Predicting the current potential and future world wide distribution of the onion maggot, Delia

15 Pages·2017·3.66 MB·English

RESEARCHARTICLE
Predicting the current potential and future
world wide distribution of the onion maggot,
Delia antiqua using maximum entropy
ecological niche modeling
ShuoyingNing1,3☯,JiufengWei2☯,JinianFeng1,3*
1 KeyLaboratoryofPlantProtectionResourcesandPestManagement,MinistryofEducation,Entomological
a1111111111 Museum,CollegeofPlantProtection,NorthwestA&FUniversity,Yangling,Shaanxi,P.R.China,2 Collegeof
a1111111111 Agriculture,ShanxiAgriculturalUniversity,Taigu,Shanxi,P.R.China,3 StateKeyLaboratoryofCropStress
a1111111111 BiologyforAridAreas,NorthwestA&FUniversity,Yangling,Shaanxi,P.R.China
a1111111111
☯Theseauthorscontributedequallytothiswork.
a1111111111
*[email protected]
Abstract
OPENACCESS
Climatechangewillmarkedlyimpactbiology,populationecology,andspatialdistribution
Citation:NingS,WeiJ,FengJ(2017)Predicting
patternsofinsectpestsbecauseoftheinfluenceoffuturegreenhouseeffectsoninsect
thecurrentpotentialandfutureworldwide
distributionoftheonionmaggot,Deliaantiqua developmentandpopulationdynamics.Onionmaggot,Deliaantiqua,larvaearesubterra-
usingmaximumentropyecologicalniche neanpestswithlimitedmobility,thatdirectlyfeedonbulbsofAlliumsp.andrenderthem
modeling.PLoSONE12(2):e0171190.
completelyunmarketable.Modelingthespatialdistributionofsuchawidespreadanddam-
doi:10.1371/journal.pone.0171190
agingpestiscrucialnotonlytoidentifycurrentpotentiallysuitableclimacticareasbutalsoto
Editor:HugoRebelo,UniversityofPorto,
predictwherethepestislikelytospreadinthefuturesothatappropriatemonitoringand
PORTUGAL
managementprogramscanbedeveloped.Inthisstudy,MaximumEntropyNicheModeling
Received:February11,2016
wasusedtoestimatethecurrentpotentialdistributionofD.antiquaandtopredictthefuture
Accepted:January18,2017 distributionofthisspeciesin2030,2050,2070and2080byusingemissionscenario(A2)
Published:February3,2017 with7climatevariables.Theresultsofthisstudyshowthatcurrentlyhighlysuitablehabitats
forD.antiquaoccurthroughoutmostofEastAsia,someregionsofNorthAmerica,Western
Copyright:©2017Ningetal.Thisisanopen
accessarticledistributedunderthetermsofthe Europe,andWesternAsiancountriesneartheCaspianseaandBlackSea.Inthefuture,we
CreativeCommonsAttributionLicense,which predictanevenbroaderdistributionofthispestspreadmoreextensivelythroughoutAsia,
permitsunrestricteduse,distribution,and
NorthAmericaandEurope,particularlyinmostofEuropeancountries,Centralregionsof
reproductioninanymedium,providedtheoriginal
UnitedStatesandmuchofEastAsia.Ourpresentdayandfuturepredictionscanenhance
authorandsourcearecredited.
strategicplanningofagriculturalorganizationsbyidentifyingregionsthatwillneedto
DataAvailabilityStatement:Allrelevantdataare
developIntegratedPestManagementprogramstomanagetheonionmaggot.Thedistribu-
withinthepaperanditsSupportingInformation
files. tionforecastswillalsohelpgovernmentstooptimizeeconomicinvestmentsinmanagement
programsforthispestbyidentifyingregionsthatareorwillbecomelesssuitableforcurrent
Funding:Thisresearchwasfinanciallysupported
bytheSpecialFundforAgro-scientificResearchin andfutureinfestations.
PublicInterest(GrantNo.201303027).Thefunder
hadnoroleinstudydesign,datacollectionand
analysis,decisiontopublish,orpreparationofthe
manuscript.
