Bob KeaneUSDA Forest ServiceRocky Mountain Research StationBob KeaneUSDA Forest ServiceRocky Mountain Research Station

Predicting ecological responses to climate change is “wicked” HARD!Three Reasons

Predicting ecological responses to climate change is “wicked” HARD!Three Reasons

Interactionsall climate change impacts result from complex interactions between climate, vegetation, topography, humans, and a host of other factors

Vegetation

Disturbance

Wildlife

Humans Climate

Scaleall climate change responses are scale dependent in both time and space

Moritz

M. A.

et.al.

2005.

PNAS

;102:1

7912-1

7917

Climate Projectionsall climate projections have a high degree of uncertainty that increases with finer scales

from Talbert and others (2014)

Sula, Montana CMIP5 Data Extrapolation

Climate Change ImpactsPredicting landscape change Four major approaches: Climate Change ImpactsPredicting landscape change Four major approaches: “Ask the expert”

Deduction, inference, association “Study it”

Empirical and experimental studies “Analyze it”

Bioclimatic envelope statistical modeling “Simulate it”

Biophysical simulation modeling

“Ask the expert” Deduction, inference, association

“Study it” Empirical and experimental studies

“Analyze it” Bioclimatic envelope statistical modeling

“Simulate it” Biophysical simulation modeling

Exploring climate change impacts in northern Rocky Mountain ForestsThis presentation:

Exploring climate change impacts in northern Rocky Mountain ForestsThis presentation:• Disturbance• Vegetation• Interactions• Vulnerability assessments

• Disturbance• Vegetation• Interactions• Vulnerability assessments

Exploring climate change impacts in northern Rocky Mountain ForestsExploring climate change impacts in northern Rocky Mountain Forests• The information was taken from multiple

sources:• Review of literature• Statistical modeling studies• Simulation modeling• The landscape model FireBGCv2

• The information was taken from multiple sources:• Review of literature• Statistical modeling studies• Simulation modeling• The landscape model FireBGCv2

Old Climate scenarios (HadCM3 GCM - Mote 2003, Mote et al. 2007)• H-Historical climate (recorded weather)• B2 (A1B): WARM AND WET (+1.6ºC; +9% ppt)• A2: HOT AND DRY (+4ºC; -7% precip.)Based on IPCC (2007) projectionsNew Climate Scenarios (Hadley synthesis of 7 GCMs)• H-Historical climate (recorded weather)• RCP4.5: WARM AND WET (+2.6ºC; +130% ppt)• RCP8.5: HOT AND DRY (+5ºC; 90% ppt)Based on IPCC (2011) projections

DisturbanceMore influential than vegetation development

DisturbanceMore influential than vegetation development

Role of disturbance in climate change• Catalyst• Facilitator

Adaptations to disturbance will be more important than adaptations to climate

Role of disturbance in climate change• Catalyst• Facilitator

Adaptations to disturbance will be more important than adaptations to climate

Climate Change and Wildland Fire – NRM ForestsLonger Fire Seasons• Earlier frost dates• Deeper droughts• Fuels will be drier longer• More of landscape will be drier longer• Lower humidity, higher temperature• Disrupted phenologies and fire adaptations

Climate Change and Wildland Fire – NRM ForestsLonger Fire Seasons• Earlier frost dates• Deeper droughts• Fuels will be drier longer• More of landscape will be drier longer• Lower humidity, higher temperature• Disrupted phenologies and fire adaptations

Climate Change and Wildland FireIncreased Lightning• More convective storms• Greater storm intensity – Higher winds• 30% increase in global lightning• Greater occurrence during drought• Higher cloud to ground strikes • Greater number of positive strikes

Climate Change and Wildland FireIncreased fuel production• Higher productivity results in an increase in burnable biomass• Increased fuels will be more contagious and connected• Productivity will increase canopy fuels

Climate Change and Wildland Fire – NRM ForestsGreater fire frequencies and intensities• More intense fire is expected because of the following:

