Estimating crop yield potential at regional to national scales

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ContentslistsavailableatSciVerseScienceDirect

Field

Crops

Research

j o ur n a l ho me p a g e :w w w . e l s e v i e r . c o m / l o c a t e / f c r

Estimating

crop

yield

potential

at

regional

to

national

scales

Justin

van

Wart

a,∗

_{, K.}

_Christian

_Kersebaum

b

_{, Shaobing}

_Peng

c

_{, Maribeth}

_Milner

a

_,

_Kenneth

_G.

_Cassman

a

a_Department_of_Agronomy_and_{Horticulture,}_University_of_{Nebraska-Lincoln,}₂₀₂_Keim_Hall,_Lincoln,_NE_68583-0915,_USA b_{Leibniz-Center}_of_Agricultural_Landscape_Research_(ZALF),_Eberswalder_Straße₈₄_D-15374_Müncheberg,_Germany

c_Crop_Physiology_and_Production_Center_(CPPC),_National_Key_Laboratory_of_Crop_Genetic_Improvement,_MOA_Key_Laboratory_of_Crop_Physiology,_Ecology_and_Cultivation_(The_Middle

ReachesofYangtzeRiver),HuazhongAgriculturalUniversity,Wuhan,Hubei430070,China

a

r

t

i

c

l

e

i

n

f

o

Articlehistory: Received18June2012 Receivedinrevisedform 24November2012 Accepted27November2012 Keywords: Yieldpotential Simulationmodel Foodsecurity Yieldgap Rice Maize Wheat

a

b

s

t

r

a

c

t

Worldpopulationwillincrease35%by2050,whichmayrequiredoublingcropyieldsonexistingfarmland tominimizeexpansionofagricultureintoremainingrainforests,wetlands,andgrasslands.Whetherthis ispossibledependsonclosingthegapbetweenyieldpotential(Yp,yieldwithoutpest,disease,nutrient orwaterstresses,orYwunderwater-limitedrainfedconditions)andcurrentaveragefarmyieldsinboth developedanddevelopingcountries.Quantifyingtheyieldgapisthereforeessentialtoinformpolicies andprioritizeresearchtoachievefoodsecuritywithoutenvironmentaldegradation.Previousattempts toestimateYpandYwatagloballevelhavebeentoocoarse,general,andopaque.Ourpurposewasto developaprotocoltoovercometheselimitationsbasedonexamplesforirrigatedriceinChina,irrigated andrainfedmaizeintheUSA,andrainfedwheatinGermany.SensitivityanalysisofsimulatedYporYw foundthatrobustestimatesrequiredspeciﬁcinformationoncropmanagement,+15yearsofobserved dailyclimatedatafromweatherstationsinmajorcropproductionzones,andcoverageof40–50%oftotal nationalproductionarea.NationalYpestimateswereweightedbypotentialproductionwithin100-km ofreferenceweatherstations.Thisprotocolisappropriateforcountriesinwhichcropsaremostlygrown inlandscapeswithrelativelyhomogenoustopography,suchasprairies,plains,largevalleys,deltasand lowlands,whichaccountforamajorityofglobalfoodcropproduction.Resultsareconsistentwiththe hypothesisthataveragefarmyieldsplateauwhentheyreach75–85%ofestimatednationalYp,which appearstooccurforriceinChinaandwheatinGermany.Predictionofwhenaveragecropyieldswill plateauinothercountriesisnowpossiblebasedontheestimatedYporYwceilingusingthisprotocol.

1. Introduction

Worldpopulationisprojectedtoincrease35%by2050,which willrequirea 70–100% risein foodproduction givenprojected trends in diets, consumption, and income (Bruinsma, 2009; Rosegrantetal.,2009;UNFPA,2010).Increasedfoodproductioncan beachievedbyraisingcropyieldsonexistingfarmland,expanding cropproductionarea,orboth.Expansionofcroparea,however, comesat the expense of substantial greenhouse gasemissions (IPCC,2007;Searchingeretal.,2008),whichwouldcontributeto climatechange(KarlandTrenberth,2003).

Theextenttowhichincreasedfoodproductionrequires expan-sionofcultivatedareawillbedeterminedlargelybycropyield potential(Yp),whichisdeﬁnedasthemaximumattainableyield per unit land area that can be achieved by a particular crop

∗ Correspondingauthor.

E-mailaddresses:Justin.vanwart@gmail.com(J.vanWart),ckersebalm@zalf.de

(K.C.Kersebaum),speng@mail.hzau.edu.cn(S.Peng),

Mmilner1@unl.edu(M.Milner),kcassman1@unl.edu(K.G.Cassman).

cultivarinanenvironmenttowhichitisadaptedwhenpestsand diseasesareeffectivelycontrolledandnutrientsarenon-limiting (Evans, 1993). In irrigated systems, Yp is determined by tem-peratureregimeand solarradiationduringthegrowingseason. Water-limitedyieldpotential(hereaftercalledwater-limitedyield; Yw)istherelevantmeasureofmaximumyieldattainableinrainfed systems.DespitetheimportanceofYpandYwtofoodproduction capacity,theyarenotexplicitlyconsideredinstudiesofindirect landusechangeasaffectedbypoliciesaboutbiofuels(Searchinger etal.,2008),conservationofbiodiversity(Phalanetal.,2011),or futurefoodsecurity(Godfrayetal.,2010).Accurateestimatesof YpandYwarealsoneededtointerpretyieldtrendsinregionsand countrieswhereaggregatedataindicateyieldstagnation(Cassman etal.,2003;Lobelletal.,2009).Forexample,riceyieldsappearto haveplateauedinJapanandChina;maizeyieldshavebeen stag-nantinChina,Italy,andFrance;andwheatyieldsarenotincreasing innorthernEuropeandIndia(Brissonetal.,2010;Cassmanetal., 2010).Yieldstagnationinthesemajorgrainproductionareasputs pressureonotherregionstoeitheraccelerateyieldgrowthratesor expandcultivatedareatomakeupthedifferencebetweenglobal supplyanddemand.Hence,understandingthecauseoftheseyield 0378-4290©2012ElsevierB.V.

http://dx.doi.org/10.1016/j.fcr.2012.11.018

Open access under CC BY-NC-ND license.

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plateausiscriticaltodeterminingwhetheritispossibletoresume yieldadvanceorifthefocusshouldbeplacedonacceleratingyields inothergrainproducingregions.

