DOI: 10.7280/d1kq5q
title: Acclimation of phytoplankton Fe:C ratios dampens the biogeochemical response to varying atmospheric deposition of soluble iron

description: Dissolved iron (dFe) plays an important role in regulating marine
 biological productivity. In high-nutrient, low-chlorophyll regions
 (&gt; 33% of the global ocean) iron is the primary growth-limiting
 nutrient, and elsewhere iron can regulate nitrogen fixation and growth by
 diazotrophs. The link between iron availability and carbon export is
 strongly dependent on the phytoplankton iron quotas, or cellular Fe:C
 ratios. This ratio can vary by more than an order of magnitude in the open
 ocean and is positively correlated with ambient dFe concentrations in
 sparse field observations. The Community Earth System Model ocean
 component was modified to simulate dynamic, group-specific, phytoplankton
 iron quotas (Fe:C) that vary as a function of ambient iron concentration.
 The simulated Fe:C ratios match the spatial trends in the
 observed  Fe:C ratios. Acclimation of phytoplankton Fe:C ratios
 dampens the biogeochemical response to varying atmospheric deposition of
 soluble iron, compared to a fixed Fe:C ratio. However, varying atmospheric
 soluble iron supply still has first-order impacts on global carbon and
 nitrogen fluxes, and on nutrient limitation spatial patterns. Our results
 suggest pyrogenic Fe is a significant dFe source that rivals mineral dust
 inputs in some regions. Changes in dust flux and iron combustion sources
 (anthropogenic and wildfires) will modify atmospheric Fe inputs in the
 future. Accounting for dynamic phytoplankton iron quotas is critical for
 understanding ocean biogeochemistry and projecting its response to future
 variations in atmospheric deposition.
description: This dataset contains NetCDF output from the CESM v1.98 model,
 ocean only, Biogeochemical Elemental Cycling. The files presented are a 20
 year average for the final 20 years of a 300 year simulation (Years
 281-300). Files are provided for every simulation conducted for the
 results of the paper. This includes the optimal variable stoichiometry
 model and  fixed Fe:C versions with values of 3, 7, 10 for the four iron
 deposition simulations (onlyBC is Pyro Only, noBC is Dust Only, CESM2opt
 is Pyro + Dust, BCx2 is 2xPyro + Dust).  Supplemental
 runs include a limited variable run (with parameterization from Moore et
 al., 2004) and two fixed runs where Fe:C is set at 5 and 6, all three with
 the CESM2opt (Pyro + Dust) forcing. The
 fec_full_diaz.csv file contains the observational data of phytoplankton
 Fe:C including the following fields: num (unique location number),
 UniqueStn (unique station name), CellType3 (aflag (autotrophic
 flagellate), diatom, diaz(diazotroph), or NA), CellTypeNum (1 = diatom, 2
 = aflag, 3 = diaz, NA), FeC (phytoplankton Fe:C ratio, umol/mol),
 lowSe_FeC (lower bound standard error, umol/mol), highSE_FeC (upper bound
 standard error, umol/mol), dFe (dissolve iron, nM), lat_n (latitude, in
 degrees N), lon_E (longitude in degrees E), method (observational method,
 SXRF, GFAAS, NA) and citation for previously published data.
 The observational data has also been read into a .mat file titled
 obs_full.mat via the script
 'create_struct_obs_full_diaz.m'. The .m
 script 'read_FeC_annual_anydeg.m' reads in the CESM NetCDF
 output and saves the data as a .mat file. Minimal processing is done other
 than converting units as noted. The phytoplankton Fe:C for each group is
 also calculated, and extraneous data overwritten for the maximum and
 minimum values. Diazotroph data is also removed where biomass is
 negligible (less than 0.01 mmol/m3/s). The .m script
 'create_surface_FeC_annual_3deg_diaz.m' extracts data from the
 previous .mat file at the observational locations described below for
 surface data only. Position within the CESM grid is determined by
 optimizing least squares. The .m script
 'create_mat_WOA18_NC.m' reads a .nc file of WOA18 data on the
 CESM gx3v7 grid and creates a .mat file with no other
 processing. The .m script 'read_Fe_txt.m'
 reads a .txt file of dissolved iron observations from GEOTRACES and
 supplemental cruises and creates a .mat file,
 'master_Fe_gx3v7.mat'. The .m script
 'HNLC_index.m' calculates the HNLC index for the CESM input
 data, which is defined as the ratio between the model and WOA18 of the
 fraction of the region between 25n and 25S extending from 150E to the
 American coast within the Pacific Ocean where nitrate is less than 0.3nM.
 This script also creates the file 'HNLC_grid.mat' which contains
 a mask where the value of 1 indicates the HNLC region defined above and 0
 elsewhere. The .m script 'hnlc_stats.m'
 calculates the total net primary productivity (NPP) and particulate
 organic carbon export at 100m (POC) within the HNLC region from
 'HNLC_grid.mat'.  The .m script
 'statistics_fe_po4_no3.m' calculates CESM performance statistics
 for dissolved iron, nitrate and phosphate where the iron observations are
 compiled from  GEOTRACES and supplemental cruises, and nitrate and
 phosphate are from World Ocean Atlas 2018. The script also calculates CESM
 performance statistics for the Fe:C data. For all observational
 comparisons, the Spearman's rank correlation coefficient and RMSE are
 calculated. The unprocessed .nc, global read .mat, and
 surface observation .mat files for each CESM run are included, as well as
 the Fe:C observations in .csv and .mat files. WOA18 on the gx3v7 grid is
 included as .nc and .mat files. Dissolved iron observations from GEOTRACES
 and supplemental cruises are provided in .txt and .mat files.
description: These .nc files can be opened via Panoply, Python, or any other
 program that can import NetCDFs. The excel file can be opened using
 Microsoft Excel, Google Sheets or any other program that can import CSVs.
 The .m and .mat files can be viewed and executed with MATLAB, or viewed
 with VSCode or Python using the Scipy or PyTables libraries.