Models and Their Adaptation View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2011

AUTHORS

Zoltán Somogyi , Dóra Hidy , Györgyi Gelybó , Zoltán Barcza , Galina Churkina , László Haszpra , László Horváth , Attila Machon , Balázs Grosz

ABSTRACT

This chapter describes computer simulation models developed for ­estimating greenhouse gas fluxes of different ecosystems. In general, each model is used for the simulation of specific parts of the complex systems; therefore, merging the results of various kind of models can give a better insight. In this chapter, we describe four models used for estimating biospheric fluxes of greenhouse gases in Hungary. The Biome-BGC and the DNDC models are process-based ecological models. The adapted version of Biome-BGC is capable of describing the carbon, nitrogen, and water fluxes of the Hungarian arable lands and grasslands. This model is used to estimate the net primary production (NPP) and the net biome production. DNDC is used to predict the soil fluxes of nitrous oxide and methane, and simulates the biogeochemical cycles of carbon and nitrogen occurring in agricultural soil. MOD17 is a simple lightweight model that is based on remote sensing and ancillary meteorological information, and provides gross primary production (GPP) and NPP data. The CASMOFOR model was developed to estimate how much carbon can be accumulated in afforestation projects. More... »

PAGES

201-228

References to SciGraph publications

Book

TITLE

Atmospheric Greenhouse Gases: The Hungarian Perspective

ISBN

978-90-481-9949-5
978-90-481-9950-1

From Grant

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-90-481-9950-1_9

DOI

http://dx.doi.org/10.1007/978-90-481-9950-1_9

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1035745999


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/2008/0503", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Soil Sciences", 
        "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": "Forest Research Institute", 
          "id": "https://www.grid.ac/institutes/grid.481832.4", 
          "name": [
            "Hungarian Forest Research Institute, H-1142\u00a0Budapest, Stef\u00e1nia \u00fat. 14., Hungary"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Somogyi", 
        "givenName": "Zolt\u00e1n", 
        "id": "sg:person.012054065251.48", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012054065251.48"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Hungarian Meteorological Service", 
          "id": "https://www.grid.ac/institutes/grid.425672.0", 
          "name": [
            "Hungarian Meteorological Service, H-1675\u00a0Budapest, 39, Hungary"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Hidy", 
        "givenName": "D\u00f3ra", 
        "id": "sg:person.01257573077.74", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01257573077.74"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "E\u00f6tv\u00f6s Lor\u00e1nd University", 
          "id": "https://www.grid.ac/institutes/grid.5591.8", 
          "name": [
            "Department of Meteorology, E\u00f6tv\u00f6s Lor\u00e1nd University, H-1117\u00a0Budapest, P\u00e1zm\u00e1ny P. s. 1/A, Hungary"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Gelyb\u00f3", 
        "givenName": "Gy\u00f6rgyi", 
        "id": "sg:person.013777201417.40", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013777201417.40"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "E\u00f6tv\u00f6s Lor\u00e1nd University", 
          "id": "https://www.grid.ac/institutes/grid.5591.8", 
          "name": [
            "Department of Meteorology, E\u00f6tv\u00f6s Lor\u00e1nd University, H-1117\u00a0Budapest, P\u00e1zm\u00e1ny P. s. 1/A, Hungary"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Barcza", 
        "givenName": "Zolt\u00e1n", 
        "id": "sg:person.01200273207.36", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01200273207.36"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Leibniz Centre for Agricultural Landscape Research", 
          "id": "https://www.grid.ac/institutes/grid.433014.1", 
          "name": [
            "Leibniz-Centre for Agricultural Landscape Research, D-15374\u00a0M\u00fcncheberg, Eberswalder Strasse 84, Germany"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Churkina", 
        "givenName": "Galina", 
        "id": "sg:person.015411075556.48", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015411075556.48"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Hungarian Meteorological Service", 
          "id": "https://www.grid.ac/institutes/grid.425672.0", 
          "name": [
            "Hungarian Meteorological Service, H-1675\u00a0Budapest, 39, Hungary"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Haszpra", 
        "givenName": "L\u00e1szl\u00f3", 
        "id": "sg:person.010630213426.23", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010630213426.23"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Hungarian Meteorological Service", 
          "id": "https://www.grid.ac/institutes/grid.425672.0", 
          "name": [
            "Hungarian Meteorological Service, H-1675\u00a0Budapest, 39, Hungary"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Horv\u00e1th", 
        "givenName": "L\u00e1szl\u00f3", 
        "id": "sg:person.012262476147.78", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012262476147.78"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Hungarian Meteorological Service", 
          "id": "https://www.grid.ac/institutes/grid.425672.0", 
          "name": [
            "Hungarian Meteorological Service, H-1675\u00a0Budapest, 39, Hungary"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Machon", 
        "givenName": "Attila", 
        "id": "sg:person.015750757722.70", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015750757722.70"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "E\u00f6tv\u00f6s Lor\u00e1nd University", 
          "id": "https://www.grid.ac/institutes/grid.5591.8", 
          "name": [
            "Department of General and Inorganic Chemistry, E\u00f6tv\u00f6s Lor\u00e1nd University, H-1117\u00a0Budapest, P\u00e1zm\u00e1ny P. s. 1/A, Hungary"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Grosz", 
        "givenName": "Bal\u00e1zs", 