Oneexplanationforyieldplateausisthataveragefarmyields haveapproachedaYporYwceiling.Thatis,plateausoccurbecause itis impossibleforaverageyieldin a regionor nationtoreach Yp orYw for two reasons: (1)100% of farmers cannot achieve the perfectionof crop and soil management required to reach YporYw, and(2) cropresponsetoadditionalinputs exhibitsa diminishingmarginalyieldbenefitasyieldapproachesthe ceil-ing,whichdecreasesthemarginalcost-benefitofadditionalinputs andreducesincentivestoexploitthesmallremaininggapbetween farmyieldlevelsandYporYw.Thisisnottosaythatplateausare duetoreducedefficienciesinresponsetoinputs.Onthecontrary, improvedcultivarswithimprovedresistancetobioticandabiotic stressresistanceachievehigheryieldsthantheoldercultivarsthey replaceatthesamelevelofinputs,whichmeansgreaterinputuse efficiencies.Instead,plateausmayreflectthefactthatasyieldsrise towardtheplateau,marginalreturntoadditionalinputsbecome smallerandthusfarmershavelessmotivationtotryandachieve highest possibleyield. Therefore, averageregionaland national yieldscanbepredictedtoplateauwhentheyreach70–90%ofYp orYw(Cassman,1999;Cassmanetal.,2003;Grassinietal.,2009). BecausethereislittleevidencethattheYpceilinghasincreased duringthepast30yearsinmaizeandrice(Cassman,1999;Duvick andCassman,1999;Pengetal.,1999)orwheat(Grayboschand Peterson,2010),accurateestimatesofceilingyieldlevelsare criti-caltodeterminewhetherplateauingcropyieldsresultfromlackof anexploitablegapbetweenaveragefarmyieldsandYpinirrigated systems,orYwinrainfedsystems.

AtissueiswhetheravailablemethodstoestimateYpandYware goodenoughtohelpinterpretyieldtrendsthatindicateaplateau ortoinformdevelopmentofpoliciesthatseektoreduceGHG emis-sionsfromagriculture,includingdirectandindirecteffectsofland usechange.CropsimulationmodelscanbeusedtoestimateYpand Ywbasedoncurrentmanagement,geneticfeaturesofthecrop, weatherandwatersupply.Butcropmodelsthatperformwellin evaluationofyieldatthefieldorfarmlevelsdonotgenerally per-formwellwhenscaleduptoregionalornationallevels(Witetal., 2005).Inlargepartthisperformanceproblemreflectsdifficultyin scalingweatherdatafrompointestimatesatground-basedstations tolargergeospatialscales.

A common approach for estimating current or future crop yieldsata globallevelutilizesa weather databaseinterpolated to0.5◦×0.5◦ grid,or roughly 3100km2 _at _the_equator₍_Fischer

etal., 2002;Lobell and Field,2007;Priya and Shibasaki,2001). Thestrengthofthisinterpolatedgridapproachisthatitprovides globalcoverageofterrestrialecosystems.Twoweaknessesof spa-tialinterpolationofdataare:(1)itreducesthedegreeofvariability intemperature,rainfall,andsolarradiationacrossalandscapedue tovariationintopographywithinthegridcell,and(2)the geospa-tialdistributionofcropareawithinagridisnotuniformandis typicallyconcentratedincertainzonesacrossthelandscape.The attenuationofvariabilityintemperature,rainfallandsolar radia-tioncanresultinoverorunder-estimationofyieldsforcropsthat relyonrainfallbyasmuchas10–50%(Baronetal.,2005). Further-more,thequalityofgeospatiallyinterpolatedweatherdataisnot uniformacrosstheglobebecausegeospatialdensityofweather sta-tionsisverylowinsomeregions.Anotherapproachistoassume highestyieldingﬁeldsforaparticularenvironmentasyield poten-tialyields,buttheseyieldsmaybetheresultofasinglegoodyear anddonotrepresentlong-termaverageyieldpotentialforagiven location(Lickeretal.,2010).Assumingallareasoftheglobecan behandledinthesamewayignorescomplexityinthegeospatial distributionofcultivatedlandduetodifferencesintopographyand weather.Useofactualweatherdataoveranumberofyearsfrom

groundstationsthatarespatiallycongruentwithgeospatial distri-butionofcropproductionavoidssuchweaknessesassociatedwith useofinterpolatedweatherdataor“averaged”cropproduction statisticsinestimatingYporYw.

Anotherissueisthemostappropriate time-stepforweather datausedtosimulatecropyields.Previousglobal,national,and regionalestimatesofYporYwaremostlybasedonweatherdata derivedfrommonthlymeansorsimulatedclimaticyearsbasedon historicalvariances(Andarzianetal.,2008;Deryngetal.,2011; Neumannetal.,2010;Nonhebel,1994;PriyaandShibasaki,2001; vanBusseletal.,2011).However,monthlymeansaretoocoarse andinterpolatingthesemeanstoderivedailyvaluesdoesnot cap-turewithinmonthvariabilityaddingadditionaluncertaintytothe weatherinputdata.AccuratesimulationofYpor Ywrequiresa dailytimesteptofullycapturetheimpactofcurrentcrop manage-mentpractices,oradaptivemanagementinresponsetochanges inclimateaswellasthehistoricalvariabilityofweather within thecourseofthemonth.BothYpandYwarehighlysensitiveto thedateofplantingand cultivarselection intermsofmaturity, which togetherdeterminethetiming ofkeygrowthstages and lengthofcrop-growingseason(Cassmanetal.,2010;Grassinietal., 2009;WangandConnor,1996;Yangetal.,2006).Suchsensitivityis especiallyimportanttoestimateYpandYwbysimulationofcrops grownintemperateagroecologicalzones,suchastheU.S.CornBelt, wherelengthofgrowingseasonisdeterminedbyexpecteddateof firstandlastfrost.Specificationofplantingandmaturitydatesalso areimportantinmultiplecroppingsystemsintropicaland semi-tropicalregionswheretwoorthreecropcyclesoccureachyearon thesamefield.

Inadditiontoweatherdatawithdailytime-step,an appropri-atesimulationmodelis neededtoestimateYpandYw. Models shouldbewelldocumentedandvalidatedagainstyieldsofcrops growninfieldswhere,apartfromweather,yield-limitingfactors havebeeneliminated(Kropffetal.,1993;Lobelletal.,2009;Yang etal.,2006).Whilesomepreviousstudieshaveusedgeneric, non-species-specificrelationshipsbetweenincidentsolarradiationand plant biomassproduction toestimatenet primary productivity (PenningdeVriesetal.,1997;DoorenbosandKassam,1979),such modelsarenotabletosimulatecropphenology,whichiscontrolled byspecies-specifictraitsessentialforaccuratesimulationofcrop maturityandgrainyield.

Basedonreviewoftheliterature,weconcludethatavailable methodsdo notgiverobust,reproducible, andtransparent esti-matesofcropYporYwatregionaltonationalscales.Giventhe needforaccurateestimatesofceilingyieldlevelsforinterpreting currentyieldtrendsandforstudiesoffuturefoodsecurityandland useunderchangingclimate,wesetouttodevelopan appropri-atemethodforestimatingtheseyieldbenchmarksatregionalto nationalscales.Todevelopsuchaprotocolrequiresaddressingthe followingissues:(1)whataretheminimumweatherdata require-mentsforaccuratesimulationofYporYwatagivenlocation,(2) whatlevelofspeciﬁcityincropmanagementpracticesisrequired, and(3)howbesttoscaleupestimatesofYpandYwfrom location-speciﬁcestimatestoregionalandnationalscales.Thesequestions wereexaminedforrainfedandirrigatedmaizeintheUSA(28Mha and 4Mha harvested area, respectively), irrigated rice in China (30Mha),andrainfedwheatinGermany(3Mha).Ourattemptsto answertothesequestionsledustoproposeaprotocolfor estimat-ingYpandYwatregionaltonationalscales.

2. Materialsandmethods

2.1. Geospatialdistributionofharvestedcroparea

Ageospatialdatabaseofharvestedcroparea(Portmannetal., 2010)wasusedtoidentifyregionswithlargecropproductionarea.

