Biogeochemical impact of TAIGA flux to deep sea environment View Homepage


Ontology type: schema:MonetaryGrant     


Grant Info

YEARS

2008-2012

FUNDING AMOUNT

127010000 JPY

ABSTRACT

To estimate the impacts of deep-sea hydrothermal activity (TAIGA), we quantified the chemical, biological, and ecological parameters of deep-sea hydrothermal plume in time and space. We developed in situ sensors, water sampler, and acoustic survey methods to observe the plume. These methods were applied at the 18 hydrothermal area using research vessels with AUV, ROV, submersible, or wired deep-tow. We found the strong positive correlation between microbial community structures and hydrothermal chemical compositions, which validate the evidence for ‘4 types of TAIGA hypothesis’. We developed the methods to measure the primary production of microbes in deep-sea and estimate the primary production rate in the plume. We found the evidence that the microbial primary production affected the zooplankton in deep sea by stable isotopic analysis. More... »

URL

https://kaken.nii.ac.jp/grant/KAKENHI-PLANNED-20109003

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/2008/2206", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "type": "DefinedTerm"
      }
    ], 
    "amount": {
      "currency": "JPY", 
      "type": "MonetaryAmount", 
      "value": "127010000"
    }, 
    "description": "To estimate the impacts of deep-sea hydrothermal activity (TAIGA), we quantified the chemical, biological, and ecological parameters of deep-sea hydrothermal plume in time and space. We developed in situ sensors, water sampler, and acoustic survey methods to observe the plume. These methods were applied at the 18 hydrothermal area using research vessels with AUV, ROV, submersible, or wired deep-tow. We found the strong positive correlation between microbial community structures and hydrothermal chemical compositions, which validate the evidence for \u20184 types of TAIGA hypothesis\u2019. We developed the methods to measure the primary production of microbes in deep-sea and estimate the primary production rate in the plume. We found the evidence that the microbial primary production affected the zooplankton in deep sea by stable isotopic analysis.", 
    "endDate": "2012-12-31T00:00:00Z", 
    "funder": {
      "id": "https://www.grid.ac/institutes/grid.54432.34", 
      "type": "Organization"
    }, 
    "id": "sg:grant.5994754", 
    "identifier": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "5994754"
        ]
      }, 
      {
        "name": "kaken_id", 
        "type": "PropertyValue", 
        "value": [
          "20109003"
        ]
      }
    ], 
    "inLanguage": [
      "en"
    ], 
    "keywords": [
      "plume", 
      "TAIGA flux", 
      "research vessel", 
      "hydrothermal areas", 
      "biogeochemical impacts", 
      "deep sea environment", 
      "evidence", 
      "AUV", 
      "situ sensors", 
      "ecological parameters", 
      "hydrothermal chemical compositions", 
      "primary production rates", 
      "water samplers", 
      "ROV", 
      "acoustic survey methods", 
      "deep sea", 
      "zooplankton", 
      "chemical", 
      "taiga", 
      "deep-sea hydrothermal plume", 
      "space", 
      "METHODS", 
      "microbes", 
      "microbial community structure", 
      "microbial primary production", 
      "strong positive correlation", 
      "type", 
      "deep-sea hydrothermal activity", 
      "stable isotopic analysis", 
      "TAIGA hypothesis\u2019.", 
      "impact", 
      "tow", 
      "submersible", 
      "time", 
      "primary production"
    ], 
    "name": "Biogeochemical impact of TAIGA flux to deep sea environment", 
    "recipient": [
      {
        "id": "https://www.grid.ac/institutes/grid.26999.3d", 
        "type": "Organization"
      }
    ], 
    "sameAs": [
      "https://app.dimensions.ai/details/grant/grant.5994754"
    ], 
    "sdDataset": "grants", 
    "sdDatePublished": "2021-01-20T02:25", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com.uberresearch.data.processor/core_data/20181219_192338/projects/base/kaken_projects_24.xml.gz", 
    "startDate": "2008-01-01T00:00:00Z", 
    "type": "MonetaryGrant", 
    "url": "https://kaken.nii.ac.jp/grant/KAKENHI-PLANNED-20109003"
  }
]
 