        "id": "sg:person.07503031661.45", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07503031661.45"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1093/treephys/9.1-2.147", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000826009"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.agrformet.2009.07.009", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001032629"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/treephys/26.6.807", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002471246"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/treephys/25.7.873", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1002732473"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/jpe/rtp005", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006037134"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/jpe/rtp005", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006037134"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1175/1087-3562(2000)004<0003:pasaot>2.0.co;2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1007032336"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.eja.2004.02.002", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016603016"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/94jb03097", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018300099"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0304-3800(88)90112-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1019499690"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0304-3800(88)90112-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1019499690"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf00386231", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032536189", 
          "https://doi.org/10.1007/bf00386231"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf00386231", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032536189", 
          "https://doi.org/10.1007/bf00386231"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/2004jg000004", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034205768"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/2004jg000004", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034205768"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.5194/hess-3-477-1999", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034790936"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.5194/hess-3-477-1999", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034790936"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10342-006-0125-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035627671", 
          "https://doi.org/10.1007/s10342-006-0125-7"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1098/rstb.1977.0140", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039498064"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.rse.2004.12.011", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1041903085"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/1467-9868.00294", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042110240"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1023/a:1009859006242", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043091008", 
          "https://doi.org/10.1023/a:1009859006242"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.1365-2486.2005.00930.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043274284"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.agrformet.2003.09.009", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044976260"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0168-1923(00)00170-2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050846224"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.agrformet.2005.04.005", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052962499"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.agrformet.2005.04.005", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052962499"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s00704-004-0080-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053632174", 
          "https://doi.org/10.1007/s00704-004-0080-5"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1063/1.1699114", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1057769646"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/jexbot/49.suppl_1.419", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1059785002"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2307/2401901", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1069911654"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3354/cr008183", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1071158572"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3354/cr021001", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1071159472"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2011", 
    "datePublishedReg": "2011-01-01", 
    "description": "This chapter describes computer simulation models developed for \u00adestimating greenhouse gas fluxes of different ecosystems. In general, each model is used for the simulation of specific parts of the complex systems; therefore, merging the results of various kind of models can give a better insight. In this chapter, we describe four models used for estimating biospheric fluxes of greenhouse gases in Hungary. The Biome-BGC and the DNDC models are process-based ecological models. The adapted version of Biome-BGC is capable of describing the carbon, nitrogen, and water fluxes of the Hungarian arable lands and grasslands. This model is used to estimate the net primary production (NPP) and the net biome production. DNDC is used to predict the soil fluxes of nitrous oxide and methane, and simulates the biogeochemical cycles of carbon and nitrogen occurring in agricultural soil. MOD17 is a simple lightweight model that is based on remote sensing and ancillary meteorological information, and provides gross primary production (GPP) and NPP data. The CASMOFOR model was developed to estimate how much carbon can be accumulated in afforestation projects.", 
    "editor": [
      {
        "familyName": "Haszpra", 
        "givenName": "L\u00e1szl\u00f3", 
        "type": "Person"
      }
    ], 
    "genre": "chapter", 
    "id": "sg:pub.10.1007/978-90-481-9950-1_9", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isFundedItemOf": [
      {
        "id": "sg:grant.3750284", 
        "type": "MonetaryGrant"
      }
    ], 
    "isPartOf": {
      "isbn": [
        "978-90-481-9949-5", 
        "978-90-481-9950-1"
      ], 
      "name": "Atmospheric Greenhouse Gases: The Hungarian Perspective", 
      "type": "Book"
    }, 
    "name": "Models and Their Adaptation", 
    "pagination": "201-228", 
    "productId": [
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/978-90-481-9950-1_9"
        ]
      }, 
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "aa47f32f97cd04663aa634a6dd57da147802084e7f741fa1eefa7f97119e5d8d"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1035745999"
        ]
      }
    ], 
    "publisher": {
      "location": "Dordrecht", 
      "name": "Springer Netherlands", 
      "type": "Organisation"
    }, 
    "sameAs": [
      "https://doi.org/10.1007/978-90-481-9950-1_9", 
      "https://app.dimensions.ai/details/publication/pub.1035745999"
    ], 
    "sdDataset": "chapters", 
    "sdDatePublished": "2019-04-15T22:56", 
    "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/v90/0000000001_0000000264/records_8695_00000265.jsonl", 
    "type": "Chapter", 
    "url": "http://link.springer.com/10.1007/978-90-481-9950-1_9"
  }
]
 

