Development of primer sets for multiplex and qPCR assays targeting Skeletonema species and their application to field samples View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-01-30

AUTHORS

Natsumi Enjoji, Toshiya Katano, Yuki Yoshinaka, Fuka Furuoka, Yutaro Ando, Machiko Yamada, Tomomi Hamasaki, Emika Miyamura, Mayuko Otsubo, Katsuhide Yokoyama

ABSTRACT

Skeletonema is a dominant diatom, especially in coastal waters. However, species identification and quantification in the natural environment has not yet been established, as species identification can be nearly impossible with light microscopy. In the present study, we developed primer sets for multiplex and real-time PCR to identify and enumerate the 10 Skeletonema species, and applied this technique to samples obtained from the tidal zone of the Chikugo River and its adjacent waters of the Ariake Sea from spring to summer. In total, eight Skeletonema species were detected during the investigation. Among the eight, the S. marinoi–dohrnii complex was detected at all three stations. Skeletonema potamos was the second most frequently detected, mainly in the Chikugo River. The overall number of detected species was low at the upper tidal zone of the Chikugo River, where salinity was < 2. These results reveal the diverse Skeletonema community in the brackish environment, and the primer sets designed in the present study are useful for analyzing species composition of Skeletonema. More... »

PAGES

1-16

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10872-018-00504-3

DOI

http://dx.doi.org/10.1007/s10872-018-00504-3

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1111779820


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0502", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Environmental Science and Management", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/05", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Environmental Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Fukuoka Women's University", 
          "id": "https://www.grid.ac/institutes/grid.411574.2", 
          "name": [
            "Graduate School of Marine Science and Technology, Tokyo University of Marine Science and Technology, 4-5-7 Konan, Minato-ku, 108-8477, Tokyo, Japan", 
            "Fukuoka Women\u2019s University, 1-1-1, Kasumigaoka, Higashi-ku, 813-8529, Fukuoka, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Enjoji", 
        "givenName": "Natsumi", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Tokyo University of Marine Science and Technology", 
          "id": "https://www.grid.ac/institutes/grid.412785.d", 
          "name": [
            "Graduate School of Marine Science and Technology, Tokyo University of Marine Science and Technology, 4-5-7 Konan, Minato-ku, 108-8477, Tokyo, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Katano", 
        "givenName": "Toshiya", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Tokyo University of Marine Science and Technology", 
          "id": "https://www.grid.ac/institutes/grid.412785.d", 
          "name": [
            "Graduate School of Marine Science and Technology, Tokyo University of Marine Science and Technology, 4-5-7 Konan, Minato-ku, 108-8477, Tokyo, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Yoshinaka", 
        "givenName": "Yuki", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Tokyo University of Marine Science and Technology", 
          "id": "https://www.grid.ac/institutes/grid.412785.d", 
          "name": [
            "Graduate School of Marine Science and Technology, Tokyo University of Marine Science and Technology, 4-5-7 Konan, Minato-ku, 108-8477, Tokyo, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Furuoka", 
        "givenName": "Fuka", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Tokyo University of Marine Science and Technology", 
          "id": "https://www.grid.ac/institutes/grid.412785.d", 
          "name": [
            "Graduate School of Marine Science and Technology, Tokyo University of Marine Science and Technology, 4-5-7 Konan, Minato-ku, 108-8477, Tokyo, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ando", 
        "givenName": "Yutaro", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Fukuoka Women's University", 
          "id": "https://www.grid.ac/institutes/grid.411574.2", 
          "name": [
            "Fukuoka Women\u2019s University, 1-1-1, Kasumigaoka, Higashi-ku, 813-8529, Fukuoka, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Yamada", 
        "givenName": "Machiko", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Fukuoka Women's University", 
          "id": "https://www.grid.ac/institutes/grid.411574.2", 
          "name": [
            "Fukuoka Women\u2019s University, 1-1-1, Kasumigaoka, Higashi-ku, 813-8529, Fukuoka, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Hamasaki", 
        "givenName": "Tomomi", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Fukuoka Women's University", 
          "id": "https://www.grid.ac/institutes/grid.411574.2", 
          "name": [
            "Fukuoka Women\u2019s University, 1-1-1, Kasumigaoka, Higashi-ku, 813-8529, Fukuoka, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Miyamura", 
        "givenName": "Emika", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Fukuoka Women's University", 
          "id": "https://www.grid.ac/institutes/grid.411574.2", 
          "name": [
            "Fukuoka Women\u2019s University, 1-1-1, Kasumigaoka, Higashi-ku, 813-8529, Fukuoka, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Otsubo", 
        "givenName": "Mayuko", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Tokyo Metropolitan University", 
          "id": "https://www.grid.ac/institutes/grid.265074.2", 
          "name": [
            "Graduate School of Urban Environmental Sciences, Tokyo Metropolitan University, 1-1 Minami-Osawa, Hachioji-shi, 192-0397, Tokyo, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Yokoyama", 
        "givenName": "Katsuhide", 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1007/s00253-009-2249-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000599498", 
          "https://doi.org/10.1007/s00253-009-2249-4"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00253-009-2249-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000599498", 
