Improved accuracy and spatial resolution for bio-logging-derived chlorophyll a fluorescence measurements in the Southern Ocean

The ocean’s meso- and submeso-scales (1-100 km, days to weeks) host features like filaments and eddies that have a key structuring effect on phytoplankton distribution, but that due to their ephemeral nature, are challenging to observe. This problem is exacerbated in regions with heavy cloud coverage and/or difficult access like the Southern Ocean, where observations of phytoplankton distribution by satellite are sparse, manned campaigns costly, and automated devices limited by power consumption. Here, we address this issue by considering high-resolution in-situ data from 18 bio-logging devices deployed on southern elephant seals (Mirounga leonina) in the Kerguelen Islands between 2018 and 2020. These devices have submesoscale-resolving capabilities of light profiles due to the high spatio-temporal frequency of the animals’ dives (on average 1.1 +-0.6 km between consecutive dives, up to 60 dives per day), but observations of fluorescence are much coarser due to power constraints. Furthermore, the chlorophyll a concentrations derived from the (uncalibrated) bio-logging devices’ fluorescence sensors lack a common benchmark to properly qualify the data and allow comparisons of observations. By proposing a method based on functional data analysis, we show that a reliable predictor of chlorophyll a concentration can be constructed from light profiles (14 686 in our study) and matchups with satellite ocean-color data, thus enabling effective (1) homogenization then calibration of the bio-logging devices’ fluorescence data and (2) filling of the spatial gaps in coarse-grained fluorescence sampling. The developed method improves the spatial resolution of the chlorophyll a field description from ~30 km to ~12 km. These results open the way to empirical study of the coupling between physical forcing and biological response at submesoscale in the Southern Ocean, especially useful in the context of upcoming high-resolution ocean-circulation satellite missions like SWOT.


Biological oceanography


Chla fluorescence, Southern Ocean, Sensor calibration, Submesoscale, Southern elephant seal, bio-logging tag


-35N, -75S, 20E, 150W


The Satellite Relayed Data Logger (SRDL, see Boehme et al., 2009) developed by the Sea Mammal Research Unit (SMRU, UK) is a bio-logging device designed for marine mammals like the SES. SRDLs commonly include a Conductivity, Temperature and Depth (CTD) sensor head. Optionally, SRDLs may include a light sensor, and a fluorometer to measure Chla fluorescence. SRDLs can also act as high-frequency sampling loggers which need to be recovered when the SESs are back ashore in order to obtain access to the data.

The light sensor embedded in the SRDL is a Hamamatsu S1227-1010BR photodiode (340-1000 nm spectral response range, 100 mm2 effective photosensitive area). The photodiode points to the right side of the animal with a 90º angle compared to the frontward axis of the animal. The SRDL light sensor provides an estimate of the diffused light level in the animal’s environment (L, expressed in μmol quanta.m-2.s-1).

SRDLs also include a fluorometer (Valeport Hyperion 470 nm/696 nm emission/reception) that sample Fluo at 0.5 Hz. However, to optimize tags’s energy consumption, their Fluo sampling resolution was reduced so that the onset of the fluorescence sensor was triggered only every ~15 dives and Fluo was only sampled during the ascending phase of the dives from Zinf = 200 m to the surface. Accordingly, the SRDLs performed around four fluorescence profiles every 24 hours.




Data processing demo for the prediction of [Chla] from light profiles at (sub)mesoscale with Southern Elephant Seal bio-logging data (MEOP data,
318 Mo.tar.xz
How to cite
Le Ster LOÏC, Claustre HERVÉ, D'Ovidio FRANCESCO, Nerini DAVID, Picard BAPTISTE, Guinet CHRISTOPHE (2023). Improved accuracy and spatial resolution for bio-logging-derived chlorophyll a fluorescence measurements in the Southern Ocean. SEANOE.
In addition to properly cite this dataset, it would be appreciated that the following work(s) be cited too, when using this dataset in a publication :
Le Ster Loïc, Claustre Hervé, d’Ovidio Francesco, Nerini David, Picard Baptiste, Guinet Christophe (2023). Improved accuracy and spatial resolution for bio-logging-derived chlorophyll a fluorescence measurements in the Southern Ocean. Frontiers in Marine Science, 10.

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