CompetingInterests:Theauthorshavedeclared
thatnocompetinginterestsexist.
PLOSONE|DOI:10.1371/journal.pone.0171190 February3,2017 1/15
Predictionofcurrentpotentialandfutureworldwidedistributionofonionmaggot
Introduction
Climateisoneoftheprincipalfactorsdefiningthepotentialrangeofinsectsandclimate
changedirectlyaffectsthedistributionofspecies[1–2].Considerableevidencesuggeststhat
theaverageglobaltemperatureswillincreaseby2–4˚Cbetweenthepresentand2100under
severaldifferentgreenhousegasemissionscenarios[3–4].Globalwarmingwilllikelyaffect
almostallaspectsofinsectlifehistoryandpopulationdynamicssuchasdevelopmentrate,vol-
tinism,anddistributionrange[5–8].Risingtemperaturescansignificantlyinfluencethekey
physiologicalcharacteristicsthataffectthedistributionandseasonalactivityofinsectpests[9–
10]andchangethelikelihoodofseverepestdamagebyturningclimaticallyunsuitablehabitats
intosuitableonesorviceversa[11–12].Becauseofthesensitivityofinsectstoweathercondi-
tions,globalclimatechangewillpotentiallydrasticallyalterpestoutbreaks[13–15].
Theonionmaggot,Deliaantiqua,isaworldwideandseriouschronicpestwithanarrow
hostrangewithinthegenusAlliumsuchasOnion(AlliumcepaL.),Scallion(Alliumfistulosum
L.)andGarlic(AlliumsativemL.)thatsignificantlydamagesplantsinsubtropicalregions
throughouttheworld[16–17].Theinitialoccurrenceofonionmaggotwasreportedinthe
USAinsomeregionsofWisconsinintheearlytwentiethcentury[18].Thispestcontinuesto
causeseriousdamageinAsia,particularlyinChinaandJapan,Europe,andNorthAmerica
[19–21].Theonionmaggothasthreeorfourgenerationsannually,andthefirstgeneration
causesthegreatesteconomiclossbecausethelarvaekillyoungplants[22].Second-andthird-
generationlarvaecauselittledamagetothecroprelativetothefirstgeneration,butfeeding
injurycandistortbulbsandallowentryofpathogens,bothofwhichrendercropsunmarket-
able[23–24].
Manystudieshaveinvestigatedtheecologyandphysiologyoftheonionmaggot,andthe
currentworldwidedistributionofthepestisfairlywellknown.However,itislikelythatthe
futuredistributionofthispestwillbeexpandedbecauseofthecontinuedeffectsofglobal
warming.Currently,noonehasuseddistributionrecordsandcurrentandpredictedclimactic
datatopredictfuturechangesinthedistributionofthispest.MostofAlliumplantshavevery
higheconomicvalueandtheyalsorankhighpositionamongvegetablesproductionthrough-
outtheworld[25].Thistypeofinformationwillbeabsolutelynecessaryforscientistsand
farmersinvolvedinproductionofAlliumcropsthroughouttheworldtodevelopfuturemoni-
toringandmanagementstrategiesthancanminimizelosses,particularlyinareaswherethe
pesthasnotcausedseriousdamagepriortoglobalwarming.
Severaldistributionmodelshavebeendevelopedtoprovideinformationaboutthefuture
potentialeffectsofclimatechangeonthefuturedistributionofinsectspecies.Themostwell
knownmodelstopredictthedistributionofinsectsbasedonclimacticinputsinclude:GLM,
GAM,BRT,BIOCLIM,CLIMEX,GARPandMaxEnt,etc[15,26].Inrecentcomparisons
usingseveraltypesofalgorithmstopredictspeciesdistribution,MaxEntwasregardedasthe
best-performingmodelusingpresence-onlydataandshowedabetterperformancecompara-
bleto16otheralgorithms,suchasgenerallinearmodels(GLM)[27–28].Inseveralprevious
studies,MaxEntwasappliedtopredictthepotentialdistributionofspecies,suchas:Stinkbug
(Halyomorphahalys)[29],Winterannualgrass(BromustectorumL.)[30],andFruitfly(Bactro-
ceradorsalis)[31],andSpinypocketmice(Rodentia:Heteromyidae)[32],etc.
