Lidar Monitoring of Chlorophyll a During the XXIX and XXXI Italian Antarctic Expeditions View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-04

AUTHORS

Luca Fiorani, Federico Angelini, Florinda Artuso, Dario Cataldi, Francesco Colao

ABSTRACT

Although it is known that the Ross Sea is responsible for more than a quarter of CO2 absorption of the Southern Ocean, more information is needed to model the primary production of this key area. In particular, it is necessary to improve the characterization of the size class distribution, biomass and taxonomic composition of phytoplankton in the Ross Sea. Recently, an innovative compact lidar fluorosensor was deployed for real-time sensing of chlorophyll a, during the Ross Sea Mesoscale Experiment (RoME), conducted in the XXIX (2014) and XXXI (2016) Italian Antarctic expeditions. Furthermore, high-performance liquid chromatography (HPLC) was also performed to provide pigment analysis of in situ samples. Lidar fluorosensors are laser-induced fluorescence (LIF) instruments and have been extensively operated by the Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA) since the 1990s to monitor water bodies. Spectra obtained with LIF contain signatures of phytoplankton pigments, chromophoric dissolved organic matter and dispersed impurities, such as crude oils. The study of algal pigments provides not only the phytoplankton biomass—directly linked to chlorophyll a—but also its taxonomic composition through detection of several accessory pigments. Moreover, some models allow the identification of phytoplankton size classes. Lidar and HPLC mapped the spatiotemporal distribution of algal biomass and showed that during RoME, the phytoplankton assemblage structure was dominated by large-size cells (micro-phytoplankton) and the prevailing algal groups were diatoms. Lidar fluorosensors provide fast measurements of phytoplankton pigmentsThey are the “missing link” between satellite radiometers and in situ instrumentsHigh performance liquid chromatography integrates lidar fluorosensorsPhytoplankton spatiotemporal distribution was mapped in the Ross Sea (Antarctica)Phytoplankton functional types and size classes were retrieved Lidar fluorosensors provide fast measurements of phytoplankton pigments They are the “missing link” between satellite radiometers and in situ instruments High performance liquid chromatography integrates lidar fluorosensors Phytoplankton spatiotemporal distribution was mapped in the Ross Sea (Antarctica) Phytoplankton functional types and size classes were retrieved More... »