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/grant.5994754'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/grant.5994754'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/grant.5994754'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/grant.5994754'


 

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

69 TRIPLES      19 PREDICATES      55 URIs      48 LITERALS      4 BLANK NODES

Subject Predicate Object
1 sg:grant.5994754 schema:about anzsrc-for:2206
2 schema:amount N0c48c2a3f806451dbd02c864163fb035
3 schema:description To estimate the impacts of deep-sea hydrothermal activity (TAIGA), we quantified the chemical, biological, and ecological parameters of deep-sea hydrothermal plume in time and space. We developed in situ sensors, water sampler, and acoustic survey methods to observe the plume. These methods were applied at the 18 hydrothermal area using research vessels with AUV, ROV, submersible, or wired deep-tow. We found the strong positive correlation between microbial community structures and hydrothermal chemical compositions, which validate the evidence for ‘4 types of TAIGA hypothesis’. We developed the methods to measure the primary production of microbes in deep-sea and estimate the primary production rate in the plume. We found the evidence that the microbial primary production affected the zooplankton in deep sea by stable isotopic analysis.
4 schema:endDate 2012-12-31T00:00:00Z
5 schema:funder https://www.grid.ac/institutes/grid.54432.34
6 schema:identifier N660aa3ae84b141069df27851d3518e7f
7 Nabf90a0e88714a85a14f3a54d17a581d
8 schema:inLanguage en
9 schema:keywords AUV
10 METHODS
11 ROV
12 TAIGA flux
13 TAIGA hypothesis’.
14 acoustic survey methods
15 biogeochemical impacts
16 chemical
17 deep sea
18 deep sea environment
19 deep-sea hydrothermal activity
20 deep-sea hydrothermal plume
21 ecological parameters
22 evidence
23 hydrothermal areas
24 hydrothermal chemical compositions
25 impact
26 microbes
27 microbial community structure
28 microbial primary production
29 plume
30 primary production
31 primary production rates
32 research vessel
33 situ sensors
34 space
35 stable isotopic analysis
36 strong positive correlation
37 submersible
38 taiga
39 time
40 tow
41 type
42 water samplers
43 zooplankton
44 schema:name Biogeochemical impact of TAIGA flux to deep sea environment
45 schema:recipient https://www.grid.ac/institutes/grid.26999.3d
46 schema:sameAs https://app.dimensions.ai/details/grant/grant.5994754
47 schema:sdDatePublished 2021-01-20T02:25
48 schema:sdLicense https://scigraph.springernature.com/explorer/license/
49 schema:sdPublisher N76d8e508d1874a5e88a62353599441be
50 schema:startDate 2008-01-01T00:00:00Z
51 schema:url https://kaken.nii.ac.jp/grant/KAKENHI-PLANNED-20109003
52 sgo:license sg:explorer/license/
53 sgo:sdDataset grants
54 rdf:type schema:MonetaryGrant
55 N0c48c2a3f806451dbd02c864163fb035 schema:currency JPY
56 schema:value 127010000
57 rdf:type schema:MonetaryAmount
58 N660aa3ae84b141069df27851d3518e7f schema:name kaken_id
59 schema:value 20109003
60 rdf:type schema:PropertyValue
61 N76d8e508d1874a5e88a62353599441be schema:name Springer Nature - SN SciGraph project
62 rdf:type schema:Organization
63 Nabf90a0e88714a85a14f3a54d17a581d schema:name dimensions_id
64 schema:value 5994754
65 rdf:type schema:PropertyValue
66 anzsrc-for:2206 schema:inDefinedTermSet anzsrc-for:
67 rdf:type schema:DefinedTerm
68 https://www.grid.ac/institutes/grid.26999.3d schema:Organization
69 https://www.grid.ac/institutes/grid.54432.34 schema:Organization
 




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


...