| Resumo: |
Background, Questions and Methods
Recent studies have emphasized that local and geographic patterns of species distributions can be set by a variety of factors related to weather and climate, including exposure to lethal environmental conditions, indirect effects on consumers and competitors, and sublethal effects of physiological stress on growth and reproduction. Predicting where, when and with what magnitude these impacts are most (and least) likely to occur is imperative if we are to effectively plan for (i.e. adapt to) the effects of climate change.

We developed a series of methods for translating patterns of environmental “signals” into organismal responses in intertidal ecosystems. Importantly, “organismal climatologies” – long term patterns of organism temperature measured using in situ biomimetic sensors - show distinct differences from patterns based on environmental temperature (air or water temperature). Similarly, we explored the use of dynamic energy budget models, linked to heat budget models of animal temperature, to examine temporal and spatial patterns of sublethal stress and growth. 

Results and Conclusions
Comparisons of four different metrics of stress- seasonal averages, extreme temperatures, number of “stressful days” (>32°C) and return time of stress events – show that temporal and spatial patterns of sublethal stress do not always track patterns of lethal exposure. In other words, simply knowing average temperature often tells us very little about exposure to extremes and vice versa. These results are consistent with the idea that extreme events can occur during the temporal synchrony of multiple “normal” events- for example low wave splash, extreme low tides and high solar radiation. Results also suggest that the combination of heat budget models with dynamic energy budgets are potentially an effective way to predict spatial patterns of intertidal organisms, but that we still need more physiological data regarding the role of aerial body temperature in driving growth and reproduction.

|
