Migang climate risks on the farm: tree nut perspecve...Migang Climate: Almond Case Study Reduced...
Transcript of Migang climate risks on the farm: tree nut perspecve...Migang Climate: Almond Case Study Reduced...
Mi#ga#ng climate risks on the farm: tree nut
perspec#ve DavidDoll
TreeNutPomologyAdvisorUCCEMerced
Let’s Talk About the Weather…
“Somethingwecan’tcontrol,but….“somethinginwhichwehavetomanage.”
“Itimpactseverythingwedo.”
“Theycantevengettheweatherright,howcantheypredictclimate?”
Let’s Talk About the Climate…
VariousforecasJngmodelsareaddingtotheconfusion;Noabilitytodeterminelongrangeforecasts;Lackofconcernforthelongtermduetoday-to-dayoperaJonmanagement. Inmanycases,notmuchcanbedone
onaday-to-daybasistomanage.
Concerns: Weather v/s Climate
WeatherConcerns• Rainduringbloom/harvest• Springfrostevents• Lateseasonrains
ClimateConcerns• Flooding/drought• Warmerwintersandsprings• HoTersummers• ShiUingrainfallpaTerns
Managedonaday-to-daybasis
Managedonafarmdevelopmentlevel
WeatherConcerns• Rainduringbloom/harvest• Springfrostevents• Lateseasonrains
ClimateConcerns• Flooding/drought• Warmerwintersandsprings• HoTersummers• ShiUingrainfallpaTerns
Managedonaday-to-daybasis
Managedonafarmdevelopmentlevel
Mi#ga#ng Risks: Almond Case Study
Mi#ga#ng Weather: Almond Case Study
Rainduringbloom:• Placementof2-2.5strong,8framehives/acre;• UJlizaJonoffungicides;• VarieJesresistanttodisease;• DiversificaJonofbloomJmings.
SpringFrost• AlmondflowersandnutsaresensiJvetofreezingtemperatures• UJlizestrategiestoincreaseorchardheat(e.g.mowcovercrop,useofsprinklersystems)• PlantlaterbloomingvarieJes
Mi#ga#ng Weather: Almond Case Study
Lateseasonrains• AllagriculturalcropsaresuscepJbletodiseases,whichthriveinwarm,wetcondiJons;• UseofproperlyJmedpesJcides;• ResistantvarieJes.
Mi#ga#ng Weather: Almond Case Study
RainDuringHarvest• Almondshavetobebroughttotheprocessorataspecifiedmoisturelevel• UJlizaJonofextrapassestoreduceorcharddebris,quickerdryingJme• SelectearlierharvesJngvarieJes.
Mi#ga#ng Weather: Almond Case Study
MethodsofManagement:• Orchardlayoutanddesign(e.g.varieJes,irrigaJonsystems);• Increasedinvestment;• IncreasedoperaJonalcosts;• Increasedenvironmentalimpact.
Mid-term(10-20years)
Mi#ga#ng Weather: On-farm Op#ons
Short-term(1-5years)
Long-term(20-50years)
WeatherConcerns• Rainduringbloom/harvest• Springfrostevents• Lateseasonrains
ClimateConcerns• Flooding/drought• Warmerwintersandsprings• HoTersummers• ShiUingrainfallpaTerns
Managedonaday-to-daybasis
Managedonadevelopmentbasis
Mi#ga#ng Risks: Almond Case Study
ManagingDrought/Floods• LandselecJonandpurchase;• DiversificaJonofparcellocaJons;• Diversifyingwaterresourcesontheranch;• Installingdrainagesystems
Mi#ga#ng Climate: Almond Case Study
Figure4.SafewinterchillinCalifornia'sCentralValleyin1950,2000,2041–2060and2080–
2099,calculatedwiththeDynamicModel.
Mi#ga#ng Climate: Almond Case Study ReducedWinterChill
LuedelingE,ZhangM,GirvetzEH(2009)ClimaJcChangesLeadtoDecliningWinterChillforFruitandNutTreesinCaliforniaduring1950–2099.PLoSONE4(7):e6166.doi:10.1371/journal.pone.0006166hTp://www.plosone.org/arJcle/info:doi/10.1371/journal.pone.0006166
Mi#ga#ng Climate: Almond Case Study Warmerwinters,springs• Earlierbloom,increasedfrostrisk;• DevelopmentoflowchillvarieJes/higherspringheatunitaccumulaJon;• UJlizaJonofheatreflecJngproductstodelaybloom;• Differentdiseaseandinsectpressures.
