The use of crop models for international climate change impact assessment View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

1998

AUTHORS

C. Rosenzweig , A. Iglesias

ABSTRACT

The methodology for an assessment of potential impacts of climate change on world crop production, including quantitative estimates of yield and water-use changes for major crops, is described. Agricultural scientists in 18 countries estimated potential changes in crop growth and water use using compatible crop models and consistent climate change scenarios. The crops modeled were wheat, rice, maize and soybean. Site-specific estimates of yield changes for the major crops modeled were aggregated to national levels for use in a world food trade model, the Basic Linked System. The study assessed the implications of climate change for world crop yields for arbitrary and GCM equilibrium and transient climate change scenarios. The climate change scenarios were tested with and without the direct physiological effects of CO2 on crop growth and water use, as reported in experimental literature. Climate change impacts on crop yields incorporating farm-level adaptation were also simulated, based on different assumptions about shifts in crop planting dates, changes in crop variety, and level of irrigation. More... »

PAGES

267-292

References to SciGraph publications

Book

TITLE

Understanding Options for Agricultural Production

ISBN

978-90-481-4940-7
978-94-017-3624-4

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-94-017-3624-4_13

DOI

http://dx.doi.org/10.1007/978-94-017-3624-4_13

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1017293141


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": "Goddard Institute for Space Studies", 
          "id": "https://www.grid.ac/institutes/grid.419078.3", 
          "name": [
            "Goddard Institute for Space Studies, Columbia University, 2880 Broadway, New York, New York\u00a010025, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Rosenzweig", 
        "givenName": "C.", 
        "id": "sg:person.0741100364.79", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0741100364.79"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Instituto Nacional de Investigaci\u00f3n y Tecnolog\u00eda Agraria y Alimentaria", 
          "id": "https://www.grid.ac/institutes/grid.419190.4", 
          "name": [
            "Centro de Investigaci\u00f3n Forestal, Instituto Nacional de Investigaciones Agrarias (INIA), Madrid, Spain"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Iglesias", 
        "givenName": "A.", 
        "id": "sg:person.015070010545.37", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015070010545.37"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1016/0168-1923(86)90054-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013874793"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0168-1923(86)90054-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013874793"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/gb001i001p00001", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018623130"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1175/1520-0477(1987)068<1116:otdorc>2.0.co;2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1019068339"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/j.0033-0124.1990.00020.x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022539490"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1175/1520-0493(1983)111<0609:etdgmf>2.0.co;2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022548070"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1175/1520-0469(1987)044<1211:lscosw>2.0.co;2", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025211147"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/367133a0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1028087951", 
          "https://doi.org/10.1038/367133a0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/00139157.1989.9928943", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1036700144"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1029/jd093id08p09341", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1039346451"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0168-1923(87)90038-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049322958"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0168-1923(87)90038-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049322958"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/345219a0", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053012610", 
          "https://doi.org/10.1038/345219a0"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2134/agronj1983.00021962007500050014x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1068991146"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2134/jeq1983.00472425001200040028x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1069001366"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2307/1242694", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1069409822"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3354/cr003079", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1071158331"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "1998", 
    "datePublishedReg": "1998-01-01", 
    "description": "The methodology for an assessment of potential impacts of climate change on world crop production, including quantitative estimates of yield and water-use changes for major crops, is described. Agricultural scientists in 18 countries estimated potential changes in crop growth and water use using compatible crop models and consistent climate change scenarios. The crops modeled were wheat, rice, maize and soybean. Site-specific estimates of yield changes for the major crops modeled were aggregated to national levels for use in a world food trade model, the Basic Linked System. The study assessed the implications of climate change for world crop yields for arbitrary and GCM equilibrium and transient climate change scenarios. The climate change scenarios were tested with and without the direct physiological effects of CO2 on crop growth and water use, as reported in experimental literature. Climate change impacts on crop yields incorporating farm-level adaptation were also simulated, based on different assumptions about shifts in crop planting dates, changes in crop variety, and level of irrigation.", 
    "editor": [
      {
        "familyName": "Tsuji", 
        "givenName": "Gordon Y.", 
        "type": "Person"
      }, 
      {
        "familyName": "Hoogenboom", 
        "givenName": "Gerrit", 
        "type": "Person"
      }, 
      {
        "familyName": "Thornton", 
        "givenName": "Philip K.", 
        "type": "Person"
      }
    ], 
    "genre": "chapter", 
    "id": "sg:pub.10.1007/978-94-017-3624-4_13", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": {
      "isbn": [
        "978-90-481-4940-7", 
        "978-94-017-3624-4"
      ], 
      "name": "Understanding Options for Agricultural Production", 
      "type": "Book"
    }, 
    "name": "The use of crop models for international climate change impact assessment", 
    "pagination": "267-292", 
    "productId": [
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/978-94-017-3624-4_13"
        ]
      }, 
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "526432bdfa1053506a939a8d5799446af8aeea59af0810cf04b2b5149f6952a0"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1017293141"
        ]
      }
    ], 
    "publisher": {
      "location": "Dordrecht", 
      "name": "Springer Netherlands", 
      "type": "Organisation"
    }, 
    "sameAs": [
      "https://doi.org/10.1007/978-94-017-3624-4_13", 
      "https://app.dimensions.ai/details/publication/pub.1017293141"
    ], 
    "sdDataset": "chapters", 
    "sdDatePublished": "2019-04-15T21:01", 
    "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_8690_00000253.jsonl", 
    "type": "Chapter", 
    "url": "http://link.springer.com/10.1007/978-94-017-3624-4_13"
  }
]
 