– High accumulated fuels– Denser tree canopies– Widespread drought conditions– High wind events– Previous fire management -- Exclusion

Climate Change and Wildland Fire – NRM ForestsGreater fire frequencies and intensitiesHigher Temperatures Will Increase Burn Areas In the West

How much more area will burn eachyear if temperatures rise 1.8 oF:at least 6 times more

5-6 times more

4-5 times more

3-4 times more

2 - 3 times more

up to 2 times more

National Research Council, 2011

MC2 Modeling Results Fire Rotation (Annual % burned)

Climate Change and Wildland FireLarger fires• Fires are predicted to be larger for the following reasons:

– Greater fuel accumulation– Continuous fuel beds– Greater chance for higher winds– More of landscape in drought– Burn longer with long fire seasons

moisture deficit in forests 1970–2003moisture deficit in forests 1970–2003

Wildfires >1,000 ha 1970–2003

Wildfires >1,000 ha 1970–2003

Fires Acres

Westerling, A. L. 2016. Increasing western US forest wildfire activity: sensitivity to changes in the timing of spring. Philosophical Transactions of the Royal Society of London B: Biological Sciences 371.

Washington6

1970 2010

Idaho30

1970 2010

Montana

20

1970 2010

Oregon10

1970 2010

Wyoming10

1970 2010

California40

1970 2010

Nevada4

1970 2010

Arizona20

1970 2010

New Mexico10

1970 2010

Colorado8

1970 2010

Utah8

1970 2010

Temperatures and Wildfire Numbers Have Increased Across the West

Spring-SummerTemperature ChangeTrend (oF per decade)

0.40

0.30

0.20

0.10

Fires Acres

Climate Change and Wildland FireAn Historical Perspective• Ten to 100 times more land burned prior to European Settlement

– National historical fire return interval 17-22 years• Large fires were common but rarely catastrophic• Most ecosystems are adapted to fire• Climate driven increase in wildland fire is mostly a anthropogenic concern Native American burning

Whitebark pine at Galena Summit, IdahoWhitebark pine at Galena Summit, Idaho

Currently experiencing a major mountain pine beetle epidemic Occurring in most of western North America

Currently experiencing a major mountain pine beetle epidemic Occurring in most of western North America

Major Causes Favorable weather Abundant host species Reduced habitat heterogeneityCausal MechanismsFire exclusionClimate change

Major Causes Favorable weather Abundant host species Reduced habitat heterogeneityCausal MechanismsFire exclusionClimate change

Climate ChangeMountain Pine Beetle

Increase in wave years Increase in spread distances Wider window on wave years Mutation of disease

Increase in wave years Increase in spread distances Wider window on wave years Mutation of disease

Near Snowbowl Ski Area, Missoula MontanaNear Snowbowl Ski Area, Missoula Montana

Climate ChangeWhite pine blister rust

Move upwards in elevation years Move northwards in latitude Outbreak frequency about the same No temperature link

Move upwards in elevation years Move northwards in latitude Outbreak frequency about the same No temperature link

Increase in SBW in Great Lakes Region CanadaIncrease in SBW in Great Lakes Region Canada

Climate ChangeSpruce budworm

Future Vegetation Dynamics

Predicted increase in plant biomass under A2 climate

Bachelet et al., Environment 2007

Northern Rockies Vulnerability Assessment and Adaptation Plan MC2 Modeling Reference Material for the GYAAboveground Live Carbon

Northern Rockies Vulnerability Assessment and Adaptation Plan MC2 Modeling Reference MaterialPotential Evapotranspiration (Drought)

