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

0

500000

1000000

1500000

2000000

2500000

3000000

3500000

0 5 10 15 20 25

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: tpathak@ucanr.edu

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: tpathak@ucanr.edu

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

1985

1987

1989

1991

1993

1995

1997

1999

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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THANKYOU!kripajagan@berkeley.edu

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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THANKYOU!kripajagan@berkeley.edu