Comparing nestling growth models across bird species with the Nestling Growth App

Comparative studies of nestling growth typically rely on logistic growth-rate constants ( k ) to position species along the slow–fast life-history continuum, yet most analyses fit a single model without formally evaluating alternatives. Five deterministic growth models, Logistic, Gompertz, Richards, von Bertalanffy, and extreme-value function, were fitted to nestling mass, tarsus, and wing-chord data from eight bird species spanning a ∼250-fold body-mass range (∼20–5,500 g), including six Neotropical passerines and two non-passerines ( Megadyptes antipodes and Tachymarptis melba ). No single model was universally best-supported: four different models were selected across the eight species when ranked by information-theoretic criteria. In four of six Neotropical species, different morphometric traits favoured different best-fit models within the same species. Logistic k ranged from 0.078 d -1 in M. antipodes to 0.537 d -1 in Lanio versicolor , and interspecific growth-rate rankings shifted depending on which model was fitted. These results indicate that reliance on a single assumed growth model can bias parameter estimates and alter the comparative inferences drawn across species. We recommend reporting parameters from the best-supported model for each species–trait combination together with logistic k, so that results remain comparable with previous studies. Analyses used the open-source Nestling Growth App, and predictive checks compared information-criterion support with held-out performance in the two larger non-passerine datasets.