Agro-climatic classification systems for estimating the global distribution of livestock numbers and commodities
Identifieur interne : 000B57 ( Istex/Corpus ); précédent : 000B56; suivant : 000B58Agro-climatic classification systems for estimating the global distribution of livestock numbers and commodities
Auteurs : David H. White ; Godfrey A. Lubulwa ; Ken Menz ; Heping Zuo ; William Wint ; Jan SlingenberghSource :
- Environment International [ 0160-4120 ] ; 2001.
English descriptors
- KwdEn :
Abstract
Investment in agricultural research in developing countries is being increasingly targeted at those agro-climatic zones and issues where the economic and environmental benefits may be expected to be greatest. This first requires that the zones themselves be defined, along with information on domestic livestock numbers and commodity output within agro-climatic zones in different countries. Different methods for classifying agro-climatic zones were compared. These included methods based on estimated length of growing period (LGP) using rainfall and temperature data, the ratio of precipitation to potential evapotranspiration (PET), and on more detailed agronomic models, remote sensing data and land use information. Zonation based on LGP has already been linked to existing national livestock data. By defining agro-climatic zones and relating concentrations of livestock populations to those of humans, it is possible to make realistic estimates of livestock populations and the production of livestock commodities for most developing countries. Detailed agro-climatic analyses of Mainland East Asia and Sri Lanka have recently been undertaken using the GROWEST agronomic model. Using this model as the basis of agro-climatic classification appears to be significantly superior, particularly in temperate environments, to approaches based solely on LGP. Different ways of subdividing countries and continents into agro-climatic or agro-ecological zones (AEZs) are reviewed in this paper. In addition, we show how the numbers of production and commodities from domestic livestock can be allocated to such zones. We also indicate how some of this information can be applied.
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DOI: 10.1016/S0160-4120(01)00080-0
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This first requires that the zones themselves be defined, along with information on domestic livestock numbers and commodity output within agro-climatic zones in different countries. Different methods for classifying agro-climatic zones were compared. These included methods based on estimated length of growing period (LGP) using rainfall and temperature data, the ratio of precipitation to potential evapotranspiration (PET), and on more detailed agronomic models, remote sensing data and land use information. Zonation based on LGP has already been linked to existing national livestock data. By defining agro-climatic zones and relating concentrations of livestock populations to those of humans, it is possible to make realistic estimates of livestock populations and the production of livestock commodities for most developing countries. Detailed agro-climatic analyses of Mainland East Asia and Sri Lanka have recently been undertaken using the GROWEST agronomic model. Using this model as the basis of agro-climatic classification appears to be significantly superior, particularly in temperate environments, to approaches based solely on LGP. Different ways of subdividing countries and continents into agro-climatic or agro-ecological zones (AEZs) are reviewed in this paper. In addition, we show how the numbers of production and commodities from domestic livestock can be allocated to such zones. We also indicate how some of this information can be applied.</div></front></TEI><istex><corpusName>elsevier</corpusName><author><json:item><name>David H. White</name><affiliations><json:string>E-mail: dwhite@acslink.aone.net.au</json:string><json:string>ASIT Consulting, PO Box 328, Hawker, ACT 2614, Australia</json:string></affiliations></json:item><json:item><name>Godfrey A. 