A common approach to climate change predictions is the use of correlative techniques, in which a single variable, such as air or water temperature, is used as a proxy for the body temperature of a particular organism, and range shifts are forecasted or hindcasted based on these data. These techniques can be applied to multiple species over large geographic areas, and for certain regions and organisms, this approach works well; for others, it fails to indicate even relative stress, especially when multiple factors can strongly influence body temperature. In this case a more complex biophysical model, which accounts for the mechanisms by which environmental factors are translated into body temperature, becomes necessary. This is frequently the case in the rocky intertidal zone, where a complex interplay of factors drive the body temperatures of the organisms that live there.
My research is focused on determining which factor or factors—such as solar radiation, air temperature, water temperature, wind speed, or wind direction—would be most useful as proxies in the absence of a complete heat budget model and how the usefulness of each factor as a proxy varies between sites. I hope to determine which site-specific differences cause a correlative approach to be useful in some areas and less so in others. I also hope to compare the accuracy of this approach to previously developed models and to determine its usefulness in predicting mortality events.