HoRerSummers• Impactsonnutqualityandrateofdevelopment;• IncreasedinsecJcideapplicaJons;• Increasedwatercosts.
Mi#ga#ng Climate: Almond Case Study
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InsectPopulaJonDevelopment
FirstHarvest
Moreinsects,moredamage,moresprays,lessmoney!
ShiSingRainfallPaRerns• Increasesinfungicideandherbicideusage;• ImpactscropqualityandproducJvity.
Mi#ga#ng Climate: Almond Case Study
MethodsofManagement:• BreedingofvarieJes;• Increasedcapitaloutlay;• Increasedfarmingcosts(sprays,chillingopJons);• Choiceofcrop.
Long(20-50years)
Mi#ga#ng Climate: On-farm Op#ons
Medium(10-20years)
Short/Medium(5-20years)
Medium/Long(10-50years)
Mi#ga#ng Climate and Weather
Farmsizewillinfluencetheabilitytoadapt!
Expenses/ResearchTimeline High/LongLow/Short
ManagingWeather ManagingClimate
NewvarieJes;BeTercropmodelling;FarmDiversificaJon-cropsandlocaJon;Infrastructureimprovements.
SiteselecJon;NewmodesofacJonforpesJcides;Techniquestoincreasechill,decreasesunburn;Moreefficientfarmequipment.
Orchardlayout;VarietyselecJon;IrrigaJonsystems.
Economicswillplayapartinadop[onofprac[ces.
Whatweknow:Itisgoingtobeexpensive
• Croploss;• IncreasedoperaJonalexpenses;
• Farmerswillgooutofbusiness.
ChangesincroppingpaTernswilloccur.ItwillrequiremulJplestrategiestomanage.
Whatweneed:BeTerforecasJngtohelpinfluenceweatherbaseddecisions.Moretoolstocontrolunknownissues(emergingdiseases,pests).Moreinvestmentinlongtermpublicresearch(breedingprograms,moreaccuratecropmodelling).Policythatprovidessupporttotheindustry;Infrastructureorpolicyimprovementsthathelpmanageclimateinfluencedinputs.
Mi#ga#ng Climate and Weather
Climate Impacts on California Agriculture and Tools for Managing Risks
Tapan Pathak, Ph.D. Cooperative Extension Specialist- Climate Adaptation in Agriculture University of California Merced
Email: [email protected]
Facts about California Agriculture
¤ 76,400 farms producing more than 400 commodities with a farm-gate value of $54 billion
¤ Leading producer of almonds and pistachios in the world
¤ Leading fresh market vegetable producing state
¤ Leading the nation in milk production, producing 41.2 billion pounds of milk
California's top—ten valued commodities
¤ Milk — $9.4 billion
¤ Almonds — $5.9 billion
¤ Grapes — $5.2 billion
¤ Cattle, Calves — $3.7 billion
¤ Strawberries — $2.5 billion
¤ Lettuce — $2 billion
¤ Walnuts — $1.8 billion
¤ Tomatoes — $1.6 billion
¤ Pistachios — $1.6 billion
¤ Hay — $1.3 billion
Climate Variability and Climate Change
¤ Climate Variability is a measure of shorter term climate fluctuations above or below long term average
¤ Climate Change is a measure of longer term statistically significant continuous change (increase or decrease) in the measures of climate, such as temperature, rainfall, frequency of extreme events
Pacific Decadal Oscillation
• Average temperature across the US has increased at an average rate of 0.13°F per decade
• Southwest has experienced significant warming
• Seven of the top 10 warmest years on record have occurred since 1998
Changes in California Temperatures
Cordero et al. (2011)
Changes in Average US temperatures
How can a change of one or two degrees in global average temperatures have an impact on our lives?
