Premium
Validation of a spectral light‐photosynthesis model and use of the model in conjunction with remotely sensed pigment observations
Author(s) -
Berthon JeanFrançois,
Morel André
Publication year - 1992
Publication title -
limnology and oceanography
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.7
H-Index - 197
eISSN - 1939-5590
pISSN - 0024-3590
DOI - 10.4319/lo.1992.37.4.0781
Subject(s) - irradiance , photosynthesis , standard deviation , environmental science , chlorophyll a , atmospheric sciences , chemistry , physics , optics , statistics , mathematics , biochemistry
The predictions of a spectral light‐photosynthesis model are compared with field data. The model calculations are based on pigment (chlorophyll and pheophytin) and temperature profiles and, when available, on irradiance recorded on deck. The agreement between computed and measured production values is satisfying over the full range (10 −4 −1 g C m −3 d −1 or 0.03–10 g C m −2 d −1 ). It is better when 14 C fixation has been measured via the in situ method; a small bias appears when production was measured on deck (simulated in situ method). In both cases however the standard deviation remains similar and computed and measured column production agrees within a factor of ∼3. The same data set is also used to predict column production from pigment concentration within only the top layer, as supposedly remotely sensed. The model is run in combination with pigment profiles, which are “reconstructed” (in magnitude and shape) as a function of the upper layer concentration with statistical relationships previously established. The agreement between computed and measured production (within a factor 3.3 at 1 SD) is encouraging. The model uses mean and constant physiological parameters, which actually vary in the natural environment. Among these parameters, the Chl‐specific absorption by phytoplankton algae and, to a lesser extent, the maximum quantum yield for growth are crucial. Very likely their variations are the main causes of divergence between predicted and field values.