Global change will inevitably affect climate and ocean dynamics in a non-homogeneous manner, and effects on local environmental stressors such as temperature, salinity, and pH will vary regionally. Thus, community and population responses to climate change will likely vary between regional scales as well. I am interested in how local environmental stressors will influence intertidal organism fitness, and how such responses will translate to a population and community level.
Mechanistic models use organisms’ functional traits to predict physiological and ecological responses to their environment. This methodology can provide a better understanding of how environmental conditions influence growth, reproduction, survival, and distribution under different environmental conditions. The models are based on the concept that organisms take energy from food and use it for maintenance, growth, maturation, and reproduction; and environmental conditions such as temperature affect the way organisms use this energy.
My research interests include the use of such functional trait based bioenergetic models to predict the response of intertidal communities to the various consequences of climate change across a range of spatial scales. I am also interested in the level of temporal and spatial data resolution necessary to achieve explicit model predictions that are necessary for policy and decision makers. I validate predictions using real measurements of life history traits taken in the field, as well as take experimental measurements of functional traits under various relevant stressors to test for local adaptation over a biogeographic range.