Evaluating a multispectral miniaturised fluorometer with three excitation channels for predicting phytoplankton community structure indices from BGC-Argo float observations
Abstract
Phytoplankton community composition is a key determinant of ocean biogeochemical cycles, yet its observation from autonomous platforms remains challenging. In this study, we assessed the potential of in situ multispectral excitation fluorescence (MXF) to predict phytoplankton community structure indices in the Northwestern Mediterranean Sea. With a view toward applications on Biogeochemical-Argo (BGC-Argo) profiling floats, we evaluated a miniaturised, three-excitation-channel fluorometer. Laboratory measurements on ten phytoplankton strains confirmed that MXF ratios at 440, 470, and 532 nm provide taxon-specific signatures, especially for picocyanobacteria and green algae. Field observations of phytoplankton pigments were clustered into four ecologically distinct phytoplankton communities across the seasonal cycle, which defined the targeted phytoplankton community structure indices. A machine learning model was then trained to classify these clusters using MXF and additional bio-optical indices. Results show that existing BGC-Argo configurations (single-wavelength fluorescence, particulate backscattering, and beam attenuation coefficients) reliably distinguish broad community structures, such as pico- versus microphytoplankton dominance, but resolving finer pigment-based differences requires the additional spectral information provided by MXF. The different excitation channels contributed unequally: 440 and 470 nm provided robust pigment sensitivity across communities, while 532 nm was particularly informative for detecting phycoerythrin-rich taxa. Overall, combining MXF with bio-optical proxies improved classification performance by integrating pigment-specific and size-structure information, demonstrating the potential of MXF to enhance autonomous monitoring of phytoplankton community dynamics and their role in ocean biogeochemical cycles.
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BibTeX
@article{petit2026evaluating,
title = {{Evaluating a multispectral miniaturised fluorometer with three excitation channels for predicting phytoplankton community structure indices from BGC-Argo float observations}},
author = {Flavien Petit and Julia Uitz and Louison Dufour and Collin Roesler and Frédéric Partensky and Laurence Garczarek and Priscillia Gourvil and Céline Dimier and Melek Golbol and Vincenzo Vellucci and David Antoine and Christophe Penkerc'H and Vincent Taillandier and Hervé Claustre},
journal = {Biogeosciences},
year = {2026},
month = jul,
doi = {10.5194/bg-23-4561-2026},
url = {https://hal.science/hal-05780172v1},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Evaluating a multispectral miniaturised fluorometer with three excitation channels for predicting phytoplankton community structure indices from BGC-Argo float observations
AU - Flavien Petit
AU - Julia Uitz
AU - Louison Dufour
AU - Collin Roesler
AU - Frédéric Partensky
AU - Laurence Garczarek
AU - Priscillia Gourvil
AU - Céline Dimier
AU - Melek Golbol
AU - Vincenzo Vellucci
AU - David Antoine
AU - Christophe Penkerc'H
AU - Vincent Taillandier
AU - Hervé Claustre
PY - 2026
DA - 2026/07/06
JO - Biogeosciences
DO - 10.5194/bg-23-4561-2026
UR - https://hal.science/hal-05780172v1
AB - Phytoplankton community composition is a key determinant of ocean biogeochemical cycles, yet its observation from autonomous platforms remains challenging. In this study, we assessed the potential of in situ multispectral excitation fluorescence (MXF) to predict phytoplankton community structure indices in the Northwestern Mediterranean Sea. With a view toward applications on Biogeochemical-Argo (BGC-Argo) profiling floats, we evaluated a miniaturised, three-excitation-channel fluorometer. Laboratory measurements on ten phytoplankton strains confirmed that MXF ratios at 440, 470, and 532 nm provide taxon-specific signatures, especially for picocyanobacteria and green algae. Field observations of phytoplankton pigments were clustered into four ecologically distinct phytoplankton communities across the seasonal cycle, which defined the targeted phytoplankton community structure indices. A machine learning model was then trained to classify these clusters using MXF and additional bio-optical indices. Results show that existing BGC-Argo configurations (single-wavelength fluorescence, particulate backscattering, and beam attenuation coefficients) reliably distinguish broad community structures, such as pico- versus microphytoplankton dominance, but resolving finer pigment-based differences requires the additional spectral information provided by MXF. The different excitation channels contributed unequally: 440 and 470 nm provided robust pigment sensitivity across communities, while 532 nm was particularly informative for detecting phycoerythrin-rich taxa. Overall, combining MXF with bio-optical proxies improved classification performance by integrating pigment-specific and size-structure information, demonstrating the potential of MXF to enhance autonomous monitoring of phytoplankton community dynamics and their role in ocean biogeochemical cycles.
SN - 1726-4170
SN - 1726-4189
ER -