Literature DB >> 29720410

Mammoth grazers on the ocean's minuteness: a review of selective feeding using mucous meshes.

Keats R Conley1, Fabien Lombard2, Kelly R Sutherland3.   

Abstract

Mucous-mesh grazers (pelagic tunicates and thecosome pteropods) are common in oceanic waters and efficiently capture, consume and repackage particles many orders of magnitude smaller than themselves. They feed using an adhesive mucous mesh to capture prey particles from ambient seawater. Historically, their grazing process has been characterized as non-selective, depending only on the size of the prey particle and the pore dimensions of the mesh. The purpose of this review is to reverse this assumption by reviewing recent evidence that shows mucous-mesh feeding can be selective. We focus on large planktonic microphages as a model of selective mucus feeding because of their important roles in the ocean food web: as bacterivores, prey for higher trophic levels, and exporters of carbon via mucous aggregates, faecal pellets and jelly-falls. We identify important functional variations in the filter mechanics and hydrodynamics of different taxa. We review evidence that shows this feeding strategy depends not only on the particle size and dimensions of the mesh pores, but also on particle shape and surface properties, filter mechanics, hydrodynamics and grazer behaviour. As many of these organisms remain critically understudied, we conclude by suggesting priorities for future research.
© 2018 The Author(s).

Entities:  

Keywords:  bentho-pelagic coupling; grazers; pteropods; selective feeding; tunicates

Mesh:

Year:  2018        PMID: 29720410      PMCID: PMC5966591          DOI: 10.1098/rspb.2018.0056

Source DB:  PubMed          Journal:  Proc Biol Sci        ISSN: 0962-8452            Impact factor:   5.349


  26 in total

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Journal:  PLoS One       Date:  2018-01-03       Impact factor: 3.240

5.  From the surface to the seafloor: How giant larvaceans transport microplastics into the deep sea.

Authors:  Kakani Katija; C Anela Choy; Rob E Sherlock; Alana D Sherman; Bruce H Robison
Journal:  Sci Adv       Date:  2017-08-16       Impact factor: 14.136

6.  New technology reveals the role of giant larvaceans in oceanic carbon cycling.

Authors:  Kakani Katija; Rob E Sherlock; Alana D Sherman; Bruce H Robison
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Authors:  Julia Hosp; Yoshimasa Sagane; Gemma Danks; Eric M Thompson
Journal:  PLoS One       Date:  2012-07-05       Impact factor: 3.240

9.  A mechanistic individual-based model of the feeding processes for Oikopleura dioica.

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10.  Ecological-network models link diversity, structure and function in the plankton food-web.

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Journal:  Sci Rep       Date:  2016-02-17       Impact factor: 4.379

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  6 in total

1.  The vertical distribution and biological transport of marine microplastics across the epipelagic and mesopelagic water column.

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Journal:  Sci Rep       Date:  2019-06-06       Impact factor: 4.379

2.  Eukaryotic and cyanobacterial communities associated with marine snow particles in the oligotrophic Sargasso Sea.

Authors:  Regitze B C Lundgreen; Cornelia Jaspers; Sachia J Traving; Daniel J Ayala; Fabien Lombard; Hans-Peter Grossart; Torkel G Nielsen; Peter Munk; Lasse Riemann
Journal:  Sci Rep       Date:  2019-06-20       Impact factor: 4.379

3.  Rewiring and indirect effects underpin modularity reshuffling in a marine food web under environmental shifts.

Authors:  Domenico D'Alelio; Bruno Hay Mele; Simone Libralato; Maurizio Ribera d'Alcalà; Ferenc Jordán
Journal:  Ecol Evol       Date:  2019-09-30       Impact factor: 2.912

4.  Suspension feeders: diversity, principles of particle separation and biomimetic potential.

Authors:  Leandra Hamann; Alexander Blanke
Journal:  J R Soc Interface       Date:  2022-01-26       Impact factor: 4.118

5.  Sponges sneeze mucus to shed particulate waste from their seawater inlet pores.

Authors:  Niklas A Kornder; Yuki Esser; Daniel Stoupin; Sally P Leys; Benjamin Mueller; Mark J A Vermeij; Jef Huisman; Jasper M de Goeij
Journal:  Curr Biol       Date:  2022-08-10       Impact factor: 10.900

Review 6.  Machine learning techniques to characterize functional traits of plankton from image data.

Authors:  Eric C Orenstein; Sakina-Dorothée Ayata; Frédéric Maps; Érica C Becker; Fabio Benedetti; Tristan Biard; Thibault de Garidel-Thoron; Jeffrey S Ellen; Filippo Ferrario; Sarah L C Giering; Tamar Guy-Haim; Laura Hoebeke; Morten Hvitfeldt Iversen; Thomas Kiørboe; Jean-François Lalonde; Arancha Lana; Martin Laviale; Fabien Lombard; Tom Lorimer; Séverine Martini; Albin Meyer; Klas Ove Möller; Barbara Niehoff; Mark D Ohman; Cédric Pradalier; Jean-Baptiste Romagnan; Simon-Martin Schröder; Virginie Sonnet; Heidi M Sosik; Lars S Stemmann; Michiel Stock; Tuba Terbiyik-Kurt; Nerea Valcárcel-Pérez; Laure Vilgrain; Guillaume Wacquet; Anya M Waite; Jean-Olivier Irisson
Journal:  Limnol Oceanogr       Date:  2022-06-30       Impact factor: 5.019

  6 in total

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