Ocean acidification responses in paralarval squid swimming behavior using a novel 3D tracking system
Online Publication Date2017-08-22
Print Publication Date2018-02
Permanent link to this recordhttp://hdl.handle.net/10754/625744
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AbstractChronic embryonic exposure to ocean acidification (OA) has been shown to degrade the aragonitic statolith of paralarval squid, Doryteuthis pealeii, a key structure for their swimming behavior. This study examined if day-of-hatching paralarval D. pealeii from eggs reared under chronic OA demonstrated measurable impairments to swimming activity and control. This required the development of a novel, cost-effective, and robust method for 3D motion tracking and analysis. Squid eggs were reared in pCO2 levels in a dose-dependent manner ranging from 400 to 2200 ppm. Initial 2D experiments showed paralarvae in higher acidification environments spent more time at depth. In 3D experiments, velocity, particularly positive and negative vertical velocities, significantly decreased from 400 to 1000 ppm pCO2, but showed non-significant decreases at higher concentrations. Activity and horizontal velocity decreased linearly with increasing pCO2, indicating a subtle impact to paralarval energetics. Patterns may have been obscured by notable individual variability in the paralarvae. Responses were also seen to vary between trials on cohort or potentially annual scales. Overall, paralarval swimming appeared resilient to OA, with effects being slight. The newly developed 3D tracking system provides a powerful and accessible method for future studies to explore similar questions in the larvae of aquatic taxa.
CitationZakroff C, Mooney TA, Wirth C (2017) Ocean acidification responses in paralarval squid swimming behavior using a novel 3D tracking system. Hydrobiologia. Available: http://dx.doi.org/10.1007/s10750-017-3342-9.
SponsorsWe thank D. Remsen, the MBL Marine Resources Center staff, and MBL Gemma crew for their support in acquiring squid. R. Galat and the facilities staff of the WHOI ESL provided system support. D. McCorkle, KYK Chan, and M. White provided valuable insight on the OA system. E. Moberg, A. Beet, and A. Solow assisted in the development and coding of the 3D model system. We also thank E. Bonk, K. Hoering, M. Lee, D. Weiler, and A. Schlunk for their assistance and input with the experiments. This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No. 1122374. This project is funded by NSF Grant No. 1220034.