A model for the description of feeding regulation by mesozooplankton under different conditions of temperature and prey nutritional status

Emmanuel Acheampong, Emmanuel Acheampong, Inga Hense, Michael A. St. John

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

Ecosystem modelling studies that consider mesozooplankton feeding regulation have primarily focused on the impact of prey nutritional status and temperature separately, despite experimental evidence for strong links between these two factors. Here, we propose a method based on optimal feeding behaviour of individual mesozooplankton that can be used to derive acclimative food ingestion, assimilation, and respiration under different temperature and food conditions. In the model, animals first evaluate the nutritional value of prey organisms based on their temperature-specific demand for energy and structural biochemical substances. They then regulate their feeding behaviour as well as metabolic physiology in order to satisfy their specific biochemical requirements for maintenance and growth. The approach is applicable to all heterotrophic plankton. In the example presented here the model has been configured to simulate egg production by the calanoid copepod Acartia tonsa. The model realistically reproduces the observed rates for egg production, as well as carbon (C) and nitrogen (N) gross growth efficiencies of egg production by Acartia in response to changes in both algal C:N-ratio and temperature. Results suggest that enhanced temperature accelerates respiratory consumption of the N assimilated by mesozooplankton, and thus decreases the rates for reproduction at higher temperatures. They also show that the optimum temperature for maximum egg production increases with algal C:N-ratio. These findings support and extend conclusions previously obtained for mesozooplankton and indicate that ocean warming could alter the role of Acartia spp. in planktonic food webs. © 2013 Elsevier B.V.
Original languageEnglish
JournalEcological Modelling
Volume272
Pages (from-to)84-97
ISSN0304-3800
DOIs
Publication statusPublished - 2014

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