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Data from: Generation length of the world's amphibians and reptiles

Mancini, Giordano1; Santini, Luca1; Cazalis, Victor; Ficetola, Gentile Francesco2; Meiri, Shai3; Roll, Uri4; Silvestri, Sofia1; Pincheira-Donoso, Daniel5; Di Marco, Moreno1

Published Mar 07, 2025; Updated Mar 25, 2025 on Dryad. https://doi.org/10.5061/dryad.w0vt4b93t

Data files

Mar 07, 2025 version files 7.60 MB
Mar 25, 2025 version files 8.02 MB

Abstract

Variation in life histories influences demographic processes, from adaptive changes to population declines leading to extinction. Among life history traits, generation length offers a critical feature to forecast species’ demographic trajectories such as population declines (widely used by the IUCN Red List) and adaptability to environmental change over time. Therefore, estimates of generation length are crucial to monitor demographic stability or predict future changes in highly threatened organisms, particularly amphibians and reptiles, which are particularly threatened among vertebrates and for which uncertainty in future impacts remains high. Despite its importance, generation length for amphibians and reptiles is largely missing. Here, we aim to fill-in this gap by modeling generation lengths for amphibians, squamates and testudines as a function of species size, climate, life history, and phylogeny using generalized additive models and phylogenetic generalized least squares. We estimated generation lengths for 5,059 (57%) amphibians, 8,722 (73%) squamates and 117 (32%) testudines. Our models performed well for most families (e.g., Bufonidae among amphibians, Lacertidae and Colubridae among squamates, and Geoemydidae among testudines), while we found high uncertainty around the prediction of a few families, notably Chamaeleonidae. Species’ body size and mean temperature were the main predictors of generation length in all groups. Although our estimates are not meant to substitute robust and validated measurements from field studies or natural history museums, they can help reduce existing biases in conservation assessments until field data will be comprehensively available.