The scales of an experiment can significantly affect the way we perceive the results, and this may be a particularly important consideration when trying to predict the likely impacts of climate change. For instance, a monthly temperature average in the intertidal can change very little, but the day-to-day temperatures can range up to 20 degrees or more! As a result, it is important to consider how environments change from a non-human organism’s “point of view” rather than relying on averages that may be simple to keep track of, but in the end may mean little to animals.
Professor Brian Helmuth, in collaboration with several scientists from Italy, tested the effects of temporal data scales ranging from 1-6 hours on predictions of how the Mediterranean mussel, Mytilus galloprovincialis responds to environmental change. The study, led by graduate student Valeria Montalto, used both real weather data recorded at five different sites in Italy as well as IPCC climate model predictions for the same time periods as inputs to Dynamic Energy Budget models to see if the results of both approaches varied.
The study, which recently appeared in the journal Ecological Modeling, found that hindcasted weather data estimated using the IPCC models can give predictions similar to measured data, but only when the modeled data are considered at scales relevant to mussels. These results suggest that climate models can provide predictions of the inevitable biological responses to climate change, and that considerations of the ecology and physiology of organisms being impacted is vital.