Detecting the presence of fish farm-derived organic matter at the seafloor using stable isotope analysis of phospholipid fatty acids

Mayor, Daniel J. ORCID: https://orcid.org/0000-0002-1295-0041; Gray, Nia B.; Hattich, Giannina S.I.; Thornton, Barry. 2017 Detecting the presence of fish farm-derived organic matter at the seafloor using stable isotope analysis of phospholipid fatty acids. Scientific Reports, 7. 5146. https://doi.org/10.1038/s41598-017-05252-w

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Abstract/Summary

The expansion of global aquaculture activities is important for the wellbeing of future generations in terms of employment and food security. Rearing animals in open-exchange cages permits the release of organic wastes, some of which ultimately reaches the underlying sediments. The development of rapid, quantitative and objective monitoring techniques is therefore central to the environmentally sustainable growth of the aquaculture industry. Here, we demonstrate that fish farm-derived organic wastes can be readily detected at the seafloor by quantifying sediment phospholipid fatty acids (PLFAs) and their carbon stable isotope signatures. Observations across five farms reveal that farm size and/or distance away from it influence the spatial distribution of the generated organic wastes and their effect on benthic bacterial biomass. Comparison to the isotopic signatures of fish feed-derived PLFAs indicates that 16:0 and 18:1(n-9) are potential biomarkers for fish farm-derived organic wastes. Our results suggest that stable isotope analysis of sediment PLFAs has potential for monitoring the environmental performance of aquaculture activities, particularly given the increasing prevalence of terrigenous organic matter in aquaculture feed stocks because it is isotopically district to marine organic matter.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1038/s41598-017-05252-w
ISSN:	2045-2322
Date made live:	17 Jul 2017 15:00 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/517087

Item Type:

Publication - Article

Digital Object Identifier (DOI):

https://doi.org/10.1038/s41598-017-05252-w

ISSN:

2045-2322

Date made live:

17 Jul 2017 15:00 +0 (UTC)

URI:

https://nora.nerc.ac.uk/id/eprint/517087