Shannon R. Conradie, Michael R. Kearney, Blair O. Wolf, Susan J. Cunningham, Marc T. Freeman, Ryno Kemp, Andrew E. McKechnie

An evaluation of a biophysical model for predicting avian thermoregulation in the heat

  • Insect Science
  • Molecular Biology
  • Animal Science and Zoology
  • Aquatic Science
  • Physiology
  • Ecology, Evolution, Behavior and Systematics
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ABSTRACT Survival and reproduction of endotherms depend on their ability to balance energy and water exchange with their environment, avoiding lethal deficits and maximising gains for growth and reproduction. At high environmental temperatures, diurnal endotherms maintain body temperature (Tb) below lethal limits via physiological and behavioural adjustments. Accurate models of these processes are crucial for predicting effects of climate variability on avifauna. We evaluated the performance of a biophysical model (NicheMapR) for predicting evaporative water loss (EWL), resting metabolic rate (RMR) and Tb at environmental temperatures approaching or exceeding normothermic Tb for three arid-zone birds: southern yellow-billed hornbill (Tockus leucomelas), southern pied babbler (Turdoides bicolor) and southern fiscal (Lanius collaris). We simulated metabolic chamber conditions and compared model outputs with thermal physiology data collected at air temperatures (Tair) between 10 and 50°C. Additionally, we determined the minimum data needed to accurately model diurnal birds' thermoregulatory responses to Tair using sensitivity analyses. Predicted EWL, metabolic rate and Tb corresponded tightly with observed values across Tair, with only minor discrepancies for EWL in two species at Tair≈35°C. Importantly, the model captured responses at Tair=30–40°C, a range spanning threshold values for sublethal fitness costs associated with sustained hot weather in arid-zone birds. Our findings confirm how taxon-specific parameters together with biologically relevant morphological data can accurately model avian thermoregulatory responses to heat. Biophysical models can be used as a non-invasive way to predict species’ sensitivity to climate, accounting for organismal (e.g. physiology) and environmental factors (e.g. microclimates).

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