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.10.1007/978-94-017-3624-4_13'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-94-017-3624-4_13'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-94-017-3624-4_13'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-94-017-3624-4_13'


 

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

132 TRIPLES      23 PREDICATES      42 URIs      20 LITERALS      8 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/978-94-017-3624-4_13 schema:about anzsrc-for:06
2 anzsrc-for:0607
3 schema:author Nc02051eb1a7d4a59bc7f0cbc1ac0905b
4 schema:citation sg:pub.10.1038/345219a0
5 sg:pub.10.1038/367133a0
6 https://doi.org/10.1016/0168-1923(86)90054-7
7 https://doi.org/10.1016/0168-1923(87)90038-4
8 https://doi.org/10.1029/gb001i001p00001
9 https://doi.org/10.1029/jd093id08p09341
10 https://doi.org/10.1080/00139157.1989.9928943
11 https://doi.org/10.1111/j.0033-0124.1990.00020.x
12 https://doi.org/10.1175/1520-0469(1987)044<1211:lscosw>2.0.co;2
13 https://doi.org/10.1175/1520-0477(1987)068<1116:otdorc>2.0.co;2
14 https://doi.org/10.1175/1520-0493(1983)111<0609:etdgmf>2.0.co;2
15 https://doi.org/10.2134/agronj1983.00021962007500050014x
16 https://doi.org/10.2134/jeq1983.00472425001200040028x
17 https://doi.org/10.2307/1242694
18 https://doi.org/10.3354/cr003079
19 schema:datePublished 1998
20 schema:datePublishedReg 1998-01-01
21 schema:description The methodology for an assessment of potential impacts of climate change on world crop production, including quantitative estimates of yield and water-use changes for major crops, is described. Agricultural scientists in 18 countries estimated potential changes in crop growth and water use using compatible crop models and consistent climate change scenarios. The crops modeled were wheat, rice, maize and soybean. Site-specific estimates of yield changes for the major crops modeled were aggregated to national levels for use in a world food trade model, the Basic Linked System. The study assessed the implications of climate change for world crop yields for arbitrary and GCM equilibrium and transient climate change scenarios. The climate change scenarios were tested with and without the direct physiological effects of CO2 on crop growth and water use, as reported in experimental literature. Climate change impacts on crop yields incorporating farm-level adaptation were also simulated, based on different assumptions about shifts in crop planting dates, changes in crop variety, and level of irrigation.
22 schema:editor N01cf55aac6fe4868b010f43222c4fbb9
23 schema:genre chapter
24 schema:inLanguage en
25 schema:isAccessibleForFree false
26 schema:isPartOf Ncbbcf2d5037f445fb9b0a7b72390c524
27 schema:name The use of crop models for international climate change impact assessment
28 schema:pagination 267-292
29 schema:productId N1b1fa0634d3648b9b54a59299198ca34
30 N8cc8aae0d3014ec19277653a426b3324
31 Nbf98cfb1b48d4f539939ecd79b6fa223
32 schema:publisher N9c998ac4b5f04bd8b88e0cdae8571b1b
33 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017293141
34 https://doi.org/10.1007/978-94-017-3624-4_13
35 schema:sdDatePublished 2019-04-15T21:01
36 schema:sdLicense https://scigraph.springernature.com/explorer/license/
37 schema:sdPublisher Ne81f6260a3ec4ef4a13b4b6ed996a9e9
38 schema:url http://link.springer.com/10.1007/978-94-017-3624-4_13
39 sgo:license sg:explorer/license/
40 sgo:sdDataset chapters
41 rdf:type schema:Chapter
42 N01cf55aac6fe4868b010f43222c4fbb9 rdf:first N9c97444daabc4ff18f786d048c189432
43 rdf:rest Nbe208a8b793a411b8a048246efb4ad71
44 N1b1fa0634d3648b9b54a59299198ca34 schema:name doi
45 schema:value 10.1007/978-94-017-3624-4_13
46 rdf:type schema:PropertyValue
47 N265d0390a17d4271a8dbd779ca3fb76f rdf:first sg:person.015070010545.37
48 rdf:rest rdf:nil
49 N5725a1910cb644d88f3aa769d29af12d schema:familyName Thornton
50 schema:givenName Philip K.
51 rdf:type schema:Person
52 N5ecc65084b024604ab3e20430cdf2df9 rdf:first N5725a1910cb644d88f3aa769d29af12d
53 rdf:rest rdf:nil
54 N8cc8aae0d3014ec19277653a426b3324 schema:name readcube_id
55 schema:value 526432bdfa1053506a939a8d5799446af8aeea59af0810cf04b2b5149f6952a0
56 rdf:type schema:PropertyValue
57 N9c97444daabc4ff18f786d048c189432 schema:familyName Tsuji
58 schema:givenName Gordon Y.
59 rdf:type schema:Person
60 N9c998ac4b5f04bd8b88e0cdae8571b1b schema:location Dordrecht
61 schema:name Springer Netherlands
