Reverse engineering field-derived vertical distribution profiles to infer larval swimming behaviors

James, M. K.; Polton, J. A. ORCID: https://orcid.org/0000-0003-0131-5250; Brereton, A. R.; Howell, K. L.; Nimmo-Smith, W. A. M.; Knights, A. M.. 2019 Reverse engineering field-derived vertical distribution profiles to infer larval swimming behaviors. Proceedings of the National Academy of Sciences, 116 (24). 11818-11823. https://doi.org/10.1073/pnas.1900238116

Before downloading, please read NORA policies.

Preview

Text 11818.full.pdf Download (851kB) | Preview

Abstract/Summary

Biophysical models are well-used tools for predicting the dispersal of marine larvae. Larval behavior has been shown to influence dispersal, but how to incorporate behavior effectively within dispersal models remains a challenge. Mechanisms of behavior are often derived from laboratory-based studies and therefore, may not reflect behavior in situ. Here, using state-of-the-art models, we explore the movements that larvae must undertake to achieve the vertical distribution patterns observed in nature. Results suggest that behaviors are not consistent with those described under the tidally synchronized vertical migration (TVM) hypothesis. Instead, we show (i) a need for swimming speed and direction to vary over the tidal cycle and (ii) that, in some instances, larval swimming cannot explain observed vertical patterns. We argue that current methods of behavioral parameterization are limited in their capacity to replicate in situ observations of vertical distribution, which may cause dispersal error to propagate over time, due to advective differences over depth and demonstrate an alternative to laboratory-based behavioral parameterization that encompasses the range of environmental cues that may be acting on planktic organisms.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1073/pnas.1900238116
ISSN:	0027-8424
Date made live:	06 Aug 2019 14:26 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/524642

Actions (login required)

View Item

Document Downloads

More statistics for this item...