JOURNAL ARTICLE

Elemental composition and stoichiometry of krill and salps.

  • Published In: Journal of Plankton Research, 2023, v. 45, n. 2. P. 372 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Plum, Christoph; Möller, Fenja-Marie; Smykala, Mike; Moorthi, Stefanie 3 of 3

Abstract

This article focuses on comparing the elemental stoichiometry of Antarctic krill (Euphausia superba) and the pelagic tunicate salp (Salpa thompsoni) to understand their differing nutrient requirements and potential impacts on Southern Ocean biogeochemistry. Field data from the Northern Antarctic Peninsula showed that S. thompsoni has significantly lower body carbon (C), nitrogen (N), and phosphorus (P) content but lower C:P and N:P ratios than E. superba, indicating a higher phosphorus demand in salps. A systematic literature review of 33 euphausiid and 19 salp species revealed that, on average, salps tend to have higher C:N, C:P, and N:P ratios than krill, with considerable variability influenced by species, size, season, and latitude. These findings suggest that shifts from krill to salp dominance, as observed with climate-driven changes, could alter nutrient recycling and elemental fluxes in marine ecosystems, but stoichiometric demands vary across ecological contexts and species. The study highlights the need for more comprehensive stoichiometric data, especially on phosphorus, to improve predictions of how changing zooplankton communities affect ocean nutrient cycles and food webs.

Additional Information

  • Source:Journal of Plankton Research. 2023/03, Vol. 45, Issue 2, p372
  • Document Type:Article
  • Subject Area:Science
  • Publication Date:2023
  • ISSN:0142-7873
  • DOI:10.1093/plankt/fbad005
  • Accession Number:162858379
  • Copyright Statement:Copyright of Journal of Plankton Research is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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