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.10.1007/978-90-481-9950-1_9'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-90-481-9950-1_9'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-90-481-9950-1_9'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-90-481-9950-1_9'


 

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

218 TRIPLES      23 PREDICATES      54 URIs      20 LITERALS      8 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/978-90-481-9950-1_9 schema:about anzsrc-for:05
2 anzsrc-for:0503
3 schema:author Na1563d6186ce461eaffb92c45487ebae
4 schema:citation sg:pub.10.1007/bf00386231
5 sg:pub.10.1007/s00704-004-0080-5
6 sg:pub.10.1007/s10342-006-0125-7
7 sg:pub.10.1023/a:1009859006242
8 https://doi.org/10.1016/0304-3800(88)90112-3
9 https://doi.org/10.1016/j.agrformet.2003.09.009
10 https://doi.org/10.1016/j.agrformet.2005.04.005
11 https://doi.org/10.1016/j.agrformet.2009.07.009
12 https://doi.org/10.1016/j.eja.2004.02.002
13 https://doi.org/10.1016/j.rse.2004.12.011
14 https://doi.org/10.1016/s0168-1923(00)00170-2
15 https://doi.org/10.1029/2004jg000004
16 https://doi.org/10.1029/94jb03097
17 https://doi.org/10.1063/1.1699114
18 https://doi.org/10.1093/jexbot/49.suppl_1.419
19 https://doi.org/10.1093/jpe/rtp005
20 https://doi.org/10.1093/treephys/25.7.873
21 https://doi.org/10.1093/treephys/26.6.807
22 https://doi.org/10.1093/treephys/9.1-2.147
23 https://doi.org/10.1098/rstb.1977.0140
24 https://doi.org/10.1111/1467-9868.00294
25 https://doi.org/10.1111/j.1365-2486.2005.00930.x
26 https://doi.org/10.1175/1087-3562(2000)004<0003:pasaot>2.0.co;2
27 https://doi.org/10.2307/2401901
28 https://doi.org/10.3354/cr008183
29 https://doi.org/10.3354/cr021001
30 https://doi.org/10.5194/hess-3-477-1999
31 schema:datePublished 2011
32 schema:datePublishedReg 2011-01-01
33 schema:description This chapter describes computer simulation models developed for ­estimating greenhouse gas fluxes of different ecosystems. In general, each model is used for the simulation of specific parts of the complex systems; therefore, merging the results of various kind of models can give a better insight. In this chapter, we describe four models used for estimating biospheric fluxes of greenhouse gases in Hungary. The Biome-BGC and the DNDC models are process-based ecological models. The adapted version of Biome-BGC is capable of describing the carbon, nitrogen, and water fluxes of the Hungarian arable lands and grasslands. This model is used to estimate the net primary production (NPP) and the net biome production. DNDC is used to predict the soil fluxes of nitrous oxide and methane, and simulates the biogeochemical cycles of carbon and nitrogen occurring in agricultural soil. MOD17 is a simple lightweight model that is based on remote sensing and ancillary meteorological information, and provides gross primary production (GPP) and NPP data. The CASMOFOR model was developed to estimate how much carbon can be accumulated in afforestation projects.
34 schema:editor N80546a631f9643b98b649e5f065d6647
35 schema:genre chapter
36 schema:inLanguage en
37 schema:isAccessibleForFree false
38 schema:isPartOf Nb844368fb7c44e6ab113d3370e9f724d
39 schema:name Models and Their Adaptation
40 schema:pagination 201-228
41 schema:productId N3568f62a8b9b4d148de5196286ae1f51
42 N69b18b6aedb84e8e892f1db1f1afe73c
43 Nb2c8dae99fc44b428a7e88721538aa1e
44 schema:publisher N51f3b5f7dbc34b73ba171665313d2bba
