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1IntroductionAmongallcrops,grapevineisoneofthosewhichinspiredthehighestnumberofbioclimaticanalysisrelatedtoclimatechange(HallandJones,2009;Andersonetal.,2012;Molitoretal.,2014;Koufosetal.,
2014;Dunnetal.,2015).Theterm“terroir” itselfstemsfromthe ideathatwineproduction issteadilyentangledwiththeenvironmental features– includingclimate–whichcharacterizeoriginandgrowingofa
variety.Climatechangeobviouslyposesurgentquestionsaboutthefutureofpremiumwineproductioninmanywine-growingregions.Morethanformostcrops,themaintenanceofthelinkofmanywineswiththeir
typicalproductionareasisanaddedvaluewhichimpactsontheculturaland–ultimately–marketvalueoftheproducts.Hence,itisofconcernforwinegrowers–aswellasforallthewineproductionspin-offs–to
knowwhichclimaticconditionsanareaisgoingtofaceinachangingclimatescenario.
Generallyspeaking,warmeranddrierconditionshavemostlycontributedtoanincreaseofwinequalityinmanyregionsoftheworld(Jonesetal.,2005;Daluetal.,2013).Ifthelatterauthorshighlighted
above all the improvements ofwinequality in the last 50 years, attributing an important role towarmer climate conditions, on the otherhand, the sameauthors claimed that a further increase could take the
bioclimatic physical driver beyond the optimum, leading to a worsening of ratings. For warm vine-growing regions, a temperature increase would probably bring with itself the undesired effect of a dramatic
Originalpapers
Simulationsofquantitativeshiftinbio-climaticindicesintheviticulturalareasofTrentino(ItalianAlps)byanopensourceRpackage
EmanueleEccela,⁎
AlessandraLuciaZollob,c
PaolaMercoglianob,c
RobertoZorerd
aDepartmentofSustainableAgro-ecosystemsandBioresources,ResearchandInnovationCentre,FondazioneEdmundMach(FEM),ViaE.Mach1,38010SanMicheleall’Adige,Italy
bMeteorologyLaboratory,CentroItalianoRicercheAerospaziali(CIRA),ViaMaiorises.n.c.,81043Capua,Italy
cRegionalModelsandGeo-HydrogeologicalImpactsDivision,CentroEuro-MediterraneosuiCambiamentiClimatici,ViaMaiorises.n.c.,81043Capua,Italy
dDepartmentofBiodiversityandMolecularEcology,ResearchandInnovationCentre,FondazioneEdmundMach,ViaE.Mach1,38010SanMicheleall’Adige,Italy
⁎Correspondingauthor.
Abstract
Inconsiderationofthesteadyentanglementsofviticulturewiththeenvironmentalfeatures– includingclimate– it isofconcerntoprojectwhichclimaticconditionsanareaisexpectedtofaceina
changingclimatescenario.Aquantitativeapproachhelps inassessingclassshift inclimateclassification;both“generic”climaticandbioclimatic indiceswereconsidered inthisstudy,namely:Köppen –
Geigertypesandsubtypes,aridity(6indices),and“Internationalvineandwineorganization”(OIV)classification(10indices).AllindiceswereeasilycalculatedbyanopensourceRlibrary(ClimClass),which
alsoincludestoolsforbasepre-processingofweatherseries.FutureclimatescenariosforthisstudywereobtainedusingtheRegionalClimateModel(RCM)COSMO-CLM,employingtwoIPCC’sgreenhouse
gasconcentrations(RCP4.5andRCP8.5),statisticallydownscaledto39weatherstationsinTrentino,aregionintheItalianAlps.Thesimulationsenvisagethenewclimaticprofileofthearea,withashift
towardswarmerandsomewhatdrierconditions.Whilenolimitationtowinegrowingisexpectedintheloweraltitudeareas,newclimaticsuitabilityisprojectedformountainareas,presentlydevotedtoother
soiluses.Thelatteranalysiswastheresultofacalibrationofathermalrequirementindextothepresentsoiluseconditionintheregion.
Keywords:Grapevine;Climatechange;Models;Indices;OIV;Italy
restrictionofthesuitableviticulturalareas(Whiteetal.,2006;HallandJones,2009).Moriondoetal.(2011)suggestedpossiblenegativeeffectsoftemperatureincreaseonwinequalityintheMediterraneanarea
(particularlyItaly).Therecordedadvanceinphenologicaltiming(CaffarraandEccel,2011;Tomasietal.,2011;Fragaetal.,2015)isaclearwarningagainstachangeinthematchbetweenavarietyanditslong-lived
growingcontext,questioningthesubsistenceofthebalancebetweentheripeningprocessandthemeteorologicalconditionsoccurringintherelevantperiod(Mullinsetal.,1992).Theactionofmeteorologicaldrivers
onphysiologicaldevelopmentmayalsoaffectyield(Bindietal.,1996;DuchêneandSchneider,2005;Webbetal.,2008),duetoanexpectedhigher,unsatisfiedwaterdemandinsummer,andtoashorterripening
period.
Spreadingviticulturalareasnorthwardentailstheshortcomingofashiftofproductionareastoregionswhichmaybenewtoeitherspecificvarietiesoreventovinegrowing(Fragaetal.,2016;Jones,2006).
Moriondoetal.(2011)suggestedpossiblenegativeeffectsoftemperatureincreaseonwinequalityintheMediterraneanarea,highlightingthatspreadingthecultivationareastohigheraltitudeswithinthesame
geographiccontextoffersthechancetomeetbetterconditionsthantheonesexpectedinthetraditionalproductionareasatlowerelevations,accordingtotheclimaticscenarios.Trentino,atemperatewine-producing
areaintheItalianAlps,canbenefitofthealtitudinalrangeofmountainregionstofaceaprogressivewarmingofclimaticconditions.
