Models and Their Adaptation View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2010-10-06

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

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/2008/05", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Environmental Sciences", 
        "type": "DefinedTerm"
      }, 
      {
        "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"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Hungarian Forest Research Institute, Stef\u00e1nia \u00fat. 14., H-1142, Budapest, Hungary", 
          "id": "http://www.grid.ac/institutes/grid.481832.4", 
          "name": [
            "Hungarian Forest Research Institute, Stef\u00e1nia \u00fat. 14., H-1142, Budapest, 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, 39, H-1675, Budapest, Hungary", 
          "id": "http://www.grid.ac/institutes/grid.425672.0", 
          "name": [
            "Hungarian Meteorological Service, 39, H-1675, Budapest, 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": "Department of Meteorology, E\u00f6tv\u00f6s Lor\u00e1nd University, P\u00e1zm\u00e1ny P. s. 1/A, H-1117, Budapest, Hungary", 
          "id": "http://www.grid.ac/institutes/grid.5591.8", 
          "name": [
            "Department of Meteorology, E\u00f6tv\u00f6s Lor\u00e1nd University, P\u00e1zm\u00e1ny P. s. 1/A, H-1117, Budapest, 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": "Department of Meteorology, E\u00f6tv\u00f6s Lor\u00e1nd University, P\u00e1zm\u00e1ny P. s. 1/A, H-1117, Budapest, Hungary", 
          "id": "http://www.grid.ac/institutes/grid.5591.8", 
          "name": [
            "Department of Meteorology, E\u00f6tv\u00f6s Lor\u00e1nd University, P\u00e1zm\u00e1ny P. s. 1/A, H-1117, Budapest, 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, Eberswalder Strasse 84, D-15374, M\u00fcncheberg, Germany", 
          "id": "http://www.grid.ac/institutes/grid.433014.1", 
          "name": [
            "Leibniz-Centre for Agricultural Landscape Research, Eberswalder Strasse 84, D-15374, M\u00fcncheberg, 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, 39, H-1675, Budapest, Hungary", 
          "id": "http://www.grid.ac/institutes/grid.425672.0", 
          "name": [
            "Hungarian Meteorological Service, 39, H-1675, Budapest, 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, 39, H-1675, Budapest, Hungary", 
          "id": "http://www.grid.ac/institutes/grid.425672.0", 
          "name": [
            "Hungarian Meteorological Service, 39, H-1675, Budapest, 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": "Department of Botany and Plant Physiology, Szent Istv\u00e1n University, P\u00e1ter K. u. 1., H-2103, G\u00f6d\u00f6ll\u0151, Hungary", 
          "id": "http://www.grid.ac/institutes/grid.129553.9", 
          "name": [
            "Hungarian Meteorological Service, 39, H-1675, Budapest, Hungary", 
            "Center for Environmental Science, E\u00f6tv\u00f6s Lor\u00e1nd University, P\u00e1zm\u00e1ny P. s. 1/A, H-1117, Budapest, Hungary", 
            "Department of Botany and Plant Physiology, Szent Istv\u00e1n University, P\u00e1ter K. u. 1., H-2103, G\u00f6d\u00f6ll\u0151, 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": "Department of General and Inorganic Chemistry, E\u00f6tv\u00f6s Lor\u00e1nd University, P\u00e1zm\u00e1ny P. s. 1/A, H-1117, Budapest, Hungary", 
          "id": "http://www.grid.ac/institutes/grid.5591.8", 
          "name": [
            "Department of General and Inorganic Chemistry, E\u00f6tv\u00f6s Lor\u00e1nd University, P\u00e1zm\u00e1ny P. s. 1/A, H-1117, Budapest, 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"