45 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035745999
46 https://doi.org/10.1007/978-90-481-9950-1_9
47 schema:sdDatePublished 2019-04-15T22:56
48 schema:sdLicense https://scigraph.springernature.com/explorer/license/
49 schema:sdPublisher Nb235d2956c2a42be8b177821620f3c32
50 schema:url http://link.springer.com/10.1007/978-90-481-9950-1_9
51 sgo:license sg:explorer/license/
52 sgo:sdDataset chapters
53 rdf:type schema:Chapter
54 N1df0accf5266467da925cbe39e1de703 rdf:first sg:person.013777201417.40
55 rdf:rest Nd36f57c08f2147149c1856da4a8f7222
56 N259f07a2e0c14448915afa6f36c361ab rdf:first sg:person.015411075556.48
57 rdf:rest Nd10188bf6db947ac8a48c7b46319ac90
58 N3568f62a8b9b4d148de5196286ae1f51 schema:name dimensions_id
59 schema:value pub.1035745999
60 rdf:type schema:PropertyValue
61 N51f3b5f7dbc34b73ba171665313d2bba schema:location Dordrecht
62 schema:name Springer Netherlands
63 rdf:type schema:Organisation
64 N69b18b6aedb84e8e892f1db1f1afe73c schema:name doi
65 schema:value 10.1007/978-90-481-9950-1_9
66 rdf:type schema:PropertyValue
67 N6e9a49e2f5814da3b33c50559bf4b57e rdf:first sg:person.015750757722.70
68 rdf:rest N9dafc78443b54202a9b1f3521ea260f9
69 N783d0a77b10d49b1a67dc49e88a6ed40 schema:familyName Haszpra
70 schema:givenName László
71 rdf:type schema:Person
72 N80546a631f9643b98b649e5f065d6647 rdf:first N783d0a77b10d49b1a67dc49e88a6ed40
73 rdf:rest rdf:nil
74 N9dafc78443b54202a9b1f3521ea260f9 rdf:first sg:person.07503031661.45
75 rdf:rest rdf:nil
76 Na1563d6186ce461eaffb92c45487ebae rdf:first sg:person.012054065251.48
77 rdf:rest Nd33a560a236d409ab7b0e795d08d11f3
78 Nb235d2956c2a42be8b177821620f3c32 schema:name Springer Nature - SN SciGraph project
79 rdf:type schema:Organization
80 Nb2c8dae99fc44b428a7e88721538aa1e schema:name readcube_id
81 schema:value aa47f32f97cd04663aa634a6dd57da147802084e7f741fa1eefa7f97119e5d8d
82 rdf:type schema:PropertyValue
83 Nb844368fb7c44e6ab113d3370e9f724d schema:isbn 978-90-481-9949-5
84 978-90-481-9950-1
85 schema:name Atmospheric Greenhouse Gases: The Hungarian Perspective
86 rdf:type schema:Book
87 Nd10188bf6db947ac8a48c7b46319ac90 rdf:first sg:person.010630213426.23
88 rdf:rest Nd7a1b63c516c4213b792d6a819ad8e48
89 Nd33a560a236d409ab7b0e795d08d11f3 rdf:first sg:person.01257573077.74
90 rdf:rest N1df0accf5266467da925cbe39e1de703
91 Nd36f57c08f2147149c1856da4a8f7222 rdf:first sg:person.01200273207.36
92 rdf:rest N259f07a2e0c14448915afa6f36c361ab
93 Nd7a1b63c516c4213b792d6a819ad8e48 rdf:first sg:person.012262476147.78
94 rdf:rest N6e9a49e2f5814da3b33c50559bf4b57e
95 anzsrc-for:05 schema:inDefinedTermSet anzsrc-for:
96 schema:name Environmental Sciences
97 rdf:type schema:DefinedTerm
98 anzsrc-for:0503 schema:inDefinedTermSet anzsrc-for:
99 schema:name Soil Sciences
100 rdf:type schema:DefinedTerm
101 sg:grant.3750284 http://pending.schema.org/fundedItem sg:pub.10.1007/978-90-481-9950-1_9
102 rdf:type schema:MonetaryGrant
103 sg:person.010630213426.23 schema:affiliation https://www.grid.ac/institutes/grid.425672.0
104 schema:familyName Haszpra
105 schema:givenName László
106 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010630213426.23
107 rdf:type schema:Person
108 sg:person.01200273207.36 schema:affiliation https://www.grid.ac/institutes/grid.5591.8
109 schema:familyName Barcza
110 schema:givenName Zoltán
111 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01200273207.36
112 rdf:type schema:Person
