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Model-based data analysis of the effect of winter mixing on primary production in a lake under reoligotrophication

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  • Krishna, Shubham
  • Ulloa, Hugo N.
  • Kerimoglu, Onur
  • Minaudo, Camille
  • Anneville, Orlane
  • Wüest, Alfred

Abstract

Nutrient loading, in combination with climate change are important drivers of primary productivity in lakes. Understanding and forecasting future changes in primary production (PP) in response to local and global forcing are major challenges for developing sustainable lake management. The objective of this study is to understand and characterize the mechanisms underlying the large differences in observed PP rates and nutrient concentrations between two consecutive years (2012 and 2013) in Lake Geneva, Switzerland. For this purpose, we apply a one-dimensional (1D) physical–biogeochemical model system. The Framework of Aquatic Biogeochemical models (FABM) interface is used to couple the General Ocean Turbulence Model (GOTM) with a biogeochemical model, the Ecological Regional Ocean Model (ERGOM). We calibrated GOTM, by adjusting physical parameters, with the observed temperature profiles. A model calibration method is implemented to minimize model-data misfits and to optimize the biological parameters related to phytoplankton growth dynamics.

Suggested Citation

  • Krishna, Shubham & Ulloa, Hugo N. & Kerimoglu, Onur & Minaudo, Camille & Anneville, Orlane & Wüest, Alfred, 2021. "Model-based data analysis of the effect of winter mixing on primary production in a lake under reoligotrophication," Ecological Modelling, Elsevier, vol. 440(C).
  • Handle: RePEc:eee:ecomod:v:440:y:2021:i:c:s0304380020304634
    DOI: 10.1016/j.ecolmodel.2020.109401
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    References listed on IDEAS

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    1. Kerimoglu, Onur & Jacquet, Stéphan & Vinçon-Leite, Brigitte & Lemaire, Bruno J. & Rimet, Frédéric & Soulignac, Frédéric & Trévisan, Dominique & Anneville, Orlane, 2017. "Modelling the plankton groups of the deep, peri-alpine Lake Bourget," Ecological Modelling, Elsevier, vol. 359(C), pages 415-433.
    2. Marten Scheffer & Steve Carpenter & Jonathan A. Foley & Carl Folke & Brian Walker, 2001. "Catastrophic shifts in ecosystems," Nature, Nature, vol. 413(6856), pages 591-596, October.
    3. Krishna, Shubham & Pahlow, Markus & Schartau, Markus, 2019. "Comparison of two carbon-nitrogen regulatory models calibrated with mesocosm data," Ecological Modelling, Elsevier, vol. 411(C).
    4. Shimoda, Yuko & Arhonditsis, George B., 2016. "Phytoplankton functional type modelling: Running before we can walk? A critical evaluation of the current state of knowledge," Ecological Modelling, Elsevier, vol. 320(C), pages 29-43.
    5. Soetaert, Karline & Petzoldt, Thomas, 2010. "Inverse Modelling, Sensitivity and Monte Carlo Analysis in R Using Package FME," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 33(i03).
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