      }
    ], 
    "datePublished": "2010-10-06", 
    "datePublishedReg": "2010-10-06", 
    "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, 
    "isPartOf": {
      "isbn": [
        "978-90-481-9949-5", 
        "978-90-481-9950-1"
      ], 
      "name": "Atmospheric Greenhouse Gases: The Hungarian Perspective", 
      "type": "Book"
    }, 
    "keywords": [
      "net primary production", 
      "Biome-BGC", 
      "gross primary production", 
      "primary production", 
      "process-based ecological models", 
      "greenhouse gas fluxes", 
      "net biome production", 
      "DNDC model", 
      "agricultural soils", 
      "soil fluxes", 
      "different ecosystems", 
      "afforestation projects", 
      "arable land", 
      "biogeochemical cycles", 
      "gas fluxes", 
      "ecological model", 
      "NPP data", 
      "greenhouse gases", 
      "remote sensing", 
      "nitrous oxide", 
      "water flux", 
      "carbon", 
      "computer simulation model", 
      "nitrogen", 
      "biospheric fluxes", 
      "DNDC", 
      "grassland", 
      "meteorological information", 
      "simulation model", 
      "ecosystems", 
      "soil", 
      "flux", 
      "land", 
      "production", 
      "specific parts", 
      "MOD17", 
      "Hungary", 
      "methane", 
      "better insight", 
      "sensing", 
      "complex systems", 
      "adaptation", 
      "gases", 
      "project", 
      "model", 
      "cycle", 
      "kinds of models", 
      "chapter", 
      "part", 
      "information", 
      "insights", 
      "data", 
      "simulations", 
      "results", 
      "lightweight model", 
      "system", 
      "oxide", 
      "kind", 
      "adapted version", 
      "version", 
      "Hungarian arable lands", 
      "biome production", 
      "simple lightweight model", 
      "ancillary meteorological information", 
      "CASMOFOR model"
    ], 
    "name": "Models and Their Adaptation", 
    "pagination": "201-228", 
    "productId": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1035745999"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/978-90-481-9950-1_9"
        ]
      }
    ], 
    "publisher": {
      "name": "Springer Nature", 
      "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": "2021-12-01T20:11", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-springernature-scigraph/baseset/20211201/entities/gbq_results/chapter/chapter_45.jsonl", 
    "type": "Chapter", 
    "url": "https://doi.org/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.

197 TRIPLES      23 PREDICATES      89 URIs      82 LITERALS      7 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 N3bfad98ffd01430885f8520679ef2ce6
4 schema:datePublished 2010-10-06
5 schema:datePublishedReg 2010-10-06
6 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.
7 schema:editor Nbc003dd8e5384d03949d1efa02894612
8 schema:genre chapter
9 schema:inLanguage en
10 schema:isAccessibleForFree false
11 schema:isPartOf N52f9d203569a45d38e2455e568fa13f9
12 schema:keywords Biome-BGC
13 CASMOFOR model
14 DNDC
15 DNDC model
16 Hungarian arable lands
17 Hungary
18 MOD17
19 NPP data
20 adaptation
21 adapted version
22 afforestation projects
23 agricultural soils
24 ancillary meteorological information
25 arable land
26 better insight
27 biogeochemical cycles
28 biome production
29 biospheric fluxes
30 carbon
31 chapter
32 complex systems
33 computer simulation model
34 cycle
35 data
36 different ecosystems
37 ecological model
38 ecosystems
39 flux
40 gas fluxes
41 gases
42 grassland
43 greenhouse gas fluxes
44 greenhouse gases
45 gross primary production
46 information