Inthisstudy,wecollectedtheoccurrencedataforonionmaggotbasedonextensiverefer-
encesandweusedMaxEnttoestimatethecurrentpotentialdistributionofD.antiquaandto
predictthefuturedistributionofthisspeciesin2030,2050,2070and2080.Basedontheresults
ofthesepredictions,weprovideatheoreticalreferenceframeworkforthemanagementand
preventionofonionmaggot.
PLOSONE|DOI:10.1371/journal.pone.0171190 February3,2017 2/15
Predictionofcurrentpotentialandfutureworldwidedistributionofonionmaggot
Methods
Occurrencedataandstudyarea
Occurrencedatawerecollatedfromsurveyspublishedintheresearchliterature.Atotalof
128occurrencerecordsforDeliaantiquawereusedinouranalysis.Geo-coordinatesforeach
chosendatapointwereeitherreferencedfrominformationpresentedintheliteratureorby
usingGoogleEarthcoordinates(S1Table).
Occurrencedataareoftenbiasedduetodifferencesinsamplingintensity.Inorderto
reducetheimpactforclusteredoccurrencedataonMaxEntmodels,weusedaraster(gridsize
approximately10km2)andrandomlyselectedonerecordpercellinthisstudy[33–34].This
methodreducedthenumberofoccurrencesto99pointsusedforfurtherstudy.
Somestudiesusingenvironmentalvariablesoverlargeareas(eg.allovertheworld)have
ledtoconservativepredictionsofcurrentspeciesdistributionandunder-estimatedtheextent
ofclimatechange[33–34].Moreover,somestudiessuggestedthattheonionmaggotisa
chronicpestofcultivatedAlliumsp.throughouttheHolarcticregion[16,35].Therefore,we
selectedNorthAmerica,EuropeandWestAsia,East-AsiaandJapanrespectivelyasthetarget
areasinourmodeling.
Environmentallayers
Currentenvironmentalparameters. Nineteenenvironmentalvariableswhichhad30’spa-
tialresolution(~1km)wereusedinourpresentstudy(Bio1-19)(http://www.worldclim.org/)
[26,36].Correlationanalyseswereusedtoselectbioclimaticlayers.Weselectedlayersthatwere
nothighlycorrelated(r<0.9)becausemanystudieshaveshownthathighlycorrelatedvariables
affecttheresultsforspeciesdistributionmodeling(S2Table)[37–40].Furthermore,manypre-
viousstudiesofthebiologyandpersistenceofonionmaggotinfestationsshowthattemperature
isabasicimpactfactorforsubterraneanpests,suchasDeliaantiqua,becauseitdeterminesthe
extentofspreadandinducesspecificphysiologicalbehaviors[18–20,22].Temperaturenotonly
determinesthesuitabilityofhabitatsforthispest,butalsoinduceskeyphysiologicalprocesses
suchasdiapause[41–42].Thesevenbioclimaticlayersincludedinourmodelingstudieswere
obtainedfromWorldclim(Table1)[36].
Futureenvironmentalparameters. Forfutureclimaticpredictions,weuseddownscaled
predictionsavailableintheWorldclimdatabasefromover24differentGCMsusedinthe
IPCCFourthAssessmentReport[4].TheIPCCSRES(IntergovernmentalPanelonClimate
ChangeSpecialreportofEmissionscenarios)includedtwoemissionsscenarios,theA2andB2
scenarios.Toillustratetheworst-caseclimatechangeprediction,wechoseA2asthefuturecli-
matescenario.TheA2emissionsscenarioassumesrelativelyrapidpopulationgrowthandrel-
ativelyhighglobalCO emissionsincreasingtoalmost5timesthe1990valuesby2100.TheB2
2
Table1. FactorsincludedaspredictorvariablestomodelthepotentialglobaldistributionsofDelia
antiqua.
