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Specimen-based records and geographic locations of brittle stars (Echinodermata) collected from Sagami Bay
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  • Masanori Okanishi,
  • Hisanori Kohtsuka,
  • Naohiro Hasegawa,
  • Takeshi Osawa*
Masanori Okanishi
Hiroshima Shudo University

Corresponding Author:[email protected]

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Hisanori Kohtsuka
The University of Tokyo
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Naohiro Hasegawa
Hiroshima Shudo University
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Takeshi Osawa*
Tokyo Metropolitan University Faculty of Urban Environmental Sciences Graduate School of Urban Environmental Sciences
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Abstract

Brittle stars are marine invertebrates that often dominate the seafloor. Their global distribution range and abundance make them useful as marine environmental bio-indicators. Despite their importance, however, there is limited availability of data on brittle star specimens in Japan. In this study, we focused on Sagami Bay, one of the oldest Japanese sea areas for the study of brittle stars, and organized the data of the specimens obtained there. This collection included specimens collected between 2005 and 2021, with a total of 738 samples, which were identified as 112 species. In this data set we ignored the duplication at each sampling site. All data are deposited in the Global Biodiversity Information Facility (GBIF) through the Japan Node of GBIF and are thus accessible through the GBIF portal under the Creative Commons Attribution 4.0 International license. The complete data set for this abstract, published in the journal’s Data Paper section, is available in electronic format in MetaCat in JaLTER at http:/++++++(Scheduled to be obtained after acceptance).
20 Sep 2024Submitted to Ecological Research
26 Sep 2024Submission Checks Completed
26 Sep 2024Assigned to Editor
26 Sep 2024Review(s) Completed, Editorial Evaluation Pending
06 Oct 2024Reviewer(s) Assigned
28 Oct 2024Editorial Decision: Revise Minor
04 Nov 20241st Revision Received
05 Nov 2024Submission Checks Completed
05 Nov 2024Assigned to Editor
05 Nov 2024Review(s) Completed, Editorial Evaluation Pending
12 Nov 2024Reviewer(s) Assigned
30 Nov 2024Editorial Decision: Accept