For about every 2°F of warming, we can expect to see:
¤ 5—15% reductions in the yields of crops as currently grown
¤ 3—10% increases in the amount of rain falling during the heaviest precipitation events, which can increase flooding risks
¤ 5—10% decreases in stream flow in some river basins
¤ 200%—400% increases in the area burned by wildfire in parts of the western United States
Source: http://www.epa.gov/climatechange/facts.html
How does temperature increases affect plants?
Trends in Chill Hours • Around the year 1950,
growers in the Central Valley could rely on between 700 and 1200 Chilling Hours
• By 2000, this number had already declined by up to 30% in some regions
• Chill Hours are projected to decrease significantly under future climate change scenario
Length of Growing Season
Precipitation Trends
Since 1901, global precipitation has increased at an av- erage rate of 0.2 percent per decade, while precipitation in the contiguous 48 states has increased at a rate of 0.5 percent per decade.
Extreme Precipitation Indicators
Slide Courtesy: Teamrat Ghezzehei
Climate Information for Managing Risks
¤ Climate has direct influence on agricultural production
¤ Integrating climate information into agricultural decisions can enhance agricultural resiliency to climate risks
¤ However, this information is not always available in a format that is desirable to agricultural producers/decision makers
¤ Translating climate information into actionable knowledge can greatly enhance growers’ capacity to manage risks and increase productivity
Climate Information Needs
¤ United States Government Accountability Office – “USDA faces the challenge of turning the large amount of often technical climate research into readily understandable information.”
¤ Decision support processes need to take account of the values and goals of stakeholders, evolving scientific information, and perceptions of risk. (National Climate Assessment)
¤ Climate Change Consortium for Specialty Crops report- “CDFA should compile a list of grower needs for weather data and forecast products”
Examples of Agro-Climate Decision Support Systems
Adaptation to Climate Variability-Southeast US
ENSO Adaptations – Example 1
ENSO Adaptations – Example 2
ENSO Adaptations – Example 3
Example from the Midwest
Tapan Pathak, Ph.D. Cooperative Extension Specialist- Climate Adaptation in Agriculture University of California Merced
Email: [email protected]
Usingclimateinformationforlong-termadaptation
planning:
KripaJagannathan-PhDcandidate,UCBerkeley
“On-FarmClimateAdapta2onDecisions:WhereTheoryMeetsPrac2ce”:CalCAN2017Summit-28Feb2017
Informa(onneeds,modelingcapabili(es&tools
BACKGROUNDWhytouseclimateinforma2oninlong-term
planning?
CLIMATE&WEATHERINFOAREIMPORTANTTypeofinforma=on Farmdecisionsaffected
Weather(daystoweeks) • Dailyforecastsuptoaweekaheadof2me
• Timingofplan2ngorharvest,fer2lizerorpes2cideapplica2on
• Irriga2onscheduling
Weather/Climate(monthstoyears)
• Probabili2esofseasonalrainfall&temperature
• Seasonalforecastsofdryspells
• Cropvarie2estoplant• Intensityoffer2lizerorpes2cide
orwater• Intensifyordiversifycrops
Climate(10yrsorlonger) • Projec2onsoffuturetemperatureorrainfallorheatwaves
• Futuredroughts/floods
• Majorcapitalinvestmentlandpurchase,irriga2onsystemetc.
• Decidingwhetherornottofarm• Changingfarmingsystems
Source:CGIARCCAFS 3
UTILITYOFLONG-TERMPROJECTIONSOVERLOOKED…
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§ Informa2onnotimmediatelyac2onablebutgointo5-10yearorlongerplansi.e.‘farmdevelopmentplans’
§ Climateoneamongmanyfactorsinfluencingdecisions
§ UncertaintyBio-physical Decisions
Climate
PestsSoils
Policies
MarketsPreference
Economic
Somefactorsaffec=nglong-termdecisions
....BUTUN-PREPAREDNESSCANBEVERYCOSTLY!
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Costofinac2on&unpreparednesscanbeveryhigh!Effec2veadapta2onrequiresuseofrobustclimateknowledge(Dilling&Lemos2010,Tang&Dessai2012).
Informeddecisionsaboutuncertainfuturemaybebeferthanuninformeddecisions.