EnvironmentalVariables
Bio01 Annualmeantemperature(˚C)
Bio02 Meandiurnaltemperaturerange(mean(periodmax-min))(˚C)
Bio04 Temperatureseasonality(CofV)
Bio05 Maxtemperatureofwarmestmonth(˚C)
Bio06 Mintemperatureofcoldestmonth(˚C)
Bio13 Precipitationofwettestmonth(mm)
Bio14 Precipitationofdriestmonth(mm)
doi:10.1371/journal.pone.0171190.t001
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Predictionofcurrentpotentialandfutureworldwidedistributionofonionmaggot
scenariopredictsslowercontinuingpopulationgrowthanddiversetechnologicalchanges
resultinginglobalCO emissionsjustdoubletheir1990valuesby2100.Thesescenarioscov-
2
ered7different30yearrunningmeanperiods:2010–2039(2020s),2020–2049(2030s),2030–
2059(2040s),2040–2069(2050s),2050–2079(2060s),2060–2089(2070s)and2070–2099
(2080s).Inthisstudy,4meanperiodswereusedforfutureprediction:2030,2050,2070and
2080.Alldimensionsweresetat30’spatialresolutionforfurtheranalysis.
Ecologicalnichemodeling
Ecologicalnichesandassociatedpotentialgeographicrangescanbeapproximatedusing
correlativealgorithmsthatrelateknownpoint-occurrencedatatodigitalGISdatalayers,
andsummarizespatialvariationsintheselayersinmultidimensionalenvironmentalspace
[43].
ThemaximumentropymethodasimplementedinMaxEntversion3.3.3softwareisusedto
createmodelsofthesuitablecurrentandfuturenichedistributionsofspecies[44–47]andhas
beenwidelycontributedtoestimatespeciesdistributions[48–49].Thissoftwarewasusedin
ourstudybecauseofthreereasons:1)ithasbeenbetterthanotheralgorithmsinpredicting
species’distributionsthatreflectthetruephysiologicalorclimaticconditions[50];2)itper-
formsbetterthanothermodelssuchasBIOCLIMandGARPinpredictingtheeffectsofcli-
matechangeondistribution[27,51];3)itfindstheprobabilitydistributionofmaximum
entropy(thatwhichisclosesttouniform)subjecttoconstraintsimposedbytheobservedspa-
tialdistributionsofthespeciesandenvironmentalconditions[45].
Inthisstudy,thealgorithmwasrunforthevariablesatcurrentclimaticconditionswith5
replicates,500iterationsand10000randombackgroundpoints.Then,weperformedmodel-
ingprojectionsforfutureclimatescenarios(2030,2050,2070,and2080).WeletMaxEntselect
bothsuitableregularizationvaluesandfunctionsofclimatevariablesautomatically,whichit
achievesbasedonconsiderationsofsamplesize.MaxEntoutputsacontinuousindex,ranging
from0to1,thatisanindicatorofrelativesuitabilityforthespecies,basedontheprincipleof
maximumentropy,asconstrainedbytheinputoccurrencedata.Weranthemodelsusingthe
defaultregularizationvaluesthathavebeentunedtoperformwellacrossavarietyoforganisms
andregions[52].
Modelevaluation
Toassesstheperformanceofthemodels,theareasunderthecurve(AUC)metricsofthe
receiveroperatorcharacteristics(ROC)curveswereusedinthecurrentstudy[53].TheAUC
wasobtainedbythethresholdindependentreceiveroperatingcharacteristic(ROC)analysis
[49].AROCcurveshowstheperformanceofamodelwhoseoutputdependsonathreshold
parameter,ittestswhetheramodelclassifiesspeciespresencemoreaccuratelythanrandom
predictions.AperfectmodelhasanAUCvalueof1,butperformanceisexcellentwhenthe
AUCvalueis>0.9[54].Intheprocessofmodeling,80%ofoccurrencelocalitieswereran-
domlyselectedastrainingdata,whiletheremaining20%servedfortestingtheresultingmod-
els[55].