          "https://doi.org/10.1007/s00253-009-2249-4"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00253-009-2249-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000599498", 
          "https://doi.org/10.1007/s00253-009-2249-4"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1128/aac.46.7.2155-2161.2002", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003005551"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/plankt/fbq150", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003053560"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/09670262.2011.565128", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003273874"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1529-8817.1980.tb03061.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006640650"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.hal.2006.12.004", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008518047"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.protis.2014.08.001", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023546983"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1529-8817.2006.00305.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023649327"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3390/d2070973", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025048538"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10872-010-0062-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031921376", 
          "https://doi.org/10.1007/s10872-010-0062-4"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.protis.2007.09.004", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034881638"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1529-8817.2005.04066.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035948051"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1529-8817.2011.00976.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038039363"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10811-012-9816-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038064621", 
          "https://doi.org/10.1007/s10811-012-9816-2"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/plankt/fbq127", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1038413102"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1128/aem.02389-06", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039553854"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1128/aem.66.11.4641-4648.2000", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047818468"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3800/pbr.9.168", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050329961"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2331/suisan.16-00040", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050542310"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1529-8817.2005.04067.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053282048"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s12562-013-0671-0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053691618", 
          "https://doi.org/10.1007/s12562-013-0671-0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3354/ame040121", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1071158048"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3354/meps11843", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1071173011"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2019-01-30", 
    "datePublishedReg": "2019-01-30", 
    "description": "Skeletonema is a dominant diatom, especially in coastal waters. However, species identification and quantification in the natural environment has not yet been established, as species identification can be nearly impossible with light microscopy. In the present study, we developed primer sets for multiplex and real-time PCR to identify and enumerate the 10 Skeletonema species, and applied this technique to samples obtained from the tidal zone of the Chikugo River and its adjacent waters of the Ariake Sea from spring to summer. In total, eight Skeletonema species were detected during the investigation. Among the eight, the S. marinoi\u2013dohrnii complex was detected at all three stations. Skeletonema potamos was the second most frequently detected, mainly in the Chikugo River. The overall number of detected species was low at the upper tidal zone of the Chikugo River, where salinity was < 2. These results reveal the diverse Skeletonema community in the brackish environment, and the primer sets designed in the present study are useful for analyzing species composition of Skeletonema.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s10872-018-00504-3", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isFundedItemOf": [
      {
        "id": "sg:grant.6118444", 
        "type": "MonetaryGrant"
      }, 
      {
        "id": "sg:grant.5907762", 
        "type": "MonetaryGrant"
      }
    ], 
    "isPartOf": [
      {
        "id": "sg:journal.1313776", 
        "issn": [
          "0916-8370", 
          "1573-868X"
        ], 
        "name": "Journal of Oceanography", 
        "type": "Periodical"
      }
    ], 
    "name": "Development of primer sets for multiplex and qPCR assays targeting Skeletonema species and their application to field samples", 
    "pagination": "1-16", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "e6918db5e292594e90c34cf184290ed36996c71ee1e2fd94783b5c1478fc65f3"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s10872-018-00504-3"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1111779820"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s10872-018-00504-3", 
      "https://app.dimensions.ai/details/publication/pub.1111779820"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T08:58", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000326_0000000326/records_68439_00000000.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://link.springer.com/10.1007%2Fs10872-018-00504-3"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s10872-018-00504-3'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s10872-018-00504-3'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s10872-018-00504-3'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s10872-018-00504-3'


 

This table displays all metadata directly associated to this object as RDF triples.