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Fig.1. DistributionofNOAAweatherstationswith20+yearsofweatherdatasince1985.

Thisdatasetcontainstheharvestedareaof26cropsona0.5◦× 0.5◦

globalgrid,andforeachcrop,itdistinguishesirrigatedfromrainfed harvestedcroparea.Toourknowledge,itisthemostdetailedand comprehensivegeospatialdatabaseoncropareadistribution cur-rentlyavailable.Ofparticularnoteisthatthegeospatialdistribution ofcropareawasbasedonnationallyreporteddatacorroboratedby satelliteimagery.

2.2. Selectionofreferenceweatherstationsandqualitycontrol measures

Weatherdatabasesofsufﬁcientgeospatialcoverageand qual-ity are essential in simulating crop yields at larger scales.We usedobservedweatherdatafromselectedstations,referredtoas referenceweatherstations(RWS),foundintheNationalOceanic andAtmosphericAssociation(NOAA),GlobalSummaryoftheDay (GSOD).Thisglobaldatasetincludesdailyvaluesforsurface max-imum and minimum temperature (Tmax, Tmin), precipitation, windspeed, and dewpoint temperature(NationalOceanic and AtmosphericAssociation,2010).Datafromstationsinthisdatabase undergo a number of quality control measures as described at: http://www.ncdc.noaa.gov/oa/climate/ghcn-daily/. Geospatial coverageisquitedenseinNorthAmerica,EuropeandEastAsia, andreasonablywelldistributedinpopulatedareasofsouthand southeastAsia,Africa,andLatinAmerica(Fig.1).Weatherstations aresparse,however,inareaswithlowpopulationdensityorlack ofinfrastructure.

WeatherstationswereonlyconsideredasapotentialRWSif they:(1)hadatleast20yearsofdatasince1980,(2)werelocatedin aprovinceorstatethatcontained>2%oftotalnationalproduction forthecropinquestion,and(3)hadfewerthan10%ofdata-daysand

fewerthan30consecutivedata-daysmissing.UsingthePortmann etal.(2010)geographicdistributionofcroparea,ArcGISwasused toiterativelysumtheharvestedareawithinabufferzoneofﬁxed radiusaroundeachstation,andstationswithinacountrywerethen ranked.Thestationwithgreatestharvestedareawithinthisbuffer zonewasselectedasareferenceweatherstation(RWS).Allother stationsneartheselectedRWS(withintwicethedistanceofthe bufferzoneradius)weretheneliminatedfromfurther consider-ationtoavoidoverlappingbufferzones,andthestationwiththe largestharvestedcropareaamongremainingstationswasthen selectedasasecondRWS.Theprocesswasrepeateduntil>50%of nationallyharvestedareafellwithin100kmofselectedRWS.In somecasescropproductionareaishighlyconcentratedsuchthat >50%ofnationallyharvestedareacannotbeachievedwithoutsome overlapamongRWS.Inthis case,5kmincrementaloverlapwas alloweduntil>50%ofnationallyharvestedareacouldbeachieved with25stationsorless.Thisselectionprocessavoidedsubjective selectionofRWS,limitedthenumberofstationsrequiredfor esti-mation,minimizedoverlapofbufferzonesusedforweighting,and providedgoodgeospatialcoverageofregionsthatcontributedmost tototal nationalproductionofthecropinquestion.Minimizing thenumberofRWSbecomesimportantbecauseinformationabout cropmanagementpractices withinbufferzonesisalsorequired foraccurateYpand Ywsimulation,anditrequiresconsiderable efforttoobtainthesedata(seeSection2.4below).Abufferzoneof 100kmwasusedforthisstudy.Zonesof50kmand150kmwere alsoconsidered,butdidnotallowfor50%coverageofharvested areabecauseof toomuchoverlap (150km)ornot enougharea covered(50km)(datanotshown).Preliminaryevaluationsof sta-bilityofYpandYwestimatesbasedonnumberofconsecutiveyears ofweatherdataandamountofcropareacoveredbyRWSbuffers

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Table1

Inﬂuenceofdateoftransplantingordirectseeding(D.seed)plantingdatesandmaturitydate,orboth(dayofyear=DOY)onsimulatedYp(Mgha−1₎_using_NOAA-SR2_for

selectprovincesandricecroppingsystems.

Province Season BaseYp(Mgha−1) TransplantDOY MaturityDOY TransplantandmaturityDOY

+7 −7 +7 −7 −7,+7 +7,−7 Sichuan Single 9.2 −4% 3% 7% −10% 10% −13% Anhui Early 3.3 −11% 11% 15% −15% 18% −23% Anhui Middle 8.6 −5% 3% 13% −14% 16% −18% Anhui D.Seed 6.1 −15% 12% −6% −8% 22% −24% Anhui Late 4.4 −10% 0% 4% −10% 13% −18%

indicatedthat20yearsand40–50%areacoveragewassufﬁcient

toobtainstableestimates.Thiswasconﬁrmedbymorethorough

analysisasprovidedinthispaper.

UsingthisRWSselectionproceduremadeitpossibletoobtain

>50% coverage of total national harvested area for irrigated

rice in China (∼29Mha total harvested area, ﬁve-year average,

2004–2008)andirrigatedmaizeintheUSA(∼3Mhatotalharvested

area,2004–2008)withoutneedforoverlapamongRWS(Table2).

In contrast, rainfed maize production in the USA (∼28Mha, 2004–2008)ishighlyconcentratedinthecentralandeasternCorn Belt,asareweatherstationdata,suchthatupto25kmoverlapwas requiredbetweensomeoftheRWStocover14Mha(50%)of har-vestedareabasedonthePortmannetal.(2010)geospatialdata. Becauseofrelativelysmalllandareaandrelativelylargenumber ofweatherstationswithgoodqualityweatherdatainGermany, only6RWSwererequiredtocover>50%oftotalharvestedareaof rainfedwheat(∼3Mha).

WeatherdataforeachselectedRWSweresubjectedtoquality control(QC)measurestoﬁllinmissingdataandidentifyandcorrect erroneousvaluesthatoccurduetotechnicalproblemscommonin weatherdataacquisition.Aspatialregressiontest(SRT)(Hubbard etal.,2005)wasusedtocheckandcorrectweatherdataatagiven RWSagainstdatafromnearbystationsbasedonthestrengthof cor-relationbetweennearbyandreferencestationdata.Developedfor useintheMidwestUSA,thisQCmethodwasfoundtooutperform otherQCapproachesinawidevarietyofclimate-zones(Hubbard etal.,2007;Youetal.,2008).Atleast2neareststationswereused withtheSRTtoidentifyandcorrectmissingandsuspiciousvalues forTmin,Tmax,dewpointtemperature,windspeed,and precipita-tion.Typicallyabout0.5%ofobservationswerecorrected,roughly 2daysperyear.FollowingHubbardetal.(2005),adailyvaluewas ﬂaggedassuspiciousifitwasgreaterthan3standarddeviations (5for precipitation)fromtheSRTvalue,which is a regression-estimatedvaluebasedon15daysbeforeandafterthedailyvalue inquestion.Inrarecaseswhereasingledailyrecordwasmissing fromtheRWSandnearbystations(<0.01%ofallvalues),the aver-ageoftheprecedingandsucceedingdaywassubstitutedforthe missingvalue.