47 insights
48 kind
49 kinds of models
50 land
51 lightweight model
52 meteorological information
53 methane
54 model
55 net biome production
56 net primary production
57 nitrogen
58 nitrous oxide
59 oxide
60 part
61 primary production
62 process-based ecological models
63 production
64 project
65 remote sensing
66 results
67 sensing
68 simple lightweight model
69 simulation model
70 simulations
71 soil
72 soil fluxes
73 specific parts
74 system
75 version
76 water flux
77 schema:name Models and Their Adaptation
78 schema:pagination 201-228
79 schema:productId N5022457a40cc4300b99995d660b180c2
80 Nc9679e888f554d5694d0c23c36172d87
81 schema:publisher Ncd4f8878bbac4d52b87078330c21d7f0
82 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035745999
83 https://doi.org/10.1007/978-90-481-9950-1_9
84 schema:sdDatePublished 2021-12-01T20:11
85 schema:sdLicense https://scigraph.springernature.com/explorer/license/
86 schema:sdPublisher Ndc3e003c844c49b4b6e43905276353d6
87 schema:url https://doi.org/10.1007/978-90-481-9950-1_9
88 sgo:license sg:explorer/license/
89 sgo:sdDataset chapters
90 rdf:type schema:Chapter
91 N0f54b6ab7ca04a189a53be5a4b50a284 rdf:first sg:person.012262476147.78
92 rdf:rest Nde6ff50d99654f0f947d2419d29ad45d
93 N194e881037454729bd84ac2355bcd4c3 rdf:first sg:person.015411075556.48
94 rdf:rest Nd735ca481d9441d18956053168baafd9
95 N2033b2164f25483781120008fefbee82 rdf:first sg:person.01200273207.36
96 rdf:rest N194e881037454729bd84ac2355bcd4c3
97 N3bfad98ffd01430885f8520679ef2ce6 rdf:first sg:person.012054065251.48
98 rdf:rest Ne1d54a5ff90a488d981b9f010017088b
99 N5022457a40cc4300b99995d660b180c2 schema:name dimensions_id
100 schema:value pub.1035745999
101 rdf:type schema:PropertyValue
102 N52f9d203569a45d38e2455e568fa13f9 schema:isbn 978-90-481-9949-5
103 978-90-481-9950-1
104 schema:name Atmospheric Greenhouse Gases: The Hungarian Perspective
105 rdf:type schema:Book
106 N9ef931fcab274d62b7c5d114837ee7c4 rdf:first sg:person.013777201417.40
107 rdf:rest N2033b2164f25483781120008fefbee82
108 Nbc003dd8e5384d03949d1efa02894612 rdf:first Ncfb89526e11e4d4d83be56e30e0e6520
109 rdf:rest rdf:nil
110 Nc9679e888f554d5694d0c23c36172d87 schema:name doi
111 schema:value 10.1007/978-90-481-9950-1_9
112 rdf:type schema:PropertyValue
113 Ncd4f8878bbac4d52b87078330c21d7f0 schema:name Springer Nature
114 rdf:type schema:Organisation
115 Ncfb89526e11e4d4d83be56e30e0e6520 schema:familyName Haszpra
116 schema:givenName László
117 rdf:type schema:Person
118 Nd735ca481d9441d18956053168baafd9 rdf:first sg:person.010630213426.23
119 rdf:rest N0f54b6ab7ca04a189a53be5a4b50a284
120 Ndc3e003c844c49b4b6e43905276353d6 schema:name Springer Nature - SN SciGraph project
121 rdf:type schema:Organization
122 Nde6ff50d99654f0f947d2419d29ad45d rdf:first sg:person.015750757722.70
123 rdf:rest Ne0096b5fcb8c424d879869b482939b63
124 Ne0096b5fcb8c424d879869b482939b63 rdf:first sg:person.07503031661.45
125 rdf:rest rdf:nil
126 Ne1d54a5ff90a488d981b9f010017088b rdf:first sg:person.01257573077.74
127 rdf:rest N9ef931fcab274d62b7c5d114837ee7c4
128 anzsrc-for:05 schema:inDefinedTermSet anzsrc-for:
129 schema:name Environmental Sciences
130 rdf:type schema:DefinedTerm
131 anzsrc-for:0503 schema:inDefinedTermSet anzsrc-for:
132 schema:name Soil Sciences
133 rdf:type schema:DefinedTerm
134 sg:person.010630213426.23 schema:affiliation grid-institutes:grid.425672.0
135 schema:familyName Haszpra
136 schema:givenName László
137 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.010630213426.23
138 rdf:type schema:Person
139 sg:person.01200273207.36 schema:affiliation grid-institutes:grid.5591.8
140 schema:familyName Barcza
141 schema:givenName Zoltán