PAGES

1-11

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s41742-019-00169-w

DOI

http://dx.doi.org/10.1007/s41742-019-00169-w

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1112215493


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/2008/0607", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Plant Biology", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/06", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Biological Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "National Agency For New Technologies, Energy and Sustainable Economic Development", 
          "id": "https://www.grid.ac/institutes/grid.5196.b", 
          "name": [
            "Nuclear Fusion and Safety Technologies Department, ENEA, Via Enrico Fermi 45, 00044, Frascati, Italy"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Fiorani", 
        "givenName": "Luca", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "National Agency For New Technologies, Energy and Sustainable Economic Development", 
          "id": "https://www.grid.ac/institutes/grid.5196.b", 
          "name": [
            "Nuclear Fusion and Safety Technologies Department, ENEA, Via Enrico Fermi 45, 00044, Frascati, Italy"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Angelini", 
        "givenName": "Federico", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "National Agency For New Technologies, Energy and Sustainable Economic Development", 
          "id": "https://www.grid.ac/institutes/grid.5196.b", 
          "name": [
            "Nuclear Fusion and Safety Technologies Department, ENEA, Via Enrico Fermi 45, 00044, Frascati, Italy"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Artuso", 
        "givenName": "Florinda", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "National Agency For New Technologies, Energy and Sustainable Economic Development", 
          "id": "https://www.grid.ac/institutes/grid.5196.b", 
          "name": [
            "Nuclear Fusion and Safety Technologies Department, ENEA, Via Enrico Fermi 45, 00044, Frascati, Italy"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Cataldi", 
        "givenName": "Dario", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "National Agency For New Technologies, Energy and Sustainable Economic Development", 
          "id": "https://www.grid.ac/institutes/grid.5196.b", 
          "name": [
            "Nuclear Fusion and Safety Technologies Department, ENEA, Via Enrico Fermi 45, 00044, Frascati, Italy"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Colao", 
        "givenName": "Francesco", 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1080/01431161.2016.1204479", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001128095"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.dsr2.2008.09.017", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001319870"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jmarsys.2016.10.010", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007423800"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jmarsys.2016.10.010", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007423800"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.jmarsys.2016.10.010", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007423800"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/0143116021000053797", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1010161086"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.rse.2008.03.011", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012974618"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1098/rstb.2010.0125", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015149421"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.pocean.2013.12.008", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016393329"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/0143116021000047938", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016609911"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/2005jc003207", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017502843"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.rse.2011.11.013", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1017712279"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/s095410200300107x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021952999"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/s095410200300107x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021952999"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1146/annurev-marine-010213-135114", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022166679"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.4319/lo.2000.45.5.1130", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022744438"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0967-0637(00)00045-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023095530"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/2009gb003680", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023536061"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/2006jc003816", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024047449"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/2007jc004551", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025357683"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.rse.2009.11.022", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025476269"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/2008gl035624", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028056973"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1046/j.1365-3040.1999.00419.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036640520"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/gcb.12623", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043071491"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0378-4347(00)00603-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044472632"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.4319/lo.1982.27.2.0218", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050226309"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10750-012-1149-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051043631", 
