Journal cover Journal topic
Biogeosciences An interactive open-access journal of the European Geosciences Union
Journal topic
Volume 11, issue 11
Biogeosciences, 11, 2939–2960, 2014
https://doi.org/10.5194/bg-11-2939-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
Biogeosciences, 11, 2939–2960, 2014
https://doi.org/10.5194/bg-11-2939-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 05 Jun 2014

Research article | 05 Jun 2014

Examination of the role of the microbial loop in regulating lake nutrient stoichiometry and phytoplankton dynamics

Y. Li1,2,3, G. Gal4, V. Makler-Pick5,6, A. M. Waite7,*, L. C. Bruce1,7, and M. R. Hipsey1,7 Y. Li et al.
  • 1Aquatic Ecodynamics, School of Earth & Environment, The University of Western Australia, Crawley WA 6009, Australia
  • 2Department of Ecology, Jinan University, Guangzhou 510632, China
  • 3School of Environmental Science & Engineering, Ocean University of China, Qingdao 266100, China.
  • 4Kinneret Limnological Laboratory, Israel Oceanographic and Limnological Research, Migdal 14950, Israel
  • 5Faculty of Civil and Environmental Engineering, Technion-Israel Institute of Technology, Haifa 32000, Israel
  • 6Oranim Academic College of Education, Kiryat Tivon 36006, Israel
  • 7The Oceans Institute, The University of Western Australia, Crawley WA 6009, Australia
  • *current address: Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung, Am Handelshafen 12, 27570 Bremerhaven, Germany

Abstract. The recycling of organic material through bacteria and microzooplankton to higher trophic levels, known as the "microbial loop", is an important process in aquatic ecosystems. Here the significance of the microbial loop in influencing nutrient supply to phytoplankton has been investigated in Lake Kinneret (Israel) using a coupled hydrodynamic–ecosystem model. The model was designed to simulate the dynamic cycling of carbon, nitrogen and phosphorus through bacteria, phytoplankton and zooplankton functional groups, with each pool having unique C : N : P dynamics. Three microbial loop sub-model configurations were used to isolate mechanisms by which the microbial loop could influence phytoplankton biomass, considering (i) the role of bacterial mineralisation, (ii) the effect of micrograzer excretion, and (iii) bacterial ability to compete for dissolved inorganic nutrients. The nutrient flux pathways between the abiotic pools and biotic groups and the patterns of biomass and nutrient limitation of the different phytoplankton groups were quantified for the different model configurations. Considerable variation in phytoplankton biomass and dissolved organic matter demonstrated the sensitivity of predictions to assumptions about microbial loop operation and the specific mechanisms by which phytoplankton growth was affected. Comparison of the simulations identified that the microbial loop most significantly altered phytoplankton growth by periodically amplifying internal phosphorus limitation due to bacterial competition for phosphate to satisfy their own stoichiometric requirements. Importantly, each configuration led to a unique prediction of the overall community composition, and we conclude that the microbial loop plays an important role in nutrient recycling by regulating not only the quantity, but also the stoichiometry of available N and P that is available to primary producers. The results demonstrate how commonly employed simplifying assumptions about model structure can lead to large uncertainty in phytoplankton community predictions and highlight the need for aquatic ecosystem models to carefully resolve the variable stoichiometry dynamics of microbial interactions.

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