Thisworkaimsatprovidinganin-depthanalysisoftheprojectedchangeinthequantitativebioclimaticindicesthathavebeendevelopedtoassessthelandscapesuitabilityforviticulture.Themodelchainfor
thisanalysiswasbuiltbyapplyingacodewhichcalculatesclimateindicestotheoutputofclimatesimulations.
2Materialsandmethods2.1Geographical,climatologicalandviticulturalfeatures
Trentino isa6212km2 region in thecentral-easternItalianAlps (Fig.1).Altituderangesbetween70ma.s.l. (lowerSarcaValley) to3769m (Cevedalepeak).Trentinoclimate ismostlyoceanic,withsomeareasshowing
featuresoftransitiontoamorecontinental-alpineclimate,coolerandoftendrier,moretypicaloftheinnermountainvalleys.Precipitationismostlydistributedovertwomaxima,intheautumn(main)andinthespring(secondary).
ThecurrentviticulturalareasinTrentinoconsistofabout10,.000ha,distributedfrom70to850ma.s.l.Thelistofthecultivatedgrapevines(Vitisviniferassp.vinifera)includesbothredandwhitevarieties,mainlyfromFrance
(white:Pinotgris,Chardonnay,Sauvignon;rosé:Gewürztraminer;red:Pinotnoir,Merlot,CabernetSauvignon)inadditiontosomelocalcultivars(white:Nosiola;rosé:Schiavagentile;red:Teroldego,Marzemino,Lagrein)andthe
SwissMüllerThurgau,whichissuccessfullycultivateduptothehighestelevations.
Themostupdatedlandusemap(August2003),includingviticulture,hasbeendrawnanditisprovidedbytheurbanplanningserviceoftheAutonomousProvinceofTrento.ThemapisavailableasEsrishapefileattheTrentino
OPENdatawebsite(http://dati.trentino.it/)underCreativeCommonsZero–CC0v1.0Universaltermsofuse.
Fig.1Mapofthe39selectedweatherstations(PATMeteoTrentino).
2.2Observationaldataset39dailymeteorologicalseriesofprecipitationandtemperatureweremadeavailablefromMeteotrentino,themeteorologicalserviceoftheAutonomousProvinceofTrento(Fig.1).Theseriescoveredallthealtitudinalrangeof
theregion,fromthe90ma.s.l.ofTorbole,intheproximityofLakeGarda,to2600ma.s.l.ofCareserdam,anartificialreservoirintheheartofcentralAlps.Theseseriesarethesame (Pleasedelete"arethesame")werechosenaccording
totheirlengthandqualitytobias-correctanddownscalethemodeloutputinOrientgateproject(http://www.orientgateproject.org/)–seefurther.
2.3ClimatesimulationsClimatedataforthisstudywereobtainedusingtheRegionalClimateModel(RCM)COSMO-CLM(Rockeletal.,2008),theclimateversionoftheoperationalnon-hydrostaticmesoscaleweatherforecastmodelCOSMO-LM
developedbytheGermanWeatherService(DWD)andoptimizedatCMCC,REMHIdivision.ThemainfeaturesofthemodelandofitssetuparereportedinBucchignanietal.(2015)andarebrieflyrecalledinTable1.Simulationswere
performedover Italy,employingaspatial resolutionof0.0715° (about8km). InitialandboundaryconditionswereprovidedbyglobalmodelCMCC-CM(Scoccimarroetal.,2011),whoseatmosphericcomponent (ECHAM5)hasa
horizontalresolutionofabout85km.Thetimeperiodconsideredwas1976–2070;specifically,theCMIP5historicalexperiment(basedonhistoricalgreenhousegasconcentrations)wasusedfortheperiod1976–2005,while,forthe
period2006–2070,twodifferentsimulationswereperformed,employingtheIPCCRCP4.5andRCP8.5greenhousegas(GHG)concentrations.RCP4.5scenarioischaracterizedbyastabilizationinGHGemissionsafteryear∼2070,
whileRCP8.5byarapidlyincreasingGHGconcentration.Numericalsimulationswereperformedemploying512coresonaclusterof30IBMP575nodes,installedatCMCCwithanaggregatepeakpowerof18TFlops.Theelapsed
timerequiredtosimulateoneclimatologicalyearwasabout20h.
Table1MainfeaturesofCOSMO-CLMsimulationsetup.
COSMO-CLMmodelversion 4.8_clm13
INT2LMmodelversion 1.10_clm2
Horizontaldiscretization Second-orderdifferencetechnique
Horizontalresolution 0.0715°
Computationalmesh 224×230gridpoints
Timestep 40s
Timeintegrationscheme Third-orderRunge–Kutta
Convectionscheme Tiedtke
Numberofverticallevels 40
Numberofsoillevels 7
Soilmodel TERRA_ML
Frequencyupdateboundaryconditions 6h
The simulations have been deeply analysed in Bucchignani et al. (2015) and – in terms of extreme events – in Zollo et al. (2015a), showing a general good agreement with observed data. Furthermore, as explained in
Bucchignanietal.(2015),theresultsofthesesimulationsareconsistent,intermsofbothmeanbiasandprojections,withthoseobtainedfromtheEURO-CORDEXensembledata(Giorgietal.,2009),whichrepresentthe‘state-of-the-
art’ofregionalclimatesimulationsoverEuropeat0.11°ofhorizontalresolution.AlthoughRCMsarepowerfultoolsfordescribingsmallscaleclimateconditions,theirdirectuseinimpactstudiesisstillchallengingsincetheyare
commonlybiased.Inordertoprovidecorrectedclimatescenarios,simulateddatawerebias-correctedconsideringastatisticaldownscalingapproachbasedonquantilemapping(Zolloetal.,2015b).Specifically,simulateddatawere
downscaledatstationlevelusingdatafromtheavailablemeteorologicalstationsdescribedinSection2.2.