Toimprovedisplaysofpredictionsinthisstudy,thelogisticoutputofMaxEnt,which
rangesfrom0(unsuitability)to1(highsuitability),wasused[52].Conversionofthecontinu-
oussuitabilityindexmapstobinaryhabitatandnon-habitatchartsrequiredaprobability
thresholdtodeterminethepotentialchangeincurrentandfuturehabitatsofspecies.Todefine
habitatsandnon-habitatsforDeliaantiqua,the“maximumtrainingsensitivityplusspecificity”
thresholdwasemployedinourstudy[56].
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Predictionofcurrentpotentialandfutureworldwidedistributionofonionmaggot
Thepredictedresultswereclassifiedintofourlevelsofsuitability:unsuitable(0-threshold),
marginallysuitable(threshold-0.4),moderatelysuitable(0.4–0.6)andhighlysuitableareas
(0.6–1).
WeusedArcview3.3(ESRI)tooutputourmapinourstudies.
Results
Statisticalmodelevaluation
Basedonknownoccurrencesofonionmaggotandcurrentclimatedata,wegeneratedgeo-
graphicdistributionmapspredictingareaswhereonionmaggotmightoccur.Themodelper-
formanceforthispestwasbetterthanrandom(AUC=0.94fortrainingdataandAUC=
0.923fortestdata);thus,themodelproducedhighlyeffectiveinpredictingthesuitablehabitat
areaforthisspecies.Our“maximumtrainingsensitivityplusspecificity”thresholdvalueof
0.29wasobtainedfromthe5timereplication.
Currentandpotentialdistribution
ThepresentdistributionofDeliaantiquaintheworldaccordingtotheoccurrencerecordswe
obtainedfromtheliteratureisillustratedinFig1.ThecurrentclimatepredictionsfromMax-
Entshowedthefollowingpotentialdistributionpatternsforthevariouspartsoftheworld:(1)
wideareasofNorthAmerica,particularlytheCentralandEasternpartsoftheUnitedStates
(especiallytheAtlanticoceancoastalareas,southerncoastalregionsofAlaska,andsome
Northernandcentralstates)andtheEasternSouthernareasofCanadaborderingtheUS(2)
EuropeandwesternAsia,particularlytheEasternEuropeanandWesternAsiancountries
neartheCaspianseaandBlackSea(especiallyEngland,Ireland,Denmark,Ukraine,Turkey
andKazakhstan)(3)EasternAsia-MostofChina,Japan,NorthKoreaandSouthKorea(Figs
2–5).
Themodelpredictionsforcurrentdistributionandtheactualrecordeddistributiondata
shownintheoccurrencerecordsfittogetherverywell.Seventy-ninepercentoftheoccurrence
recordsfromaroundtheworldoccurredintheareasthatthemodelpredictedwouldbehighly
Fig1.Thecurrentglobaldistributionofonionmaggot,Deliaantiqua.ReprintedfromESRIdataunderaCCBYlicense,with
permissionfromEnvironmentalSystemsResearchInstitute,Inc.,originalcopyright2016.
doi:10.1371/journal.pone.0171190.g001
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Predictionofcurrentpotentialandfutureworldwidedistributionofonionmaggot
Fig2.FuturepotentialsuitablehabitatsforDeliaantiquaontheNorthAmericacontinentpredictedby
MaxEnt.Thelettersshowpredictionsforthecurrent,2030,2050,2070and2080timeframes(A:Current;B:
2030;C:2050;D:2070;E:2080).Red=highlysuitableareas;Blue=Moderatelysuitableareas;Yellow=
Marginallysuitableareas.
doi:10.1371/journal.pone.0171190.g002
suitableareasforonionmaggotdevelopment.Themodelpredictionsforareasaroundthe
worldthatwouldbemoderatelyormarginallysuitableforonionmaggotdevelopmentare
extensive,mainlyincluding:NorthAmerica,CentralandWesternEurope,EasternAsia,and
theCaspianandBlackSearegions.IntheUSAandEuropethesepredictedregionsthatareless
optimalfordevelopmentofthispestareactuallymuchlargerthanthepredictedhighlysuitable
areas.InChina,JapanandNorthKorea,thereareverylargeregionspredictedtobehighly
suitable,whichareslightlylessthanthesumofmoderatelyandmarginallysuitableregions.
ButinSouthKorea,almostallregionsarepredictedtobemoderatelysuitable.
