A physiological trait-based approach to predicting the responses of species to experimental climate warming

• Published in: Ecology (Durham) 2012-11, Vol.93 (11), p.2305-2312
• Main Authors: Diamond, Sarah E., Nichols, Lauren M., McCoy, Neil, Hirsch, Christopher, Pelini, Shannon L., Sanders, Nathan J., Ellison, Aaron M., Gotelli, Nicholas J., Dunn, Robert R.
• Format: Article
• Language: English
• Subjects: Adaptation, Physiological - genetics; Adaptation, Physiological - physiology; Animal and plant ecology; Animal, plant and microbial ecology; Animals; Ants; Ants - classification; Ants - genetics; Ants - physiology; Biological and medical sciences; Boundaries; Climate Change; Climate models; Climatology. Bioclimatology. Climate change; Correlation analysis; critical thermal maximum; Duke Forest, North Carolina, USA; Earth, ocean, space; Ecological modeling; Ecosystem; ectotherm responses to global warming; Environmental conditions; Exact sciences and technology; External geophysics; Forest ecology; Forest insects; Forests; Formicidae; Fundamental and applied biological sciences. Psychology; General aspects; global change; Global warming; Harvard Forest, Massachusetts, USA; Hot Temperature; Insect ecology; maximum entropy; Measurement; Meteorology; Modeling; Models, Biological; physiology; Species; species distribution model; Species Specificity; temperate hardwood forests, eastern North America; thermal tolerance; Trees
• ISSN: 0012-9658; 1939-9170
• DOI: 10.1890/11-2296.1

Physiological tolerance of environmental conditions can influence species-level responses to climate change. Here, we used species-specific thermal tolerances to predict the community responses of ant species to experimental forest-floor warming at the northern and southern boundaries of temperate hardwood forests in eastern North America. We then compared the predictive ability of thermal tolerance vs. correlative species distribution models (SDMs) which are popular forecasting tools for modeling the effects of climate change. Thermal tolerances predicted the responses of 19 ant species to experimental climate warming at the southern site, where environmental conditions are relatively close to the ants' upper thermal limits. In contrast, thermal tolerances did not predict the responses of the six species in the northern site, where environmental conditions are relatively far from the ants' upper thermal limits. Correlative SDMs were not predictive at either site. Our results suggest that, in environments close to a species' physiological limits, physiological trait-based measurements can successfully forecast the responses of species to future conditions. Although correlative SDMs may predict large-scale responses, such models may not be accurate for predicting site-level responses.