2.4ClimaticandbioclimaticindicesAllindiceswerecalculatedbytheRpackageClimClass2.0.1(Ecceletal.,2015),freelyavailableatRCranrepository(https://cran.r-project.org/).Thepackagemakesuseofmonthlyordailyseries,accordingtotheclassof
indicestobecalculated:monthlyforKöppen–Geigerclimateclassification,foraridityindices,andforRiou’sdroughtindex(oneoftheOIVindices),dailyforallbioclimaticindicesexceptRiou’s.Thecodescancarryoutgapfilling
operations,ifrequired,fortheinstrumentalseries.Meandailyandmonthlytemperatureswerecalculatedasaveragesbetweencorrespondingminimaandmaxima,availableeitherasrecordsorclimateprojections,accordingly.
2.4.1Climateclassification
(i) Köppen–Geigerclimatetypesandsub-types.TheclassicalclimateclassificationfollowsthedescriptiongiveninTrewarthaandLyle(1980).Therearefivemainclimatetypes(Ato–pleasereplaceFwithEF),andmoresub-types,accordingtothegeneralprecipitation
regimeandtoitsdistributionalongtheyear.
(ii) Aridityindices.Fiveannualindicesarecalculated:Ia–DeMartonne,Im–Thornthwaite,Q–Emberger,R–Lang,Io–Rivas-MartinezandRivas-Sáenz(detailsinAppendix1–SupplementaryMaterial,andinClimClassusermanual).
2.4.2BioclimaticindicesforviticultureOIV(2012)selectedandsuggestedalistof10indicesusefulforassessingtheclimaticclassificationofwine-growingregions.Inthepresentwork,weusedareducedlistoftheproposedindices(descriptioninAppendix1)
groupedbyphysiologicalmeaning.GrowingSeasonaverageTemperature(GST),WinklerIndex(WI),orGrowingDegreeDays(GDD),BiologicallyEffectiveDegreeDays(BEDD),HuglinheliothermicIndex(HI)areindicatorsoftheheat
requirements,necessary forapropervinedevelopmentandgraperipening.These four indiceswere testedagainst theactualgrapevinepresence in thearea, toassessa roughviticulturalareaaccording to the future,expected
conditions, as simulated by the climatic model. For the assessment of exposure of grapevine to biotic and abiotic adversities we considered the minimum temperature during rest period (Tn_rest), minimum temperature during
vegetativeperiod(Tn_veg),andmaximumtemperatureduringvegetativeperiod(Tx_veg).
ToniettoandCarbonneau(2004)proposedtoclassifyworldviticulturalareasaccordingtothreebioclimaticindices,amongthoselistedabove:Huglin’sheliothermicIndex(HI),CoolnightIndex(CI),andRiou’sDroughtIndex
(DI).Alltheseindices(seeAppendix1,Supplementarymaterial)werecalculatedtoassessclimate-drivenchanges.
2.5AssessmentofchangesintheviticulturalareaThepotentialenlargementoftheviticulturalareas,withrespecttoclimatechangescenariosandgeo-morphologicalfeatures,hasbeenassessedusingopensourceGISsoftware(QGISGeographicInformationSystemver.2.8.2,
QGISDevelopmentTeam),ahighresolutiondigitalelevationmodel(10m),andfinallyalandusemap,bothprovidedbythe“P.A.T.SistemaInformativoAmbienteeTerritorio”serviceoftheProvinceofTrento.
3Results3.1SimulatedclimatechangesinTrentino
Thebias-correctedanddownscaledclimatedatadescribedinSection2.3wereanalysedintermsofclimatechangesignaloverTrentino,consideringtheanomalybetweenthemeanclimatologyinthereferencepastperiodand
intwodifferentfutureperiods:2021–2050and2041–2070.
Asconcernsprecipitation, theprojectedclimatechangesignal indicatesageneraldecreaseof total rainfallandnumberof rainydays; incontrast,an increaseofmeanprecipitationamountonwetdaysandprecipitation
maximumisprojected.Furthermore,anincreaseinthenumberofconsecutivedrydaysandadecreaseinthenumberofconsecutivewetdaysisexpected.Ingeneral,comparisonofresultsobtainedwithscenariosRCP4.5andRCP8.5
indicatesthatthesignoftheclimatechangesignalgenerallyremainsthesameforbothscenarios,buttheintensityofthesignalisgreaterforRCP8.5.
For temperature, theclimatechangesignal indicatesasignificant increase.Specifically, this increase ishigher for themoredistant futureperiod (2041–2070), ismoreaccentuated for scenarioRCP8.5, andaffectsboth
minimumandmaximumtemperature.Inlinewiththisincreaseintemperature,thenumbersoffrostandicedays(dayswithTmin<0°CandTmax<0°C,respectively)showadecreaseandthenumberofsummerdays(dayswith
Tmax>25°C)anincrease.Forthevegetativeseason(ApriltoOctober),themeanoftheexpectedincreaseonallstationsis1.4–1.5°Cforthetimewindow2021–2050,whilefor2041–2070theextentoftheincreaseandtherangeof
valuesaremuchhigher:2.5to–3.0°C.