113 sg:person.012054065251.48 schema:affiliation https://www.grid.ac/institutes/grid.481832.4
114 schema:familyName Somogyi
115 schema:givenName Zoltán
116 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012054065251.48
117 rdf:type schema:Person
118 sg:person.012262476147.78 schema:affiliation https://www.grid.ac/institutes/grid.425672.0
119 schema:familyName Horváth
120 schema:givenName László
121 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012262476147.78
122 rdf:type schema:Person
123 sg:person.01257573077.74 schema:affiliation https://www.grid.ac/institutes/grid.425672.0
124 schema:familyName Hidy
125 schema:givenName Dóra
126 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01257573077.74
127 rdf:type schema:Person
128 sg:person.013777201417.40 schema:affiliation https://www.grid.ac/institutes/grid.5591.8
129 schema:familyName Gelybó
130 schema:givenName Györgyi
131 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013777201417.40
132 rdf:type schema:Person
133 sg:person.015411075556.48 schema:affiliation https://www.grid.ac/institutes/grid.433014.1
134 schema:familyName Churkina
135 schema:givenName Galina
136 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015411075556.48
137 rdf:type schema:Person
138 sg:person.015750757722.70 schema:affiliation https://www.grid.ac/institutes/grid.425672.0
139 schema:familyName Machon
140 schema:givenName Attila
141 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015750757722.70
142 rdf:type schema:Person
143 sg:person.07503031661.45 schema:affiliation https://www.grid.ac/institutes/grid.5591.8
144 schema:familyName Grosz
145 schema:givenName Balázs
146 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07503031661.45
147 rdf:type schema:Person
148 sg:pub.10.1007/bf00386231 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032536189
149 https://doi.org/10.1007/bf00386231
150 rdf:type schema:CreativeWork
151 sg:pub.10.1007/s00704-004-0080-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053632174
152 https://doi.org/10.1007/s00704-004-0080-5
153 rdf:type schema:CreativeWork
154 sg:pub.10.1007/s10342-006-0125-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035627671
155 https://doi.org/10.1007/s10342-006-0125-7
156 rdf:type schema:CreativeWork
157 sg:pub.10.1023/a:1009859006242 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043091008
158 https://doi.org/10.1023/a:1009859006242
159 rdf:type schema:CreativeWork
160 https://doi.org/10.1016/0304-3800(88)90112-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019499690
161 rdf:type schema:CreativeWork
162 https://doi.org/10.1016/j.agrformet.2003.09.009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044976260
163 rdf:type schema:CreativeWork
164 https://doi.org/10.1016/j.agrformet.2005.04.005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052962499
165 rdf:type schema:CreativeWork
166 https://doi.org/10.1016/j.agrformet.2009.07.009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001032629
167 rdf:type schema:CreativeWork
168 https://doi.org/10.1016/j.eja.2004.02.002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016603016
169 rdf:type schema:CreativeWork
170 https://doi.org/10.1016/j.rse.2004.12.011 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041903085
171 rdf:type schema:CreativeWork
172 https://doi.org/10.1016/s0168-1923(00)00170-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050846224