192 TRIPLES      21 PREDICATES      47 URIs      16 LITERALS      5 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s10872-018-00504-3 schema:about anzsrc-for:05
2 anzsrc-for:0502
3 schema:author N7a552ed002d54961b2be5cf4c795f55b
4 schema:citation sg:pub.10.1007/s00253-009-2249-4
5 sg:pub.10.1007/s10811-012-9816-2
6 sg:pub.10.1007/s10872-010-0062-4
7 sg:pub.10.1007/s12562-013-0671-0
8 https://doi.org/10.1016/j.hal.2006.12.004
9 https://doi.org/10.1016/j.protis.2007.09.004
10 https://doi.org/10.1016/j.protis.2014.08.001
11 https://doi.org/10.1080/09670262.2011.565128
12 https://doi.org/10.1093/plankt/fbq127
13 https://doi.org/10.1093/plankt/fbq150
14 https://doi.org/10.1111/j.1529-8817.1980.tb03061.x
15 https://doi.org/10.1111/j.1529-8817.2005.04066.x
16 https://doi.org/10.1111/j.1529-8817.2005.04067.x
17 https://doi.org/10.1111/j.1529-8817.2006.00305.x
18 https://doi.org/10.1111/j.1529-8817.2011.00976.x
19 https://doi.org/10.1128/aac.46.7.2155-2161.2002
20 https://doi.org/10.1128/aem.02389-06
21 https://doi.org/10.1128/aem.66.11.4641-4648.2000
22 https://doi.org/10.2331/suisan.16-00040
23 https://doi.org/10.3354/ame040121
24 https://doi.org/10.3354/meps11843
25 https://doi.org/10.3390/d2070973
26 https://doi.org/10.3800/pbr.9.168
27 schema:datePublished 2019-01-30
28 schema:datePublishedReg 2019-01-30
29 schema:description Skeletonema is a dominant diatom, especially in coastal waters. However, species identification and quantification in the natural environment has not yet been established, as species identification can be nearly impossible with light microscopy. In the present study, we developed primer sets for multiplex and real-time PCR to identify and enumerate the 10 Skeletonema species, and applied this technique to samples obtained from the tidal zone of the Chikugo River and its adjacent waters of the Ariake Sea from spring to summer. In total, eight Skeletonema species were detected during the investigation. Among the eight, the S. marinoi–dohrnii complex was detected at all three stations. Skeletonema potamos was the second most frequently detected, mainly in the Chikugo River. The overall number of detected species was low at the upper tidal zone of the Chikugo River, where salinity was < 2. These results reveal the diverse Skeletonema community in the brackish environment, and the primer sets designed in the present study are useful for analyzing species composition of Skeletonema.
30 schema:genre research_article
31 schema:inLanguage en
32 schema:isAccessibleForFree false
33 schema:isPartOf sg:journal.1313776
34 schema:name Development of primer sets for multiplex and qPCR assays targeting Skeletonema species and their application to field samples
35 schema:pagination 1-16
36 schema:productId N22594427b55d4cb58bd99c2a21a15d3c
37 Ncaefd389ca1a4e9ab4e8d0f6f27dd020
38 Nf2cfcbcce41c410789eef749dafe6245
39 schema:sameAs https://app.dimensions.ai/details/publication/pub.1111779820
40 https://doi.org/10.1007/s10872-018-00504-3
41 schema:sdDatePublished 2019-04-11T08:58
42 schema:sdLicense https://scigraph.springernature.com/explorer/license/
43 schema:sdPublisher Nfcfa5fbf5af94490a9b0299f1462c808
44 schema:url https://link.springer.com/10.1007%2Fs10872-018-00504-3
45 sgo:license sg:explorer/license/
46 sgo:sdDataset articles
47 rdf:type schema:ScholarlyArticle
48 N00af2f8ab2504e8e9270e2c2134707d7 schema:affiliation https://www.grid.ac/institutes/grid.411574.2
49 schema:familyName Otsubo
50 schema:givenName Mayuko
51 rdf:type schema:Person
52 N0d4f1645191845db9b5b9929a27e06c1 rdf:first N95a1ca547d3d43f4b511e43cbeb2fe71
53 rdf:rest Na29fb8a9e5d540c5b84675440158734d
54 N169007e5ce404fd59647a846860cc63c schema:affiliation https://www.grid.ac/institutes/grid.412785.d
55 schema:familyName Furuoka
56 schema:givenName Fuka
57 rdf:type schema:Person
58 N18f38d4232a44633ba28689524a5b043 rdf:first Nd7d500efb0b2495091e4ab36901323ff
59 rdf:rest N0d4f1645191845db9b5b9929a27e06c1
60 N22594427b55d4cb58bd99c2a21a15d3c schema:name readcube_id