Evapotranspiration,relativehumidity,incidentsolarradiation, and vaporpressureare notmeasuredor reportedin theNOAA weatherdata,buttheyarerequiredbyoneormoreofthecrop simulationmodelsusedinthisstudy.Hence,evapotranspiration andrelativehumiditywereestimatedfollowingAllenetal.(1998). VaporpressurewasestimatedusingtheWobusmethod(Gerald

andWheatley,1984).Incidentsolarradiationwasobtainedinone oftwoways:(1)derived fromthesquarerootofthedifference betweendailyminimumandmaximum temperaturemultiplied byextraterrestrialsolarradiationandaconstant(Hargreavesand Samani,1982)or(2) obtainedfromNASAagroclimatologysolar radiationdata,whichareavailableona1◦by1◦globalgrid.These datawereobtainedfromtheNASALangleyResearchCenterPOWER ProjectfundedthroughtheNASAEarthScienceDirectorateApplied ScienceProgram.WethereforehadtwosourcesofNOAAweather dataforcropsimulation,bothusingactualdatafortemperatureand rainfallbutwithdifferentsourcesofdataforsolarradiation:either derived (Hargreaves andSamani, 1982),hereaftercalled NOAA-SR1,orbasedonsolarradiationfromtheNASA-POWERdatabase, hereaftercalledNOAA-SR2.

2.3. Soilproperties

Soiltextureandbulkdensityhavealargeinfluenceonwater holdingcapacity andarerequired forsimulation ofYw (Saxton etal.,1986).ForeachRWS,thedominantagriculturalsoilwithinthe 100kmbufferzonewasidentified.ForU.S.maizeproduction,soil texturewasidentifiedforthemostabundantsoiltypeassociated withthedensestmaizeproductionareawithineachRWSselected asaRWSforirrigatedorrainfedproduction.Thiswasachievedby evaluatingsoiltypesandareadistributionintheSSURGOdatabase (SoilSurveyStaff,2010)inrelationtothegeospatialdistribution of2009maizearea(NASS,2010a)withineach100kmRWSbuffer zone.Whenthereweretwoormoresoilsofsimilarextentand congruencewithmaizearea,thesoilwithhighestlandcapability class(KlingebielandMontgomery,1961)wasselectedasthemost representativesoilformaizeproductionintheRWSbufferzone.In GermanysoilswithineachRWSwereidentifiedusingadigitalsoil map(1:1.000.000)usingsoilprofiledescriptionsfordominantsoil typesfromHartwichetal.(1995).Forirrigatedrice,soilwater hold-ingcapacityisnotasensitivevariableforsimulationofYpbecause itisassumedthatfarmerscanapplyirrigationwheneverrainfall fallsbelowcropwaterrequirements.Therefore,simulationsofrice YpinChinadidnotrequirespecificationofsoilproperties. 2.4. Cropmanagement

Forthecropsandcountriesexaminedhere,farmershaveready accesstolatesttechnologiesand informationregardingplanting dates,seedingratesortransplantingpatterns,andcultivars.Indeed,

Table2

NationalestimatedYpandreported5-yearaverage(2004–2008)yields(takenfromIRRIforChina,FAOforGermanyandNASSfortheUS).

Country-crop Years Water

regime

Harvestedareain100km bufferzones(Mha)

Harvestedareaa

(Mha)

Coverage Ya(Mgha−1₎ _Yp_(Mgha−1₎ _Ya/Yp_(%)

China-rice 86–08 IR 15.0 29.12 51% 6.4 7.8 82%

US-maize 86–08 RF 14.0 27.7 50% 9.7 13.2 73%

US-maize 86–08 IR 1.9 3.5 54% 11.7 15.1 77%

German-wheat 86–08 RF 1.6 3.1 52% 7.6 9.5 80%

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therearefewbarrierstoaltermanagementofthesepracticesif suchchangeswouldresultinhigheryieldsandproﬁt.Forthis rea-son,managementspeciﬁcationsforallsimulationswerebasedon currentaveragefarmerpracticesineachlocationwhereYporYw wassimulated.

Managementpracticesandtheextentofharvestedareaforrice systemsinChinawereobtainedfromagronomistsineachofthe majorrice-producingprovincesacrossChina.Dominantrice crop-pingsystemsrangedfromthree,two, oronericecropperyear onthesamepieceoflanddependingonwhethertheclimatewas warmenoughforyear-roundcropproduction.Morethan40 differ-entrice-basedcroppingsystemswereidentifiedin17provinces. Foreachricecrop,ineachofthedifferentcroppingsystems,crop managementdataincludedplantpopulationfordirect-seededrice orhillspacingintransplantedrice,dateofsowingortransplanting andtransplantseedlingage,dateoffloweringandmaturity,andthe mostwidelyusedcultivar.Emergencewasassumedtooccur7days afterdirectseeding.Cropphenology(seeding,flowering,and matu-ritydates)andtransplantingdatesreportedforeachricecropping systemwithinaprovincewereusedtoestimategenotype-specific coefficientsrequiredforsimulationofYpwithinRWSbufferzones locatedinthatprovinceusingcompanionsoftwareoftherice sim-ulationmodel(ORYZA2000).

Data for average U.S. maize sowing date by county were obtainedfromtheUSDA’sRiskManagementAgency(RMA),which requiresfarmersenrolledinUSDAinsuranceprogramstoreport theirplantingdatesbyfield.ForeachcountyinwhichaRWSwas located,theplantingdatewasconsideredtobethedateonwhich 50%ofthemaizeareawasplanted(meanvaluefor2003–2008). Seedingrateand growingdegreedaysrequired toreach matu-rityforthemostcommonhybridsusedwereobtainedfromfield researchers,seedcompanyagronomists,andfarmersfamiliarwith cropmanagementpracticesinbufferzoneareasaroundeachRWS. Iflong-termaverageyieldssimulatedbythemaizecropmodel(see Section2.5below)usingthereportedhybridmaturity(quantified bycumulativerelativematuritydays,calledCRM)hada>20%risk offrostoccurringbeforeendofgrainfilling,CRMwasadjustedafew daysearlieruntilriskoffrostwas<20%.Hybridmaturity,quantified incumulativerelativematuritydays(CRM),wasadjusteddown.

PhenologicaldataforwheatinGermany(sowing,emergence, spike emergence, physiological maturity) were obtained from observationsoftheGermanWeatherService(DWD,www.dwd.de). Data of regional wheatarea, yields, and the mostwidely used cultivars indifferent regions wereobtainedfrom theliterature (SelingandLindhauer,2005;Selingetal.,2009), while informa-tiononmostwidelyusedseedingratewereobtainedfromwheat breedersandagronomists.Genotype-speciﬁcparametersforthe cultivarsusedwereobtainedfromtheGENCALCprogram,which iterativelychangesgenotypiccoefﬁcientsuntilsimulationresults matchreporteddatesofphenologicalstages(Huntetal.,1993). 2.5. Cropsimulation

Crop Yp and Yw were simulated from 1990–2008 using ORYZA2000for ricein China(Boumanet al.,2001),1990–2008 usingHybridMaizeformaizeintheUS(Yangetal.,2004),andfrom 1983–1992using CERES-Wheat for wheat in Germany (Ritchie etal.,1985).Eachofthesemodelsrequiresdailyvaluesof maxi-mumandminimumtemperatureandsolarradiationtosimulate Yp,andalsorainfallforsimulationofYw.Grainyieldoutputsfrom themodelsarereportedatstandardmoisturecontentsof14,15.5, and13.5kgH2Okg−1grainforrice,maizeandwheat,respectively.