62 rdf:type schema:Organisation
63 Nbe208a8b793a411b8a048246efb4ad71 rdf:first Nd67f2c9b99a2466dbc002532ce733c02
64 rdf:rest N5ecc65084b024604ab3e20430cdf2df9
65 Nbf98cfb1b48d4f539939ecd79b6fa223 schema:name dimensions_id
66 schema:value pub.1017293141
67 rdf:type schema:PropertyValue
68 Nc02051eb1a7d4a59bc7f0cbc1ac0905b rdf:first sg:person.0741100364.79
69 rdf:rest N265d0390a17d4271a8dbd779ca3fb76f
70 Ncbbcf2d5037f445fb9b0a7b72390c524 schema:isbn 978-90-481-4940-7
71 978-94-017-3624-4
72 schema:name Understanding Options for Agricultural Production
73 rdf:type schema:Book
74 Nd67f2c9b99a2466dbc002532ce733c02 schema:familyName Hoogenboom
75 schema:givenName Gerrit
76 rdf:type schema:Person
77 Ne81f6260a3ec4ef4a13b4b6ed996a9e9 schema:name Springer Nature - SN SciGraph project
78 rdf:type schema:Organization
79 anzsrc-for:06 schema:inDefinedTermSet anzsrc-for:
80 schema:name Biological Sciences
81 rdf:type schema:DefinedTerm
82 anzsrc-for:0607 schema:inDefinedTermSet anzsrc-for:
83 schema:name Plant Biology
84 rdf:type schema:DefinedTerm
85 sg:person.015070010545.37 schema:affiliation https://www.grid.ac/institutes/grid.419190.4
86 schema:familyName Iglesias
87 schema:givenName A.
88 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015070010545.37
89 rdf:type schema:Person
90 sg:person.0741100364.79 schema:affiliation https://www.grid.ac/institutes/grid.419078.3
91 schema:familyName Rosenzweig
92 schema:givenName C.
93 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0741100364.79
94 rdf:type schema:Person
95 sg:pub.10.1038/345219a0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053012610
96 https://doi.org/10.1038/345219a0
97 rdf:type schema:CreativeWork
98 sg:pub.10.1038/367133a0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028087951
99 https://doi.org/10.1038/367133a0
100 rdf:type schema:CreativeWork
101 https://doi.org/10.1016/0168-1923(86)90054-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013874793
102 rdf:type schema:CreativeWork
103 https://doi.org/10.1016/0168-1923(87)90038-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049322958
104 rdf:type schema:CreativeWork
105 https://doi.org/10.1029/gb001i001p00001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018623130
106 rdf:type schema:CreativeWork
107 https://doi.org/10.1029/jd093id08p09341 schema:sameAs https://app.dimensions.ai/details/publication/pub.1039346451
108 rdf:type schema:CreativeWork
109 https://doi.org/10.1080/00139157.1989.9928943 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036700144
110 rdf:type schema:CreativeWork
111 https://doi.org/10.1111/j.0033-0124.1990.00020.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1022539490
112 rdf:type schema:CreativeWork
113 https://doi.org/10.1175/1520-0469(1987)044<1211:lscosw>2.0.co;2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025211147
114 rdf:type schema:CreativeWork
115 https://doi.org/10.1175/1520-0477(1987)068<1116:otdorc>2.0.co;2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019068339
116 rdf:type schema:CreativeWork
117 https://doi.org/10.1175/1520-0493(1983)111<0609:etdgmf>2.0.co;2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022548070
118 rdf:type schema:CreativeWork
119 https://doi.org/10.2134/agronj1983.00021962007500050014x schema:sameAs https://app.dimensions.ai/details/publication/pub.1068991146
120 rdf:type schema:CreativeWork
121 https://doi.org/10.2134/jeq1983.00472425001200040028x schema:sameAs https://app.dimensions.ai/details/publication/pub.1069001366
122 rdf:type schema:CreativeWork
123 https://doi.org/10.2307/1242694 schema:sameAs https://app.dimensions.ai/details/publication/pub.1069409822
124 rdf:type schema:CreativeWork
125 https://doi.org/10.3354/cr003079 schema:sameAs https://app.dimensions.ai/details/publication/pub.1071158331
126 rdf:type schema:CreativeWork
127 https://www.grid.ac/institutes/grid.419078.3 schema:alternateName Goddard Institute for Space Studies
128 schema:name Goddard Institute for Space Studies, Columbia University, 2880 Broadway, New York, New York 10025, USA
129 rdf:type schema:Organization
130 https://www.grid.ac/institutes/grid.419190.4 schema:alternateName Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria
131 schema:name Centro de Investigación Forestal, Instituto Nacional de Investigaciones Agrarias (INIA), Madrid, Spain
132 rdf:type schema:Organization
 




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


...