Futureclimatepredictions
TheMaxEntmodelswithA2emissionscenariosforpotentialdistributionofDeliaantiquafor
2030,2050,2070,and2080areillustratedin(Figs2–5).Tosimplifythefigures,theglobaldis-
tributionissubdividedintothreeregions:NorthAmerica,EuropeandWestAsia,EastAsia.
a)NorthAmerica. InNorthAmerica(Fig2),theMaxEntmodelcurrentlypredictsthata
fewregionsinNorthernandNorth-easterncoastalstatesofAmerica,suchasNewYork,New
Jersey,Ohio,Maryland,Indiana,IllinoisandIowa,havehighlysuitableclimateforDeliaanti-
qua.Also,themodelpredictsthatmostoftheMid-northernandNorth-easterncoastalareas
ofAmericaaremoderatelyandmarginallysuitableclimaticareasforthisspecies.Inthefuture
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Predictionofcurrentpotentialandfutureworldwidedistributionofonionmaggot
Fig3.FuturepotentialsuitablehabitatsforDeliaantiquaonEuropeandWestAsiacontinent
predictedbyMaxEnt.Thelettersshowpredictionsforthecurrent,2030,2050,2070and2080timeframes(A:
Current;B:2030;C:2050;D:2070;E:2080).Red=highlysuitableareas;Blue=Moderatelysuitableareas;
Yellow=Marginallysuitableareas.
doi:10.1371/journal.pone.0171190.g003
predictionsin2030to2080,theselessoptimalsuitableareaswillgraduallyexpandtoinclude
moreoftheNorthernandMid-westernstatessuchasKansas,Oklahoma,ColoradoandUtah.
Inaddition,themodelpredictsthathighlysuitableareasforonionmaggotinSouthernAlaska
willgreatlyincreasebetween2030to2080.
InCanada,theSouthernareasofOntarioandQuebecjustnorthoftheUSborderwill
remainmostlymoderatelysuitableforthepestinfutureclimacticpredictions.Theunsuitable
areasinNewfoundlandandNewBrunswickwillgraduallybecomemarginallysuitablefor
onionmaggotby2030andthisareawillcontinuouslyincreaseorbecomeevenmoresuitable
regions.Inaddition,thepredictionsshowedthatSouthernNovaScotiaandSouthernNew
Brunswickwillbehighlysuitableforthepestby2030,andthensteadilyincrease(Fig2).
Ingeneral,MaxEntpredictsthathighlysuitableareasforonionmaggotinNorthAmerica
willgraduallyincreaseuntil2080.Also,themoderatelyandmarginallysuitableareaswillgrad-
uallyincreasebymorethan39%and32%inthefuture,respectively.Thehighlysuitableareas
willalsoincreaseandthenwillstabilizeto10.24sqkmby2080(Fig6A).
b)EuropeandWestAsia. TheMaxEntmodelpredictedthatafewareasinNorth-West-
ernEuropeandtheWesternAsianregionsneartheCaspianseaandblackSeawillbehighly
suitableforOnionmaggotbetween2030to2080,particularlyinSouthernEngland,Southern
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Predictionofcurrentpotentialandfutureworldwidedistributionofonionmaggot
Fig4.FuturepotentialsuitablehabitatsforDeliaantiquaonChina&theKoreacontinentusing
MaxEnt.Thelettersshowpredictionsforthecurrent,2030,2050,2070and2080timeframes(A:Current;B:
2030;C:2050;D:2070;E:2080).Red=highlysuitableareas;Blue=Moderatelysuitableareas;Yellow=
Marginallysuitableareas.
doi:10.1371/journal.pone.0171190.g004
Norway,SouthernSweden,Netherlands,Belgium,South-westernRussia,SouthernTurkey
andSouthernKazakhstan,etc.By2080,therangeofmaximallysuitableareasforthispestwill
spreadtomanyregionsinNorthernEuropesuchasIcelandandNorth-westernRussia.Also,
themodelpredictsthatmoderatelyandmarginallysuitableareasfortheonionmaggotwill
greatlyincreasebetween2030to2080.By2080,themodelpredictsthatmostcountriesof
Europewillhavesuitablelivingconditionsforthispest,includinglargepartsofWestern
Europe,WesternRussiaandNorthernKazakhstan.
