Next Article in Journal
Research on the Construction of a Digital Twin System for the Long-Term Service Monitoring of Port Terminals
Previous Article in Journal
Size-Dependent Microplastic Fragmentation Model
 
 
Article
Peer-Review Record

A Parallelized Climatological Drifter-Based Model of Sargassum Biomass Dynamics in the Tropical Atlantic

J. Mar. Sci. Eng. 2024, 12(7), 1214; https://doi.org/10.3390/jmse12071214
by Karl Payne *, Khalil Greene and Hazel A. Oxenford
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Reviewer 3: Anonymous
J. Mar. Sci. Eng. 2024, 12(7), 1214; https://doi.org/10.3390/jmse12071214
Submission received: 18 May 2024 / Revised: 26 June 2024 / Accepted: 27 June 2024 / Published: 19 July 2024
(This article belongs to the Section Marine Biology)

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The study introduces a parallelized climatological drifter-based model to simulate sargassum biomass dynamics. This is a significant advancement in modeling due to its computational efficiency and ability to handle large datasets (Lines 178-180). The model incorporates three dominant sargassum morphotypes (S. fluitans III, S. natans I, S. natans VIII), which enhances the biological realism of the simulations (Lines 103-106). Utilizing Monte Carlo simulations to account for parametric uncertainty is a robust method for improving the reliability of biomass accumulation predictions (Lines 116-117). The model accounts for spatial variability in sea surface temperature (SST), which is critical for accurate growth rate estimations and enhances ecological realism (Lines 107-108, 162-165). It also successfully replicates the seasonal distribution of sargassum for the simulated period, capturing the increase and subsequent decline in biomass (Lines 16-18). Parallel computing using the Python multiprocessing module significantly reduces execution time, enabling rapid hypothesis testing and operational forecasting (Lines 178-180, 186-190). However, some drawbacks also have to be mentioned. While the study provides mortality and sinking rates, these parameters might oversimplify the complex life processes of sargassum under varying environmental conditions. What is more, the validation of the model is limited to a short period (May 2017 to August 2017), which might not capture long-term trends or variability in sargassum dynamics. The study area is confined to the Central Atlantic and the Eastern Caribbean, potentially limiting the model's applicability to other regions experiencing sargassum influxes (Lines 124-127, 128-130). The model relies heavily on external data sources for satellite images, current, wind, and SST data, which might introduce uncertainties or biases depending on data quality and resolution (Lines 144-145, 155-157, 161-163).

In conclusion, this study presents a novel and efficient approach to modeling sargassum biomass dynamics, addressing several complexities of the ecosystem. However, the limitations related to data quality, model validation period, and resource requirements indicate areas for further research and development. I understand the continuous lack of data in modeling, therefore I suggest accepting the manuscript with minor revisions.

Author Response

Reviewer comment #1: The study introduces a parallelized climatological drifter-based model to simulate sargassum biomass dynamics. This is a significant advancement in modeling due to its computational efficiency and ability to handle large datasets (Lines 178-180). The model incorporates three dominant sargassum morphotypes (S. fluitans III, S.natans I, S. natans VIII), which enhances the biological realism of the simulations (Lines 103-106). Utilizing Monte Carlo simulations to account for parametric uncertainty is a robust method for improving the reliability of biomass accumulation predictions (Lines 116-117). The model accounts for spatial variability in sea surface temperature (SST), which is critical for accurate growth rate estimations and enhances ecological realism (Lines 107-108, 162-165). It also successfully replicates the seasonal distribution of sargassum for the simulated period, capturing the increase and subsequent decline in biomass (Lines 16-18). Parallel computing using the Python multiprocessing module significantly reduces execution time, 
enabling rapid hypothesis testing and operational forecasting (Lines 178-180, 186-190). 

Authors’ response #1: The authors would like to thank to reviewer for their comments and accurate capturing the main contributions of this paper.

Reviewer comment #2: However, some drawbacks also have to be mentioned. While the study provides mortality and sinking rates, these parameters might oversimplify the complex life processes of sargassum under varying environmental conditions. What is more, the validation of the model is limited to a short period (May 2017 to August 2017), which might not capture long-term trends or variability in sargassum dynamics. The study area is confined 
to the Central Atlantic and the Eastern Caribbean, potentially limiting the model's applicability to other regions experiencing sargassum influxes (Lines 124-127, 128-130). The model relies heavily on external data sources for satellite images, current, wind, and SST data, which might introduce uncertainties or biases depending on data quality and resolution (Lines 144-145, 155-157, 161-163).