142 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01200273207.36
143 rdf:type schema:Person
144 sg:person.012054065251.48 schema:affiliation grid-institutes:grid.481832.4
145 schema:familyName Somogyi
146 schema:givenName Zoltán
147 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012054065251.48
148 rdf:type schema:Person
149 sg:person.012262476147.78 schema:affiliation grid-institutes:grid.425672.0
150 schema:familyName Horváth
151 schema:givenName László
152 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012262476147.78
153 rdf:type schema:Person
154 sg:person.01257573077.74 schema:affiliation grid-institutes:grid.425672.0
155 schema:familyName Hidy
156 schema:givenName Dóra
157 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01257573077.74
158 rdf:type schema:Person
159 sg:person.013777201417.40 schema:affiliation grid-institutes:grid.5591.8
160 schema:familyName Gelybó
161 schema:givenName Györgyi
162 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.013777201417.40
163 rdf:type schema:Person
164 sg:person.015411075556.48 schema:affiliation grid-institutes:grid.433014.1
165 schema:familyName Churkina
166 schema:givenName Galina
167 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015411075556.48
168 rdf:type schema:Person
169 sg:person.015750757722.70 schema:affiliation grid-institutes:grid.129553.9
170 schema:familyName Machon
171 schema:givenName Attila
172 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015750757722.70
173 rdf:type schema:Person
174 sg:person.07503031661.45 schema:affiliation grid-institutes:grid.5591.8
175 schema:familyName Grosz
176 schema:givenName Balázs
177 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07503031661.45
178 rdf:type schema:Person
179 grid-institutes:grid.129553.9 schema:alternateName Department of Botany and Plant Physiology, Szent István University, Páter K. u. 1., H-2103, Gödöllő, Hungary
180 schema:name Center for Environmental Science, Eötvös Loránd University, Pázmány P. s. 1/A, H-1117, Budapest, Hungary
181 Department of Botany and Plant Physiology, Szent István University, Páter K. u. 1., H-2103, Gödöllő, Hungary
182 Hungarian Meteorological Service, 39, H-1675, Budapest, Hungary
183 rdf:type schema:Organization
184 grid-institutes:grid.425672.0 schema:alternateName Hungarian Meteorological Service, 39, H-1675, Budapest, Hungary
185 schema:name Hungarian Meteorological Service, 39, H-1675, Budapest, Hungary
186 rdf:type schema:Organization
187 grid-institutes:grid.433014.1 schema:alternateName Leibniz-Centre for Agricultural Landscape Research, Eberswalder Strasse 84, D-15374, Müncheberg, Germany
188 schema:name Leibniz-Centre for Agricultural Landscape Research, Eberswalder Strasse 84, D-15374, Müncheberg, Germany
189 rdf:type schema:Organization
190 grid-institutes:grid.481832.4 schema:alternateName Hungarian Forest Research Institute, Stefánia út. 14., H-1142, Budapest, Hungary
191 schema:name Hungarian Forest Research Institute, Stefánia út. 14., H-1142, Budapest, Hungary
192 rdf:type schema:Organization
193 grid-institutes:grid.5591.8 schema:alternateName Department of General and Inorganic Chemistry, Eötvös Loránd University, Pázmány P. s. 1/A, H-1117, Budapest, Hungary
194 Department of Meteorology, Eötvös Loránd University, Pázmány P. s. 1/A, H-1117, Budapest, Hungary
195 schema:name Department of General and Inorganic Chemistry, Eötvös Loránd University, Pázmány P. s. 1/A, H-1117, Budapest, Hungary
196 Department of Meteorology, Eötvös Loránd University, Pázmány P. s. 1/A, H-1117, Budapest, Hungary
197 rdf:type schema:Organization
 




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


...