Mysteries Under the Mundane Help Save Species
Jake Ferguson studies seasonality to aid predictions of animal population trends. "I have always been interested in the mysteries underlying what appears to be mundane," he says. "Everyday life and trends in animal populations through time . . . turn out to be very difficult to explain."

Credit: Jake Ferguson

This ScienceLives article was provided to Live Science's Expert Voices: Op-Ed & Insights in partnership with the National Science Foundation.

Seasons come and season go, but to Jake Ferguson, the ebb and flow of resources that occur with seasonal change are rich with data that can be used to answer theoretical and applied questions in ecology. As a postdoctoral fellow at the National Institute for Mathematical and Biological Synthesis, which is funded by the National Science Foundation, Ferguson creates models of seasonality that can help improve predictions of animal population growth and decline.

Despite an initial foray into studying physics as an undergraduate and even earning a master's degree in the field, Ferguson’s research is now firmly grounded in the fields of mathematics and ecology, where he conducts research relevant to the management and conservation of wildlife species.

Name: Jake Ferguson
Age: 34
Institution: National Institute for Mathematical and Biological Synthesis
Hometown: Seattle, Wash.
Field of Study: Population Ecology

The National Science Foundation: What is your field and why does it inspire you? 

Jake Ferguson: I am a population ecologist. I have always been interested in the mysteries underlying what appears to be mundane. Everyday life and trends in animal populations through time are among those things that we experience but that turn out to be very difficult to explain. I chose this field because of the opportunity to get outdoors in nature as well as to do mathematics. I mostly do the latter these days, however.

NSF: Please describe your current research. 

J.F.: Seasonality is the ebb and flow of resources throughout the year. Most models of animal population growth ignore seasonality, and this may make it difficult to detect the impact of local environmental factors on population growth and decline. My goal is to incorporate seasonality into models of animal population growth in order to understand the consequences of these dynamics. I am especially interested in how the way we formulate models may lead, or mislead, our research efforts.

NSF: What is the primary aim of your research?

J.F.: I model the seasonal patterns of resources and use these to improve our understanding of the impact of local environmental factors on future population trends. These models may be able to improve predictions of the population's response to local environmental factors. Overall my motivation is the need for better tools to connect important biological processes to population management and conservation decisions. 

NSF: What is the biggest obstacle to achieving your objective(s)?

J.F.: Building models that are both usable and useful is a very difficult balance to find. Usable models are those that are simple enough that we can understand them well and connect them to data. Useful models are able to provide insight into ecological processes to learn about the population things that we wouldn't be able to learn otherwise.

NSF: How does your work benefit society? 

J.F.: Species conservation and management is a major factor motivating my work. 

NSF: What do you like best about your work?

J.F.: I love that I get to be inspired by being outside observing nature. I also love working with field biologists and trying to describe their data and intuitions with mathematics.

NSF: What has been your most discouraging professional moment and how did you recover? What did you learn?

J.F.: I have had several discouraging moments as a graduate student, though the most difficult was leaving my first field of study, physics. I completed my masters and was originally planning on doing a PhD. I realized that this wasn't the field for me, a difficult process that made me feel like a failure and left me searching for a new place in the world. Luckily, this led to my discovery of ecology. I couldn't believe there was a magical career where you could get paid to hike around all day in the summer and do math in the winter. 

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NSF: What is the best professional advice you ever received?

J.F.: My masters advisor, Mark Taper, said something to the effect that, "A good model should surprise you." Of course most of the time when a model surprises me, it is because I made an error somewhere. However, there are times when the model is right and I was wrong. This perspective contrasts many modeling efforts in ecology, which are purely descriptive. Although this is an important component of scientific work, the projects I have found most joy in and those that make my job most rewarding are those that take me someplace new and surprise me. 

NSF: What exciting developments lie in the future for your field?

J.F.: Ultimately, if we wish to predict the impacts of climate change on species, we will need a solid understanding of how environmental factors drive populations. The ongoing incorporation of high-resolution satellite and observational data into ecological models will greatly improve our ability to understand and predict the properties of ecological systems. As systems like the National Ecological Observatory Network go up, there will be many exciting opportunities to link ecological processes to data.

NSF: What do you do when you're not in the lab or out in the field?

J.F.: I love to go hiking with my dogs. I've also recently discovered woodworking.

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