61 schema:value e6918db5e292594e90c34cf184290ed36996c71ee1e2fd94783b5c1478fc65f3
62 rdf:type schema:PropertyValue
63 N5d9c9e81dcc549f38908336921d1d18d rdf:first N00af2f8ab2504e8e9270e2c2134707d7
64 rdf:rest Nd914bcdb73b247c9aa9bb49a6b66c5c5
65 N64a46a978b6b4a96958cfd9a868a380d rdf:first N7232196cbe6d409e8c75335ad21f7e0c
66 rdf:rest Nda42a8ac31cf4347be05ad9d346c6494
67 N7232196cbe6d409e8c75335ad21f7e0c schema:affiliation https://www.grid.ac/institutes/grid.412785.d
68 schema:familyName Katano
69 schema:givenName Toshiya
70 rdf:type schema:Person
71 N7a552ed002d54961b2be5cf4c795f55b rdf:first Nb3ddaf7c8ac8464490ed28048feb6794
72 rdf:rest N64a46a978b6b4a96958cfd9a868a380d
73 N7d3dc08edfe24945b5d35834a3678c69 schema:affiliation https://www.grid.ac/institutes/grid.412785.d
74 schema:familyName Yoshinaka
75 schema:givenName Yuki
76 rdf:type schema:Person
77 N7f0b51fb88fa4805a45096ade12883b4 rdf:first Nc6ab5709cbf9415790c92d6c093208ec
78 rdf:rest N18f38d4232a44633ba28689524a5b043
79 N87e2ae102ebd41b79d2b3be35d71ad33 schema:affiliation https://www.grid.ac/institutes/grid.411574.2
80 schema:familyName Miyamura
81 schema:givenName Emika
82 rdf:type schema:Person
83 N95a1ca547d3d43f4b511e43cbeb2fe71 schema:affiliation https://www.grid.ac/institutes/grid.411574.2
84 schema:familyName Hamasaki
85 schema:givenName Tomomi
86 rdf:type schema:Person
87 N9f56bec34b784b668010357a887062ff schema:affiliation https://www.grid.ac/institutes/grid.265074.2
88 schema:familyName Yokoyama
89 schema:givenName Katsuhide
90 rdf:type schema:Person
91 Na29fb8a9e5d540c5b84675440158734d rdf:first N87e2ae102ebd41b79d2b3be35d71ad33
92 rdf:rest N5d9c9e81dcc549f38908336921d1d18d
93 Nb3ddaf7c8ac8464490ed28048feb6794 schema:affiliation https://www.grid.ac/institutes/grid.411574.2
94 schema:familyName Enjoji
95 schema:givenName Natsumi
96 rdf:type schema:Person
97 Nc6ab5709cbf9415790c92d6c093208ec schema:affiliation https://www.grid.ac/institutes/grid.412785.d
98 schema:familyName Ando
99 schema:givenName Yutaro
100 rdf:type schema:Person
101 Nc7192a7a2ffa41c589ff0d48dd51e150 rdf:first N169007e5ce404fd59647a846860cc63c
102 rdf:rest N7f0b51fb88fa4805a45096ade12883b4
103 Ncaefd389ca1a4e9ab4e8d0f6f27dd020 schema:name dimensions_id
104 schema:value pub.1111779820
105 rdf:type schema:PropertyValue
106 Nd7d500efb0b2495091e4ab36901323ff schema:affiliation https://www.grid.ac/institutes/grid.411574.2
107 schema:familyName Yamada
108 schema:givenName Machiko
109 rdf:type schema:Person
110 Nd914bcdb73b247c9aa9bb49a6b66c5c5 rdf:first N9f56bec34b784b668010357a887062ff
111 rdf:rest rdf:nil
112 Nda42a8ac31cf4347be05ad9d346c6494 rdf:first N7d3dc08edfe24945b5d35834a3678c69
113 rdf:rest Nc7192a7a2ffa41c589ff0d48dd51e150
114 Nf2cfcbcce41c410789eef749dafe6245 schema:name doi
115 schema:value 10.1007/s10872-018-00504-3
116 rdf:type schema:PropertyValue
117 Nfcfa5fbf5af94490a9b0299f1462c808 schema:name Springer Nature - SN SciGraph project
118 rdf:type schema:Organization
119 anzsrc-for:05 schema:inDefinedTermSet anzsrc-for:
120 schema:name Environmental Sciences
121 rdf:type schema:DefinedTerm
122 anzsrc-for:0502 schema:inDefinedTermSet anzsrc-for:
123 schema:name Environmental Science and Management
124 rdf:type schema:DefinedTerm
125 sg:grant.5907762 http://pending.schema.org/fundedItem sg:pub.10.1007/s10872-018-00504-3
126 rdf:type schema:MonetaryGrant
127 sg:grant.6118444 http://pending.schema.org/fundedItem sg:pub.10.1007/s10872-018-00504-3
128 rdf:type schema:MonetaryGrant
129 sg:journal.1313776 schema:issn 0916-8370
130 1573-868X
131 schema:name Journal of Oceanography
132 rdf:type schema:Periodical
133 sg:pub.10.1007/s00253-009-2249-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000599498
134 https://doi.org/10.1007/s00253-009-2249-4
135 rdf:type schema:CreativeWork
136 sg:pub.10.1007/s10811-012-9816-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038064621
137 https://doi.org/10.1007/s10811-012-9816-2
138 rdf:type schema:CreativeWork
139 sg:pub.10.1007/s10872-010-0062-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031921376
