Keane - Impacts & vulnerabilities for northern Rockies forests
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Dr. Robert Keane of RMRS Missoula Fire Lab and contributor to the Northern Rockies Adaptation Partnership assessment, presents climate change impacts and vulnerabilities for forests of the northern Rockies at the Adaptive Silviculture for Climate Change (ASCC) Workshop.
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Keane - Impacts & vulnerabilities for northern Rockies forests
- 1. Bob Keane USDA Forest Service Rocky Mountain Research Station Bob Keane USDA Forest Service Rocky Mountain Research Station
- 2. Predicting ecological responses to climate change is “wicked” HARD! Three Reasons Predicting ecological responses to climate change is “wicked” HARD! Three Reasons
- 3. Interactions all climate change impacts result from complex interactions between climate, vegetation, topography, humans, and a host of other factors Vegetation Disturbance Wildlife Humans Climate
- 4. Scale all climate change responses are scale dependent in both time and space MoritzM.A.et.al.2005.PNAS;102:17912-17917
- 5. Climate Projections all climate projections have a high degree of uncertainty that increases with finer scales from Talbert and others (2014)
- 6. Sula, Montana CMIP5 Data Extrapolation
- 7. Climate Change Impacts Predicting landscape change Four major approaches: Climate Change Impacts Predicting 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
- 8. Exploring climate change impacts in northern Rocky Mountain Forests This presentation: Exploring climate change impacts in northern Rocky Mountain Forests This presentation: •Disturbance •Vegetation •Interactions •Vulnerability assessments •Disturbance •Vegetation •Interactions •Vulnerability assessments
- 9. Exploring climate change impacts in northern Rocky Mountain Forests Exploring 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
- 10. 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) projections New 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
- 11. Disturbance More influential than vegetation development Disturbance More 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
- 12. Climate Change and Wildland Fire – NRM Forests Longer 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
- 13. Climate Change and Wildland Fire – NRM Forests Longer 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
- 14. Climate Change and Wildland Fire Increased 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
- 15. Climate Change and Wildland Fire Increased fuel production • Higher productivity results in an increase in burnable biomass • Increased fuels will be more contagious and connected • Productivity will increase canopy fuels
- 16. Climate Change and Wildland Fire – NRM Forests Greater 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
- 17. Climate Change and Wildland Fire – NRM Forests Greater fire frequencies and intensities Higher Temperatures Will Increase Burn Areas In the West How much more area will burn each year 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
- 18. MC2 Modeling Results Fire Rotation (Annual % burned)
- 19. Climate Change and Wildland Fire Larger 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 1970–2003 moisture deficit in forests 1970–2003 Wildfires >1,000 ha 1970–2003 Wildfires >1,000 ha 1970–2003
- 20. Fir es Ac res 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.
- 21. Washington 6 1970 2010 Idaho 30 1970 2010 Montana 20 1970 2010 Oregon 10 1970 2010 Wyoming 10 1970 2010 California 40 1970 2010 Nevada 4 1970 2010 Arizona 20 1970 2010 New Mexico 10 1970 2010 Colorado 8 1970 2010 Utah 8 1970 2010 Temperatures and Wildfire Numbers Have Increased Across the West Spring-Summer Temperature Change Trend (oF per decade) 0.40 0.30 0.20 0.10 Fir es Ac res
- 22. Climate Change and Wildland Fire An 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
- 23. 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 heterogeneity Causal Mechanisms Fire exclusion Climate change Major Causes Favorable weather Abundant host species Reduced habitat heterogeneity Causal Mechanisms Fire exclusion Climate change Climate Change Mountain Pine Beetle