Eachofthesemodelshavebeenwelldocumentedandvalidatedin ﬁeldexperimentswithoptimalmanagementtoallowexpressionof YporYwacrossawiderangeofenvironments(Bolingetal.,2010; BoumanandvanLaar,2006;Fengetal.,2007;Ghaffarietal.,2001;

Grassinietal.,2009;Liuetal.,2008;Singhetal.,2008;Timsina and Humphreys, 2006; Yang et al., 2006, 2004). ORYZA2000 requiresfourgenotype-specificcoefficientstodetermine pheno-logical development and final maturity, and it simulates daily canopyCO2 assimilationand total respiration.Dailynetcarbon

assimilationisestimatedbydifferenceandassimilateisallocated toroots,stems,leavesandgraindependingonstageof develop-ment(Boumanetal.,2001).HybridMaize issimilarinstructure toORYZA2000,butonlyrequiresasinglegenotype-specificinput parameter:growingdegreedaysuntilthecropreaches physiolog-icalmaturity(Yangetal.,2004).Mostofthemajorseedcompanies provide information on growing degree days to physiological maturity for theircommercial hybrids. Unlike ORYZA2000 and HybridMaize,whichsimulategrossphotosynthesisandrespiration separately,CERES-Wheatusestemperature-adjustedradiationuse efficiencytoconvertphotosyntheticallyactiveintercepted radia-tionintodrymatter(Jonesetal.,2003;Ritchieetal.,1985,1988). CERES-Wheatrequires6genotype-specificcoefficientstosimulate phenologicaldevelopmentinresponsetotemperature, photope-riod,andvernalizationrequirements.

2.6. EstimatingYporYwatregionalandnationalscales Regionalornationalestimatedyieldpotential(YP

R)isa

produc-tionweightedaveragedeﬁnedas: YP R =

PP i

Hi

foralliintheregionandforPP

i =YiP×Hi (1)

wherePP

i isthepotentialproduction,Hiistheharvestedareawithin

100km,andYP

i istheestimatedYporYwofRWSi.AnestimateofYp

orYwwithinaRWS100kmbufferzoneisderivedfromsimulations basedontheweatherdatafromtheRWSandcropmanagement practicesintheregionasdescribedabove.Forregionswheremore thanonecropisgrowneachyearonthesamepieceofland,suchas themultiplericecroppingsystemsinChina,YP

i isdeﬁnedastotal

potentialproductionofeachcroppingsystem(early-season, late-season,etc.)dividedbythetotalareaplantedtoallricecropping systemssimulatedatthatRWS.Thesenational,long-term aver-ageYpandYwestimateswerecomparedagainstreported5-year averagenationalyields(Ya).TheseYadataarerepresentativeat thenationalscale,notataregionalscale.Whilethismethodof up-scalingworkswellforcountriesinwhichcropsaregrowninlarge, mostlyhomogenoustopographies,asisthecaseforthecropsand countriesexaminedinthispaper,modiﬁcationofup-scalingwill berequired,suchasuseofsmallerbufferzonesandagro-climatic zones,incountrieswherecropsaregrowninregionswithgreater heterogeneityintopography.

2.7. EvaluationofrequirementsforrobustYpandYwestimation SimulationsofYw forrainfedU.S.maize andGermanwheat were evaluated using three sources of weather data: NOAA-SR1andNOAA-SR2aspreviouslydescribed,andabenchmarkdata sourcethatprovidesdailymeasurementofallparametersrequired for cropsimulation. For maize, the benchmarkdatabases were obtainedfromtheHigh PlainsRegional ClimateCenter(HPRCC, 2011),whichisanetworkofweatherstationsinthewesternCorn Belt. For wheat,benchmark data were obtainedfrom the Ger-man WeatherService (DWD,2009).For irrigated rice in China, thebenchmarkweatherdatacamefromtheChinaMeteorological Association(CMA,2009).Ineachcountry,foursiteswereselected atwhichtherewerebothabenchmarkandNOAAweatherstation withat least10 years of weather data (1990–2008 for US and China,1983–1992forGermany).SitesincludedCedarRapids,IA, Lincoln,NE, McCook,NE and GrandIsland, NE in theUSA,Bad

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Hersfeld,Braunschweig,Düsseldorf,andGeisenheiminGermany, andChengdu,Chongqing,Nanning,andGushiinChina.

Toexplorehow manyyears ofweather dataarerequiredto obtainarobustestimateoflong-termaverageYporYw,we sim-ulatedYwat23sitesacrosstheU.S.CornBelt from1986–2009 andthencalculatedtheaverageYwforeachandevery consecu-tiveintervalof2,3,4...and23yearswithinthesedatasets.This gaveus21observationsof2-yearaverages,20observationsof 3-yearaverages,etc.ateachsite.Themeanandstandarddeviationof allobservationsforeachintervalwerethencomputedandusedto calculatethecoefﬁcientofvariation(CV).

ToevaluatesensitivityofYpandYwtospeciﬁcationof manage-mentpractices,simulationswereperformedusingreportedand modiﬁedmanagementpracticesandcropphenologyforselected sites.For selected simulationsof riceYp in China(inHoushan, AnhuiandChengdu,Sichuan),transplantingdate(orseedingdate fordirectlyseededsystems),maturitydate(representingan ear-lierorlatermaturingcultivar),andacombinationofthetwowere adjustedby ±7dayscompared toreportedvalues. Forselected rainfedUSmaizesimulations(GrandIsland,NE,CedarRapids,IA andGrissom,IN),plantingdatewasadjustedby±7and±14days, cumulativerelativematuritydayswereadjustedby_±4days, seed-ingratewasadjustedby±12,000seedsha−1andacombinationof theseadjustmentswerecomparedwithsimulationsmadeusing thereportedmanagement.Thesesiteswereselectedforthis sensi-tivityanalysisbecausetheyrepresentawiderangeofricecropping systemsforirrigatedriceinChina,andforlargedifferencesin rain-fallacrosstheU.S.CornBelt.

TheinﬂuenceofharvestedareacoveredbyRWSbufferzones contributing to national estimates of Yp or Yw was examined throughcalculationsofYwforUS,YpforChina,andYwforGermany byincrementallyaddingastationtothenationalestimate, follow-ingthepreviouslydescribedprotocolforselectingstations,until 50%ormoreofnationallyreportedharvestedareawascoveredby 100kmbuffers.Atissuewashowmuchareacoveragewasneeded toachieveastableestimateofYporYw.

