We use the global coupled physical‐biogeochemical model NEMO/PISCES (Aumont et al., 2015 (link)), which represents nitrate, ammonium, phosphate, silicic acid and dissolved iron cycling, the full carbon and oxygen systems, two phytoplankton groups (nanophytoplankton and diatoms) and two zooplankton size classes (microzooplankton and mesozooplankton) and has been extensively used to study regional and global ocean biogeochemistry (e.g. Aumont et al., 2017 (link); Gorgues et al., 2019 (link); Kwiatkowski, Aumont, Bopp, & Ciais, 2018 (link); Richon et al., 2017 (link); Tagliabue & Resing, 2016 (link)). Recent developments of the PISCES model have included micronutrient cycling such as Cu (Richon & Tagliabue, 2019 (link)), Zn, Co (Tagliabue et al., 2018 (link)) and Mn to build a new version of the model called PISCES‐BYONIC. The model is fully described and evaluated in supplement (Text S1 ). We present here the key information on the model.
In the standard version of PISCES‐BYONIC, the phytoplankton macronutrient stoichiometry (C:N:P) is fixed, but it is variable for micronutrients (Fe, Co, Cu, Mn and Zn), chlorophyll and silica. The maximum micronutrient:C molar quotas are 80E‐6 for Fe, 40 and 123 for Zn in nanophytoplankton and diatoms, respectively, 16E‐6 for Cu, 1.2E‐6 for Co and 8E‐6 for Mn, which broadly reflects available observational constraints (e.g. Twining & Baines, 2013 (link); Twining et al., 2015 (link)). The zooplankton molar micronutrient to carbon stoichiometry is fixed to 10E‐6 for Fe, Zn and Cu, and to 0.16E‐6 and 1E‐6 for Co and Mn, respectively, following the more limited observational understanding (see Baines et al., 2016 (link); Ratnarajah et al., 2014 (link); Twining & Baines, 2013 (link)).
The impacts of climate change on micronutrient recycling and recycling stoichiometry were simulated using offline physical fields from the IPSL‐CM5A climate model, as in previous work (Kwiatkowski, Aumont, Bopp, & Ciais, 2018 (link); Tagliabue et al., 2020 (link)). We performed two simulations: a preindustrial control (PICONTROL) from 1801 to 2100 with atmospheric CO2 concentrations fixed to the preindustrial value. Then, from 1851 to 2100, we performed a second simulation initialized from year 1851 of the PICONTROL, with CO2 concentrations varying according to the historical pathway until 2005 and switching to the high emissions RCP8.5 scenario (Riahi et al., 2011 (link)) from 2006 to 2100. Previous studies using NEMO/PISCES under the RCP8.5 scenario showed a global increase in stratification, increased SST and decrease in surface macronutrients leading to changes in plankton distribution and stoichiometry (Kwiatkowski, Aumont, & Bopp, 2018 (link); Kwiatkowski, Aumont, Bopp, & Ciais, 2018 (link)).
For our simulations, we use constant external nutrient sources (hydrothermal vents, rivers and aerosols). Sedimentary sources of Co and Mn are O2 dependent (Tagliabue et al., 2018 (link)). To assess our results, we define two periods of time: PRESENT (model results averaged over 1991–2000) and FUTURE (model results averaged over 2091–2100). Previous work with this model has shown that microzooplankton recycling accounts for most of micronutrient recycling fluxes (see Richon et al., 2020 (link)); therefore, we focus here on microzooplankton.
In the standard version of PISCES‐BYONIC, the phytoplankton macronutrient stoichiometry (C:N:P) is fixed, but it is variable for micronutrients (Fe, Co, Cu, Mn and Zn), chlorophyll and silica. The maximum micronutrient:C molar quotas are 80E‐6 for Fe, 40 and 123 for Zn in nanophytoplankton and diatoms, respectively, 16E‐6 for Cu, 1.2E‐6 for Co and 8E‐6 for Mn, which broadly reflects available observational constraints (e.g. Twining & Baines, 2013 (link); Twining et al., 2015 (link)). The zooplankton molar micronutrient to carbon stoichiometry is fixed to 10E‐6 for Fe, Zn and Cu, and to 0.16E‐6 and 1E‐6 for Co and Mn, respectively, following the more limited observational understanding (see Baines et al., 2016 (link); Ratnarajah et al., 2014 (link); Twining & Baines, 2013 (link)).
The impacts of climate change on micronutrient recycling and recycling stoichiometry were simulated using offline physical fields from the IPSL‐CM5A climate model, as in previous work (Kwiatkowski, Aumont, Bopp, & Ciais, 2018 (link); Tagliabue et al., 2020 (link)). We performed two simulations: a preindustrial control (PICONTROL) from 1801 to 2100 with atmospheric CO2 concentrations fixed to the preindustrial value. Then, from 1851 to 2100, we performed a second simulation initialized from year 1851 of the PICONTROL, with CO2 concentrations varying according to the historical pathway until 2005 and switching to the high emissions RCP8.5 scenario (Riahi et al., 2011 (link)) from 2006 to 2100. Previous studies using NEMO/PISCES under the RCP8.5 scenario showed a global increase in stratification, increased SST and decrease in surface macronutrients leading to changes in plankton distribution and stoichiometry (Kwiatkowski, Aumont, & Bopp, 2018 (link); Kwiatkowski, Aumont, Bopp, & Ciais, 2018 (link)).
For our simulations, we use constant external nutrient sources (hydrothermal vents, rivers and aerosols). Sedimentary sources of Co and Mn are O2 dependent (Tagliabue et al., 2018 (link)). To assess our results, we define two periods of time: PRESENT (model results averaged over 1991–2000) and FUTURE (model results averaged over 2091–2100). Previous work with this model has shown that microzooplankton recycling accounts for most of micronutrient recycling fluxes (see Richon et al., 2020 (link)); therefore, we focus here on microzooplankton.
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