Detecting environmentally dependent developmental plasticity in fossilized individuals - Anieke Brombacher; Alex Searle-Barnes; James M. Mulqueeney; Christopher D. Standish; J. Andy Milton; Orestis L. Katsamenis; Richard A. Watson; Clive Trueman; Ian Sinclair; Paul A. Wilson; Gavin L. Foster; Thomas H. G. Ezard (Proceedings of the National Academy of Sciences, 2025)
The fossil record provides the most powerful evidence of large-scale biodiversity change on Earth, but it does so at coarse and often idiosyncratic temporal scales. One critical problem that arises concerns the evolutionary consequences of individual environmental experience. Individuals respond to their environment instantaneously, whereas the resolution of most fossil records aggregates multiple paleoenvironments over time scales beyond individual lifespans. Therefore, the presence of phenotypic plasticity in deep time and the extent of its influence on macroevolution remain poorly understood. Using coupled computed tomography and laser ablation inductively coupled plasma mass spectrometry protocols, we studied the environmental dependence of developmental trajectories across three sister species of macroperforate planktonic foraminifera. A foraminiferal shell preserves all stages of the individual’s ontogeny, as well as the environmental state experienced throughout its lifetime. Generalized additive mixed effect (GAMM) models show that somatic growth rates differ among the three Menardella species and that these are inversely correlated with calcification temperature, as reconstructed from Mg/Ca measurements through ontogeny. This environmental dependence varies among species: The thermal sensitivity of individual chamber-to-chamber growth rates of Menardella limbata and Menardella pertenuis is double that seen in Menardella exilis . In contrast, no such environmental signal was recovered for architectural shape traits. Our integrated approach is widely applicable and demonstrates that detecting developmental plasticity in the fossil record is feasible. Extrapolating these techniques in deep time promises to revolutionize our understanding of the ways in which environmentally associated trait variation drove the diversification of life on Earth.