DOI: 10.5061/dryad.v41ns1s4v
title: Data for: Observed declines in upper ocean phosphate-to-nitrate availability

description: Climate warming is increasing ocean stratification, which in turn should
 decrease the flux of nutrients to the upper ocean. This may slow
 marine primary productivity, causing cascading effects throughout
 food webs. However, observing changes in nutrient concentrations at
 the ocean surface is challenging because they are often below
 detection limits. The nutricline depth, where nutrient
 concentrations reach well-detected levels, is related to productivity and
 indicates upper ocean nutrient availability. Here, we quantified
 nutricline depths from a global database of observed vertical
 nitrate and phosphate profiles (1972 - 2022) to
 assess contemporary trends in global nutrient availability. We
 found strong evidence that the P-nutricline (phosphacline) is mostly
 deepening, especially throughout the southern hemisphere, but the
 N-nutricline (nitracline) remains mostly stable. Earth System Model
 simulations support the hypothesis that reduced iron stress and
 increased nitrogen fixation buffer the nitracline, but not
 phosphacline, against increasing stratification. These contemporary trends
 are expected to continue in the coming decades, leading to
 increasing phosphorus but not nitrogen stress for marine
 phytoplankton, with important ramifications for ocean biogeochemistry and
 food web dynamics.
description: # Data for: Observed declines in upper ocean phosphate-to-nitrate
 availability
 [https://doi.org/10.5061/dryad.v41ns1s4v](https://doi.org/10.5061/dryad.v41ns1s4v) Essential files and code for the analyses described in "Observed declines in upper ocean phosphate-to-nitrate availability" by Gerace et al. ## Description of the data and file structure **Dataset_S1:** * Spreadsheets (the data needs to remain in these spreadsheets for the data analysis scripts to work) * "GOSHIP (no3=3)" is the nutricline depths from GO-SHIP (*1*)  for each unique site and year using thresholds of 3 µmol/kg and 3/16 µmol/kg for nitrate and phosphate, respectively. * "GOSHIP (no3=1)" is the nutricline depths from GO-SHIP for each unique site and year using thresholds of 1 µmol/kg and 1/16 µmol/kg for nitrate and phosphate, respectively. * "GOSHIP (no3=5)" is the nutricline depths from GO-SHIP for each unique site and year using thresholds of 5 µmol/kg and 5/16 µmol/kg for nitrate and phosphate, respectively. * "GOSHIP Density (no3=3)" is the nutricline densities from GO-SHIP for each unique site and year using thresholds of 3 µmol/kg and 3/16 µmol/kg for nitrate and phosphate, respectively. * "GOSHIP (no3=3)months, no filter" is the nutricline depths from GO-SHIP for each unique site and month using thresholds of 3 µmol/kg and 3/16 µmol/kg for nitrate and phosphate, respectively, without any spatial restrictions applied. * "GLODAP (no3=3)" is the nutricline depths from GLODAPv2.2022 (*2*) for each unique site and year using thresholds of 3 µmol/kg and 3/16 µmol/kg for nitrate and phosphate, respectively. * "WOD (no3=3)" is the nutricline depths from the World Ocean Database (*3*) for each unique site and year using thresholds of 3 µmol/kg and 3/16 µmol/kg for nitrate and phosphate, respectively. * "GOSHIP Means (no3=3)" is the nutricline depths from GO-SHIP averaged over 1972-2022 for each unique site using thresholds of 3 µmol/kg and 3/16 µmol/kg for nitrate and phosphate, respectively. * "GLODAP Means (no3=3)" is the nutricline depths from GLODAPv2.2022 averaged over 1972-2022 for each unique site using thresholds of 3 µmol/kg and 3/16 µmol/kg for nitrate and phosphate, respectively. * "WOD Means (no3=3)" is the nutricline depths from the World Ocean Database averaged over 1972-2022 for each unique site using thresholds of 3 µmol/kg and 3/16 µmol/kg for nitrate and phosphate, respectively. * "BATS (no3=3)" is the nutricline depths from the Bermuda Atlantic Time-series Study ([BATS Data | BIOS](https://bios.asu.edu/bats/bats-data)) from 1998-2022 using thresholds of 3 µmol/kg and 3/16 µmol/kg for nitrate and phosphate, respectively. * "HOT (no3=3)" is the nutricline depths from the Hawaii Ocean Time-series ([HOT-DOGS: the Hawaii Ocean Time-series Data Organization & Graphical System](https://hahana.soest.hawaii.edu/hot/hot-dogs/interface.html)) from 1998-2022 using thresholds of 3 µmol/kg and 3/16 