The Food And Agriculture Organization's Gridded Livestock Of The World
See discussions, stats, and author profiles for this publication at: he Food and Agriculture Organization'sGridded Livestock of the WorldArticle in Veterinaria italiana · July 2007Source: PubMedCITATIONSREADS574873 authors:Timothy Paul RobinsonGianluca FranceschiniInternational Livestock Research Institute (IL Food and Agriculture Organization of the Uni 70 PUBLICATIONS 1,430 CITATIONS7 PUBLICATIONS 195 CITATIONSSEE PROFILESEE PROFILEWilliam WintUniversity of Oxford150 PUBLICATIONS 3,889 CITATIONSSEE PROFILESome of the authors of this publication are also working on these related projects:Insect Plant Relationships View projectVector borne diseases View projectAll content following this page was uploaded by William Wint on 20 March 2017.The user has requested enhancement of the downloaded file. All in-text references underlined in blue are added to the original documentand are linked to publications on ResearchGate, letting you access and read them immediately.
Veterinaria Italiana, 43 (3), 745-751The Food and Agriculture Organization’s GriddedLivestock of the WorldTimothy P. Robinson(1), Gianluca Franceschini(1) & William Wint(2)SummaryLivestock sector planning, policy developmentand analysis are frequently hampered by thepaucity of reliable and accessible informationon the distribution, abundance and use oflivestock. In an attempt to redress this shortfall,the Food and Agriculture Organization’sAnimal Production and Health Division (FAOAGA) has, in collaboration with theEnvironmental Research Group Oxford,developed the ‘Gridded Livestock of theWorld’ database which provide the firststandardised global, sub-national resolutionmaps of the major agricultural livestockspecies. These are now freely available fordownload on the FAO website. The data areproduced in Environmental Systems ResearchInstitute grid format for cattle, buffalo, sheep,goats, pigs, chickens and other poultry. Themap values are animal densities per squarekilometre, at a resolution of 3 minutes of arc(approximately 5 km at the Equator), and arederived from official census and survey data.Reported statistics are then processed using acombination of suitability masking and spatialdisaggregation by statistical modelling oflivestock densities based on empiricalrelationships between livestock densities andenvironmental variables in similar agroecological zones. The spatial nature of theselivestock data allows a wide array ofapplications. Livestock distribution data givean estimation of production; they evaluateimpact (both of and on livestock) by applyinga variety of rates; and they provide thedenominator in prevalence and incidenceestimates for epidemiological applications, andthe host distributions for transmission models.KeywordsDisease, Distribution, Food and AgricultureOrganization, Geographic information system,Gridded Livestock of the World, Livestock,Modelling, Production.Il “Gridded Livestock of theWorld” dell’Organizzazionedelle Nazioni Unite perl’Alimentazione e l’Agricoltura(FAO)RiassuntoLa scarsità d’informazioni accessibili e attendibilisulla distribuzione, abbondanza e uso del bestiamerappresenta frequentemente un ostacolo allaprogettazione, all’analisi e alle politiche di sviluppodel settore zootecnico. Nel tentativo di colmarequesta lacuna, la Divisione della Produzione eSalute Animale dell’Organizzazione delle NazioniUnite per l’Alimentazione e l’Agricoltura (FAOAGA), in collaborazione con il Gruppo di RicercaAmbientale dell’Universitá di Oxford, hasviluppato il “Gridded Livestock of the World”,che fornisce la prima mappatura mondiale, a unarisoluzione subnazionale, della distribuzione delleprincipali specie animali di interesse agricolo. Lemappe possono essere scaricate gratuitamente dalsito della FAO. I dati sono prodotti in formatoESRI grid per bovini, bufali, pecore, capre, maiali,(1) Livestock Information, Sector Analysis and Policy Branch, Food and Agriculture Organization of the UnitedNations, Viale delle Terme di Caracalla, 00153 Rome, Italytim.robinson@fao.org(2) Environmental Research Group Oxford, Department of Zoology, University of Oxford, South Parks Road, OxfordOX1 3PS, United Kingdom IZS A&M 2007www.izs.it/vet italianaVol. 43 (3), Vet Ital745