3. Results

3.1. Evaluationofweatherdatarequirements

ForYporYwsimulatedusingbenchmarkweatherdata,NOAA temperature and rainfall coupled with derived solar radiation (NOAA-SR1)largelyoverestimatedYpandYwcomparedtoNOAA datawithNASAobservedsolarradiation(NOAA-SR2)(Fig.2).The overestimationwasgreatestforirrigatedriceinChina(+41%), mod-erateforrainfedwheatinGermany(+12%),andrelativelysmallfor U.S.rainfedmaize(+4%).WithinChina,overestimationwasgreatest inSichuan,amountainousprovincewherericeisgrowninirrigated valleysasopposedtootherprovinceswheretopographyismostly ﬂat.TopographyinmaizeandwheatproducingareasoftheUSA andGermanyisalsomostlyﬂat.IntheUS CornBelt,estimated solarradiationcloselyapproximatedobservedsolarradiation, per-hapsbecausethisareaissimilartotheoneinwhichtheestimation procedurewascalibrated(Hargreaves,1994).

AnnualestimatesofYporYwwereaveragedfrom1986–2009 (from 2 to 23-year averages) and the CV of these long-term, consecutive-yearaverageestimatescompared.Long-termaverage estimateswereconsideredrobustiftheyachievedaCVlessthan 0.05.ForrainfedmaizeintheU.S.CornBelt,thenumberof consec-utiveyearsofweatherdatarequiredtoobtainaYwestimatewitha CVof0.05wasassociatedwithmeanannualrainfallacrossa tran-sectofRWSintheU.S.CornBelt(Fig.3).Atlocationswhereannual rainfallwas>900mm(>−90◦_longitude),_only_2–8_years

consecu-tiveweatherdatawereneededwhereas11–15yearswererequired

Fig.2. ComparisonofYpsimulatedwithtwosourcesofNOAAweatherdata,either usingderivedsolarradiation(NOAASR1)orobservedsolarradiationfromthe NASA-POWERdatabase(NOAA-SR2)versusabenchmarkfromweatherstationsatwhich allrequiredweatherdataweredirectlymeasured.Valuesshownrepresent19-year meansforeachoffoursitesforriceandmaizeand10-yearmeansforeachoffour sitesinGermany.

atsiteswithannualrainfall<700mm(<−96◦_longitude)._In_a

sim-ilarexercisefor10RWSand32systemsofirrigatedriceinChina, aCVof0.05wasachievedwithin12consecutiveyearsforallsites analyzed.

3.2. SensitivityofYptochangesincropmanagement

Relativelysmallchangesincropmanagementspeciﬁcationsas inputtoyieldsimulationshadrelativelylargeeffectsonYpofrice (Table1).The impactof managementwasgreatestin crop sys-temspracticedinAnhui wherefarmersgrowatleasttwocrops annuallyonthesamepieceofland.Forexample,delayoradvance oftransplantingdatebysevendaysresultedinYpestimatesthat were−15to+12%greaterthanreportedtransplantingdates. Sim-ilarly,increasingordecreasingcropmaturitybysevendaysledto arangeof−15to+15%insimulatedYp.Andiffarmerscombined bothdelayedoradvancedtransplantingwithricecultivarswitha longerorshortermaturity,therangeinsimulatedYpvariedbyas

Fig.3.YearsofconsecutiveweatherdatarequiredtoobtainsimulatedYwformaize intheU.S.CornBeltwithaCVof0.05.TheeasternmostlocationisYoungstown,OH whilethewesternmostisGrandIsland,NE.Averageannualrainfallfortwolocations atextremesoftheregressionlineareprovidedasreferencepointsfortheinsert, whichshowstheeast–westpatternoftheannualrainfallgradient.

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muchas46%(directseeded;D.Seed)comparedtocurrentpractices. InSichuanwithonlyonericecropperyear,Ypwassomewhatless sensitivetoeffectsofchangesinmanagementwitharangeof25% inYpduetocombinedeffectsoftransplantingdateandcultivar maturity.LikeSichuan,onlyonemaizecropisplantedeachyearin theU.S.CornBelt.Changingrelativematurityby±4days(roughly equivalentto52growingdegreedays,Celsius),resultedinmore than1tha−1differenceinYw.Andalthoughtheimpactof increas-ingrelativematurityby+4daystoachievealongergrowingseason hadapositiveeffectonsimulatedYw,itincreasedtheriskoffrost occurrencebeforegrainﬁllingends,whichincreasedvariabilityin Yw(datanotshown).

3.3. Geospatialcoveragenecessaryforaccuratecharacterization ofnationalYpandYw

Nationalestimates of Yw for both U.S. maize and wheat in Germanywererobustwithonlyasmallportionofnational pro-ductionareacoverage.Forexample,averagesimulatedYwofU.S. rainfedmaizerangedfrom13.4to14.3tha−1astheproportionof totalrainfedmaize areacoveredbyRWSbufferzonesincreased fromabout10%to40%.Incontrast,estimatednationalYpof irri-gatedriceinChinavariedfrom12tha−1toabout8.0tha−1asthe proportionofcoveredareaincreasedfrom5%to40%oftotalrice area(Fig.4).Thisisduetothreefactors:(i)selectionprotocolfor choosingRWS,(ii)spatialdistributionofriceyieldsinChina,and (iii)widediversityofricecroppingsystemsfoundinChina,where 2oreven3ricecropsareplantedeachseason,makingwindows foroptimalsowingandharvestingrelativelynarrow.Accordingto theprotocol,theﬁrstRWSselectedarethoseinareaswithgreatest riceproductionareadensitywithinthe100kmbufferzonesaround candidateweatherstations.InChina,theseareasalsohavethe high-estyieldpotential,meaningthataslower-yieldingproductionareas areaddedtotheweightednationalaverage,theestimatednational Ypdeclines.Itthereforerequiredatleast40%coverageofharvested cropareatoattainconsistentnationalyieldestimatesforirrigated riceinChinaduetothelargediversityofcroppingsystems.In con-trast,stableestimatesofYporYwwereobtainedwithrelatively lowcoverageofharvestedcropareafor USmaizeandwheatin Germanywheretopography, climate,and croppingsystems are relativelyhomogeneous.Inallthreecountries,coverageof40%of harvestedareawithin100kmofRWSprovidedrobustestimatesof YporYwandestimateswerenotimprovedbyaddingadditional RWStoincreasecoverageofharvestedarea.

3.4. NationalYpandYwestimates

NationalYpestimatesforirrigatedriceinChinaandmaizeinthe USA,andrainfedYwforU.SmaizeandrainfedwheatinGermany aregiveninTable2.EachestimateisbasedonselectedRWSthat includeatleast50%oftotalproductionareaforeachcrop,which required22RWSandnearly100simulationsforYpofriceinChina (includingthedifferentrice croppingsystems),24 RWSand an equivalentnumberofsimulationsforYwofUSrainfedmaize,4 RWSandsimulationsforYpofU.S.irrigatedmaize,and6RWSand simulationsforYwofrainfedwheatinGermany.InChina, multi-plecroppingsystemsandthelocationofsomeRWSbufferzones acrossneighboringprovincesrequiredalargenumberof simula-tionsbasedonthericecroppingsystemsineachprovince.

AveragefarmyieldsofriceinChinaandwheatinGermanywere 82and80%ofestimatednationalYpandYw,respectively.In con-trast,current averageYw ofrainfedU.S maizewasonly73% of estimatedYw,whichindicatesalargerexploitableyieldgapthan forriceinChinaorwheatinGermany.Likewise,rainfedUSmaize hasalargeryieldgapthanirrigatedmaize.