Despiteuncertainty,long-termprojec2onscanprovideinforma2ononbroadtrendsthathelpinbeferplanningorprepara2on.
Photocredits:HouseCommifeeonNaturalResources.
Photocredits:ww2.kqed.org,JoshEdelson/AFP/GefyImages
FARMERS’INFORMATIONNEEDSInterviewswithalmondgrowersintheCentralValley
INTERVIEWS
Roleofclimateinfoindecision-making
Relevantclima=cvariables/metrics
Howtomakeinfoonfutureclimate‘usable’
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§ Semi-structuredinterviews(CentralValley)§ Farmers,Farmadvisors,industryboardmembers
§ Non-random,purposeful,andsnowballsampling
Preliminaryfindings(nottobecitedordistributed)
INTERVIEWTHEMES
CURRENTUSEOFWEATHER/CLIMATEDATA
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Diversityofgrowers
Datalovers
“spreadsheetjunkie”
“lovecrunchingdata”
Farmobservers
“crops/soilwillspeaktous”
“dataaloneisnotthatimportant”
Dataindifferent
“cantdoanythingaboutit”
KEYCLIMATICVARIABLESFORTHEALMONDCROP
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Dormancy(Nov-Feb)• Chillhours
Bloom&Pollina2on(Feb-Mar)• Frostpaferns• wind,temp,rain
MaturingNuts(Apr-Jun)• Temp• Extremelyhotdays
Hull-split&Harvest(Jul-Oct)• Rainorhighhumidity• Extremelyhotdays
Photocredits:http://www.amira.ca/en/info_almond.htmandhttp://www.belehrisestates.com.au/almond_growing_cycle.php
Long-termprojec(onsforsuchcrop-
specificclima(cvariablesarenotreadilyavailable.
Snowpackandwateravailability.
GROWERSAREEXPERIENCINGCHANGESINCLIMATE
§ Mostsaidtheyexperiencedwarmerwintersandlesserfog.
§ Otherkeyimpactsmen2onedwere:
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Hofersprings
Earlierandquickerbloom
Pes2cidespray2mingschanged
Hofersummers
Earlierharvest
Snowpackchange
Anecdotal
Changeinpests/disease
paradigms
USEFULNESSOFINFORMATIONDEPENDSONITSSPECIFICITYTOCONTEXT
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Useful• Contextualizedprojec2ons:“Chillhourswillreduceby10hrs/yrinthenext10-20yrs”
• Clarifythatinfoisforlongertermdecision-makingscalesnotday-to-daydecisions
Notuseful• Broadaveragetempprojec2ons:
• “Statewideavgtempwillincreaseby3-5degFby2050”
• “Wintermintempwillincreaseby2-4degFby2050”
• Climateinfoprovidedwithoutdecision-makingcontext
Tailored
Purpose
WHATABOUTUNCERTAINTY?
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Accuracy
Needaccurateweathernotclimate.
Tolerantofuncertain2esat
clima2c2mescales
Riskexpression
Confidence,likelihood,orscenarios.
>60%likelihoodok,70-80%verygood
“Everypredica(oncomeswith
uncertaintyandweworkwiththatall
the(me”
“Yes–Iknowyoudonothaveacrystalball”
CANTHISINFORMATIONLEADTOADAPTIVEDECISIONS?
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Whatcanyoudowiththedata??
Adjustments
Cropvarie2es,rootstocks
Frostprotec2on
Efficientirriga2on
Transforma2on
Differentcrops
Lessercrops
Abandonfarming
Solu2onsarerprompts
SUMMARYOFINTERVIEWFINDINGS
Thereisinterestinlong-terminforma2onifitiscontext&crop-
specific
Projec2onsmusttransparentlyinclude
uncertain2es/likelihoods/confidence
Farmersmaybeopentothinkingabout
adap2veac2onsbasedonprojec2ons
Greatvalueinhavingopendiscussionsand
dialogueswithgrowers!!
