4.5 Article

The influence of physical and physiological processes on the spatial heterogeneity of a Microcystis bloom in a stratified reservoir

Journal

ECOLOGICAL MODELLING
Volume 289, Issue -, Pages 133-149

Publisher

ELSEVIER SCIENCE BV
DOI: 10.1016/j.ecolmodel.2014.07.010

Keywords

Daecheong reservoir; Microcystis aeruginosa; Spatial heterogeneity; ELCOM-CAEDYM; Buoyancy control; Coupled physical-ecological model

Categories

Funding

  1. National Research Foundation of Korea (NRF) - Ministry of Education, Science and Technology [2012R1A1A2007689]
  2. National Research Foundation of Korea [2012R1A1A2007689] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

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A three-dimensional coupled hydrodynamic and ecological model, ELCOM-CAEDYM, was extended to include buoyancy control dynamics for cyanobacteria, and validated in the stratified Daecheong Reservoir (Korea). Specifically, the model was used to explore the physical and biological processes that determined the temporal and spatial variability of Microcystis aeruginosa (hereafter Microcystis) biomass during an abnormally intense mono-specific bloom event. Inclusion of the buoyancy control function within the coupled model considerably improved the model predictability by capturing the biomass accumulation at the surface during the bloom, and the shift of the dominant group from green algae to cyanobacteria. Results indicated that physical processes, particularly inflow mixing, played a dominant role in determining the spatial heterogeneity of Microcystis biomass through the local control of nutrient availability. In addition, the shallow mixed layer depth (z(m)) relative to the euphotic depth (z(p)) under a stable thermal stratification provided a perfect physical habitat for the dominance of this cyanobacteria relative to other species, due to their buoyancy control capability. This work demonstrates that the coupled hydrodynamic and ecological modeling has advanced to a stage where it may be used to interpret field data and subject to a suitable level of validation, the model may be used as a management decision support tool. (C) 2014 Elsevier B.V. All rights reserved.

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