          "https://doi.org/10.1007/s10750-012-1149-2"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10750-012-1149-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051043631", 
          "https://doi.org/10.1007/s10750-012-1149-2"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-642-55844-3_5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051410769", 
          "https://doi.org/10.1007/978-3-642-55844-3_5"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-3-642-55844-3_5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051410769", 
          "https://doi.org/10.1007/978-3-642-55844-3_5"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11120-006-9065-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052683290", 
          "https://doi.org/10.1007/s11120-006-9065-9"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1126/science.227.4683.163", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062529671"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1364/ao.37.003222", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1065113228"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1364/ao.42.002767", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1065118145"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3354/meps077183", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1071167606"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.5670/oceanog.2001.06", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1073067111"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.5670/oceanog.2012.80", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1073068152"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/01431161.2016.1274446", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1083924818"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pone.0176033", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1085008907"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2019-04", 
    "datePublishedReg": "2019-04-01", 
    "description": "Although it is known that the Ross Sea is responsible for more than a quarter of CO2 absorption of the Southern Ocean, more information is needed to model the primary production of this key area. In particular, it is necessary to improve the characterization of the size class distribution, biomass and taxonomic composition of phytoplankton in the Ross Sea. Recently, an innovative compact lidar fluorosensor was deployed for real-time sensing of chlorophyll a, during the Ross Sea Mesoscale Experiment (RoME), conducted in the XXIX (2014) and XXXI (2016) Italian Antarctic expeditions. Furthermore, high-performance liquid chromatography (HPLC) was also performed to provide pigment analysis of in situ samples. Lidar fluorosensors are laser-induced fluorescence (LIF) instruments and have been extensively operated by the Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA) since the 1990s to monitor water bodies. Spectra obtained with LIF contain signatures of phytoplankton pigments, chromophoric dissolved organic matter and dispersed impurities, such as crude oils. The study of algal pigments provides not only the phytoplankton biomass\u2014directly linked to chlorophyll a\u2014but also its taxonomic composition through detection of several accessory pigments. Moreover, some models allow the identification of phytoplankton size classes. Lidar and HPLC mapped the spatiotemporal distribution of algal biomass and showed that during RoME, the phytoplankton assemblage structure was dominated by large-size cells (micro-phytoplankton) and the prevailing algal groups were diatoms. Lidar fluorosensors provide fast measurements of phytoplankton pigmentsThey are the \u201cmissing link\u201d between satellite radiometers and in situ instrumentsHigh performance liquid chromatography integrates lidar fluorosensorsPhytoplankton spatiotemporal distribution was mapped in the Ross Sea (Antarctica)Phytoplankton functional types and size classes were retrieved Lidar fluorosensors provide fast measurements of phytoplankton pigments They are the \u201cmissing link\u201d between satellite radiometers and in situ instruments High performance liquid chromatography integrates lidar fluorosensors Phytoplankton spatiotemporal distribution was mapped in the Ross Sea (Antarctica) Phytoplankton functional types and size classes were retrieved", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s41742-019-00169-w", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1047339", 
        "issn": [
          "1735-6865", 
          "2008-2304"
        ], 
        "name": "International Journal of Environmental Research", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "2", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "13"
      }
    ], 
    "name": "Lidar Monitoring of Chlorophyll a During the XXIX and XXXI Italian Antarctic Expeditions", 
    "pagination": "1-11", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "5becc6742dfa347f0a692755e55187e7f251120882f8c586e0a4bbef57af101d"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s41742-019-00169-w"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1112215493"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s41742-019-00169-w", 
      "https://app.dimensions.ai/details/publication/pub.1112215493"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T14:17", 
    "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/v90/0000000372_0000000372/records_117092_00000003.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://link.springer.com/10.1007%2Fs41742-019-00169-w"
  }
]
 