µmol/kg for nitrate and phosphate, respectively. * Variables * "year" is the year the nutricline depth was sampled (year) * "lat_degN" is the latitude coordinate the nutricline depth was sampled (degrees North) * "lon_degE" is the longitude coordinate the nutricilne depth was sampled (degrees East) * "Zno3_m" is the nitracline depth (meters) * "Zpo4_m" is the phosphacline depth (meters) * "Zno3_Zpo4_m" is the difference between the nitracline and phosphacline depths (meters) * "Zno3_kgm-3" is the nitracline density (kilograms divided by meters cubed) * "Zpo4_kgm-3" is the phosphacline density (kilograms divided by meters cubed) Empty and non-applicable entries are labeled as "#NUM!" in this file. **Data analysis scripts and related files:** The first part of each script name describes the dataset or models that the script analyzes. The later part of the script name describes what analysis was performed. Other scripts that do not follow this format are universal functions. A brief description of the script's purpose is commented on the top lines of each script. Here is each script with the respective description of its purpose: Models analyses: \- CESM2_Kwon_figureS8: Plot the mean nutricline depths and trends from flexible vs. fixed phosphate uptake in CESM2 (Kwon et al., 2022) (*4*). \- CESM2_Kwon_fixedCP_ZNO3_ZPO4: Find the ZNO3 and ZPO4 in the fixed phosphate uptake experiment in CESM2 by Kwon et al. (2022). \- CESM2_Kwon_flexibleCP_ZNO3_ZPO4: Find the ZNO3 and ZPO4 in the flexible phosphate uptake experiment in CESM2 by Kwon et al. (2022). \- CESM2_MARBLv2_figure4: Plot iron deposition experiment results from CESM2 MARBL 8P4Z (Yu et al. 2024) (*5*), index the nutricline trends based on primary nutrient limitation of different phytoplankton (Figure 4) \- CESM2_MARBLv2_Nfix_global_mean: Ocean nitrogen fixation in iron deposition experiments in CESM2 MARBL 8P4Z (Yu et al. 2024) iron deposition experiments \- CESM2_MARBLv2_nutlim: Index each gridpoint of the global ocean with the primary nutrient limitation of different phytoplankton from iron deposition experiments in CESM2 MARBL 8P4Z (Yu et al. 2024) \- CESM2_MARBLv2_ZNO3_ZPO4: Find nutricline depths from iron deposition experiments in the CESM2 MARBL 8P4Z nc files. \- CMIP6_dbar_to_m_convert: Nutricline data in CMIP6 was originally in dbar ("Data"), so needs to convert to m ("Data_m") \- CMIP6_figure3: Plots the nutricline depths and N fixation rates of all available CMIP6 models under historical, SSP245, and SSP585 emission scenarios (Figure 3) \- CMIP6_historical_Nfix_annual: Find annual ocean N fixation rates for each CMIP6 model in the historical scenario \- CMIP6_historical_ZNO3: Find ZNO3 and TNO3 in CMIP6 models under the historical emissions scenario \- CMIP6_historical_ZPO4: Find ZPO4 and TPO4 in CMIP6 models under the historical emissions scenario \- CMIP6_Nfix_global_mean: Find the global mean rate of ocean N fixation across CMIP6 models \- CMIP6_ssp245_Nfix_annual: Find annual ocean N fixation rates for each CMIP6 model in the ssp245 scenario \- CMIP6_ssp245_ZNO3: Find ZNO3 and TNO3 in CMIP6 models under the ssp245 emissions scenario \- CMIP6_ssp245_ZPO4: Find ZPO4 and TPO4 in CMIP6 models under the ssp245 emissions scenario \- CMIP6_ssp585_Nfix_annual: Find annual ocean N fixation rates for each CMIP6 model in the ssp585 scenario \- CMIP6_ssp585_ZNO3: Find ZNO3 and TNO3 in CMIP6 models under the ssp585 emissions scenario \- CMIP6_ssp585_ZPO4: Find ZPO4 and TPO4 in CMIP6 models under the ssp585 emissions scenario Cruise observations and climatology analyses: \- GLODAP_climatology_residuals_figureS7: Compare nutrient concentrations from the interpolated GLODAPv2.2016 (*6*) climatology with concentrations from observations to test if there is a bias in measurement accuracy over time. \- GOSHIP_nutrient_limitation_figureS1: Compare nutricline depths with nutrient limitation as determined by bioassay experiments (Browning & Moore, 2023) or Prochlorococcus metagenomics (Ustick et al., 2021) (*7*,*8*). \- GLODAP_ZNO3_ZPO4: See how GLODAPv2.2022 cruise data compares with GOSHIP cruise data. First find ZNO3_glodap, then find ZPO4_glodap (starts line 167) \- GOSHIP_ZNO3: Find Z_NO3 and T_NO3 values in GOSHIP cruises from 1972 - 2022. Note that the GOSHIP cruise files are nc format. Concentration thresholds, latitude bounds, and depth bounds are