An amniote life‐history database to perform comparative analyses with birds, mammals, and reptiles

TLDR

Life‑history research across taxa relies on large, standardized data sets, yet amniote data are fragmented across disparate databases, publications, and expert compilations, creating challenges for macroecological analyses. To enable comparative studies of amniote life histories, the authors assembled a comprehensive database from peer‑reviewed species studies, macroecological papers, existing databases, books, and other aggregated sources. They extracted raw data, resolved taxonomic inconsistencies through computational and manual methods, harmonized subspecies and species information via a data‑sharing algorithm that accounts for taxonomic changes, and reported median values when multiple measurements existed. The resulting database normalizes up to 29 life‑history parameters for 21,322 bird, mammal, and reptile species.

Abstract

Studying life‐history traits within and across taxonomic classifications has revealed many interesting and important patterns, but this approach to life history requires access to large compilations of data containing many different life‐history parameters. Currently, life‐history data for amniotes (birds, mammals, and reptiles) are split among a variety of publicly available databases, data tables embedded in individual papers and books, and species‐specific studies by experts. Using data from this wide range of sources is a challenge for conducting macroecological studies because of a lack of standardization in taxonomic classifications, parameter values, and even in which parameters are reported. In order to facilitate comparative analyses between amniote life‐history data, we created a database compiled from peer‐reviewed studies on individual species, macroecological studies of multiple species, existing life‐history databases, and other aggregated sources as well as published books and other compilations. First, we extracted and aggregated the raw data from the aforementioned sources. Next, we resolved spelling errors and other formatting inconsistencies in species names through a number of computational and manual methods. Once this was completed, subspecies‐level data and species‐level data were shared via a data‐sharing algorithm to accommodate the variety of species transformations (taxonomic promotions, demotions, merges, divergences, etc.) that have occurred over time. Finally, in species where multiple raw data points were identified for a given parameter, we report the median value. Here, we report a normalized and consolidated database of up to 29 life‐history parameters, containing at least one life‐history parameter for 21 322 species of birds, mammals, and reptiles.