Fig.4. VariationinestimatednationalYporYwmaizeintheUS,riceinChinaand wheatinGermanyasinﬂuencedbythenumberofreferenceweatherstations(solid blackcircles)andassociatedproportionofharvestedtotalcropareausedtosimulate YporYw(openblackcircles).RangeofsimulatedYporYwatallreferenceweather stations(RWS)areshownbytheopenredcircles.ThenumberofRWSatwhich50% coverageofnationalharvestedareaoccursisshownbytheblackdottedline.

4. Discussion

Quantitative analyses of food security and environmental changeareoftenperformedtohelpguideformulationofregional andnationalpolicies.Accuracy,reproducibility,andtransparency areessentialattributesofsuchstudiesinordertoallowchallenge byothersandtoinstillconﬁdenceintheresults.Theseattributes aredifﬁculttoachieveinestimationsofYpandYwdueto limita-tionsonqualityofweatherdataatappropriategeospatialdensities thatarecongruentwithdistributionofharvestedcroparea,scarcity ofgeospatiallyexplicitinformationoncropmanagementpractices andsoils,andlackofappropriatecropmodels.Resultsfromthe currentstudy,however,indicateitispossibletoattainrobustand transparentestimatesofnationalYporYwifcarefulattentionis given tothemore sensitivecomponentsofYp and Yw estima-tion.Themethodologyexploredwithinthispaperismostsuitable forcountriesinwhichcropsaremostlygrowninprairies,plains, largevalleys,deltas,andlowlandswheretopographyisrelatively homogenous.Itisnoteworthythatalargemajorityofglobalfood cropproductionofthemajorcerealcropsoccursincountrieswhere

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thesecropsaregrownonprairies,plains,largevalleys,deltas,and lowlands.Moreover,theapproachusedherewouldbeapplicable tocountriesinwhichcropsaregrowninmorecomplex topogra-phiesalthoughprotocolsmayrequiremodification.Forexample, bufferzonesof50km,100kmand150kmwereconsideredinthe currentstudy(datanotshown).While50kmzoneswereunableto capturemorethan40%ofharvestedareawithoutalargenumber ofRWS,especiallyintheUSandChina,150kmzonescausedtoo muchoverlapamongcandidateweatherstations.Forthesereasons the100kmbufferzoneswerechosenforthisanalysis.Incountries wherecropsaregrownin moreheterogeneouslandscapesthan thoseexaminedinthispaper,smallerbufferzonesmayprovemore appropriateanditmaybenecessarytoup-scaleestimatesofYpor YwfromRWStonationallevelsusingextrapolationbasedon agro-climaticzones.Inadditiontosmallerbufferzones,beneficialfuture workwouldalsoexaminevariabilityinsoilwaterholding capac-ityanditseffectonsimulationandupscalingresults.Forthetwo countrieswhereYwwassimulated,terrainisrelativelyflatandsoil typesonwhichthemajorityofthecropisgrownarerelatively uni-formandsoonlyasingle,dominantsoiltypewasusedasinputinto modelsimulations.

EstimatesofYpandYwaresignificantlyaffectedbyseveralkey factors.Theseincludeweatherdataqualityandestimation proce-dures,specificationofplantingdateandcultivarorhybridmaturity, thenumberofyearssimulatedtoestimatelong-termaverageYp orYw,andgeospatialweightingprocedurestoarriveataggregated estimatesatprovincialornationalscales.Eachofthesefactorsaffect estimatesofYporYwtoagreaterorlesserdegreedependingon thespecificcroppingsystems,location,anddistributionofavailable dataforthecropandcountryunderinvestigation.Forexamplein U.S.rainfedmaize,variabilityinestimatesofYwdependedon rain-fallwithhighrainfallareas(>850mmyear−1)requiringonly5–7 yearsofweatherdatatoachieveaCV<0.05whilemorethan10 yearswererequiredtoachieveasimilarlowCVforestimatesof Ywinlow rainfallareas(<700mmyear−1).Thusitseemslikely thatduration ofweather datarequiredforrobustsimulation of long-termYwincreasesasrainfalldecreasesorrainfallvariability increases.ForirrigatedriceinChina,however,nocleartrendwith rainfallwasobservedbecauseirrigationeliminatesyield-reducing impactofdryyears.

Thesourceofsolarradiationdatawasalsoasensitivefactor insimulationofYporYw. Forirrigatedricein China,estimates ofsolarradiation performedpoorlyin simulatingYpin regions wheretopographywasmountainous.Althoughtheweather sta-tionsthemselvesarelocatedonﬂatterrain,temperatureinthese areasmaybemoreaffectedbymountainousclimate(thinnerair, rainshadowaffects,andtrappedair)ratherthanbycloudcoverand solarradiation,whichmakesderivationsofsolarradiationbased ondiurnaltemperaturerangeapoorproxyforincidentradiation (ThorntonandRunning,1999;Winslowetal.,2001).The overes-timationinnon-mountainousregionsmayresultfromparticulate airpollution,whichreducesincidentsolarradiationandincreases nighttimetemperatureandissubsequentlyhighinthe industri-alizedcentralandeasternChinawhereamajorityofriceisgrown (Menonetal.,2002).Incontrast,estimationofsolarradiationbased onthedifferenceinTminandTmaxappearstobemuchmore accu-rateforsimulationofcropYpandYwintheMidwestUSAbecause thealgorithmforthederivationwasbasedonresearchconducted inthisregion(Hargreaves,1994),andbecausethereisrelatively littleairpollution.Butgiventhelackofaccuracyinmodeledsolar radiationinareaswithvariabletopographyorwithparticulateair pollution,astandardmethodforestimatingYporYwwould prefer-ablyrelyonobservedorsatellitederivedsolarradiation(Baietal., 2010;Whiteetal.,2011).

Resultsfromthisstudyemphasizetheimportanceofspecifying currentcropmanagementpracticestoobtainrelevantestimatesof

YporYwatregionalornationalscales.Whilesomemayarguethe valueofsimulatingmaximumpossibleYporYwwithoutregardto currentmanagement practicesandcroppingsystems,such esti-mates do not account for the biophysical and socio-economic constraintsunderwhichfarmersmustoperate.Indeed,historically and globally farmers areefficientin allocatingtheirland, labor andcapitaltooptimizeprofitandreducerisk(HerdtandMandac, 1981;Hopper,1965;Sheriff,2005).Forthethreecountriesinwhich yieldgapwasevaluatedinthecurrentstudy,cropyieldsare rela-tivelyhighandfarmershaveaccesstorecommendationsaboutbest managementpractices.Therearetypicallynobarrierstofarmer adoptionofearlierorlatersowing,useoflongerorshortermaturity cultivars,differentseedingratesortransplantingpatternsif farm-ersbelievedthatsuchchangesmadeasignificantdifferenceinyield andprofit.Andinmultiplecroppingsystemsfarmersarenot seek-ingtooptimizeproductionofasinglecropbutratherofanentire systemthatincludesseveralcrops,suchasthecaseofirrigatedrice systemsinmuchofChina.Therefore,farmersarelikelytousethe mostappropriatecombinationofsowingdateandcropmaturity fortheircroppingsystemconsideringrisksand costsassociated withotheroptions.Andwhilethere mightbesmallyieldgains fromchangingplantpopulationsfromcurrentpractices,thereis nopublishedevidencedefining“optimal”populationsacrossthe widerangeofenvironmentsevaluatedinthisstudy.