The Food and Agriculture Organization’s Gridded Livestock of the Worldpolli e pollame. I valori della mappa rappresentanoil numero di animali per chilometro quadrato a unarisoluzione di 3 minuti d’arco (approssimativamente 5 km alla latitudine dell’equatore) e sonoderivati da rilievi e censimenti ufficiali. Lestatistiche riportate sono processate applicando una“maschera di idoneitá” e poi con unadisaggregazione spaziale, che si basa sulle relazioniempiriche tra le densitá animali e variabiliambientali in simili zone agroecologiche. La naturaspaziale di questi dati permette una vasta gamma diapplicazioni: stime sulla produzione animale;valutazioni di impatto del e sul bestiame, applicandouna serie di tassi di crescita; stime sulla prevalenzae incidenza per applicazioni epidemiologiche edistribuzione dell’ospite nei modelli di trasmissione.Parole chiaveBestiame, Distribuzione, Gridded Livestock oftheWorld,Malattie,Modellizzazione,Organizzazione delle Nazioni Unite ne, Sistema informativo geografico.IntroductionOne of the major limitations in livestock sectorplanning, policy development and analysis isthe paucity of reliable and accessibleinformation on the distribution, abundanceand use of livestock. With the objective ofredressing this shortfall, the United NationsFood and Agriculture Organization’s AnimalProduction and Health Division (FAO-AGA)has developed a global livestock informationsystem in which geo-referenced livestocknumbers and production estimates arecollated, standardised and made freelyavailable through FAO website. Where gapsexist in the available data, or where spatialdetail is insufficient, livestock numbers havebeen modelled from empirical relationshipsbetween livestock densities and environmental,demographic and climatic variables in similaragro-ecological zones. This approach enablescoarse resolution livestock statistics, forexample at provincial administrative level, tobe disaggregated into modelled raster data,with a spatial resolution, presently of about5 km.746Vol. 43 (3), Vet ItalTimothy P. Robinson, Gianluca Franceschini & William WintMethods and resultsAvailable national agricultural statistics onlivestock populations, at a range of spatialresolutions depending on availability, werecollected and standardised. These wereconverted to densities and adjusted to accountfor the area of land deemed suitable forlivestock production based on environmental,land-cover and land-use criteria. For example,livestock were excluded from areas wheresatellite-derived vegetation indices indicatedthere to be insufficient grazing, where otherfeatures of land-cover, such as elevation andslope would preclude livestock developmentand where prevailing land-use would notpermit the presence of livestock, such as inurban and protected areas. This data archiveenabled the establishment of robust statisticalrelationships between livestock densities andpredictor variables. This modelling approachhas the major advantages both of predictinglivestock densities in areas with no livestockdata and disaggregating livestock density datathat were available originally only at a coarsespatial resolution. Since the predictors ofanimal density are unlikely to be consistentfrom region to region, or across different agroecological zones, models were developedseparately for different geographical regionsand for different ecological zones (definedempirically by cluster analysis of remotelysensed climatic variables).Worked example – cattle in AfricaCattle densities were derived from variousnational census reports, livestock surveys anddata archives from 1992 to 2003. In Africa, forexample, most known cattle population datacame from fairly large administrative units;usually administrate level 1 (province) orlevel 2 (district).Values were extracted for approximately19 000 sample points regularly spaced over theland mass of Africa. A series of stepwisemultiple regression analyses was performedbetween cattle densities and a range ofpredictor variables, including satellite derivedmeasures of rainfall, temperature, vapourpressure deficit and vegetation cover,elevation, potential evapo-transpiration, lengthwww.izs.it/vet italiana IZS A&M 2007
Timothy P. Robinson, Gianluca Franceschini & William WintThe Food and Agriculture Organization’s Gridded Livestock of the Worldequations were discarded and the relationshipat the next level up was evaluated, i.e. byecological zone – level c) above, for which nwas typically c. 250-1 000). If this relationshiphad an R2 value of greater than 40% it wasused; if not, it was discarded and the regionalequations evaluated – level b) above, for whichn was typically c. 2 500-7 000. In the few casesthat these still failed to attain R2 values greaterthan 40%, the continental equation was used(for which n 19,000 and R2 values rangedbetween 38% for chickens and 64% for cattle).The result was that R2 values typically rangedbetween 50% and 80%, and all the predictiveequations used were statistically highlysignificant (P 0.001).of growing period, tsetse fly distributions andhuman population density (Table I).The models were developed at severaldifferent spatial