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This first requires that the zones themselves be defined, along with information on domestic livestock numbers and commodity output within agro-climatic zones in different countries. Different methods for classifying agro-climatic zones were compared. These included methods based on estimated length of growing period (LGP) using rainfall and temperature data, the ratio of precipitation to potential evapotranspiration (PET), and on more detailed agronomic models, remote sensing data and land use information. Zonation based on LGP has already been linked to existing national livestock data. By defining agro-climatic zones and relating concentrations of livestock populations to those of humans, it is possible to make realistic estimates of livestock populations and the production of livestock commodities for most developing countries. Detailed agro-climatic analyses of Mainland East Asia and Sri Lanka have recently been undertaken using the GROWEST agronomic model. Using this model as the basis of agro-climatic classification appears to be significantly superior, particularly in temperate environments, to approaches based solely on LGP. Different ways of subdividing countries and continents into agro-climatic or agro-ecological zones (AEZs) are reviewed in this paper. In addition, we show how the numbers of production and commodities from domestic livestock can be allocated to such zones. 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Tel.: +61-2-6254-5936; fax: +61-2-6255-2455</p></note><affiliation>ASIT Consulting, PO Box 328, Hawker, ACT 2614, Australia</affiliation></author><author xml:id="author-2"><persName><forename type="first">Godfrey A.</forename><surname>Lubulwa</surname></persName><affiliation>Australian Bureau of Statistics, PO Box 2390, Tuggeranong, ACT 2901, Australia</affiliation></author><author xml:id="author-3"><persName><forename type="first">Ken</forename><surname>Menz</surname></persName><affiliation>Australian Centre for International Agricultural Research, GPO Box 1571, Canberra, ACT 2601, Australia</affiliation></author><author xml:id="author-4"><persName><forename type="first">Heping</forename><surname>Zuo</surname></persName><affiliation>Bureau of Rural Sciences, PO Box E11, Kingston, ACT 2604, Australia</affiliation></author><author xml:id="author-5"><persName><forename type="first">William</forename><surname>Wint</surname></persName><affiliation>Environmental Research Group Oxford (ERGO), PO Box 346, Oxford, OX1 3QE, UK</affiliation></author><author xml:id="author-6"><persName><forename type="first">Jan</forename><surname>Slingenbergh</surname></persName><affiliation>Animal Production and Health Division, Food and Agricultural Organization of the United Nations (FAO), Viale delle Termi di Caracella, 00100 Rome, Italy</affiliation></author></analytic><monogr><title level="j">Environment International</title><title level="j" type="abbrev">EI</title><idno type="pISSN">0160-4120</idno><idno type="PII">S0160-4120(00)X0038-4</idno><imprint><publisher>ELSEVIER</publisher><date type="published" when="2001"></date><biblScope unit="volume">27</biblScope><biblScope unit="issue">2–3</biblScope><biblScope unit="page" from="181">181</biblScope><biblScope unit="page" to="187">187</biblScope></imprint></monogr><idno type="istex">7AB879F49ADC4B04BEF9AEDF29E624B3ADD85164</idno><idno type="DOI">10.1016/S0160-4120(01)00080-0</idno><idno type="PII">S0160-4120(01)00080-0</idno></biblStruct></sourceDesc></fileDesc><profileDesc><creation><date>2001</date></creation><langUsage><language ident="en">en</language></langUsage><abstract xml:lang="en"><p>Investment in agricultural research in developing countries is being increasingly targeted at those agro-climatic zones and issues where the economic and environmental benefits may be expected to be greatest. This first requires that the zones themselves be defined, along with information on domestic livestock numbers and commodity output within agro-climatic zones in different countries. Different methods for classifying agro-climatic zones were compared. These included methods based on estimated length of growing period (LGP) using rainfall and temperature data, the ratio of precipitation to potential evapotranspiration (PET), and on more detailed agronomic models, remote sensing data and land use