- 24. 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 Change White pine blister rust
- 25. 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 Change Spruce budworm
- 27. Predicted increase in plant biomass under A2 climate Bachelet et al., Environment 2007
- 28. Northern Rockies Vulnerability Assessment and Adaptation Plan MC2 Modeling Reference Material for the GYA Aboveground Live Carbon
- 29. Northern Rockies Vulnerability Assessment and Adaptation Plan MC2 Modeling Reference Material Potential Evapotranspiration (Drought)
- 30. Ponderosa Pine Current distribution Distribution in 2090 – A2 Climate http://forest.moscowfsl.wsu.edu/climate/species/speciesDist/Ponderosa-pine/
- 31. Douglas-fir Current distribution Distribution in 2090 – A2 Climate http://forest.moscowfsl.wsu.edu/climate/species/speciesDist/Ponderosa-pine/
- 32. Whitebark Pine Current distribution Distribution in 2090 – A2 Climate http://forest.moscowfsl.wsu.edu/climate/species/speciesDist/Ponderosa-pine/
- 33. Western White Pine Current distribution Distribution in 2090 – A2 Climate http://forest.moscowfsl.wsu.edu/climate/species/speciesDist/Ponderosa-pine/
- 34. Climate Change Statistical Modeling Efforts Changes in Vegetation in western MT Climate Change Statistical Modeling Efforts Changes 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
- 36. FireBGCv2: A research simulation platform for exploring fire, vegetation, and climate dynamics Keane, Robert E.; Loehman, Rachel A.; Holsinger, Lisa M. 2011. The FireBGCv2 landscape fire and succession model: a research simulation platform for exploring fire and vegetation dynamics. Gen. Tech. Rep. RMRS-GTR-255. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 137 p.
- 38. Number Fires vs Area Burned No fire suppression Full fire suppression No fire suppression Full fire suppression
- 39. Vegetation composition Historical Species BURNED PIPO ABGR PSME PICO LAOC ABLA PIEN PIAL LALY PIMO THPL TSHE POTR BEPA SHRUB GRASS 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 A2 Hot/dry No fire supp. B2 Warm/wet No fire supp. A2 Hot/dry Fire supp. B2 Warm/wet Fire supp.
- 40. Dominant species changes Subalpine fir Western hemlock Glacier NP
- 41. Loehman et al. 2011 Forests. Species Dynamics -Western White Pine Species Ponderosa pineG rand fir D ouglas-fir Lodgepole pine W estern larch Subalpine fir Englem ann spruce W hitebark pine Alpine larch W estern w hite pine W estern red cedar W estern hem lock Q uaking aspen Paperbirch ShrubsG rasses
- 42. Species Burned Ponderosa pine Grand fir Douglas-fir Lodgepole pine Western larch Subalpine fir Englemann spruce Whitebark pine Alpine larch Western white pine Western red cedar Western hemlock Quaking aspen Paper birch Shrubs Grasses 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 Whitebarkrestoration–EffectsofstanddensityWhitebarkrestoration–Effectsofstanddensity A2 Climate – Warmer and Drier Whitebark pine landscape dynamics Mimic Planting Rust-resistant trees Current density
- 43. 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
- 44. Dominant species changes Lodgepole pine Douglas-fir Bitterroot NF
- 46. Simulation Results: East Fork Bitterroot River
- 47. East Fork Bitterroot River Fire and fish dynamics in a changing climate East Fork Bitterroot River Fire and fish dynamics in a changing climate
- 48. NRAP Vulnerability Assessment General 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
- 49. NRAP Vulnerability Assessment Climate 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 snowpack Mote, 2003
- 50. NRAP Vulnerability Assessment Stressors 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 1970–2003 moisture deficit in forests 1970–2003
- 51. NRAP Vulnerability Assessment Sensitivity to Climate Change • Shade tolerance • Fire tolerance • Drought tolerance • Climatic tolerance • Genetic plasticity • Current abundance • Level of stress • Dispersal capability • Adaptive capacity A2 Hot/ dry No fire sup p. B2 Warm /wet No fire supp. A2 Hot/ dry Fire sup p. B2 Warm /wet Fire supp.
- 52. NRAP Vulnerability Assessment Expected Effects Mesic 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
- 53. NRAP Vulnerability Assessment Adaptive 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
- 54. NRAP Vulnerability Assessment Exposure, