Chris Yesson, Tom B Letessier, Alex Nimmo-Smith, Phil Hosegood, Andrew S Brierley, Marie Hardouin, Roland Proud
{"title":"Improved bathymetry leads to >4000 new seamount predictions in the global ocean - but beware of phantom seamounts!","authors":"Chris Yesson, Tom B Letessier, Alex Nimmo-Smith, Phil Hosegood, Andrew S Brierley, Marie Hardouin, Roland Proud","doi":"10.14324/111.444/ucloe.000030","DOIUrl":null,"url":null,"abstract":"<p><p>Seamounts are important marine habitats that are hotspots 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 10,000 to more than 60,000. Seamount locations can be estimated by extracting large, cone-like features from bathymetry grids (based on criteria of size and shape). 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 PLUS global bathymetry version 11 and examines a potential source of error in these predictions. 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 4437 from the previous predictions derived from an older global bathymetry grid (SRTM30 PLUS v6). 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.</p>","PeriodicalId":75271,"journal":{"name":"UCL open environment","volume":"3 ","pages":"e030"},"PeriodicalIF":0.0000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10171409/pdf/","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"UCL open environment","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14324/111.444/ucloe.000030","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Seamounts are important marine habitats that are hotspots 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 10,000 to more than 60,000. Seamount locations can be estimated by extracting large, cone-like features from bathymetry grids (based on criteria of size and shape). 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 PLUS global bathymetry version 11 and examines a potential source of error in these predictions. 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 4437 from the previous predictions derived from an older global bathymetry grid (SRTM30 PLUS v6). 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.
海山是重要的海洋栖息地,是物种多样性的热点地区。相对较浅的山峰、较高的生产力和近海位置使得海底山容易受到人类的影响,难以保护。目前对海山数量的估计从1万到6万不等。海底山的位置可以通过从测深网格(基于尺寸和形状标准)中提取大的锥形特征来估计。这些预测的海底山对海洋研究人员来说是有用的参考,可以帮助指导勘探。然而,这些预测依赖于支撑水深测量的调查的质量。从历史上看,质量参差不齐,但随着测绘工作朝着2030年完全覆盖海底的目标迈进,质量正在改善。本研究提出了基于SRTM30 PLUS全球水深测量版本11的海底山预测的更新,并检查了这些预测中的潜在误差来源。这一更新是由2016年在英属印度洋领土进行的海底山调查引起的,该调查访问了两个假定的海底山的位置。这些“海山”是根据之前的预测定位的,但在回声测深调查中没有发现这些特征。对英国海道测绘局航海(海军部)该地区海图的检查表明,这些假定特征的顶点的测深报告“在此深度未检测到底部”,而“此深度”与测深网格报告的海床相似:我们怀疑这些特征可能是由于最初对图表的误读造成的。我们表明,15个“幽灵海山”特征,源自对无海底测深数据的错误解释,在当前的全球测深网格和更新的海山预测中持续存在。总的来说,我们预测了37,889个海山,比之前基于较旧的全球测深网格(SRTM30 PLUS v6)的预测增加了4437个。这一增长是由于海底声学测绘的扩展,在新的测深网格中有了更多的细节。新的海底山预测可在https://doi.pangaea.de/10.1594/PANGAEA.921688上获得。