the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 07 Jan 2026
Assessing phytoplankton community composition using in-situ multispectral excitation fluorescence and potential for application to BGC-Argo profiling floats
Abstract. Phytoplankton community composition is a key determinant of ocean biogeochemical cycles, yet its observation from 20 autonomous platforms remains challenging. In this study, we assessed the potential of in situ multispectral excitation fluorescence (MXF) to discriminate phytoplankton assemblages in the Northwestern Mediterranean Sea, with a view toward applications on Biogeochemical-Argo (BGC-Argo) profiling floats. 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 along the seasonal cycle. 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 added spectral information of 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- and chlorophyll b–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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Status: final response (author comments only)
- RC1: 'Comment on egusphere-2025-6418', Anonymous Referee #1, 12 Feb 2026
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RC2: 'Comment on egusphere-2025-6418', Anonymous Referee #2, 12 Feb 2026
I strongly support the development of new optical approaches for resolving phytoplankton community structure, particularly the combined use of hyperspectral radiometry and multispectral excitation fluorescence (MXF). The present manuscript represents an important step toward evaluating MXF-based methods for this purpose.
However, I was expecting a more detailed and structured discussion regarding the feasibility and necessity of deploying instruments such as the ECO 3X1M on BGC-Argo platforms, or more generally, a clearer framework outlining what level of phytoplankton discrimination can realistically be achieved with different sensor configurations.
At present, the manuscript demonstrates that MXF adds information under certain configurations, but it does not sufficiently articulate (i) under what ecological or observational conditions MXF becomes essential rather than complementary, and (ii) what minimum or optimal sensor characteristics are required to achieve specific biological resolution targets. Without such a framework, it remains difficult to assess the broader implications for future BGC-Argo instrumentation strategies.
It is encouraged that the authors expand the discussion beyond the specific instrument tested and provide a more general conceptual and operational framework linking sensor capability to achievable phytoplankton classification performance. This would substantially strengthen the manuscript’s impact on the community.
L60: There are more works using bbp for inferring phytoplankton community structure, for example: https://doi.org/10.1029/2021JC018195. Please update the brief review.
L83: According to https://vocab.nerc.ac.uk/collection/R27/current/, the ECO_FLBBFL and ECO_FLBBFL_AP2 models use excitation wavelengths at 470 nm and 435 nm. The manuscript, however, refers to 440 nm. Please clarify this discrepancy and explain whether the 5 nm difference has any practical or spectral implications for the analyses presented.
L86: Vidussi et al. 2001 is about the Eastern Mediterranean
L105: It would be better to know whether the phytoplankton communities considered in this section are representative of the NW Mediterranean. What criteria were used to justify the selection?
Table 1: Caption “HPLC” better follow with the full name.
L131: How was the ECO 3X1M calibrated before the measurements? In addition, laboratory temperature, etc., can influence optical sensors. Were these factors monitored and accounted for during the experiments?
Citation: https://doi.org/10.5194/egusphere-2025-6418-RC2
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Yes. This subject is well fit in the scope of BG.
The concept is not novel; there are several multi-excitation fluorometers, and several studies have already been conducted, while the authors ignored them. The idea is a little bit novel; their approach (machine learning) is new compared to the previous studies. However, their MXF shows lower resolution compared to the other MXF.
They show the conclusion and it was supported by the data; however, the conclusion did not support the aims of this study: the aims of this study is to clarify the phytoplankton composition by using the MFX, but the authors show that they can divide the community into four clusters, which does not show the phytoplankton community structure or show the ecological and biogeochemical roles.
Yes. This is correct and good, but some additional descriptions are required.
Partly. Their results sometimes support their interpretations and conclusions, but in some cases, the authors' conclusions are not supported.
Yes. It’s good.
No. The authors need to cite more papers.
No. As I commented, they did not reveal the phytoplankton community structure. They were divided into four clusters, but I’m not sure that they are representative of some environments.
Yes. But it will be necessary to revise.
Partly.
Yes
Yes.
No.
No.
Yes.