InEuropeandWestAsia,highly,moderatelyandmarginallysuitableareasforonionmag-
gotarepredictedtocontinuouslyincreaseuntil2080,andtheareawillstabilizeto146.35sq
km,960.2sqkmand550.65sqkm,respectively(Fig6B).
c)EastAsia. InChina,almostalloftheNortheastern,NorthcentralandCentralregions
andsomeoftheNorthwesternandSoutheasternregionsarecurrentlyhighlysuitableforthe
onionmaggot.TheMaxEntmodelshowsthatthetotalareaofmaximumsuitablelandwill
slightlyincreaseinthefuturealthoughthemajorpartofthisareawillshiftfromsouthtonorth
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Predictionofcurrentpotentialandfutureworldwidedistributionofonionmaggot
Fig5.FuturepotentialsuitablehabitatforDeliaantiquaontheJapancontinentusingMaxEnt.The
lettersshowpredictionsforthecurrent,2030,2050,2070and2080timeframes(A:Current;B:2030;C:2050;
D:2070;E:2080).Red=highlysuitableareas;Blue=Moderatelysuitableareas;Yellow=Marginallysuitable
areas.
doi:10.1371/journal.pone.0171190.g005
andwillincludescattereddistributionsinmanyprovinces.Thesuitableareaswilldecrease
graduallyinsouthernpartsfrom2030–2080andNorthernXinjiangwillbecomemoresuitable.
Inaddition,mostofWesternandtheNorthernmostChineseregionswillremainunsuitable
foronionmaggotoutbreaks(Fig4).
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Predictionofcurrentpotentialandfutureworldwidedistributionofonionmaggot
Fig6.ComparisonoffuturepotentialsuitablehabitatareasforDeliaantiquabyMaxEntfortimeframesondifferentcontinents:
Current,2030,2050,2070and2080.Red=highlysuitableareas;Blue=Moderatelysuitableareas;Yellow=Marginallysuitableareas.A:
NorthAmerica;B:EuropeandAsia;C:China&Korea;D:Japan.
doi:10.1371/journal.pone.0171190.g006
Currently,NorthernJapan,WesternNorthKorea,andafewregionsinNortheastofSouth
KoreaarehighlyclimaticallysuitableforDeliaantiqua(Figs4and5).Themodelpredictsthat
theproportionanddistributionofhighlysuitableareaswillcontinuouslyincreaseinKorea
andNorthernJapanfrom2030–2080.Incontrasttotheriseinsuitabilityinnorthernregions,
SouthernJapanwillbecomeprogressivelylesssuitableinthefuture,andthenwillbecome
mostlymoderatelyormarginallysuitableby2080.
ThepredictionsforhighlyandmarginallysuitableregionsinChinaandKoreawillincrease
21%and5%,respectively.Incontrast,themoderatelysuitableareaswilldecrease22%by2080
(Fig6C).TheoverallpredictionsforhabitatsuitabilityinJapanwillremainfairlyconstant,
exceptthatmanyhighlysuitableregionswillbecomeonlymarginallysuitablehabitat(Fig6D).
Discussion
Inthisstudy,theMaxEntmodel’scurrentpredictionsofthemostsuitablehabitatsforthe
developmentoftheonionmaggotgenerallyagreedwithavailablehostoccurrencerecords.
AnalysesshowedthatMaxEntproducedhighlyaccuratepredictionsofAUCvaluethatwas
greaterthan0.9.Futuremodelpredictionsfrom2030–2080derivedfromaIPCCclimate
changescenarioshowedthatclimaticchangeswouldgreatlyaffecttheworld-widedistribution
ofthispest,butthespecificeffectswillvaryamongdifferentlocations.Ingeneral,themodel
predictedthattherewouldbeanexpansionofhighlyandmoderatelysuitablehabitatsinmost
areasinresponsetoglobalwarming,butthesemoresuitablehabitatswillactuallydecreaseina
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