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Keywords:

  • biophysical model;
  • energy budget;
  • energy use and costs;
  • grasshopper;
  • metabolic rate;
  • phenotype;
  • population dynamics;
  • thermal tolerance

Summary

  1. The Metabolic Theory of Ecology has renewed interest in using energetics to scale across levels of ecological organization. Can scaling from individual phenotypes to population dynamics provides insight into why species have shifted their phenologies, abundances and distributions idiosyncratically in response to recent climate change?
  2. We consider how the energetic implications of phenotypes may scale to understand population and species level responses to climate change using four focal grasshopper species along an elevation gradient in Colorado. We use a biophysical model to translate phenotypes and environmental conditions into estimates of body temperatures. We measure thermal tolerances and preferences and metabolic rates to assess rates of energy use and acquisition.
  3. Body mass declines along the elevation gradient for all species, but mass-specific metabolic rates increases only modestly. We find interspecific differences in both overall thermal tolerances and preferences and in the variation of these metrics along the elevation gradient. The more dispersive species exhibit significantly higher thermal tolerance and preference consistent with much of their range spanning hot, low elevation areas. When integrating these metrics to consider metabolic constraints, we find that energetic costs decrease along the elevation gradient due to decreasing body size and temperature. Opportunities for energy acquisition, as reflected by the proportion of time that falls within a grasshopper's thermal tolerance range, peak at mid elevations. We discuss methods for translating these energetic metrics into population dynamics.
  4. Quantifying energy balances and allocation offers a viable approach for predicting how populations will respond to climate change and the consequences for species composed of populations that may be locally adapted.