Genomic-to-space measurements reveal large-scale ocean nutrient stress

Global ocean phytoplankton growth and primary production are intimately linked to nutrient fluctuations from seasonal to millennial time scales. Rapid recycling compromises the utility of surface nutrient or phytoplankton stocks for delineating the biogeography of global ocean nutrient stress. Here, field-measured hydrography and ‘omics biomarkers of nutritional status are coupled to a satellite remote sensing metric of cell physiology to mechanistically evaluate monthly to multi-decadal shifts in global phytoplankton nutrient stress. We observe a clear biogeography in nutrient stress aligned with variations in the nutricline depth and distinctly elevated stress in nitrogen- compared to phosphate-limited waters. Regions where cells are switching to rare forms of alternative nutrients are most stressed. Temporal modes of stress are dominated by seasonal changes, but strong signatures of natural climate cycles are also apparent. Surface ocean warming over the last twenty years has led to ..., The symbol Q has been historically used to denote the phytoplankton carbon to chlorophyll ratio (Q=C:Chl), a quantity that registers the combined effects of light and nutrient availability on phytoplankton physiology (8, 39). In this work, we define a new quantity, Q’, which represents the component of C:Chl variability attributable to nutrient stress where Qobs is the satellite-derived C:Chl ratio and Qphoto is the C:Chl values estimated for a given mixed layer light environment in the absence of nutrient limitation.  In other words, Q’ is the satellite observed C:Chl normalized to the photoacclimation component of C:Chl.  Here, Qobs was estimated directly from satellite retrievals of Chl and phytoplankton carbon biomass (C or Cphyto) and Qphoto is estimated following Behrenfeld et al. This simulation integrates effects of diel variability in the underwater light field due to time of day and vertical mixing. This includes phytoplankton exposure to darkness during dawn/du..., The file format is matlab .mat. For other formats, please see
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, , # Genomic-to-space measurements reveal large-scale ocean nutrient stress

Dataset DOI: [10.5061/dryad.f4qrfj71p](https://doi.org/10.5061/dryad.f4qrfj71p)

## Description of the data and file structure

## Files and variables

**Description:** The matlab datafiles contain data for thetaprime, which is the photoacclimated normalized carbon-to-chlorophyll ratio. The data comes from satellite remote sensing (level 3) at 1 x 1 degree spatial resolution. The temporal resolution is 8 days. The dimension of each datafile is LAT x LON x TIME. Land areas are masked out. Missing data is represented by 'NaN'.

### File: thetaPrime_MODIS.mat

'thetaPrime_MODIS.mat' contains the variable 'thetaprime', 'LAT', 'LON', 'yr', and 'yd'.

#### Variables:

**thetaprime_MODIS**

* thetaprime_MODIS represents the ratio of theta_photo divided by theta_obs. Theta_photo is estimated from a photo_acclimation model. Theta_obs is the observed ratio via remote sensing from MODIS Aqua satellite. Thetaprime is unitles...,