Articles | Volume 16, issue 13
https://doi.org/10.5194/bg-16-2617-2019
https://doi.org/10.5194/bg-16-2617-2019
Research article
 | 
05 Jul 2019
Research article |  | 05 Jul 2019

Global trends in marine nitrate N isotopes from observations and a neural network-based climatology

Patrick A. Rafter, Aaron Bagnell, Dario Marconi, and Timothy DeVries

Viewed

Total article views: 4,496 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
3,134 1,285 77 4,496 94 75
  • HTML: 3,134
  • PDF: 1,285
  • XML: 77
  • Total: 4,496
  • BibTeX: 94
  • EndNote: 75
Views and downloads (calculated since 11 Jan 2019)
Cumulative views and downloads (calculated since 11 Jan 2019)

Viewed (geographical distribution)

Total article views: 4,496 (including HTML, PDF, and XML) Thereof 4,041 with geography defined and 455 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 21 Feb 2025
Download
Short summary
The N isotopic composition of nitrate (nitrate δ15N) is a useful tracer of ocean N cycling and many other ocean processes. Here, we use a global compilation of marine nitrate δ15N as an input, training, and validating dataset for an artificial neural network (a.k.a., machine learning) and examine basin-scale trends in marine nitrate δ15N from the surface to the seafloor.
Share
Altmetrics
Final-revised paper
Preprint