173 rdf:type schema:CreativeWork
174 https://doi.org/10.1029/2004jg000004 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034205768
175 rdf:type schema:CreativeWork
176 https://doi.org/10.1029/94jb03097 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018300099
177 rdf:type schema:CreativeWork
178 https://doi.org/10.1063/1.1699114 schema:sameAs https://app.dimensions.ai/details/publication/pub.1057769646
179 rdf:type schema:CreativeWork
180 https://doi.org/10.1093/jexbot/49.suppl_1.419 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059785002
181 rdf:type schema:CreativeWork
182 https://doi.org/10.1093/jpe/rtp005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006037134
183 rdf:type schema:CreativeWork
184 https://doi.org/10.1093/treephys/25.7.873 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002732473
185 rdf:type schema:CreativeWork
186 https://doi.org/10.1093/treephys/26.6.807 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002471246
187 rdf:type schema:CreativeWork
188 https://doi.org/10.1093/treephys/9.1-2.147 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000826009
189 rdf:type schema:CreativeWork
190 https://doi.org/10.1098/rstb.1977.0140 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039498064
191 rdf:type schema:CreativeWork
192 https://doi.org/10.1111/1467-9868.00294 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042110240
193 rdf:type schema:CreativeWork
194 https://doi.org/10.1111/j.1365-2486.2005.00930.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1043274284
195 rdf:type schema:CreativeWork
196 https://doi.org/10.1175/1087-3562(2000)004<0003:pasaot>2.0.co;2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007032336
197 rdf:type schema:CreativeWork
198 https://doi.org/10.2307/2401901 schema:sameAs https://app.dimensions.ai/details/publication/pub.1069911654
199 rdf:type schema:CreativeWork
200 https://doi.org/10.3354/cr008183 schema:sameAs https://app.dimensions.ai/details/publication/pub.1071158572
201 rdf:type schema:CreativeWork
202 https://doi.org/10.3354/cr021001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1071159472
203 rdf:type schema:CreativeWork
204 https://doi.org/10.5194/hess-3-477-1999 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034790936
205 rdf:type schema:CreativeWork
206 https://www.grid.ac/institutes/grid.425672.0 schema:alternateName Hungarian Meteorological Service
207 schema:name Hungarian Meteorological Service, H-1675 Budapest, 39, Hungary
208 rdf:type schema:Organization
209 https://www.grid.ac/institutes/grid.433014.1 schema:alternateName Leibniz Centre for Agricultural Landscape Research
210 schema:name Leibniz-Centre for Agricultural Landscape Research, D-15374 Müncheberg, Eberswalder Strasse 84, Germany
211 rdf:type schema:Organization
212 https://www.grid.ac/institutes/grid.481832.4 schema:alternateName Forest Research Institute
213 schema:name Hungarian Forest Research Institute, H-1142 Budapest, Stefánia út. 14., Hungary
214 rdf:type schema:Organization
215 https://www.grid.ac/institutes/grid.5591.8 schema:alternateName Eötvös Loránd University
216 schema:name Department of General and Inorganic Chemistry, Eötvös Loránd University, H-1117 Budapest, Pázmány P. s. 1/A, Hungary
217 Department of Meteorology, Eötvös Loránd University, H-1117 Budapest, Pázmány P. s. 1/A, Hungary
218 rdf:type schema:Organization
 




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


...