information. Zonation based on LGP has already been linked to existing national livestock data. By defining agro-climatic zones and relating concentrations of livestock populations to those of humans, it is possible to make realistic estimates of livestock populations and the production of livestock commodities for most developing countries. Detailed agro-climatic analyses of Mainland East Asia and Sri Lanka have recently been undertaken using the GROWEST agronomic model. Using this model as the basis of agro-climatic classification appears to be significantly superior, particularly in temperate environments, to approaches based solely on LGP. Different ways of subdividing countries and continents into agro-climatic or agro-ecological zones (AEZs) are reviewed in this paper. In addition, we show how the numbers of production and commodities from domestic livestock can be allocated to such zones. We also indicate how some of this information can be applied.</p></abstract><textClass xml:lang="en"><keywords scheme="keyword"><list><head>Keywords</head><item><term>Agro-climatic</term></item><item><term>Agro-ecological</term></item><item><term>Technology transfer</term></item><item><term>Technology spillovers</term></item><item><term>Research prioritisation</term></item></list></keywords></textClass></profileDesc><revisionDesc><change when="2001">Published</change></revisionDesc></teiHeader></istex:fulltextTEI><json:item><extension>txt</extension><original>false</original><mimetype>text/plain</mimetype><uri>https://api.istex.fr/document/7AB879F49ADC4B04BEF9AEDF29E624B3ADD85164/fulltext/txt</uri></json:item></fulltext><metadata><istex:metadataXml wicri:clean="Elsevier, elements deleted: ce:floats; body; tail"><istex:xmlDeclaration>version="1.0" encoding="utf-8"</istex:xmlDeclaration><istex:docType PUBLIC="-//ES//DTD journal article DTD version 4.5.2//EN//XML" URI="art452.dtd" name="istex:docType"><istex:entity SYSTEM="gr1" NDATA="IMAGE" name="gr1"></istex:entity></istex:docType><istex:document><converted-article version="4.5.2" docsubtype="fla" xml:lang="en"><item-info><jid>EI</jid><aid>837</aid><ce:pii>S0160-4120(01)00080-0</ce:pii><ce:doi>10.1016/S0160-4120(01)00080-0</ce:doi><ce:copyright type="full-transfer" year="2001">Elsevier Science Ltd</ce:copyright></item-info><head><ce:title>Agro-climatic classification systems for estimating the global distribution of livestock numbers and commodities</ce:title><ce:author-group><ce:author><ce:given-name>David H.</ce:given-name><ce:surname>White</ce:surname><ce:cross-ref refid="AFF1"><ce:sup>a</ce:sup></ce:cross-ref><ce:cross-ref refid="CORR1">*</ce:cross-ref><ce:e-address>dwhite@acslink.aone.net.au</ce:e-address></ce:author><ce:author><ce:given-name>Godfrey A.</ce:given-name><ce:surname>Lubulwa</ce:surname><ce:cross-ref refid="AFF2"><ce:sup>b</ce:sup></ce:cross-ref></ce:author><ce:author><ce:given-name>Ken</ce:given-name><ce:surname>Menz</ce:surname><ce:cross-ref refid="AFF3"><ce:sup>c</ce:sup></ce:cross-ref></ce:author><ce:author><ce:given-name>Heping</ce:given-name><ce:surname>Zuo</ce:surname><ce:cross-ref refid="AFF4"><ce:sup>d</ce:sup></ce:cross-ref></ce:author><ce:author><ce:given-name>William</ce:given-name><ce:surname>Wint</ce:surname><ce:cross-ref refid="AFF5"><ce:sup>e</ce:sup></ce:cross-ref></ce:author><ce:author><ce:given-name>Jan</ce:given-name><ce:surname>Slingenbergh</ce:surname><ce:cross-ref refid="AFF6"><ce:sup>f</ce:sup></ce:cross-ref></ce:author><ce:affiliation id="AFF1"><ce:label>a</ce:label><ce:textfn>ASIT Consulting, PO Box 328, Hawker, ACT 2614, Australia</ce:textfn></ce:affiliation><ce:affiliation id="AFF2"><ce:label>b</ce:label><ce:textfn>Australian Bureau of Statistics, PO Box 2390, Tuggeranong, ACT 2901, Australia</ce:textfn></ce:affiliation><ce:affiliation id="AFF3"><ce:label>c</ce:label><ce:textfn>Australian Centre for International Agricultural Research, GPO Box 1571, Canberra, ACT 2601, Australia</ce:textfn></ce:affiliation><ce:affiliation id="AFF4"><ce:label>d</ce:label><ce:textfn>Bureau of Rural Sciences, PO Box E11, Kingston, ACT 2604, Australia</ce:textfn></ce:affiliation><ce:affiliation id="AFF5"><ce:label>e</ce:label><ce:textfn>Environmental Research Group Oxford (ERGO), PO Box 346, Oxford, OX1 