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CLIMATEMODELINGCAPABILITIES
Canmodelsprovide“usable”info?:Adeeperdelveintoanalysisofchillhourprojec=ons
OBSERVEDCHILLHOURSINANDAROUNDFRESNO
200
400
600
800
1000
1200
1400
1600
18001971
1973
1975
1977
1979
1981
1983
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1987
1989
1991
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1997
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2001
2003
2005
2007
2009
2011
Chillhou
rsperyear
YearMadera Visalia HanfordFriant Lemorre FresnoMediumchill(stonefruits) Lowchill(almonds) Highchill(cherries)Linear(Fresno) 16
Decliningtrend~10ch/yr
FUTUREPROJECTIONSFORCHILLHOURSINFRESNO
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0
200
400
600
800
1000
1200
10-yeara
veragechillh
ours(ch/yr)
ModeledProjec2ons FresnoObservedChill
§ Whatthemodelscansay:§ Broadertrends:By2040~600ch/yr,By2060~500ch/yr
§ Whatthemodelscannotsay:§ Yeartoyearvariability
§ Chillinapar2cularyear,5-yearorverynear-termtrends
§ Specificmicro-clima2cprojec2onsClimateprojec2onswillremainsomewhatuncertain.However,therearebroadertrendsorpafernsthatmodelscanpredict
reasonablywell.Butisthisenough?
2030 31 32 33 --------
2040 Avg2030-40
800 400 900 300 ---- ----- 600
650 550 550 650 ---- ----- 600
CAL-ADAPTTOOLPla`ormforclimatedataandotherresourcesforCA
adapta=on
CAL-ADAPT
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Fresnoextremeheatprojec2ons,Temperaturedegreesofchange
CAL-ADAPTEXTREMEHEATTOOLDEMONSTRATION
§ Ques=onsforaudience:§ Isthetoolusefulforyoutounderstandextremeheatprojec2ons?
§ Whatinforma2ondidyoufinduseful,whatisnotuseful?
§ Whatothermetricswouldyoulikeinforma2onon?
§ Doessuchdatahelpyouinplanningforthefuturei.e.consideradap2vedecisions?§ {e.g.switchingtoheattolerantcrops/varie2es,temperaturemanagementstrategies,pestcontrol,irriga2onplanning,changingcroppingpaferns,Alterplan2ngandharves2ngschedules,etc.}
§ Anyothercommentsonusefultools/informa2onthatcanassistintakingadapta2onac2on?
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PILEUSPROJECTOFMICHIGANSTATEUNIV§ Futureclimatetool,forGDDfortartcherriesinGreatLakesRegion.hfp://pileus.msu.edu/tools/t_future.htm
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OTHERS§ Climate-smartfarmingtools(CornellUniversity)§ hfp://climatesmarxarming.org/tools/
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§ UsefultoUsableProject(U2U)§ hfps://mygeohub.org/groups/u2u/tools#U2Utools
§ UCDavisFruit&NutResearchandInforma2onCenter§ hfp://fruitsandnuts.ucdavis.edu/Weather_Services/
chilling_accumula2on_models/Chill_Calculators/
Note:Someofthesetoolsonlyhavehistoricalrecords,ornear-2meforecasts{notlong-term
climateprojec2ons}
EXTRASLIDESCal-Adapt
CAL-ADAPTEXTREMEHEATFRESNOPROJECTIONS
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PASTTRENDANDPROJECTIONSFOR2030-40
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SHORTERTIMESERIESGRAPH
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PROJECTIONSFROMDIFFERENTMODELSTOASSESSUNCERTAINTY
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MONTHLYTIME-SERIESGRAPHFROMONEMODEL
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Thischartdisplaysapointforeachdaythatexceedstheextremeheatthreshold.TimeofyearbetweenAprilthroughOctoberisplofedalongtheyaxisandeachyear1950-2100alongthexaxis.Formostareasaroundthestate,themodelsprojectnotonlyanincreaseinthenumberofdaysexpectedtoexceedtheextremeheatthreshold,butalsotheiroccurrencebothearlierandlaterintheseason.
SUMMARYOFPROJECTIONSFORFRESNO
§ Thetoolshowsextremeheatdays(EHD)inFresno.InthepastEHDwere~4days/yr,butitisprojectedtoincreaseto:§ ~18-23daysin2040-50
§ ~20-30daysin2050-60,andsoon
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TEMPERATUREDEGREESOFCHANGEMAP
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