scales, as follows:a) the entire continentb) four continental sub-regions (east, west,south and north)c) 50 ecological zonesd) each ecological zone within each region.In addition to no transformation, three sets oftransformations of the livestock density datawereassessed,namely:logarithmic,exponential and power, to address thepossibility that relationships were non-linear.The best relationship for any point (R ).Ifthestatisticalrelationship for the analysis at the ecologicalzone by region level – level d) above, for whichthe number of observations (n) was typicallyaround 250 – had an R2 value of greater than40%, then it was used. If less than 40% thoseThe selected equations were then applied tothe original imagery to generate a map ofmodelled cattle density at a spatial resolutionof three minutes of arc (approximately 5 km atthe Equator). To avoid spurious predictions,the modelled total numbers for eachTable IGeneric list of variables used in livestock distribution modellingGeneric typeVariablesLocationalLongitude, latitudeReferenceAnthropogenicDistance to roads(a)Distance to city lights(a)DemographicHuman population(b)TopographicElevation(c)Land coverNormalized difference vegetation index4, 5, 7TemperatureLand surface temperatureAir temperatureMiddle-infrared4, 5, 6, 7, 835Water and moistureVapour pressure deficitDistance to rivers(d)Cold cloud duration(e)Potential evapo-transpiration(f)4, 5, 71General climaticModelled length of growing period(f)1OtherTsetse distributions (for Africa)(g)(a) derived from layers in the Landscan archive (www.ornl.gov/sci/gist/projects/LandScan)(b) taken from the Center for International Earth Science Information Network’s (CEISIN) Gridded Population of the World (GPW)version 2 dataset (sedac.ciesin.columbia.edu/gpw)(c) global GTOPO30 1 km resolution elevation surface, produced by the Global Land Information System (GLIS) of the United StatesGeological Survey, Earth Resources Observation Systems (USGS, EROS) data po30.html)(d) derived from the USGS EROS data centre HYDRO1k data archive ex.html)(e) mean, minimum and maximum dekadal estimates of ‘cold cloud duration’ were derived from Meteosat remotely sensed data(1961-1990), obtained from FAO’s Artemis data archives(f) PET and LGP were taken from the FAO/IIASA length of growing period data /gaez/index.htm)(g) tsetse distributions used were those developed for the Programme Against African Trypanosomiasis (PAAT) Information nfosys.html) IZS A&M 2007www.izs.it/vet italianaVol. 43 (3), Vet Ital747
The Food and Agriculture Organization’s Gridded Livestock of the Worldadministrative unit were adjusted to equalthose reported for that administrative unit. Afurther product was generated, adjusting themodelled national totals to match FAO officialnational statistics for the year 2000, providinga time-standardised dataset.The modelled cattle distribution in Africamirrors the observed distribution (Fig. 1) verywell and highlights major foci, such as the Eastand southern African highlands, Tanzania,semi-arid and dry sub-humid West Africa andminor foci, such as the Gezira irrigationscheme in the Sudan, the inland delta of theRiver Niger in Mali, and south-easternZambia.Overall, human population density was amajor determinant for all species distributionsand was the primary predictor in 30% ofregression equations used. It featuredparticularly prominently in the case ofmonogastric species (pigs and chickens). Thevariables describing climatic seasonality wereimportant predictors for all livestock species,length of growing period was an importantpredictor for ruminant species, elevation wasimportant for cattle, as was the number oftsetse species – a factor peculiar to Africa.a) Observed cattle densityThus, for cattle, buffalo, sheep, goats, pigs,poultry and chickens, three global products(divided into eight regional tiles) weregenerated, as follows: the reported densities, adjusted for landsuitability the modelled densities (adjusted to matchthe original reported totals, at theadministrative level by which they werereported) the modelled distributions corrected so thatnational totals match those provided byFAOSTAT data for the year 2000 (work iscurrently underway to produce a productstandardised to FAOSTAT 2005 nationaltotals).Data disseminationThe methodology described above relatesspecifically to the Gridded Livestock of theWorld (GLW) tml). These data layers aremadefreelyavailableusingFAO’sGeoNetwork data repository (www.fao.org/geonetwork) which provides a common portalfor spatial data available from the FAO. Theunderlying database of livestock statistics isb) Modelled cattle densityNo. per km2No. per km2 121-501-551-1006-10101-25011-20 251International boundaryWaterUnsuitable for ruminantsTimothy P. Robinson, Gianluca Franceschini & William Wint 11-56-1011-200500 1 000 km21-5051-100101-250 251International boundaryWaterUnsuitable for ruminants0500 1 000 kmFigure 1Gridded Livestock of the World products for Africa748Vol. 43 (3), Vet Italwww.izs.it/vet italiana IZS A&M 2007