3.2SimulatedchangesinclimateclassificationofviticulturalareasIngeneral,theareaswhichare–orwouldeventuallybecome–suitableforvinegrowinginTrentino,canbeascribedtooneclimatetypeaccordingtoKöppen–Geiger(TrewarthaandLyle,1980):“C”(mildtemperate,rainy)–
Table2.Thesub-typeisalways“f”,whichdenotesabsenceofatruedryseason.Thefurthersub-typeofCfcanbe“a”,“b”,or“c”accordingtosummertemperature,“hot”,“cool”,or“coolandshort”,respectively;theshiftfromone
sub-typetotheotheroccurswithinatransitionrangebetweenabout250and500ma.s.l.TheotherstationsinTrentinobelongto“microthermal”climatebeltD,withonealpinestationinthe“polar”typeET(tundra-likeclimate).In
thefirstfuturetimewindow(2021–2050)atrendisevidenttotheincreaseofstationsofsubtype“a”,furtherincreasinginthesecondtimestep(2041–2070).
Table2Köppen–Geigerclimateclassificationforallstationsaccordingtoseveraltimewindowsandscenarios.Tablecellscontainthenumberofstationsineachclass.
Period&RCPscenario ′76–′05 ′21–′50 ′41–′70
4.5 8.5 4.5 8.5
Cfa 6 11 11 15 17
Cfb 24 21 21 19 20
Cfc 1 0 3 1 0
Dfb 1 0 1 3 1
Dfc 6 6 2 1 1
ET 1 1 1 0 0
Theanalysisofaridityclassesismorecomplex,involvinganumberofdifferentindices(Table3).Asageneralrule,asexpected,theclimatechangeleadstoashiftofanumberofsitestowardsdrierclasses,fromthegenerally
humidorveryhumidcategoriestogenerallysub-humidclasses,withevensomecasesofdryclassesinthefarthesttimewindow,mostlylimitedtoscenarioRCP8.5.
Table3Aridityindicesclassificationforallstationsaccordingtoseveraltimewindowsandscenarios.Tablecellscontainthenumberofstationsineachclass.SeeClimClassmanualforindexformulationsand
classificationtables.
Period&RCPscenario ′76–′05 ′21–′50 ′41–′70 PeriodRCPscenario ′76–′05 ′21–′50 ′41–′70
4.5 8.5 4.5 8.5 4.5 8.5 4.5 8.5
Ia Io
Dry 0 0 0 0 0 Ultrahyperarid 0 0 0 0 0
Semidry 0 0 0 0 0 Hyperarid 0 0 0 0 0
Mediterranean 0 0 0 0 0 Arid 0 0 0 0 0
Semihumid 0 0 0 0 0 Semiarid 0 0 0 0 0
Humid 0 0 0 0 2 Dry 0 0 0 0 0
Veryhumid.a 18 21 18 22 24 Subhumid 6 12 11 14 16
Veryhumid.b 21 18 21 17 13 Humid 25 21 20 22 22
Hyperhumid 8 6 8 3 1
Q Ultrahyperhumid 0 0 0 0 0
Desert 0 0 0 0 0
Arid 0 0 0 0 0 Im
Semiarid 0 0 0 0 0 Arid(E) 0 0 0 0 0
Subhumid 3 9 1 9 9 Semiarid(D) 0 0 0 0 0
Humid 36 30 38 30 30 Drysub-humid(C1) 0 1 0 1 2
Moistsub-hum.(C2) 2 11 2 8 12
R Humid(B1) 11 4 11 8 4
Steppe 1 0 0 0 0 Humid(B2) 4 3 4 2 7
Semiarid 0 0 0 0 5 Humid(B3) 1 7 1 8 4
Temper,warm 11 16 15 19 20 Humid(B4) 8 4 8 3 3
Temper.humid 15 13 14 12 7 Perhumid(A) 13 9 13 9 7
Humid 12 10 10 8 7
Moreindetail,Thornthwaitemoistureindex(Im),whichoffersahigherdegreeofdetail,showsageneralshifttowardslesshumidclasses,sothatinthefarthesttimewindowthemostpopulatedclasswouldbe“moistsub-
humid”,insteadof“humid–B1”,mostfrequentinthepresenttime;oneortwostationsreachthe“drysubhumid”class.Rivas-MartinezandRivas-Sáenz’sombrothermicindexattainsthesamequalitativeresult,almostequallysharing
themajorityofpresentvine-growingareabetweenthehumidandsub-humidtypes.
Inscenario′41–′70,RCP8.5,thenumberofsub-humidstationsisincreasedbyafactorof2.7,withrespecttotheinitialconditions;the“hyperhumid”classisreducedtojustonesite,whereasatthebeginningthestationsin
thisclassweresix.
ThesimulationsofEmberger’sQfactoralsoleadtoashiftfromthehumidtothesub-humidtype(inthenearesttimewindowonlyforRCP4.5scenario–amorehomogeneoussignalisdetectableforthesecondtimewindow).
Lang’spluviometricfactorRshowednegligiblechangesuntil′41–′70RCP8.5scenario;inthiscase,fivesiteswouldfallintoa“semiarid”type.AninterestingfeatureisthatsimulationsforQandImindices,inthe2021–2050RCP8.5
case,yieldeithernosignificantchangesorevenastrengtheningofhumidtypes.Finally,DeMartonneindex(Ia)showsminorchangesinthesimulations,mainlyaschangeswithinthetwosubclassesof“veryhumid”type.
Aridityindicesshowedagenerallygoodcollinearity,insomecaseswiththeexceptionofthelowervalues(driersites)andelevations.Inordertocreateanindexthatsummonsupallclassifications,irrespectiveoftheunitof
eachindex,rankshavebeencalculatedforeachstationandindex,andthemedianofrankshasbeentakenasasynthesisindex.Averystrong(p<0.001)negativecorrelationofariditywithelevationcanbeinferred(Fig.2),yielding
theexpectedresultoflesshumidclassesatthelowestelevationsites.