Theimpactofusingappropriatespeciﬁcationofcrop manage-ment canbeseenin both localand regionalornational scales. Forexample,achangeofonly7daysinplantingdateforirrigated riceinChinaaffectedsimulatedYpbyasmuchasa1Mgha−1or more.GiventheharvestedareaofirrigatedriceinAnhuiProvince, adifferenceof1Mgha−1 represents2.7millionmetrictonstotal production,whichisequivalentto550,000haofhighqualityfarm landatcurrentaverageyieldlevelsortheannualrice consump-tionofover25millionpeopleatcurrentriceconsumptionlevels inChina(ZhaiandYang,2006).Giventhis sensitivitytosowing date,estimatesofYporYwbasedonmeanmonthlyweatherdata, orweatherdataderivedfrommonthlymeans, canleadtolarge biastowardover-orunderestimationdependingonthedifference betweenactualaveragesowingdateandtheassumed(orinferred) sowingdateatthebeginning,mid-monthorendofthemonth,to accommodateuseofmonthlymeanweatherdata.

Temperatureandcumulativeinterceptedsolarradiationduring the growing season have a large influence on Yp. Total inter-ceptedradiationis sensitivetoboth intensityofsolarradiation (MJ m−2d−1)and lengthofgrowing season.Lengthof growing seasonisgovernedbytemperatureregimeandcropmanagement withregardtoplantingdateandmaturityofthemostwidelyused cropcultivars.Densityofplantsperunitlandareaalsoinfluences amountofinterceptedsolarradiation.Therefore,estimationofYp andYwrelevanttodominantcroppingsystemsinaregionrequires specificationofplantingdate,cropcultivarmaturity,andplant den-sitytypicallyusedbyfarmersinthatregion.

Becauseofthedetailedinformationrequiredtoaccurately sim-ulatecropyieldineachregion,itisexpedienttolimitthenumber ofRWSrequiredforrobustandreproducibleestimatesofYpor Ywatanationalscale.Atthesametime,ifadequateareaisnot represented,YporYwestimatesmaynotprovideaccurate repre-sentationatanationalscale.Thisisespeciallytrueinmorecomplex croppingsystemssuchasforriceinChinawheretheinitialRWS selectedinChinawasfromaprovincewhereonlyasingle, high-yieldingricecropwasgrown,whichisnottypicalofthemajorityof riceproductioninthatcountry.Subsequentstationswerelocatedin provincesthatproducemorethanonecropperyearandforwhich theYpofeachofthesemultiplecropsismuchlower.Thenational YpestimateforChina,aswellaseveryothercropandcountry ana-lyzed,variedlittleafter40–50%ofharvestedareawaswithinthe bufferzonesofselectedRWS.Whilesizeofbufferzonesmayneed

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tovarydependingonsizeofcountryforwhichnationalYporYw estimatesaredesired,achieving50%coverageofharvestedarea islikelytoproviderobustestimatesofcropproductionpotential basedonresultsfromthecurrentstudy,whichincludedcontrasting cropswitha widerangeofwaterregimesandcroppingsystem complexity.

AveragefarmyieldsofriceinChinaandwheatinGermanywere 82and80%ofestimatednationalYpandYw,respectively.In con-trast,current averageYw ofrainfedU.S maizewasonly73% of estimatedYw,whichindicatesalargerexploitableyieldgapthan forriceinChinaorwheatinGermany.BothChinaandGermany haveseenverylittleornogrowthinyieldsofriceandwheat, respec-tively,forthepastdecade,especiallycomparedtopreviousdecades (FAO,2010),despitecontinuedprogressinagriculturaltechnology andatrendtowardhigherprices.Similarly,yieldofirrigatedU.S. maizehasnotincreasedinthepastdecadeandinthisstudy cur-rentaverageyieldsareestimatedtobe77%ofYp.Theseestimates ofyieldgapforriceinChina,wheatinGermany,andirrigatedmaize intheUSAareconsistentwiththehypothesisthataveragenational yieldsbegintoplateauwhenaveragefarmyieldsreach75to85% ofYporYw(Cassmanetal.,2003;Lobelletal.,2009).Thisyield levelhasbeenproposedasthepracticallimitfornationalaverage farmyieldsbecauseitisneitherlogisticallyfeasiblenorproﬁtable for100%offarmerstoachieveyieldsequivalenttomaximum bio-physicalpotentialyields.Therefore,analysisoffutureglobalfood securityshouldrestrictcropproductionpotentialtosomefraction ofYpandYwtoavoid overestimatingnationaland globalfood productionpotential.

5. Conclusions

Resultsfromthisstudysuggestimprovedprotocolstoobtain robust,transparent,andreproducibleestimatesofYpandYwat local,regional,andnationalscalesforcountriesinwhichcropsare producedinareaswithrelativelyhomogeneoustopographies.Such aprotocolwouldhavethefollowingcomponents:

(1)userealweatherdatawithdailytimestepandavoidmonthly means,ordataderivedfrommonthlymeans,andderivedsolar radiation;

(2)15yearsofweatherdataforrainfedagriculture,while5years maybesufﬁcientforestimatesofYpforfullyirrigated produc-tionsystems;

(3)50% coverageof harvested areausing a proceduretoselect regionswithgreatestcropproductiondensity;

(4)speciﬁcationofcurrentaveragesowingdate,cultivarorhybrid maturity,andplantpopulationthatgivesmaximumyieldwith thissowing dateandcultivar/hybridmaturity.Withoutwell documentedevidenceofwhatthisoptimalplantpopulation is,estimatesofYpandYwshouldbebasedoncurrent aver-ageplantpopulationusedbyfarmersinthetargetlocationand croppingsystem;

(5)anappropriateweightingproceduretoestimateYporYwat regionalornationallevelsfrompointestimatesatselected ref-erenceweatherstations(suchasup-scalingbasedonharvested areawithinbufferzonesaroundsimulationsites);and (6)anappropriatecropmodelthathasbeenvalidatedagainstﬁeld

datainwhichcropshavebeengrowntoproduceyieldsthat approachYpandYw.

Acknowledgments

Completingtheworkreportedinthispaperwouldnothavebeen possiblewithoutinputfrom:JansBobertattheLeibnizCenterfor AgriculturalLandscapeResearchforprovidinguswithappropriate

genotypecoefﬁcientsforWheatinGermany;theCentral Agrom-eteorologicalResearchStationoftheGermanWeatherServicein BraunschweigforprovidingdataforweatherstationsinGermany; RebeccaDavisattheUSDARMA forprovidingUSmaize county levelplantingdatedata;JinshunBaiandChinaAgricultural Uni-versitygenerouslyprovideduswithobservedsolardatacollected atspeciﬁclocationsbytheChinaMeteorologicalAdministration; PatricioGrassiniandMartinvanIttersumfortheirsuggestionsfor themanuscript;andtheChineseagronomistswhoprovidedcrop managementdataforirrigatedriceinChina.

AppendixA. Supplementarydata

Supplementarydataassociatedwiththisarticlecanbefound,in theonlineversion,athttp://dx.doi.org/10.1016/j.fcr.2012.11.018.

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