Timothy P. Robinson, Gianluca Franceschini & William Wintalso used to provide statistical input for anumber of other information products. One ofthese is GLiPHA, the Global LivestockProduction and Health Atlas (www.fao.org/ag/aga/glipha/index.jsp), a user-friendly, highlyinteractive electronic atlas, developed usingKIDS, the Key Indicator Data System(www.fivims.net). The atlas provides ascaleable overview of spatial and temporalvariation of quantitative animal n of maps, tables and charts.Thematic layers include data on thebiophysical environment, socio-economics,livestock population and production, animalhealth and trade. Data are provided throughcountry projects, usually at the provincial(level 1) administrative level and a globalproject. The global project contains thefollowing national data: livestock statistics areextracted from FAOSTAT (faostat.fao.org) anddisease information is derived primarily fromthe World Organisation for Animal Health(OIE: Office International des Épizooties)HANDISTATUS II database (www.oie.int/hs2).GLiPHA can be accessed interactively from itswebsite or can be downloaded to a personalcomputer.A further route for data dissemination isthrough the standard reports produced by theFAO AGA. The national Livestock SectorBriefs and the regional Livestock SectorReviews draw upon the livestock database fortheir statistical charts and tables. These reportsare available from the AGA website (www.fao.org/ag/againfo/resources/en/pubs sap.html).ApplicationsThe spatial nature of these livestock dataallows a wide array of applications. Livestockdistribution data provide the units to whichproduction parameters (for example, calvingrates and milk yields) may be applied forestimating livestock production, they can beused to evaluate impacts, both of and onlivestock, by applying any number of differentrates, they provide the denominator inprevalence and incidence estimates forepidemiological applications and they providethe host distributions for disease transmission IZS A&M 2007The Food and Agriculture Organization’s Gridded Livestock of the Worldmodels. Many applications to which the datahave already been applied are described insome detail in a recent FAO publication (2).The following is a summary.Estimates of livestock biomass can beproduced. Composite measures of livestock,such as ‘tropical livestock units’ (TLUs),combine population densities with estimates ofthe sizes of individual animals of each speciesin different parts of the world (e.g. a NorthAmerican cow contributes 1.0 TLUs, whilst aNorth African cow only contributes 0.7 TLUs).A related application is to assess whetherlivestock populations in given areas exceeddefined thresholds, such as the carryingcapacity of the land (though the concept ofcarrying capacity for livestock is somewhatcontentious, particularly in pastoral areas).This can be extended, through herd models, toprojections of future livestock populations andestimates of production (for example, milk,meat and draft power). Production estimatescan then be combined with consumptionestimates (derived by multiplying averageconsumption rates with human populationdata) to derive production-consumptionbalances and thus to infer where livestock andlivestock products may be moving, animportant consideration both in relation totrade and to disease transmission.By appropriately adjusting the parameters inherd models, the impact of interventions(removing tsetse or controlling brucellosis, forexample) can be estimated. By linking theseestimates to current price data, they can bepresented as cash figures as an input, forexample, to benefit-cost estimates for livestockdisease interventions. As well as estimating theimpact of disease, a prerequisite for diseaserisk mapping is sound knowledge of thedistributions of susceptible species and diseasevectors. Following the United Kingdom footand mouth disease epidemic and associatedoutbreaks in continental Europe in 2001 andthe recent emergence of highly pathogenicavian influenza (HPAI or ‘bird flu’) in SouthEast Asia, attention has focused on livestockdistribution maps for modelling diseasedynamics and estimating the numbers ofanimals at risk of infection.www.izs.it/vet italianaVol. 43 (3), Vet Ital749