3.3SimulatedchangesinviticulturalindicesThemostcommonviticulturalbioclimaticindiceswereconsidered–seeAppendix1,Supplementarymaterial,fordefinitions–sevenbyOIV(2012)(BEDD,GST,WI,HI,Tn_rest,Tn_veg,andTx_veg),andthreesuggestedby
ToniettoandCarbonneau(2004).ResultsaresummarizedinTable4.
Fig.2Aridity(medianofranksofsixindices)vs.elevationforstationsinviticulturalareasforperiod1976–2005.Lowervaluesreflecthigheraridity.
Table4ClassificationaccordingtoOIVbioclimaticindicesforallstationsaccordingtoseveraltimewindowsandscenarios.Tablecellscontainthenumberofstationsineachclass.SeeAppendix1,Supplementary
material,forindexformulations.
Period&RCPscenario ′76–′05 ′21–′50 ′41–′70 PeriodRCPscenario ′76–′05 ′21–′50 ′41–′70
4.5 8.5 4.5 8.5 4.5 8.5 4.5 8.5
Tm_veg WI
Toocool<13°C
18 11 11 9 8 Toocool<850
19 10 10 9 8
Cool13–15°C
10 11 11 6 3 RegionIa850–1111
8 9 9 2 2
Intermediate15–17°C
6 6 6 12 12 RegionIb1111–1389
4 8 8 11 9
Warm17–19°C
5 8 7 5 8 RegionII1389–1667
5 4 4 5 8
Hot19–21°C
0 3 4 7 5 RegionIII1667–1944
3 4 4 4 3
Veryhot21–24°C
0 0 0 0 3 RegionIV1944–2222
0 4 4 5 4
Toohot>24°C
0 0 0 0 0 RegionV2222–2700
0 0 0 3 5
Toohot>2700
0 0 0 0 0
HI
Toocool<1200
13 9 9 8 8 BEDD
Verycool1200–1500
11 4 4 2 1 <1000 27 19 19 11 11
Cool1500–1800
4 11 11 9 4 1000–1200 4 8 8 12 11
Temperate1800–2100
5 4 4 8 11 1200–1400 6 5 5 6 6
Warmtemper2100–2400
6 5 5 3 4 1400–1600 2 7 7 8 8
Warm2400–2700
0 6 6 6 5 1600–1800 0 0 0 2 3
Verywarm2700–3000
0 0 0 3 5 1800–2000 0 0 0 0 0
Toohot>3000
0 0 0 0 1 >2000 0 0 0 0 0
AccordingtoGladstones’biologicaleffectivedegreedaysindex(BEDD),alargepartoflandinTrentinodoesnotmeettheminimumthermalrequirementforwinegrowing(lessthan1000BEDD).However,roughlyhalfof
weatherstationswhicharepresently inviticulturalareasfall inthe1200–1400BEDDclass;a fewsites fall inawarmerclass,whileothers fit in thecolderclasses.Thesimulatedprogressivewarmingreducesthenumberof the
selectedsites,currentlyunsuitableforviticulturalusebecausetoocool,tolessthanhalfoftheinitialextentinthe′41–′70timewindow(Fig.3).
ThecorrelationbetweenBEDDandelevationcanbeconsideredlinearbelow1800ma.s.l.andthereforeforeachscenariotheupperlimitforviticulturewasassessedusingthelinearregression’scoefficients(Table5)anda
thresholdvalueof1000BiologicallyEffectiveDegreeDays,whichisconsideredsufficienttofulfilthethermalrequirements,neededtocompleteboththevegetativeandreproductivecycleofgrapevine.
Table5LinearregressionsbetweenBEDDandelevationforcurrentandfutureconditions,basedonclimatechangescenarios.Theupperlimitsforviticulturehavebeencalculatedusingtheregressioncoefficients
(slopeandintercept)ofeachscenarioandthelowestvalueofBEDD(1000).Pearsoncoefficientsandthenumberofweatherstations(nr.ofsites)fallingintothesuitableareaarealsoreported.
Ref.period 1976–2005 2021–2050 2041–2070
Scenario Current RCP4.5 RCP8.5 RCP4.5 RCP8.5
Slope −0.64 −0.64 −0.65 −0.63 −0.61
Intercept 1478 1640 1654 1736 1760
Pearson −0.98 −0.98 −0.98 −0.98 −0.98
Upperlimit(ma.s.l.) 750 992 1000 1161 1243
Nr.ofsites 13 22 22 26 28
Huglin’sindex(HI)assessesthemainclassshiftsfrom“temperate”or“cool”classestothewarmeronesinthefarthestperiod,thankstotheincreasedsuitablearea,butwithagrowingnumberofcasesinthewarmerclasses
andonesiteeveninthe“toowarm”class.
Asfarasvegetativeseasonindex(GST)isconcerned,the“intermediate”class(15–17°C)remainsforallscenariosthemostpopulatedinthepresentviticulturalarea,butwithatrendofaprogressivedepopulationofthecolder
classes,andtheconsequentincreaseofmembersinthewarmerones,withafewsitesreachingtheclass“veryhot”;theareawhichistoocoolforgrapevineundergoesareductionofthesamemagnitudeasthatpredictedbyBEDD.
SimilarresultsareobtainedfromtheanalysisofWinkler’sindex(WI),whichishighlycorrelatedtoGST,beingbothmeasuresofmeanthermalconditionsduringgrowingseason(seeformulationinAppendix1,Supplementary
material).Classesof“RegionIa”arestronglyreducedinthe ′41–′70RCP8.5scenario.“RegionIV”,todaynotrepresentedinthepotentiallyviticulturalareasoftheregion,beginstobepopulatedbysomesites inthe ′21–′50time
window,andeventhethermalhigherclassof“RegionV”,thelastbeforetheclassdefinedas“toohot”,hassomesitesfittingin.