3QE, UK</ce:textfn></ce:affiliation><ce:affiliation id="AFF6"><ce:label>f</ce:label><ce:textfn>Animal Production and Health Division, Food and Agricultural Organization of the United Nations (FAO), Viale delle Termi di Caracella, 00100 Rome, Italy</ce:textfn></ce:affiliation><ce:correspondence id="CORR1"><ce:label>*</ce:label><ce:text>Corresponding author. Tel.: +61-2-6254-5936; fax: +61-2-6255-2455</ce:text></ce:correspondence></ce:author-group><ce:abstract><ce:section-title>Abstract</ce:section-title><ce:abstract-sec><ce:simple-para>Investment in agricultural research in developing countries is being increasingly targeted at those agro-climatic zones and issues where the economic and environmental benefits may be expected to be greatest. This first requires that the zones themselves be defined, along with information on domestic livestock numbers and commodity output within agro-climatic zones in different countries. Different methods for classifying agro-climatic zones were compared. These included methods based on estimated length of growing period (LGP) using rainfall and temperature data, the ratio of precipitation to potential evapotranspiration (PET), and on more detailed agronomic models, remote sensing data and land use information. Zonation based on LGP has already been linked to existing national livestock data. By defining agro-climatic zones and relating concentrations of livestock populations to those of humans, it is possible to make realistic estimates of livestock populations and the production of livestock commodities for most developing countries. Detailed agro-climatic analyses of Mainland East Asia and Sri Lanka have recently been undertaken using the GROWEST agronomic model. Using this model as the basis of agro-climatic classification appears to be significantly superior, particularly in temperate environments, to approaches based solely on LGP. Different ways of subdividing countries and continents into agro-climatic or agro-ecological zones (AEZs) are reviewed in this paper. In addition, we show how the numbers of production and commodities from domestic livestock can be allocated to such zones. We also indicate how some of this information can be applied.</ce:simple-para></ce:abstract-sec></ce:abstract><ce:keywords class="keyword"><ce:section-title>Keywords</ce:section-title><ce:keyword><ce:text>Agro-climatic</ce:text></ce:keyword><ce:keyword><ce:text>Agro-ecological</ce:text></ce:keyword><ce:keyword><ce:text>Technology transfer</ce:text></ce:keyword><ce:keyword><ce:text>Technology spillovers</ce:text></ce:keyword><ce:keyword><ce:text>Research prioritisation</ce:text></ce:keyword></ce:keywords></head></converted-article></istex:document></istex:metadataXml><mods version="3.6"><titleInfo lang="en"><title>Agro-climatic classification systems for estimating the global distribution of livestock numbers and commodities</title></titleInfo><titleInfo type="alternative" lang="en" contentType="CDATA"><title>Agro-climatic classification systems for estimating the global distribution of livestock numbers and commodities</title></titleInfo><name type="personal"><namePart type="given">David H.</namePart><namePart type="family">White</namePart><affiliation>E-mail: dwhite@acslink.aone.net.au</affiliation><affiliation>ASIT Consulting, PO Box 328, Hawker, ACT 2614, Australia</affiliation><description>Corresponding author. Tel.: +61-2-6254-5936; fax: +61-2-6255-2455</description><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Godfrey A.</namePart><namePart type="family">Lubulwa</namePart><affiliation>Australian Bureau of Statistics, PO Box 2390, Tuggeranong, ACT 2901, Australia</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Ken</namePart><namePart type="family">Menz</namePart><affiliation>Australian Centre for International Agricultural Research, GPO Box 1571, Canberra, ACT 2601, Australia</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Heping</namePart><namePart type="family">Zuo</namePart><affiliation>Bureau of Rural Sciences, PO Box E11, Kingston, ACT 2604, Australia</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">William</namePart><namePart type="family">Wint</namePart><affiliation>Environmental Research Group Oxford (ERGO), PO Box 346, Oxford, OX1 