140 https://doi.org/10.1007/s10872-010-0062-4
141 rdf:type schema:CreativeWork
142 sg:pub.10.1007/s12562-013-0671-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053691618
143 https://doi.org/10.1007/s12562-013-0671-0
144 rdf:type schema:CreativeWork
145 https://doi.org/10.1016/j.hal.2006.12.004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008518047
146 rdf:type schema:CreativeWork
147 https://doi.org/10.1016/j.protis.2007.09.004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034881638
148 rdf:type schema:CreativeWork
149 https://doi.org/10.1016/j.protis.2014.08.001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023546983
150 rdf:type schema:CreativeWork
151 https://doi.org/10.1080/09670262.2011.565128 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003273874
152 rdf:type schema:CreativeWork
153 https://doi.org/10.1093/plankt/fbq127 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038413102
154 rdf:type schema:CreativeWork
155 https://doi.org/10.1093/plankt/fbq150 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003053560
156 rdf:type schema:CreativeWork
157 https://doi.org/10.1111/j.1529-8817.1980.tb03061.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1006640650
158 rdf:type schema:CreativeWork
159 https://doi.org/10.1111/j.1529-8817.2005.04066.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1035948051
160 rdf:type schema:CreativeWork
161 https://doi.org/10.1111/j.1529-8817.2005.04067.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1053282048
162 rdf:type schema:CreativeWork
163 https://doi.org/10.1111/j.1529-8817.2006.00305.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1023649327
164 rdf:type schema:CreativeWork
165 https://doi.org/10.1111/j.1529-8817.2011.00976.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1038039363
166 rdf:type schema:CreativeWork
167 https://doi.org/10.1128/aac.46.7.2155-2161.2002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003005551
168 rdf:type schema:CreativeWork
169 https://doi.org/10.1128/aem.02389-06 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039553854
170 rdf:type schema:CreativeWork
171 https://doi.org/10.1128/aem.66.11.4641-4648.2000 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047818468
172 rdf:type schema:CreativeWork
173 https://doi.org/10.2331/suisan.16-00040 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050542310
174 rdf:type schema:CreativeWork
175 https://doi.org/10.3354/ame040121 schema:sameAs https://app.dimensions.ai/details/publication/pub.1071158048
176 rdf:type schema:CreativeWork
177 https://doi.org/10.3354/meps11843 schema:sameAs https://app.dimensions.ai/details/publication/pub.1071173011
178 rdf:type schema:CreativeWork
179 https://doi.org/10.3390/d2070973 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025048538
180 rdf:type schema:CreativeWork
181 https://doi.org/10.3800/pbr.9.168 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050329961
182 rdf:type schema:CreativeWork
183 https://www.grid.ac/institutes/grid.265074.2 schema:alternateName Tokyo Metropolitan University
184 schema:name Graduate School of Urban Environmental Sciences, Tokyo Metropolitan University, 1-1 Minami-Osawa, Hachioji-shi, 192-0397, Tokyo, Japan
185 rdf:type schema:Organization
186 https://www.grid.ac/institutes/grid.411574.2 schema:alternateName Fukuoka Women's University
187 schema:name Fukuoka Women’s University, 1-1-1, Kasumigaoka, Higashi-ku, 813-8529, Fukuoka, Japan
188 Graduate School of Marine Science and Technology, Tokyo University of Marine Science and Technology, 4-5-7 Konan, Minato-ku, 108-8477, Tokyo, Japan
189 rdf:type schema:Organization
190 https://www.grid.ac/institutes/grid.412785.d schema:alternateName Tokyo University of Marine Science and Technology
191 schema:name Graduate School of Marine Science and Technology, Tokyo University of Marine Science and Technology, 4-5-7 Konan, Minato-ku, 108-8477, Tokyo, Japan
192 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...