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/s41742-019-00169-w'

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/s41742-019-00169-w'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s41742-019-00169-w'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s41742-019-00169-w'


 

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

189 TRIPLES      21 PREDICATES      61 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s41742-019-00169-w schema:about anzsrc-for:06
2 anzsrc-for:0607
3 schema:author N082dabbbb840441698b695d9fa562a2a
4 schema:citation sg:pub.10.1007/978-3-642-55844-3_5
5 sg:pub.10.1007/s10750-012-1149-2
6 sg:pub.10.1007/s11120-006-9065-9
7 https://doi.org/10.1016/j.dsr2.2008.09.017
8 https://doi.org/10.1016/j.jmarsys.2016.10.010
9 https://doi.org/10.1016/j.pocean.2013.12.008
10 https://doi.org/10.1016/j.rse.2008.03.011
11 https://doi.org/10.1016/j.rse.2009.11.022
12 https://doi.org/10.1016/j.rse.2011.11.013
13 https://doi.org/10.1016/s0378-4347(00)00603-4
14 https://doi.org/10.1016/s0967-0637(00)00045-5
15 https://doi.org/10.1017/s095410200300107x
16 https://doi.org/10.1029/2005jc003207
17 https://doi.org/10.1029/2006jc003816
18 https://doi.org/10.1029/2007jc004551
19 https://doi.org/10.1029/2008gl035624
20 https://doi.org/10.1029/2009gb003680
21 https://doi.org/10.1046/j.1365-3040.1999.00419.x
22 https://doi.org/10.1080/0143116021000047938
23 https://doi.org/10.1080/0143116021000053797
24 https://doi.org/10.1080/01431161.2016.1204479
25 https://doi.org/10.1080/01431161.2016.1274446
26 https://doi.org/10.1098/rstb.2010.0125
27 https://doi.org/10.1111/gcb.12623
28 https://doi.org/10.1126/science.227.4683.163
29 https://doi.org/10.1146/annurev-marine-010213-135114
30 https://doi.org/10.1364/ao.37.003222
31 https://doi.org/10.1364/ao.42.002767
32 https://doi.org/10.1371/journal.pone.0176033
33 https://doi.org/10.3354/meps077183
34 https://doi.org/10.4319/lo.1982.27.2.0218
35 https://doi.org/10.4319/lo.2000.45.5.1130
36 https://doi.org/10.5670/oceanog.2001.06
37 https://doi.org/10.5670/oceanog.2012.80
38 schema:datePublished 2019-04
39 schema:datePublishedReg 2019-04-01
40 schema:description Although it is known that the Ross Sea is responsible for more than a quarter of CO2 absorption of the Southern Ocean, more information is needed to model the primary production of this key area. In particular, it is necessary to improve the characterization of the size class distribution, biomass and taxonomic composition of phytoplankton in the Ross Sea. Recently, an innovative compact lidar fluorosensor was deployed for real-time sensing of chlorophyll a, during the Ross Sea Mesoscale Experiment (RoME), conducted in the XXIX (2014) and XXXI (2016) Italian Antarctic expeditions. Furthermore, high-performance liquid chromatography (HPLC) was also performed to provide pigment analysis of in situ samples. Lidar fluorosensors are laser-induced fluorescence (LIF) instruments and have been extensively operated by the Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA) since the 1990s to monitor water bodies. Spectra obtained with LIF contain signatures of phytoplankton pigments, chromophoric dissolved organic matter and dispersed impurities, such as crude oils. The study of algal pigments provides not only the phytoplankton biomass—directly linked to chlorophyll a—but also its taxonomic composition through detection of several accessory pigments. Moreover, some models allow the identification of phytoplankton size classes. Lidar and HPLC mapped the spatiotemporal distribution of algal biomass and showed that during RoME, the phytoplankton assemblage structure was dominated by large-size cells (micro-phytoplankton) and the prevailing algal groups were diatoms. Lidar fluorosensors provide fast measurements of phytoplankton pigmentsThey are the “missing link” between satellite radiometers and in situ instrumentsHigh performance liquid chromatography integrates lidar fluorosensorsPhytoplankton spatiotemporal distribution was mapped in the Ross Sea (Antarctica)Phytoplankton functional types and size classes were retrieved Lidar fluorosensors provide fast measurements of phytoplankton pigments They are the “missing link” between satellite radiometers and in situ instruments High performance liquid chromatography integrates lidar fluorosensors Phytoplankton spatiotemporal distribution was mapped in the Ross Sea (Antarctica) Phytoplankton functional types and size classes were retrieved
