Biogeochemistry Technical

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This page is the technical anchor point for the Dissolved Organic Matter BGC project. The corresponding general interest page is Biogeochemistry.


Arctic GRO data (6 rivers, 5 times over the year 2009, plus one extra sample) provides 31 Samples in one Dataset. These are analyzed using:

  • Metadata: The physical or 'simple' observables for a given sample (pH for example)
    • This includes labor-intensive analysis e.g. to produce quantitative estimates of important molecular classes such as lignin
  • Fourier Transfrom Infrared spectrometry, abbreviated FTIR (pending)
  • Absorbance, abbreviated ABS
  • Proton Nuclear Magnetic Resonance abbreviated NMR
  • Negative-mode Fourier Transfrom Ion Cyclotron Resonance Mass Spectrometry, abbrevi FTICR-MS or MS
  • Fluorometry, producing Excitation Emission Matrices, therefore abbreviated EEM
  • Principle Component Analysis of the above, abbreviated PCA
    • kernel-PCA also used to accommodate non-linear nature of this data
  • 2D PCA analog "PARAFAC" applied to EEMs
  • Covariance: Auto-covariance of one data type with itself, or hetero-covariance of one data type with another; see Super Spectrum below
  • Clustering: Machine learning algorithms applied to data types
  • Co-Clustering: Machine learnign algorithms applied to pairs of data types
    • Initially variants on spectral co-clustering, which produce conservative sets from two source sets