Targeted behavioural and microclimate data collection substantially improves biophysical model predictions of energy expenditure in wild birds

Abstract

Energy is fundamental for life, and accurately predicting animals’ energy expenditure under changing environments is central to ecology and global change biology. Energy expenditure in free-living animals can be directly quantified using the doubly labelled water (DLW) technique or estimated by extrapolating respirometric measurements of metabolic rates or modelled using biophysical principles. However, the accuracy of these latter approaches depends on data quality and model parameterisation. We evaluated respirometry extrapolations and biophysical models for estimating daily energy expenditure (DEE) in a free-living bird, the Southern Pied Babbler (Turdoides bicolor) against DLW measurements. Respirometry extrapolations and biophysical models were parameterised using: a) assumed animal behaviour and assumed operative temperature (Te), b) assumed animal behaviour and measured Te, c) fine scale (focal) observations of behaviour under natural conditions and measured Te, or d) coarse scale (scan) behaviour observations and measured Te. We then quantified the minimum field-collected data needed to accurately predict measured DEE across a range of daily maximum air temperatures (Tair). RScripts used to predict free ranging energy expenditure in birds, using these two approaches (biophysical models and respirometry) are provided here.