Bob Keane USDA Forest Service Rocky Mountain Research Station Bob Keane USDA Forest Service Rocky Mountain Research Station
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)
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
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
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
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.
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
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