Predicting how species will respond to a changing climate is a central challenge in ecology. Species are coupled to their environments through the exchange of matter and energy; however, what they do with energy and materials is ultimately constrained by physiology and biomechanics. My research, therefore, seeks to develop a mechanistic understanding of the processes at the interface of physics and physiology to predict how animals respond to their environments. For example, in Martin et al. (2015 Eco. Let.) we showed how considering the biochemical constraints aerobic and anaerobic metabolic pathways impose on endurance drastically improves our ability to predict the migration behavior of salmon. In another case (Martin et al. 2017 Eco. Let.), our work on how the physics of flow and diffusion limits the supply of oxygen to developing embryos helped explain why salmon embryos in the field have a much lower thermal tolerance than expected from laboratory studies. In both of these studies, isolating the physical and chemical mechanisms through which the environment affects physiology allowed us to better understand how salmon are affected by their environments.

My research is often motivated by applied ecological challenges, for example predicting how populations will respond to toxic stress, or the impact of global warming on pacific salmon populations. Although I begin my research with application in mind, I try to use methods and models to generalize as much as possible.

Some of my work has used Dynamic Energy Budget theory to link individual patterns of energy acquisition and allocation to dynamics at the population level. To facilitate use of Dynamic Energy Budget theory in an population modeling context I along with several collaborators developed DEB-IBM. DEB-IBM is an individual-based implementation of Dynamic Energy Budget theory in Netlogo, a free and accessible programmable modeling environment for multi-agent simulations. We have since used DEB-IBM to explore both basic and applied questions in population ecology.


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