Petit et al. “Assessing phytoplankton community composition using in-situ multispectral excitation fluorescence and potential for application to BGC-Argo profiling floats” investigated the potential of the multispectral excitation fluorometer (MXF) to assess the phytoplankton community structure. The MXF approach is mandatory for the BGC-Argo observations, and thus, this work is important. However, there were several disadvantages in this study: one was the quality of the MXF, and the other was the approach (clustering analysis). First, they used the three excitation channels MXF; however, there are two major MXFs which have five excitation channel (FluoroProbe) and nine channels (MultiExciter). Both of them were started to apply the ocean observations (Garrido et al, 2019 https://doi.org/10.1007/s10661-019-7349-8; Wang et al. 2016 https://doi.org/10.1364/OE.24.023635; Kodama et al. 2022 https://doi.org/10.1371/journal.pone.0257258; Xu et al. 2022 https://doi.org/10.3389/fmars.2021.756180; Zhang et al. 2025 https://doi.org/10.1016/j.algal.2025.104155; Taniuchi et al. 2026 https://doi.org/10.6090/jarq.24S30). Thus, I cannot understand why the authors evaluate the ability of the ECO 3M1M. The small number of channels could identify the community structure so roughly, and thus I strongly believe that FluoroProbe and MultiExciter had an advantage for the aims of the authors’ study. Second, the authors did the clustering analysis. I agree that this analysis is useful if the clusters are representative of the ocean environments. For example, when clusters A, B, and C are grouped into diatom blooms, dinoflagellate blooms, and Prochlorococcus-rich water, this analysis is very useful; however, the authors’ results are not. Thus, this manuscript's contribution to the scientific community is very limited in its current form, and if the authors promote ECO 3M1M for BGC-Argo observations based on this manuscript, I cannot find any advantage to ocean science.
Hence, my recommendation for this manuscript has two options: 1) if the authors want to keep their conclusion (it looks like ECO 3M1M is useful for BGC-Argo observations), the authors should show the advantage of this fluorometer compared to the others, except for the identification of phytoplankton community composition. 2) If the authors will fairly describe the caveats of ECO 3M1M compared to the other MXF (FluoroProbe and MultiExciter), this manuscript could be worthy for publication. The manuscript should be fully revised for them.
Title: The clustering analysis could not show the phytoplankton community composition.
L31: Are there any evidences that 532 nm is useful for chlorophyll b? Also, for phycoerythrin, the signal from this wavelength is obscure (Palenik, 2001
https://doi.org/10.1128/AEM.67.2.991-994.2001)
L70: The authors must refer to the more recent papers.
Table1: What is the order of main pigments?
L184: What is “pure seawater”?
L191: Please check the citation style.
L201: The description of HPLC was too short. Please provide more details. Also, I’m not sure that the authors used the same HPLC machine as that of 15 years ago.
L215: The authors did not assess the reliability of the results in the present study. Also, the actual information on the size classes could not be provided from the pigments. This sentence is plastic.
L280: I could not understand “the model has a learning rate of 0.05,l 400 estimators and a maximum depth of 8.” This description is too brief.
L321: Did Six et al. (2007) and Grébert et al. (2018) describe that 532 nm is most excited at 532 nm? I could not find such descriptions in them.
L326: If so, phytoplankton that has chlorophyll b could not divide in this method.
L328: The authors only mentioned chlorophyll, but they should consider the carotenoids.
Figure 1: This shows that MXF did not show the size. Also, I cannot find the results of Chaetoceros. Why?
Figure 2: The cluster 1 and 4 looks very similar. Johnsen et al. (1997, https://doi.org/10.4319/lo.1997.42.5_part_2.1166) showed that peridinin exhibited high fluorescence with excitation wavelengths between 480 nm and 510 nm. However, ECO 3M1M does not cover this range. So, I considered that ECO 3M1M is unable to detect the presence of peridinin (dinoflagellates).
L395: Figure 2 did not show that their MXF distinguishes diatoms and dinoflagellates. This is not based on objective data.
Figure5: Please revise the quality for the manuscript level.
L487: I could not understand why the authors describe the model tuning after presenting the results from field observations.
L551: Did Morel and Saito report that 532 nm excitation is expected to significantly improve classification performance?