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Coupled physical-biogeochemical simulations of upwelling, ecological response to fresh water

Anitha Gera, R Gayathri, P Ezhilarasan, V Ranga Rao and M V Ramana Murthy

Ecological Modelling, 2023, vol. 476, issue C

Abstract: An eddy resolving 1/12⁰ coupled physical biogeochemical ocean model configured for the Indian Ocean is used to study the upwelling off the west coast of India, the dynamics of the south eastern Arabian Sea and the associated bio-physical-chemical mechanisms. The model reproduces well the climatological features and local and remotely forced dynamical processes of the upwelling system in physical variables as well as biogeochemical parameters. Modelling experiments show that fresh water from rainfall and river runoff alter the phytoplankton concentration as well as the distribution of the phytoplankton size classes. It is seen that rainfall influences the nanoplankton concentrations while river runoff influences larger diatom concentrations. Fresh water due to rainfall shoals the mixed layer (ML) and thermocline restricting upwelling due to enhanced stratification resulting in reduced nutrient and thereby reduced chlorophyll, essentially nanoplankton. Further a thinner and warmer ML modifies thermodynamics and can consequently influence zooplankton by altering mesozooplankton grazing. River runoff additionally influences by supplying nutrient causing a reduction in diatom and increase in nanoplankton concentrations thus increasing the preferred prey of zooplankton in the SEAS. Our simulations indicate phosphorous limitation in the region. The biophysical controls linking ecological responses to fresh water like zooplankton food preferences are detailed with discussions on implications to food-web dynamics of the region.

Keywords: Coupled model; Bio-physical coupling; Diatoms; River runoff; Arabian sea; Upwelling; Marine; Coastal ecosystems; Phytoplankton; Nutrients (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:476:y:2023:i:c:s0304380022003441

DOI: 10.1016/j.ecolmodel.2022.110246

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