adjustable. \- GOSHIP_ZNO3_Density: Find Z_NO3 and T_NO3 denisty values in GOSHIP cruises from 1972 - 2022. Note that the GOSHIP cruise files are nc format. Concentration thresholds, latitude bounds, and depth bounds are adjustable. \- GOSHIP_ZPO4: Find Z_PO4 and T_PO4 values in GOSHIP cruises from 1972 - 2022. Note that the GOSHIP cruise files are nc format. Concentration thresholds, latitude bounds, and depth bounds are adjustable. \- GOSHIP_ZPO4_Density: Find Z_PO4 and T_PO4 density values in GOSHIP cruises from 1972 - 2022. Note that the GOSHIP cruise files are nc format. Concentration thresholds, latitude bounds, and depth bounds are adjustable. \- WOA18_climatology_ZNO3_ZPO4: Find ZNO3 and ZPO4 in the World Ocean Atlas 2018 (*9*) climatology \- WOA18_residual_regressions_figureS3: Global regressions of the residual differences between GOSHIP observations and the monthly nutricline values in the WOA18 climatology. \- WOA18_variance_analysis_figureS4: Determining temporal variability in locational nutricline trends and how much this variability could influence the median trends. \- WOD_ZNO3: Compare ZNO3 and TNO3 from the World Ocean Database with GOSHIP cruise files \- WOD_ZPO4: Compare ZPO4 and TPO4 from the World Ocean Database with GOSHIP cruise files Necessary functions: \- pre2depth: This function computes the water depth from pressure and latitude values using a UNESCO formula. (software by Gabriel Ruiz-Martinez (2024). Conversion from water pressure to depth ([https://www.mathworks.com/matlabcentral/fileexchange/105090-conversion-from-water-pressure-to-depth](https://www.mathworks.com/matlabcentral/fileexchange/105090-conversion-from-water-pressure-to-depth)), MATLAB Central File Exchange.) \- random_populations_10k: Scramble the years of nutricline depths in a cruise dataset to construct 10k random populations \- seawater_density: This function computes seawater density from pressure, temperature, and salinity using a UNESCO formula. (software by Gabriel Ruiz-Martinez (2024). Seawater density from salinity, temperature, and pressure ([https://www.mathworks.com/matlabcentral/fileexchange/85900-seawater-density-from-salinity-temperature-and-pressure](https://www.mathworks.com/matlabcentral/fileexchange/85900-seawater-density-from-salinity-temperature-and-pressure)), MATLAB Central File Exchange.) File lists: -GOSHIP_expocodes.csv: list of unique cruise expocodes from GOSHIP cruise data sets -CMIP6_files_list.txt: list of all CMIP6 model files needed from ESGF ([ESGF MetaGrid (llnl.gov))](https://aims2.llnl.gov/search/cmip6) \## Guidelines ## These scripts require MATLAB R2020b or later to run. Most of these scripts need access to certain nc files, xlsx spreadsheets, or mat data (i.e., Data files), be sure to change the file path in the scripts accordingly. **References:** 1. CCHDO Hydrographic Data Office. “CCHDO Hydrographic Data Archive, Version 2023-12-01” in *CCHDO Hydrographic Data Archive*. (UC San Diego Library Digital Collections, 2023), [10.6075/J0CCHKOT](https://doi.org/10.6075/J0CCHKOT "ext-link"). 2. R. M. Key *et al.*, Global Ocean Data Analysis Project, Version 2 (GLODAPv2), ORNL/CDIAC-162, ND-P093. *Carbon Dioxide Information Analysis Center (CDIAC)* (2015), [10.3334/CDIAC/OTG.NDP093_GLODAPV2](https://doi.org/10.3334/CDIAC/OTG.NDP093_GLODAPV2). 3. T. P. Boyer *et al.*, “World Ocean Database 2018” in *NOAA Atlas NESDIS 87*, A.V. Mishonov, Technical Ed. (2018). 4. E. Y. Kwon *et al.*, Nutrient uptake plasticity in phytoplankton sustains future ocean net primary production. *Sci. Adv.* 8, eadd2475 (2022). 5. J. Yu *et al.*, CESM2.2-8P4Z data supporting Yu et al. (2024): Simulating ecosystem dynamics and marine biogeochemical cycles with multiple plankton functional types. *Zenodo* (2024), [10.5281/zenodo.13355401](https://doi.org/10.5281/zenodo.13355401). 6. S. K. Lauvset *et al.*, A new global interior ocean mapped climatology: the 1° × 1° GLODAP version 2. *Earth Syst. Sci. Data* 8, 325–340 (2016). 7. T. J. Browning, C. M. Moore, Global analysis of ocean phytoplankton nutrient limitation reveals high prevalence of co-limitation. *Nat. Commun.* 14, 5014 (2023). 8. L. J. Ustick *et al.*, Metagenomic analysis reveals global-scale patterns of ocean nutrient limitation. *Science* 372, 287–291 (2021). 9. H. E. Garcia *et al.*, *World Ocean Atlas 2018* (NOAA National Centers for Environmental Information, 2019).