambient temperatures associated with global climate change threaten the conservation of moose. Along with colleagues at the Norwegian institute for nature Research we are trying to determine whether there is any evidence of heat influencing moose movement, with implications for their survivability.
The other role I am hoping to play is more akin to the idea of an ecological statistician. As important as furthering ecological theory is the development and testing of the techniques that are used to do so, and there is progress to be me made in expanding our analytical toolboxes to handle such fundamentally different data types and volumes. The age of big-data in ecology is here, and like so many other disciplines, research involving statistical methods in ecology has become highly diversified.
To translate progress to practice, innovation in design of new analytical methods also requires innovation in implementation of these methods. Open-source statistical software platforms such as R have become the norm for doing so. This is because they are completely FREE! Free in two senses: free as in it does not cost any money to download and use the software; and free as is anyone can access, manipulate, and redistribute the source code. Thus, many of the contributions I hope to make will involve design and documentation of the actual software tools ecologists can use to analyze data. This idea – that I can create packages to be used by researchers in their own projects – is perhaps what I am most excited about.