3QE, UK</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Jan</namePart><namePart type="family">Slingenbergh</namePart><affiliation>Animal Production and Health Division, Food and Agricultural Organization of the United Nations (FAO), Viale delle Termi di Caracella, 00100 Rome, Italy</affiliation><role><roleTerm type="text">author</roleTerm></role></name><typeOfResource>text</typeOfResource><genre type="research-article" displayLabel="Full-length article"></genre><originInfo><publisher>ELSEVIER</publisher><dateIssued encoding="w3cdtf">2001</dateIssued><copyrightDate encoding="w3cdtf">2001</copyrightDate></originInfo><language><languageTerm type="code" authority="iso639-2b">eng</languageTerm><languageTerm type="code" authority="rfc3066">en</languageTerm></language><physicalDescription><internetMediaType>text/html</internetMediaType></physicalDescription><abstract lang="en">Investment in agricultural research in developing countries is being increasingly targeted at those agro-climatic zones and issues where the economic and environmental benefits may be expected to be greatest. This first requires that the zones themselves be defined, along with information on domestic livestock numbers and commodity output within agro-climatic zones in different countries. Different methods for classifying agro-climatic zones were compared. These included methods based on estimated length of growing period (LGP) using rainfall and temperature data, the ratio of precipitation to potential evapotranspiration (PET), and on more detailed agronomic models, remote sensing data and land use information. Zonation based on LGP has already been linked to existing national livestock data. By defining agro-climatic zones and relating concentrations of livestock populations to those of humans, it is possible to make realistic estimates of livestock populations and the production of livestock commodities for most developing countries. Detailed agro-climatic analyses of Mainland East Asia and Sri Lanka have recently been undertaken using the GROWEST agronomic model. Using this model as the basis of agro-climatic classification appears to be significantly superior, particularly in temperate environments, to approaches based solely on LGP. Different ways of subdividing countries and continents into agro-climatic or agro-ecological zones (AEZs) are reviewed in this paper. In addition, we show how the numbers of production and commodities from domestic livestock can be allocated to such zones. We also indicate how some of this information can be applied.</abstract><note type="content">Fig. 1: Estimated density of small ruminants throughout Asia, animals per square kilometers (km2) (FAO, 2000).</note><subject lang="en"><genre>Keywords</genre><topic>Agro-climatic</topic><topic>Agro-ecological</topic><topic>Technology transfer</topic><topic>Technology spillovers</topic><topic>Research prioritisation</topic></subject><relatedItem type="host"><titleInfo><title>Environment International</title></titleInfo><titleInfo type="abbreviated"><title>EI</title></titleInfo><genre type="journal">journal</genre><originInfo><dateIssued encoding="w3cdtf">200109</dateIssued></originInfo><identifier type="ISSN">0160-4120</identifier><identifier type="PII">S0160-4120(00)X0038-4</identifier><part><date>200109</date><detail type="issue"><title>Modelling & Sustainability</title></detail><detail type="volume"><number>27</number><caption>vol.</caption></detail><detail type="issue"><number>2–3</number><caption>no.</caption></detail><extent unit="issue pages"><start>87</start><end>258</end></extent><extent unit="pages"><start>181</start><end>187</end></extent></part></relatedItem><identifier type="istex">7AB879F49ADC4B04BEF9AEDF29E624B3ADD85164</identifier><identifier type="DOI">10.1016/S0160-4120(01)00080-0</identifier><identifier type="PII">S0160-4120(01)00080-0</identifier><accessCondition type="use and reproduction" contentType="copyright">©2001 Elsevier Science Ltd</accessCondition><recordInfo><recordContentSource>ELSEVIER</recordContentSource><recordOrigin>Elsevier Science Ltd, ©2001</recordOrigin></recordInfo></mods></metadata></istex></record>Pour manipuler ce document sous Unix (Dilib)
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