Biogeography of zooplankton feeding strategy

Prowe, A. E. Friederike, Visser, André W., Andersen, Ken H., Chiba, Sanae and Kiørboe, Thomas (2018) Biogeography of zooplankton feeding strategy Limnology and Oceanography . DOI 10.1002/lno.11067.

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The trait‐based approach is increasingly used in plankton ecology to understand diversity, community dynamics, and biogeography. While on the global scale phytoplankton traits are fairly well established, zooplankton traits are only beginning to be understood. One taxa‐transcending aspect of zooplankton diversity is the distinction between ambush and active feeding strategies. We present a global‐scale empirical estimate of feeding strategy derived from copepod abundance observations, which for the first time suggests a distinct trait biogeography with ambush feeding as the dominant feeding strategy at higher, but not at lower latitudes. To explain this trait biogeography, we develop a minimalist trade‐off based model of feeding strategies based on encounter rates between zooplankton predators and their phyto‐ and zooplankton prey. Encounter rates are governed by the two traits, size and motility, that trade off against predation risk. Coupled to a three‐dimensional dynamic green ocean model, our idealized encounter model captures the observed feeding strategy biogeography. In the model, this pattern arises from competing dominant food chains within the food web and is shaped by a trophic trait cascade of active vs. passive feeding in adjacent trophic levels. The dominant feeding strategy structures the pathways and efficiency of energy and biomass transfer through the model food web, with consequences for primary production, export and higher trophic levels. Understanding feeding strategies is therefore important for fisheries, biogeochemical cycling, and long‐term predictions of ecosystem dynamics and functioning by global dynamic green ocean models.

Document Type: Article
Research affiliation: OceanRep > GEOMAR > FB2 Marine Biogeochemistry > FB2-BM Biogeochemical Modeling
Refereed: Yes
DOI etc.: 10.1002/lno.11067
ISSN: 0024-3590
Projects: Dynatrait
Date Deposited: 14 Dec 2018 08:13
Last Modified: 14 Dec 2018 08:13

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