41 schema:genre research_article
42 schema:inLanguage en
43 schema:isAccessibleForFree false
44 schema:isPartOf N196e4092d8f546cc854738a924927fb2
45 Nb7d7b671f6f148249834c16e61f55e3b
46 sg:journal.1047339
47 schema:name Lidar Monitoring of Chlorophyll a During the XXIX and XXXI Italian Antarctic Expeditions
48 schema:pagination 1-11
49 schema:productId N35912e1d9498411894702e281fd09bee
50 Ne644f50be50e472ea0d1c0800496d93a
51 Nef90e64b98d04c48a36118535a00a6e5
52 schema:sameAs https://app.dimensions.ai/details/publication/pub.1112215493
53 https://doi.org/10.1007/s41742-019-00169-w
54 schema:sdDatePublished 2019-04-11T14:17
55 schema:sdLicense https://scigraph.springernature.com/explorer/license/
56 schema:sdPublisher N953db13cbccb459f92c23f6c6c04359a
57 schema:url https://link.springer.com/10.1007%2Fs41742-019-00169-w
58 sgo:license sg:explorer/license/
59 sgo:sdDataset articles
60 rdf:type schema:ScholarlyArticle
61 N082dabbbb840441698b695d9fa562a2a rdf:first N8f14642703d44753949bd80f998a0096
62 rdf:rest Nf6330a658f454cbfa2ecfbc981cfd0cf
63 N196e4092d8f546cc854738a924927fb2 schema:issueNumber 2
64 rdf:type schema:PublicationIssue
65 N294e5fabf560498b8905e9df133721c9 rdf:first N8b9161f6426d4c5089a17682bf2a90f3
66 rdf:rest Nd29c35597e6345b9a0d00747a80f2f76
67 N326b19687c474fc99dcfef1630403733 rdf:first N4cd098ba86da4b02ac0941df9a2777a1
68 rdf:rest rdf:nil
69 N35912e1d9498411894702e281fd09bee schema:name doi
70 schema:value 10.1007/s41742-019-00169-w
71 rdf:type schema:PropertyValue
72 N4cd098ba86da4b02ac0941df9a2777a1 schema:affiliation https://www.grid.ac/institutes/grid.5196.b
73 schema:familyName Colao
74 schema:givenName Francesco
75 rdf:type schema:Person
76 N8b9161f6426d4c5089a17682bf2a90f3 schema:affiliation https://www.grid.ac/institutes/grid.5196.b
77 schema:familyName Artuso
78 schema:givenName Florinda
79 rdf:type schema:Person
80 N8f14642703d44753949bd80f998a0096 schema:affiliation https://www.grid.ac/institutes/grid.5196.b
81 schema:familyName Fiorani
82 schema:givenName Luca
83 rdf:type schema:Person
84 N953db13cbccb459f92c23f6c6c04359a schema:name Springer Nature - SN SciGraph project
85 rdf:type schema:Organization
86 Nb7d7b671f6f148249834c16e61f55e3b schema:volumeNumber 13
87 rdf:type schema:PublicationVolume
88 Nd29c35597e6345b9a0d00747a80f2f76 rdf:first Ne860f36e9b55469c8f1f6a022cad6539
89 rdf:rest N326b19687c474fc99dcfef1630403733
90 Ne644f50be50e472ea0d1c0800496d93a schema:name dimensions_id
91 schema:value pub.1112215493
92 rdf:type schema:PropertyValue
93 Ne860f36e9b55469c8f1f6a022cad6539 schema:affiliation https://www.grid.ac/institutes/grid.5196.b
94 schema:familyName Cataldi
95 schema:givenName Dario
96 rdf:type schema:Person
97 Nef90e64b98d04c48a36118535a00a6e5 schema:name readcube_id
98 schema:value 5becc6742dfa347f0a692755e55187e7f251120882f8c586e0a4bbef57af101d
99 rdf:type schema:PropertyValue
100 Nf153727e4e904f9ebab69edad50a8728 schema:affiliation https://www.grid.ac/institutes/grid.5196.b
101 schema:familyName Angelini
102 schema:givenName Federico
103 rdf:type schema:Person
104 Nf6330a658f454cbfa2ecfbc981cfd0cf rdf:first Nf153727e4e904f9ebab69edad50a8728
105 rdf:rest N294e5fabf560498b8905e9df133721c9
106 anzsrc-for:06 schema:inDefinedTermSet anzsrc-for:
107 schema:name Biological Sciences
108 rdf:type schema:DefinedTerm
109 anzsrc-for:0607 schema:inDefinedTermSet anzsrc-for:
110 schema:name Plant Biology
111 rdf:type schema:DefinedTerm
112 sg:journal.1047339 schema:issn 1735-6865
113 2008-2304
114 schema:name International Journal of Environmental Research
115 rdf:type schema:Periodical
116 sg:pub.10.1007/978-3-642-55844-3_5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051410769
117 https://doi.org/10.1007/978-3-642-55844-3_5
118 rdf:type schema:CreativeWork
119 sg:pub.10.1007/s10750-012-1149-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051043631
120 https://doi.org/10.1007/s10750-012-1149-2
121 rdf:type schema:CreativeWork
122 sg:pub.10.1007/s11120-006-9065-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052683290
123 https://doi.org/10.1007/s11120-006-9065-9
124 rdf:type schema:CreativeWork
125 https://doi.org/10.1016/j.dsr2.2008.09.017 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001319870
126 rdf:type schema:CreativeWork
127 https://doi.org/10.1016/j.jmarsys.2016.10.010 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007423800
128 rdf:type schema:CreativeWork
129 https://doi.org/10.1016/j.pocean.2013.12.008 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016393329
