Fig. 3

Schematic of an example analytical workflow using CeutaOPEN within the R environment to investigate how chick morphometric data may be used to study growth and ontogeny. (a) Import the database into R using the RSQLite³¹ package. (b) Use the dplyr³² package to join the ‘Captures’ table with the ‘Nests’ table by nest “ID” to determine the “hatch_date” of each captured individual. Subset the result to individuals that have repeated captures and calculate the “age” at capture by subtracting the “hatch_date” by the capture “date”. (c) Use the bamlss³³ package (i.e., “Bayesian Additive Models for Location, Scale, and Shape”) to determine the sex-specific growth trends while controlling for repeated measures within individuals and random annual variation. Plot the fitted values to visualise the trends (see Supplementary File 1 for more details).