Ponderosa Pine

Current distribution Distribution in 2090 – A2 Climate

http://forest.moscowfsl.wsu.edu/climate/species/speciesDist/Ponderosa-pine/

Douglas-fir

Current distribution Distribution in 2090 – A2 Climate

http://forest.moscowfsl.wsu.edu/climate/species/speciesDist/Ponderosa-pine/

Whitebark Pine

Current distribution Distribution in 2090 – A2 Climate

http://forest.moscowfsl.wsu.edu/climate/species/speciesDist/Ponderosa-pine/

Western White Pine

Current distribution Distribution in 2090 – A2 Climate

http://forest.moscowfsl.wsu.edu/climate/species/speciesDist/Ponderosa-pine/

Climate ChangeStatistical Modeling EffortsChanges in Vegetation in western MT Climate ChangeStatistical Modeling EffortsChanges in Vegetation in western MT

Projections Increases in western

white pine, grand fir Decreases in

ponderosa pine, whitebark pine, lodgepole pine, subalpine fir, alpine larch

Projections Increases in western

white pine, grand fir Decreases in

ponderosa pine, whitebark pine, lodgepole pine, subalpine fir, alpine larch

Problems Emphasize only

climate-vegetation relationships

Don’t recognize genetics, dispersal, life cycles, and most importantly disturbance

Problems Emphasize only

climate-vegetation relationships

Don’t recognize genetics, dispersal, life cycles, and most importantly disturbance

Disturbance and Vegetation

FireBGCv2:A research simulation platform

for exploring fire, vegetation, and climate dynamics

Keane, Robert E.; Loehman, Rachel A.; Holsinger, Lisa M. 2011. The FireBGCv2landscape fire and succession model: a research simulation platform forexploring fire and vegetation dynamics. Gen. Tech. Rep. RMRS-GTR-255. FortCollins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 137 p.

Number Fires vs Area Burned

No fire suppression

Full fire suppression

No fire suppression

Full fire suppression

Vegetation compositionHistorical

SpeciesBURNEDPIPOABGRPSMEPICOLAOCABLAPIENPIAL

LALYPIMOTHPLTSHEPOTRBEPASHRUBGRASS

Fire Suppression•Spruce/fir replaced by hemlock/cedar•Hem/cedar replaced by P. Pine and D. fir

No Fire Suppression• Lodgepole to w. larch•Lodgepole to ponderosa pine

A2Hot/dryNo fire supp.B2 Warm/wetNo fire supp.

A2Hot/dryFire supp.B2Warm/wetFire supp.

Dominant species changes

Subalpine fir Western hemlock

Glacier NP

Loehman et al. 2011 Forests.

Species Dynamics -Western White Pine

Species

Ponderos

a pine

Grand fir

Douglas-

fir

Lodgep

ole pine

Western la

rch

Subalpine

fir

Englemann

spruce

Whitebark

pine

Alpine larc

h

Western w

hite pin

e

Western re

d cedar

Western h

emlock

Quaking

aspen

Paper bir

chShrub

sGrass

es

SpeciesBurnedPonderosa pineGrand firDouglas-firLodgepole pineWestern larchSubalpine firEnglemann spruceWhitebark pineAlpine larchWestern white pineWestern red cedarWestern hemlockQuaking aspenPaper birchShrubsGrasses

Pre-1900s stand density w/ rust resistance, no fire exclusion

Current stand density w/ rust resistant new generations, no fire exclusion

Year 100 Year 250 Year 500

Historical (1900s) stand density w/ rust resistance, no fire exclusion

Whiteb

ark res

toration

–Effec

ts of st

and den

sityWh

itebark

restora

tion –E

ffects o

f stand

density

A2 Climate – Warmer and Drier

Whitebark pine landscape dynamics

Mimic PlantingRust-resistant treesCurrent density

East Fork Bitterroot River,Montana, USA

Holsinger, L. R. Keane, L. Eby, M. Young, 2014 [in press]. Impact of climate change and fire management on stream temperature, bull trout habitat, and aquatic health. Ecosystem Modelling

East Fork Bitterroot River,Montana, USA

Holsinger, L. R. Keane, L. Eby, M. Young, 2014 [in press]. Impact of climate change and fire management on stream temperature, bull trout habitat, and aquatic health. Ecosystem Modelling

