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

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    Improved bathymetry leads to 4000 new seamount predictions in the global oceanCrossref
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        Rated 3.5 of 5.
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        Rated 4 of 5.
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        Rated 3 of 5.
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        Rated 4 of 5.
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        Rated 3 of 5.
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    Improved bathymetry leads to 4000 new seamount predictions in the global ocean

    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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      Review information

      10.14293/S2199-1006.1.SOR-GEO.AKXABB.v1.RVEAQH
      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.

      Geography
      Knolls,Environmental science,Bathymetry,Seamounts

      Review text

      Seamount information, including position, depth of the summit, is of great importance for different kinds of applications. The manuscript predicted new seamounts using newer bathymetry grids, i.e. SRTM30 global bathymetry version 11. The findings are important and meaningful for the applications of current bathymetry models. For example, they found some seamounts predicted by the old bathymetry grids are not detected by sounding data. This means some phantom seamounts exist in the old version of bathymetry grids. Also, some seamounts would not be detected by the old bathymetry grids. In general, I think the result of this manuscript is very important. Here are my comments.

      1. Although this study found new seamounts, however, there are also phantom seamounts. Hence, I think the author should point out that some erroneous predictions may exist in the new predictions. If the new results can be verified by sounding data, it would be better. However, the sounding data may be not enough. Maybe the authors can select some local regions to do an evaluation. For example, in the areas near South China Sea and the Philippines, as there is high densification of seamounts according to Figure 3.
      2. It would be more helpful for the international research community if the authors could use mathematical equations to break down the method used in addition to the content of lines 115 to 119. It can be added as an appendix.
      3. Line 64, give the geographic extent (corner coordinates) of BIOT Seamount Survey.
      4. Line 117, insert ‘where’ after ‘terminate at the point’.
      5. Line 118, “km2”->”km2
      6. It would be better to give the units of the data in the inset table of Figure 4.
      7. Line 162, change ‘removed’ to ‘resolved’.

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