The Food and Agriculture Organization’s Gridded Livestock of the WorldTimothy P. Robinson, Gianluca Franceschini & William WintMost requests for data currently relate to thedistribution of chickens and other poultryspecies. Using the modelling approachdescribed in this paper, we have been able tomeet these demands by providing detailedglobal maps of poultry distributions. Figure 2shows the distribution of poultry in east Asia,where the bird flu resurgence has beenexacerbated by very high densities of poultry(and particularly of domestic waterfowl).These data are intended for use not only byplanners, but also by a much wider range ofanalysts and research professionals. Whatmakes the data so valuable is that they areregularly updated and can be accessed directlyon the FAO website in a number of differentformats: graphics and tables (planning typeapplications)anddetailedgeographicinformation system (GIS) layers (analyticalapplications).Further applications of livestock distributiondata include estimating the environmentalimpact of livestock. Environmental impactsmay take a number of forms, such asovergrazing by ruminants and equines indensely populated mixed farming areas ofAfrica, nutrient overloading from industrialpig production in South-East Asia, or forestencroachment for beef production along thefringes of the Latin American rainforests.It is through quantitative applications, such asthose described above, that the impacts oftechnical interventions can be estimated andassessed. In addition, by incorporating thesedata into appropriate decision-supportmethodologies, the impact of livestock-sectordevelopment policies can be evaluated so thatinformedrecommendationsforpolicyadjustments can be made. These new globaldatasets are an invaluable contribution to theNo. per km2 121-501-551-1006-10101-25011-20 251International boundaryWater0Unsuitable for monogastric species5001 000 kmFigure 2Gridded Livestock of the World products for east Asia: modelled poultry density750Vol. 43 (3), Vet Italwww.izs.it/vet italiana IZS A&M 2007
Timothy P. Robinson, Gianluca Franceschini & William Wintrapidlyexpandingfieldoflivestockgeography, enabling us to explore the complexinter-relationships among people, livestockand the environment in which they coexist.AcknowledgementsThe work presented here is the result of anongoing FAO project, in collaboration with theEnvironmental Research Group OxfordThe Food and Agriculture Organization’s Gridded Livestock of the World(ERGO) and the University of Oxford. Theauthors acknowledge the input of other teammembers, including Joachim Otte, PiusChilonda, Claudia Pittiglio, Federica Chiozzaand Valentina Ercoli (Rome) and DavidRogers, Simon Hay and David Bourn (Oxford).We are grateful to Helen Guyatt and to ananonymous referee for valuable comments onthis manuscript.References1.Fischer G., van Velthuizen H., Shah M. & Nachtergaele F. 2002. Global agro-ecological assessmentfor agriculture in the 21st Century: methodology and results. Research Report RR-02-02. Laxenburg:International Institute for Applied Systems Analysis and Food and Agriculture Organization of theUnited Nations, Rome, 119.2.Food and Agriculture Organization of the United Nations (FAO) 2007. Gridded Livestock of the World(G.R.W. Wint & T. Robinson, eds). FAO, Animal Production and Health Division, Rome, 131 pp.3.Goetz S.J., Prince S.D. & Small J. 2000. Advances in satellite remote sensing of environmentalvariables for epidemiological applications. Adv Parasitol, 47, 289-307.4.Green R.M. & Hay S.I. 2002. The potential of Pathfinder AVHRR data for providing surrogates ofclimatic variables across Africa and Europe for epidemiological applications. Remote Sens Environ,79, 165-175.5.Hay S.I. 2000. An overview of remote sensing and geodesy for epidemiology and public healthapplication. Adv Parasitol, 47, 1-35.6.Hay S.I. & Lennon J.J. 1999. Deriving meteorological variables across Africa for the study and controlof vector-borne disease: a comparison of remote sensing and spatial interpolation of climate. TropMed Int Health, 4, 58-71.7.Hay S.I., Tatem A.J., Graham A.J., Goetz S.J. & Rogers D.J. 2006. Global environmental data formapping infectious disease distribution. Adv Parasitol, 62, 37-77.8.Price J.C. 1984. Land surface temperature measurement for the split window channels of theNOAA 7 advanced very high resolution radiometer. J Geophys Res, 8, 7231-7237. IZS A&M 2007View publication statswww.izs.it/vet italianaVol. 43 (3), Vet Ital751
Disease, Distribution, Food and Agriculture Organization, Geographic information system, Gridded Livestock of the World, Livestock, Modelling, Production. Il "Gridded Livestock of the World" dell'Organizzazione delle Nazioni Unite per l'Alimentazione e l'Agricoltura (FAO) Riassunto La scarsità d'informazioni accessibili e attendibili
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