My interest in the interaction between organisms and their physical environments began as an undergraduate here at USC, where I majored in marine science with an emphasis on marine ecology. I became particularly interested in the effects of climate change on ecosystems while taking coral reef ecology field courses in the Caribbean on the island of Providencia and in Australia at James Cook University. I conducted independent research in the Helmuth Lab for two years while I was an undergraduate, during which time Brian introduced me to the rocky intertidal zone. I became fascinated with this ecosystem and how it can be a model system to investigate effects of climate on organisms and species interactions. My undergraduate research consisted of constructing a preliminary heat budget model of the intertidal sea star Pisaster ochraceus.

I decided to stay at USC to get my masters degree in biology because of my keen interest in my project and the potential applications of the models I was developing. For my thesis, I constructed a computer heat budget model of P. ochraceus. This model, like the mussel and barnacle models our group has developed, calculates animal body temperatures using climatic variables, such as solar radiation, wind speed, air temperature, etc. I verified the model’s accuracy using environmental data and sea star body temperatures from the field. I also developed a biomimetic data logger for P. ochraceus. These loggers are thermal mimics of P. ochraceus, and they can be deployed in the field to continuously monitor sea star body temperatures. Also, as part of my thesis, I looked at how the vertical distribution of P. ochraceus is affected by their body temperature and thermal history.

I am currently working on using multiple species models (sea star, mussel, and barnacle) to look at how climate change could affect key species interactions and species distributions in the rocky intertidal on both within-site and latitudinal scales. I am also running the species models using climate data from a cascade of scales (microclimate, local weather, and satellite data) to determine how model accuracies change as spatial accuracy of climate data changes.