Fig.3CorrelationsbetweenBiologicallyEffectiveDegreeDaysandelevation,accordingtocurrentandfutureclimaticconditions,basedonclimatechangescenarios.Toocoolareas(lessthan1000BEDD)arenotconsideredsuitableforviticulture.
Theanalysisofindicesofextremetemperature(Table6)hasentailedfixingthresholdstoassesstherecurrenceofundesirableordangerousevents;indeed,nostandardswereproposedforsuchindices.Thevalueshavebeen
chosenalsotakingintoaccounttheirmodelledoccurrenceinthepresentconditions,andconsideringtheirabilityintrackingchangesinthedifferenttimewindowsandscenarios,asfollows.
Table6ClassificationaccordingtoOIVbioclimaticindicesforextremetemperaturesforallstationsaccordingtoseveraltimewindowsandscenarios.Tablecellscontainthenumberofstationsineachclass.See
Appendix1,Supplementarymaterial,forindexformulations.
Period&RCPscenario ′76–′05 ′21–′50 ′41–′70
4.5 8.5 4.5 8.5
Tn_rest
Below−15°C 30 30 16 18 10
Above−15°C 9 9 23 21 29
Tn_veg
Below−2°C 39 37 36 36 36
Above−2°C 0 2 3 3 3
Tx_veg
Below35°C 34 26 26 21 15
Above35°C 5 13 13 18 24
Tn_rest.Grapevineduringdormancycantoleratetemperaturesaslowas−15°Cto−25°C,accordingtosources(Düring,1997;Lisek,2009).IntheviticulturalareasofTrentino,thelattertemperaturewasneverattained,
whilesomedamagescouldalreadyoccuratminimumair temperatureofabout−15°C(Zulinietal.,2010).Thiswas the thresholdchosen forTn_rest, calculatedas theminimumreached ineach30-yearperiod.Theanalysisof
simulationsstartswithalargemajorityofstationswhereextremelylowtemperaturesoccuratleastoncein30years,andthesameconditionismaintainedfor′21–′50RCP4.5.Thefollowingscenariosshowaprogressivedecreaseof
thenumberofstationswhereextremelylowtemperaturesareattained,andin′41–′70RCP8.5theratiooftheareasbelowandabovethethresholdisalmostreversed.
Tn_veg.Giventhatthe“vegetationperiod”accordingtotheindexissettostartfromApril,aratherearlyperiodforsprouting,atemperatureof−2°C,generallyacceptedasadamagethresholdforreproductivebuds,wasset
asadiscriminatingvalueforfrostepisodesduringthesensitiveperiod,calculatedastheminimumreachedineach30-yearperiod.Thetrendforthisindexshowsonlyminorchangesalongthetimelineandtheseverityofscenarios,
withamodestdecreaseinthenumberofstationswherefrostduringthevegetativeperiodisstillsimulatedtooccur.
Tx_veg.Areasonablethresholdforphysiologicalimpairmentingrapevineis35°C(HunterandBonnardot,2011);owingtoafrequentattainmentofthisthresholdinfullsummer,themedianofeach30yearmaximumvalues
wasconsideredabetterindicatorfortheoccurrenceofhotsummerconditions.Asreferencetemperaturesprogressivelygrowaslongasscenariosbecomemoresevere,thepercentageofserieswherethe35°Cthresholdistrespassed
risesprogressively,becomingthemajorityin′41–′70RCP8.5,whentheviticulturalareaismostlyexpectedtofallinthisclass.
Ingeneral,alltheselectedindicesshowastrongdependencewithelevation,whichismaintainedinfuturescenarioswithsimilarfeaturesfor“meantemperature”indices(BEDD,GST,HI,WI).Thisrelationshipisrepresented
inFig.3forBEDD,theindexchosentoassessthearealextension.
Tonietto–Carbonneau’ssyntheticclassificationmakesuseofthreeindices,asexplainedinSection2(Table7).OneisaslightsimplificationofHuglin’sindex(HI)classification,whoseresultshavealreadybeendiscussed;
accordingtothisclassification,in′41–′70RCP8.5thefullrangeofHIclassesarepresentinTrentino.Thesecondisthe“Coolnightindex”;mostoftheseriesstillbelongtothecoolestclass,butasthereferencescenariogetswarmer,
anincreasingnumberofsitesareexpectedtofallintoa“negative”coolnessclass(CI−1),highlightingtheshifttothemacro-categoryof“warm”viticulturalclimatesforthosesites,wherenighttemperatureintheproximityofharvest
aregenerallyhigherthandesirable.TheRiou’sdroughtindex(DI)showsaprogressiveappearanceofsiteswhere,onaverage,moderatelydryconditionstakeplaceinthelastmonthofripening(September),whereas,atpresent,moist
conditionsprevailforallsites.
Table7ClassificationaccordingtoToniettoandCarbonneau’sbioclimaticindicesforallstationsaccordingtoseveraltimewindowsandscenarios.Tablecellscontainthenumberofstationsineachclass.Seetextfor
explanationsonindices.
