Multiyear trend in reproduction underpins interannual variation in gametogenic development of an Antarctic urchin

Abstract Ecosystems and their biota operate on cyclic rhythms, often entrained by predictable, small-scale changes in their natural environment. Recording and understanding these rhythms can detangle the effect of human induced shifts in the climate state from natural fluctuations. In this study, we...

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Bibliographic Details
Published in:Scientific Reports
Main Authors: Rebecca De Leij, Lloyd S. Peck, Laura J. Grange
Format: Article in Journal/Newspaper
Language:English
Published: Nature Portfolio 2021
Subjects:
R
Q
Online Access:https://doi.org/10.1038/s41598-021-98444-4
https://doaj.org/article/53518835cc5b4997873bb077f5cb5c16
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Summary:Abstract Ecosystems and their biota operate on cyclic rhythms, often entrained by predictable, small-scale changes in their natural environment. Recording and understanding these rhythms can detangle the effect of human induced shifts in the climate state from natural fluctuations. In this study, we assess long-term patterns of reproductive investment in the Antarctic sea urchin, Sterechinus neumayeri, in relation to changes in the environment to identify drivers of reproductive processes. Polar marine biota are sensitive to small changes in their environment and so serve as a barometer whose responses likely mirror effects that will be seen on a wider global scale in future climate change scenarios. Our results indicate that seasonal reproductive periodicity in the urchin is underpinned by a multiyear trend in reproductive investment beyond and in addition to, the previously reported 18–24 month gametogenic cycle. Our model provides evidence that annual reproductive investment could be regulated by an endogenous rhythm since environmental factors only accounted for a small proportion of the residual variation in gonad index. This research highlights a need for multiyear datasets and the combination of biological time series data with large-scale climate metrics that encapsulate multi-factorial climate state shifts, rather than using single explanatory variables to inform changes in biological processes.