Authors’ response #2: Regarding the mortality and sinking rates the authors acknowledge this as a limitation and are transparent in the paper by highlighting the lack of data to support parameterization of these rates. We have assumed the same for each morphotype; however, the modeling framework is flexible enough to account for variations in the parameters once data become available.
In terms of validation of the model limited to a short period (May 2017 to August 2017), one of the issues is that the forecast skill degrades beyond three months. Nevertheless, what we have done is to investigate not only a warm period (May 2017 to August 2017), but also a more temperate period (November 2021 – February 2022), for which the model was able to 
capture the dynamics. Regarding the study area, we used the Central Atlantic and the Eastern Caribbean; however, the modelling framework can be utilized for different regions once the satellite imagery, climate data, and sargassum characteristics are understood

Reviewer 2 Report

Comments and Suggestions for Authors

Payne et al., developed and applied a model to simulate the transport of Sargassum in the Tropical Atlantic as a case study. The use of seaweed is a widely studied topic that is highly relevant, especially in today’s global situation (potential climate mitigating feedstock) and especially in the studied region due to the harmful occurring algae blooms. Therefore this paper deserves recognition in this field of research. The approach of the authors is well performed, the article is well written and therefore this publication could merit publication in the Journal of Marine Science and Engineering. However, after reading the manuscript I have minor comments which ought to be addressed before publication:

-          Please capitalize and italicize Sargassum through the entire manuscript.

-          Capitalize “tropical” in the key words section.

-          Also in Line 98 and 120.

-          Please explain abbreviations first time they are used in the text. For example SST is used in Line 90 and only explained in full later on in the manuscript (Line 119).

-          Italicize S. fluitans, S. natans and in Lines 225.

-          Bracket missing in Equation 1, and one bracket too much in Equation 2.

-          Figure 3: is it the total amount of Sargassum biomass, or only the total amount of C of Sargassum biomass? Same question for Figure 4, 5 and 6.

-          Did the authors consider the C fractions in the 3 Sargassum species to be constant and not changing (with changing temperature). Since its composition changes over time (and with changing T).

-          The authors attribute nutrient availability to be one of the main reasons of these harmful algae blooms. Can this also be included in the model (besides T)?

Author Response

Comment #1: Payne et al., developed and applied a model to simulate the transport of Sargassum in the Tropical Atlantic as a case study. The use of seaweed is a widely studied topic that is highly relevant, especially in today’s global situation (potential climate mitigating feedstock) and especially in the studied region due to the harmful occurring algae blooms. Therefore, this paper deserves recognition in this field of research. The approach of the authors is well performed, the article is well written and therefore this publication could merit publication in the Journal of Marine Science and Engineering. 

Response #1: The authors would like to thank the reviewer for this comment and highlighting the main contributions of the manuscript.

Comment #2: Please capitalize and italicize Sargassum through the entire manuscript.

-          Capitalize “tropical” in the key words section.

-          Also in Line 98 and 120.

-          Please explain abbreviations first time they are used in the text. For example SST is used in Line 90 and only explained in full later on in the manuscript (Line 119).

-          Italicize S. fluitansS. natans and in Lines 225.

-          Bracket missing in Equation 1, and one bracket too much in Equation 2.

Response #2: The authors have now fixed these grammatical and typographical issues.

Comment #3: Figure 3: is it the total amount of Sargassum biomass, or only the total amount of C of Sargassum biomass? Same question for Figure 4, 5 and 6.

Response #3: In the model framework, the C content (C) is converted to  biomass considering a factor according to this paper cited (Wang et al., 2018).

Comment #4: The authors attribute nutrient availability to be one of the main reasons of these harmful algae blooms. Can this also be included in the model (besides T)?

Response #4: This would require the use of a growth model that accounts for nutrients and temperature, which we intend to incorporate in future work. One caveat is that the nutrient data are not as high a resolution as the temperature data.

 

Reviewer 3 Report

Comments and Suggestions for Authors

In general the work was well explained and presented, but the information provided was rather brief in places.

What was not clear was how much the results were controlled by the satellite derived initial sargassum values and how much by the transport model. A plot of the starting distribution of the sargassum and some snapshots showing the spatial distribution over time would be most helpful to assess this

The information on the derivations of the currents was too limited. Crucially, the main reference to for this (.Johnson, D., J. Franks, H.A. Oxenford and S-A. Cox. 2020. Pelagic sargassum prediction and marine connectivity in the Tropical 480 Atlantic. Gulf and Caribbean Research 31: 20-30 https://doi.org/10.1878/gcr.3101.15.)  appears to be listed with invalid  DOI .

A discussion of the implications for the fact that mortality appears to be greater than growth, implying much of the sargassum is sinking (?) would be interesting and increase the usefulness of the paper.

There are some comments in the attached manuscript pdf.

Comments for author File: Comments.pdf

Author Response

Please see the comments attached.

Author Response File: Author Response.pdf

Back to TopTop