Optimality-based non-Redfield plankton–ecosystem model (OPEM v1.1) in UVic-ESCM 2.9 – Part 2: Sensitivity analysis and model calibration

Abstract

Abstract. We analyse 400 perturbed-parameter simulations for two configurations of an optimality-based plankton–ecosystem model (OPEM), implemented in the University of Victoria Earth System Climate Model (UVic-ESCM), using a Latin hypercube sampling method for setting up the parameter ensemble. A likelihood-based metric is introduced for model assessment and selection of the model solutions closest to observed distributions of NO3-, PO43-, O2, and surface chlorophyll a concentrations. The simulations closest to the data with respect to our metric exhibit very low rates of global N2 fixation and denitrification, indicating that in order to achieve rates consistent with independent estimates, additional constraints have to be applied in the calibration process. For identifying the reference parameter sets, we therefore also consider the model's ability to represent current estimates of water-column denitrification. We employ our ensemble of model solutions in a sensitivity analysis to gain insights into the importance and role of individual model parameters as well as correlations between various biogeochemical processes and tracers, such as POC export and the NO3- inventory. Global O2 varies by a factor of 2 and NO3- by more than a factor of 6 among all simulations. Remineralisation rate is the most important parameter for O2, which is also affected by the subsistence N quota of ordinary phytoplankton (Q0,phyN) and zooplankton maximum specific ingestion rate. Q0,phyN is revealed as a major determinant of the oceanic NO3- pool. This indicates that unravelling the driving forces of variations in phytoplankton physiology and elemental stoichiometry, which are tightly linked via Q0,phyN, is a prerequisite for understanding the marine nitrogen inventory.

MESMO 3: Flexible phytoplankton stoichiometry and refractory DOM

“…Temperature dependence was added by Arteaga et al (2014) following the simple logarithmic temperature dependence on maximum nutrient uptake rate following (Eppley, 1972). (Chien et al, 2020;Pahlow et al, 2020). However, as we are not describing any results in this paper, we will only mention here that there is an option to calculate C:N:P using this stoichiometry model in MESMO 3.…”

“…The full description of the optimality-based stoichiometry model and its parameter calibration are presented specifically for the UVic model elsewhere (Chien et al, 2020;Pahlow et al, 2020).…”

Author response to two reviewers on gmd-2020-408

“…implemented in global ocean biogeochemical models, such as the Pelagic Interactions Scheme for Carbon and Ecosystem Studies (PISCES) (Kwiatkowski et al, 2018(Kwiatkowski et al, , 2019 and the University of Victoria Earth System Model (UVIC) (Chien et al, 2020;Pahlow et al, 2020). However, as we are not describing any results in this paper, we will only mention here that there is an option to calculate C:N:P using this stoichiometry model in MESMO 3.…”

Can Top-Down Controls Expand the Ecological Niche of Marine N2 Fixers?

“…Laboratory experiments ( Knapp, 2012 ) as well as RCT analyses and results from numerical models of different complexity ( Pahlow et al, 2013 ; Landolfi et al, 2015 ; Inomura et al, 2018 ) collectively suggest that autotrophic diazotrophs can still coexist with non-N 2 fixing phytoplankton where fixed forms of N (e.g., NO 3 – , NH 4 + , and NH 3 ) are available, which may be due to a combination of co-limitation by N and P (and possibly Fe or other micro-nutrients), greater N requirements for nutrient acquisition ( Klausmeier et al, 2004 ) and the high competitive ability of diazotrophs for P ( Pahlow et al, 2013 ). In models, with explicit representation of physiologically costly nutrient acquisition strategies, coexistence among organisms that compete for limited resources occurs for a wide range of nutrient-supply conditions ( Pahlow et al, 2013 , 2020 ; Landolfi et al, 2015 ; Inomura et al, 2018 ; Chien et al, 2020 ). Insight from these recent works highlights the key role of competitive interactions in setting the ecological niche of diazotrophs.…”