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Improved bathymetry leads to 4000 new seamount predictions in the global ocean

Chris Yesson, Tom Bech Letessier, Alex Nimmo-Smith … (2021)

Seamounts are important marine habitats that are hotpots of species diversity. Relatively shallow peaks, increased productivity and offshore locations make seamounts vulnerable to human impact and difficult to protect. Present estimates of seamount numbers vary from anywhere between 10000 to more than 60000. Seamount locations can be estimated by extracting conical shaped features from bathymetry grids. These predicted seamounts are a useful reference for marine researchers and can help direct exploratory surveys. However, these predictions are dependent on the quality of the surveys underpinning the bathymetry. Historically, quality has been patchy, but is improving as mapping efforts step up towards the target of complete seabed coverage by 2030. This study presents an update of seamount predictions based on SRTM30 global bathymetry version 11. This update was prompted by a seamount survey in the British Indian Ocean Territory in 2016, where locations of two putative seamounts were visited. These ‘seamounts’ were targeted based on previous predictions, but these features were not detected during echosounder surveys. An examination of UK hydrographic office navigational (Admiralty) charts for the area showed that the summits of these putative features had soundings reporting “no bottom detected at this depth” where “this depth” was similar to the seabed reported from the bathymetry grids: we suspect that these features likely resulted from an initial misreading of the charts. We show that 15 phantom seamount features, derived from a misinterpretation of no-bottom sounding data, persist in current global bathymetry grids and updated seamount predictions. Overall, we predict 37,889 seamounts, an increase of 4,437 from the previous predictions derived from an older global bathymetry grid (SRTM30 v. 6). This increase is due to greater detail in newer bathymetry grids as acoustic mapping of the seabed expands. The new seamount predictions are available at https://doi.pangaea.de/10.1594/PANGAEA.921688 .

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DOI:: 10.14293/S2199-1006.1.SOR-GEO.AOD2B9.v1.RZJKAA

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This work has been published open access under Creative Commons Attribution License CC BY 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Conditions, terms of use and publishing policy can be found at www.scienceopen.com.

ScienceOpen disciplines: Geography

Keywords: Knolls,Environmental science,Bathymetry,Seamounts

Review text

This study produced a global seamount census using Becker et al. (2009)’s SRTM30_PLUS bathymetric model, and reported a very interesting finding, inappropriate use of the sparsely distributed seafloor depths in historical admiralty charts may lead to erroneous presence of seamounts in global bathymetric models. However, the two stories are not well combined whereas usually only one theme is expected in a paper. This is the largest problem of this manuscript, as evidenced by the disordered structure.

The introduction of this paper has a nice start, highlighting the importance of seamount census in fishery management/research. But, the motivation of this study is not clearly presented. What is the gap in our current knowledge? What are the objectives of this paper? For example, you could say improved global bathymetric models have been released and an updated seamounts chart need to be produced. The updated chart may benefit the fishery by ***. Or, you could focus on another topic by saying that digitized historical nautical charts are used to expand the data coverage, but may lead to erroneous presence of seamounts in bathymetric models. The mechanism needs to be identified and false seamounts need to be removed from the current census. But remember to stick to one theme in a paper.

The findings reported in the “BIOT Seamount Survey” section is very interesting, but its connection with the last and next paragraphs is not well established, making it seems abrupt and standalone. How does these findings contribute to your seamount census? You can produce two seamount censuses, one produced with the “no bottom soundings” and one without, and then find a way to evaluate the improvement obtained by removing the “no bottom soundings”.

The method section is too simple, lacking of formulas and step-by-step description of how you produce the seamount census. This makes readers hard to duplicate your results. Besides, some sentences (Lines 120-122) in this section should belong to a separate section named “Data”.

You could consider adding more text to the discussion section, e.g., histogram of the seamount heights, evaluation of the reliability of results, known insufficiency in the present method that needs to be improved in the future, etc.; please refer to Wessel (2001) and Harris et al. (2014) for ways of extending the discussion. Besides, adding something specific about how your seamount census improves fishery will be helpful.

Minor problems I noticed are listed in the following.

Line 1: 4000 is not compatible with the number in the abstract.

Line 51, Line 67: Do you mean SRTM30_PLUS? Note that SRTM30 and SRTM_PLUS are two different models. Only the land and ice topography of SRTM30_PLUS comes from SRTM30.

Line 82: GEBCO 2020 has been released. Why do not you use the latest version?

Line 84: Add the text “Great Chagos Bank” onto Figure 1 to improve the readability.

Lines 117-118: This sentence is hard to understand. Please consider rewriting it.

Line 135: In the legend, the marker for “New Seamounts” is hardly visible.

Line 139: Define the EEZ shown in the legend.

Line 147: I did not find (Costello et al., 2010) in the reference list.

Line 152: Do you mean SRTM15+? Please use the name given by the author.

Line 162: Substitute “that be” by “it is”.