130 rdf:type schema:CreativeWork
131 https://doi.org/10.1016/j.rse.2008.03.011 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012974618
132 rdf:type schema:CreativeWork
133 https://doi.org/10.1016/j.rse.2009.11.022 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025476269
134 rdf:type schema:CreativeWork
135 https://doi.org/10.1016/j.rse.2011.11.013 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017712279
136 rdf:type schema:CreativeWork
137 https://doi.org/10.1016/s0378-4347(00)00603-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044472632
138 rdf:type schema:CreativeWork
139 https://doi.org/10.1016/s0967-0637(00)00045-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023095530
140 rdf:type schema:CreativeWork
141 https://doi.org/10.1017/s095410200300107x schema:sameAs https://app.dimensions.ai/details/publication/pub.1021952999
142 rdf:type schema:CreativeWork
143 https://doi.org/10.1029/2005jc003207 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017502843
144 rdf:type schema:CreativeWork
145 https://doi.org/10.1029/2006jc003816 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024047449
146 rdf:type schema:CreativeWork
147 https://doi.org/10.1029/2007jc004551 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025357683
148 rdf:type schema:CreativeWork
149 https://doi.org/10.1029/2008gl035624 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028056973
150 rdf:type schema:CreativeWork
151 https://doi.org/10.1029/2009gb003680 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023536061
152 rdf:type schema:CreativeWork
153 https://doi.org/10.1046/j.1365-3040.1999.00419.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1036640520
154 rdf:type schema:CreativeWork
155 https://doi.org/10.1080/0143116021000047938 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016609911
156 rdf:type schema:CreativeWork
157 https://doi.org/10.1080/0143116021000053797 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010161086
158 rdf:type schema:CreativeWork
159 https://doi.org/10.1080/01431161.2016.1204479 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001128095
160 rdf:type schema:CreativeWork
161 https://doi.org/10.1080/01431161.2016.1274446 schema:sameAs https://app.dimensions.ai/details/publication/pub.1083924818
162 rdf:type schema:CreativeWork
163 https://doi.org/10.1098/rstb.2010.0125 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015149421
164 rdf:type schema:CreativeWork
165 https://doi.org/10.1111/gcb.12623 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043071491
166 rdf:type schema:CreativeWork
167 https://doi.org/10.1126/science.227.4683.163 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062529671
168 rdf:type schema:CreativeWork
169 https://doi.org/10.1146/annurev-marine-010213-135114 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022166679
170 rdf:type schema:CreativeWork
171 https://doi.org/10.1364/ao.37.003222 schema:sameAs https://app.dimensions.ai/details/publication/pub.1065113228
172 rdf:type schema:CreativeWork
173 https://doi.org/10.1364/ao.42.002767 schema:sameAs https://app.dimensions.ai/details/publication/pub.1065118145
174 rdf:type schema:CreativeWork
175 https://doi.org/10.1371/journal.pone.0176033 schema:sameAs https://app.dimensions.ai/details/publication/pub.1085008907
176 rdf:type schema:CreativeWork
177 https://doi.org/10.3354/meps077183 schema:sameAs https://app.dimensions.ai/details/publication/pub.1071167606
178 rdf:type schema:CreativeWork
179 https://doi.org/10.4319/lo.1982.27.2.0218 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050226309
180 rdf:type schema:CreativeWork
181 https://doi.org/10.4319/lo.2000.45.5.1130 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022744438
182 rdf:type schema:CreativeWork
183 https://doi.org/10.5670/oceanog.2001.06 schema:sameAs https://app.dimensions.ai/details/publication/pub.1073067111
184 rdf:type schema:CreativeWork
185 https://doi.org/10.5670/oceanog.2012.80 schema:sameAs https://app.dimensions.ai/details/publication/pub.1073068152
186 rdf:type schema:CreativeWork
187 https://www.grid.ac/institutes/grid.5196.b schema:alternateName National Agency For New Technologies, Energy and Sustainable Economic Development
188 schema:name Nuclear Fusion and Safety Technologies Department, ENEA, Via Enrico Fermi 45, 00044, Frascati, Italy
189 rdf:type schema:Organization
 




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


...