Dominant species changes

Lodgepole pine Douglas-fir

Bitterroot NF

Simulation Results: East Fork Bitterroot River

East Fork Bitterroot RiverFire and fish dynamics in a changing climateEast Fork Bitterroot RiverFire and fish dynamics in a changing climate

NRAP Vulnerability AssessmentGeneral Results

Keane, R.E.; Mahalovich, M.F.; Bollenbacher, B.; Manning, M.; Loehman, R.; Jain, T.; Holsinger, L.; Larson, A.; Webster, M. 2016[in press]. Forest vegetation. In: Halofsky, J.E.; Peterson, D.L.; Dante-Wood, S.K.; Hoang, L., eds. 2016. Climate change vulnerability and adaptation in the Northern Rocky Mountains. Gen. Tech. Rep. RMRS-GTR-xxx. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station

NRAP Vulnerability AssessmentClimate Change Effect(in order of importance)

• Increasing wildfires– Level of management (suppression vs WFU)

• Increasing drought– Dry vs moist range of a species

• Longer growing seasons• Increasing insects & disease• Warmer temperatures• Decreasing snowpacks• Increasing productivity

Less spring snowpackMote, 2003

NRAP Vulnerability AssessmentStressors and Current Condition(in order of importance)

• 100+ years fire exclusion• Advancing succession• Current beetle and disease outbreak levels• Buildup of fuels (canopy, surface)• Current landscape species distributions, abundance• Availability of water• History of drought

moisture deficit in forests 1970–2003moisture deficit in forests 1970–2003

NRAP Vulnerability AssessmentSensitivity to Climate Change• Shade tolerance• Fire tolerance• Drought tolerance• Climatic tolerance• Genetic plasticity• Current abundance• Level of stress• Dispersal capability• Adaptive capacity

A2Hot/dryNo fire supp.

B2 Warm/wetNo fire supp.

A2Hot/dryFire supp.

B2Warm/wetFire supp.

NRAP Vulnerability AssessmentExpected EffectsMesic Areas• Increased growth, productivity• Accelerating succession• Greater seed production• Increased insect and disease exposure• Loss of mycorrhizae (fire)• Increased fire mortality

Xeric Areas• Decreased growth• Increased fire mortality• Greater stress – drought, competition• Decreased reproductive potential• Increased episodic mortality events

NRAP Vulnerability AssessmentAdaptive Capacity• Responses to fire• Drought tolerance• Changes in productivity• Seed dispersal characteristics• Ability to survive pests, disease• Genetic capacity – hybridization, adaptive strategy and phenotypic plasticity• Regenerative potential• Available water• Increasing productivity

NRAP Vulnerability AssessmentExposure, Risk (magnitude, likelihood)Species Magnitude of

effects Ponderosa Pine-east LowAspen ModerateCottonwood ModerateEngelmann spruce ModeratGrand fir ModerateGreen ash Moderate Limber pine ModerateLodgepole pine ModerateMountain hemlock ModeratePonderosa Pine-west ModerateSubalpine fir ModerateWestern hemlock ModerateWestern red cedar ModerateAlpine larch HighWestern larch HighWestern white pine HighWhitebark pine HighDouglas-fir High

Species Likelihood of effects

Ponderosa Pine-east LowCottonwood ModerateEngelmann spruce ModerateGrand fir ModerateLimber pine ModerateLodgepole pine ModerateMountain hemlock ModeratePonderosa Pine-west ModerateSubalpine fir ModerateWestern hemlock ModerateWestern red cedar ModerateAlpine larch HighAspen HighGreen ash HighWestern white pine HighWhitebark pine HighDouglas-fir High Western larch Very High

Species ExposureGrand fir LowSubalpine fir LowEngelmann spruce LowMountain hemlock LowPonderosa Pine-east ModeratePonderosa Pine-west ModerateWestern white pine ModerateAspen ModerateWestern red cedar ModerateWestern hemlock ModerateLodgepole pine ModerateGreen ash ModerateCottonwood ModerateLimber pine HighDouglas-fir HighWhitebark pine HighAlpine larch HighWestern larch High