Period&RCPscenario ′76–′05 ′21–′50 ′41–′70 Period&RCPscenario ′76–′05 ′21–′50 ′41–′70
4.5 8.5 4.5 8.5 4.5 8.5 4.5 8.5
CI−2 0 0 0 0 0 HI−3 24 13 13 10 9
CI−1 1 1 3 4 6 HI−2 4 11 11 9 4
CI+1 4 5 4 5 8 HI−1 5 4 4 8 11
CI+2 34 33 32 30 25 HI+1 6 5 5 3 4
HI+2 0 6 6 9 10
DI−2 24 10 19 14 9 HI+3 0 0 0 0 1
DI−1 15 19 19 20 15
DI+1 0 10 1 5 15
DI+2 0 0 0 0 0
3.4SimulatedchangesintheviticulturalareaAccordingtotheclimatechangescenarios,thecurrentviticulturalareawillpresenthigherthermalavailabilityleadingtoearlyphenologicalevents(JonesandDavis,2000),animprovementofgrapequalityforlate-ripening
varieties,andearlyharvest,particularlyforsparklingwineproduction.Moreover,apotentialextensionofthesuitableareaforviticulturetohigherregionsisexpected,althoughtherealgrowthpotentialshouldcomplywithother
importantconstraints(Table8),suchasgentleslope,favourableorientation,largeavailabilityofpotentialdailymeansun-hours(AvgSunHursVeg)andcumulatedglobalsolarradiation(CumGloRadVeg)duringthevegetativeperiod.
Finally,newpotentialareasshouldbelargeandcontiguousenoughtojustifyandsustainthecostsforvineyardestablishment.Aminimumsurfaceof1hawasset.
Table8Criteriaappliedtospatialqueries,toassessthelandscapesuitabilityforviticulture,basedoncurrentclimaticconditions,climatechangescenarios(RCP4.5and8.5),andfavourabletopographicconditions
fortheestablishmentofvineyards.AvgSunHursVeg:potentialdailymeansun-hours.CumGloRadVeg:cumulatedglobalsolarradiation.
Ref.period Scenario Elevation(ma.s.l.) Slope(%) Aspect(DEGfromNorth=0CW) AvgSunHoursVeg(h) CumGloRadVeg(kWhm−2)
1976–2005 Current <=750 <=15 >=67.5AND<=292.5 >=10 >=850
2021–2050 RCP4.5 >750AND<=992
RCP8.5 >992AND<=1000
2041–2070 RCP4.5 >1000AND<=1161
RCP8.5 >1161AND<=1243
Accordingtothecurrentclimaticconditionsandfutureclimatechangescenarios,thesuitableareasforviticulture,asaresultofthespatialqueries(Table8,Fig.4),presenttodatethreemainlanduses:annualandperennial
crops (mainlygrapevine,apple,berries,horticulture),pasturesandmeadows,andurbanorcommercialareas.Thepercentagesofnewavailablesoil foreachscenario, fromthecurrentclimaticconditions to thewarmestclimate
changescenario(′41–′70RCP8.5)aresummarizedinFig.5.
4DiscussionThe climate simulations performed according to RCP 4.5 and RCP 8.5 greenhouse gas concentrations depict a future climate scenario characterized by higher temperature, especially if the RCP 8.5 is
considered,andageneralreductionofprecipitationandincreaseinthenumber (Pleaseinsert"of")consecutivedrydays.FutureclimatescenariosconsideredinthisstudywereobtainedbyasingleRegionalClimate
Model(COSMO-CLM).Inordertoassessuncertainty,assuggestedbyIPCC,thereliabilityofprojectionsmightbeimprovedbymulti-modelensembles,weightingsingleelementswithmodelskillmeasures.However,
thehugecomputationalcosts required toperformhigh-resolutionsimulationswithmodelensembles representa limit, leaving this solution to futureworks. Indeed,COSMO-CLMresultshavebeenproved tobe
consistentwiththe‘state-of-the-art’ofregionalclimatesimulations(Bucchignanietal.,2015;Zolloetal.,2015a).
Thewidevarietyofclimatesconsideredinthisstudy,fromthe90mlowervalleybottomtohigh-mountainsites,coversthefullrangeofpresentandfuturepossibleviticulturalareas.
Ingeneral,theexpectedeffectsofwarmeranddrierconditionswouldleadtobetterripeningandsanitarystatusofthegrapesofredvarieties,increasingtheirqualityrating(Grifonietal.,2006),andtoearlier
harvestofwhitevarieties,particularlyforsparklingwineproduction,andapossibleenlargementoftheviticultureareatohigherelevation.Onlyafewwhitegrapevinevarietiesgrownintheregion,suchasMüller
Fig.4ResultsofGISspatialqueries,usedtoassessthelandscapesuitabilityforviticultureinTrentino,accordingtocurrentclimaticconditionsandfuturescenarios.
Fig.5Classification(%)ofnew,incrementalavailablesoil(withrespecttothepreviousscenario/time),accordingtothedifferentclimaticscenariosandreferenceperiods.
Thurgau,areparticularlyaffectedbywarmconditionsandnewplantingarerecommendedrightnowinthecoolerareas(above450ma.s.l.),tofulfiloptimalripening;suchvarietiesarelessresilientandaregoingto
facesomelimitationsinthelowerareas,wheretemperatureisexpectedtoattaintoohighvalues.
Besideaprobablegeneralimprovementofthegrowingconditionsforgrapevine,asawhole,thetypicalthermalregimesoftheareaswhicharepresentlyoccupiedbyvineyardsareexpectedtoshifttowards
differentbioclimaticclassifications,butonlypartiallyisthisfeaturegoingtoaffectthechoiceofthegrapevinevarieties,thankstotheirgeneralresiliencetowarmerconditions.
Extremewarmanddryconditionsarelikelytooccurmoreofteninthefuture,leadingtoahighernumberofundesirableevents;however,inTrentinomostvineyardsarenowadaysequippedwithirrigation
plants, importanttoconfronttheoccurrenceofdroughtevents.Theexpectedhigherfrequencyofdrycondition (conditions),however,shouldbetakenintoaccountiftheresultsofthisstudyareextendedtosimilar
areas,lackingsuchfacilities,orwhereirrigationisnotenvisagedintheproductionprotocol.
