Phytoplankton productivity in a tropical lake-floodplain system revealed by a process-based primary production model

Vouchlay Theng, Ratino Sith, Sovannara Uk and Chihiro Yoshimura

Ecological Modelling, 2023, vol. 479, issue C

Abstract: Our knowledge of phytoplankton productivity and its relevant factors in the tropical lake-floodplains is still scarce. Thus, this study aims to develop a two-dimensional primary production (PP) model to elucidate phytoplankton biomass and growth rates in Tonle Sap Lake, a large tropical lake-floodplain system in Cambodia. The model consists of three modules of sediment, phosphorus, and phytoplankton, explicitly describing the major processes of phytoplankton (i.e., advection-dispersion, growth, death, sedimentation, and resuspension). As the basis, the hydrological–hydrodynamics model was applied to simulate the tributary river discharges and hydrodynamics of the lake. Then, the PP model was calibrated for the period from November 2016 to July 2018 and validated from August 2018 to June 2019. The root mean square error of the simulated chlorophyll-a concentration was 18.0 µg/L in the calibration and 10.1 µg/L in the validation, indicating that the model described the major spatiotemporal variations of phytoplankton biomass and productivity in the lake. The PP model revealed that the median specific growth rate and net growth rate in this lake peaked during the low-water period (April – June) when the available dissolved inorganic phosphorus for phytoplankton uptake was higher than in other seasons. The model also allowed the comparison with other lakes regarding phytoplankton productivity, indicating that the specific growth rate of Tonle Sap Lake was in the middle of the rates of other lakes in the world. The developed model substantially helps us understand the phytoplankton productivity in tropical lake-floodplain systems.

Keywords: Primary production; Phytoplankton growth; Sediment resuspension; Tonle Sap Lake (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:479:y:2023:i:c:s0304380023000455

DOI: 10.1016/j.ecolmodel.2023.110317

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