NRAP Vulnerability AssessmentVulnerability RatingAlpine larch 1Whitebark pine 2Western white pine 3Western larch 4Douglas-fir 5Western red cedar 6Western hemlock 7Grand fir 8Engelmann spruce 9Subalpine fir 10Lodgepole pine 11Mountain hemlock 12Cottonwood 13Aspen 14Limber pine 15Ponderosa Pine-west 16Ponderosa Pine-east 17Green ash 18

Vulnerability AssessmentVulnerability Rating ComparisonSpecies NRAP RatingAlpine larch 1Whitebark pine 2Western white pine 3Western larch 4Douglas-fir 5Western red cedar 6Western hemlock 7Grand fir 8Engelmann spruce 9Subalpine fir 10Lodgepole pine 11Mountain hemlock 12Cottonwood 13Aspen 14Limber pine 15Ponderosa Pine-west 16Ponderosa Pine-east 17Green ash 18

Species PNW VulnRating

Whitebark pine 1Subalpine fir 2Engelmann spruce 3Alpine larch 4Grand fir 5Aspen 6Mountain hemlock 7Lodgepole pine 8Western hemlock 10Douglas-fir 11Western larch 12Western white pine 13Ponderosa Pine-east 14Ponderosa Pine-west 14Western red cedar 15Cottonwood 17Limber pine 18Green ash 19

Vulnerability AssessmentVulnerability Rating ComparisonSpecies NRAP RatingAlpine larch 1Whitebark pine 2Western white pine 3Western larch 4Douglas-fir 5Western red cedar 6Western hemlock 7Grand fir 8Engelmann spruce 9Subalpine fir 10Lodgepole pine 11Mountain hemlock 12Cottonwood 13Aspen 14Limber pine 15Ponderosa Pine-west 16Ponderosa Pine-east 17Green ash 18

Species Hansen Vulnerability

Whitebark pine 1Mountain hemlock 2Lodgepole pine 3Subalpine fir 4Engelmann spruce 5Western hemlock 6Western red cedar 7Western larch 8Douglas-fir 9Ponderosa Pine-east 10Ponderosa Pine-west 10Grand fir 11Aspen NAAlpine larch NAWestern white pine NACottonwood NALimber pine NAGreen ash NA

Vulnerability AssessmentExposure, Risk (magnitude, likelihood)Forest Vegetation type

Exposure Risk AssessmentMagnitude of effects

Risk AssessmentLikelihood of

effects NR

VulnerabilityRanking

Dry Ponderosa Pine and Douglas-fir Forests High High High 3

Western larch mixed conifer forests High High Very High 2

Lodgepole pine and aspen mixed conifer forests High Moderate High 4

Mixed mesic white pine, cedar, hemlock grand fir forests

Low Moderate Low 5

Whitebark pine-spruce-fir forests High High High 1

Biome Types A2, B1, 3 GCMconsensus

Perce

nt of

GNLC

C Suit

able i

n Clim

ateWhitebark/fir/spruce

Ponderosa/Dougfir

Mesic cedar/fir/hemlock

Vulnerability AssessmentExposure, Risk (magnitude, likelihood)Resource Concern Exposure Risk Assessment

Magnitude of effects

Risk AssessmentLikelihood of

effects

NRVulnerability

Ranking

Landscape heterogeneity

High Moderate High 1

Timber production

High Moderate to high in north Idaho

High in north Idaho

2

Carbon sequestration

High High Moderate 3

Predicting ecological responses to climate change is “wicked” HARD!Predicting ecological responses to climate change is “wicked” HARD! Vulnerabilities ratings are subject to local

conditions Vulnerability dependent on magnitude

and rate of climate change No climate change projection is suitable

for management analysis yet Integration of climate change with forest

planning might require a new toolbox

Vulnerabilities ratings are subject to local conditions

Vulnerability dependent on magnitude and rate of climate change

No climate change projection is suitable for management analysis yet

Integration of climate change with forest planning might require a new toolbox