Anassessmentof theexpected,plausibleexpansionof viticultural areas shouldalso consider the current landuseandexcludeunsuitable soil (i.e. urbanand industrial areas,parksandprotectedareas,
touristicplaces)fromcalculation.Pasturesandmeadowsrepresentthemostaffordableareasforanenlargementofviticultureinawarmerclimaticscenario.Infact,itisunlikelythatperennialcrops(i.e.intheapple
producingareaofNonValley)andhighqualityproductions(horticulture,berries)willbereplacedduetoclimatechange,ifnotdrivenbyadecreaseofproductionandquality;insuchconditions,changesinprofitdue
tothemarketrulescouldindeedbecomethedriversofpossiblechangesinbothgrapevarietyandcrop.
Norestrictionofviticulturalareas ispredicted to takeplaceat the lowervalleybottom,even if thechange is likely tosuggest–at least in thestrongesthypothesisof thermal increase– to consider the
convenienceofavarietalchange.
5ConclusionsInthisstudyahigh-resolutionmodellingchainwasappliedtoanAlpineareatoassessthechangeinclimaticandbioclimaticindices,withparticularreferencetotheviticulturalarea.Theresultscomefrom
theapplicationoffunctionsfromanopen-sourceRlibrary(ClimClass)totheoutputofaRegionalClimateModel(COSMO-CLM).Whilesomechangesarealreadyobservable(Ecceletal.,2015),theshiftexpectedfor
thefuturecanbequantitativelyassessedbytheuseofclimaticclassificationsandindices,specificallycreatedforviticulturalpurposes.Theimplementationoftheseindicesinanopen-sourcelibrarymayenhance
theiruseas“standards”;moreover, theR libraryClimClasssuppliesuseful tools forpre-processingclimaticseries, facilitatingtheirpreparationandanalysis inviewof theassessmentofclimaticandbio-climatic
indices.
Ageneralincreaseintheoccurrenceofwarmerand–withalesserextent–drierseasonsispredictedforeverytimewindow(2021–2050and2041–2070)andreferencescenario(RCP4.5andRCP8.5);of
course,thechangeismorepronouncedinthefarthestperiodandforthescenarioenvisagingacontinuousincreaseinGHGemission(RCP8.5).
Indicesreflecttheeffectofthisdriver:viticulturecouldbenefitfromtheexpectedeffectsofclimatechange,whichincludehigherairtemperatureanddrierconditions,withbetterripeningandsanitarystatus
ofthegrapes,andspreadingtonewsuitableareas,butattheexpenseofannualandperennialcropsormeadowsandpastures,whicharepartoftheruralmountainlandscape.Alltheseimportantdegreesoffreedom
inthevocationalchoiceofagriculturalareas,togetherwithothersarisingeitherfromagriculturalpolicyorfromtheeconomicalaspectsofwinemarketandfarmmanagement,willprobablyplaythemajorroleinthe
determinationoftherealwine-growingareas.Nevertheless,forthefirsttimeaftertheendofthe“LittleIceAge”period,ataboutthehalfof19thcentury,therearenowsomepremisesforwitnessingareturnof
climateasaco-driverinthechoiceofcrops.
6UncitedreferenceMichalet(1991).
AcknowledgmentsWork co-funded by Climate Change Funds of Provincia Autonoma di Trento, 2013, project IndiClima, and by SEE Transnational Cooperation Programme of EU, 2012, project OrientGate. Thanks to
MeteotrentinoandtheCTT-SIGunitofFond.Machfordatasupply.
AppendixA.SupplementarymaterialSupplementarydataassociatedwiththisarticlecanbefound,intheonlineversion,athttp://dx.doi.org/10.1016/j.compag.2016.05.019.
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AppendixA.SupplementarymaterialMultimediaComponent1
Supplementarydata1
Highlights
• Awarmingclimatecanleadtonewclimaticconditionsinviticulturalareas.
• Thechangecanbeassessedbyapplyingbioclimaticindicestoclimatemodeloutput.
• Climateindiceswerecalculatedbyadedicatedopen-sourceRlibrary.
• Aspreadofwine-growingareastothemountaincanbequantified.
• Highertemperaturegenerallyincreasesopportunitiesincoolviticultureclimates.
Answer:Yes.
Query:Pleasechecktheeditsmadeintheaffiliations,andcorrectifnecessary.Answer:Yes
Query:Thecountrynamehasbeeninsertedfortheaffiliations‘b’and‘c’.Pleasecheck,andcorrectifnecessary.Answer:Yes
Query:Thecitation‘HallandJones(2008)’hasbeenchangedtomatchtheyearinthereferencelist.Pleasecheck,andcorrectifnecessary.Answer:Yes
Query:References‘DuchêneandSchneider(2005)’,‘Düring(1997),andLisek(2009)’arecitedinthetextbutnotprovidedinthereferencelist.Pleaseprovidetheminthereferencelistordeletethesecitationsfromthetext.Answer:DuchêneE.,Schneider,C.,2005.Grapevineandclimaticchanges:aglanceatthesituationinAlsace.AgronSustainDev25,93-99.doi:10.1051/agro:2004057
Düring,H.,1997.Potentialfrostresistanceofgrape:Kineticsoftemperature-inducedhardeningofRieslingandSilvanerbuds.Vitis.36(4),213-214
Lisek,J.,2009.Frostdamageofbudsonone-year-oldshootsofwineandtablegrapevinecultivarsinCentralPolandfollowingthewinterof2008/2009.JournalofFruitandOrnamentalPlantResearch.17(2),149-161.
Query:Thissectioncomprisesreferencesthatoccurinthereferencelistbutnotinthebodyofthetext.Pleasepositioneachreferenceinthetextor,alternatively,deleteit.Anyreferencenotdealtwithwillberetainedinthissection.Answer:Pleasedelete.