A comprehensive database of thermal developmental plasticity in reptiles

Daniel W. A. Noble, Vaughn Stenhouse, Julia L. Riley, Daniel A. Warner, Geoffrey M. While, Wei Guo Du, Tobias Uller, Lisa E. Schwanz*

*Corresponding author for this work

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Abstract

How temperature influences development has direct relevance to ascertaining the impact of climate change on natural populations. Reptiles have served as empirical models for understanding how the environment experienced by embryos can influence phenotypic variation, including sex ratio, phenology and survival. Such an understanding has important implications for basic eco-evolutionary theory and conservation efforts worldwide. While there is a burgeoning empirical literature of experimental manipulations of embryonic thermal environments, addressing widespread patterns at a comparative level has been hampered by the lack of accessible data in a format that is amendable to updates as new studies emerge. Here, we describe a database with nearly 10, 000 phenotypic estimates from 155 species of reptile, collected from 300 studies manipulating incubation temperature (published between 1974-2016). The data encompass various morphological, physiological, behavioural and performance traits along with growth rates, developmental timing, sex ratio and survival (e.g., hatching success). This resource will serve as an important data repository for addressing overarching questions about thermal plasticity of reptile embryos.

Original languageEnglish
Article number180138
Pages (from-to)1-7
Number of pages7
JournalScientific Data
Volume5
DOIs
Publication statusPublished - 17 Jul 2018

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Copyright the Author(s) 2018. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

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Noble, D. W. A., Stenhouse, V., Riley, J. L., Warner, D. A., While, G. M., Du, W. G., ... Schwanz, L. E. (2018). A comprehensive database of thermal developmental plasticity in reptiles. Scientific Data, 5, 1-7. [180138]. https://doi.org/10.1038/sdata.2018.138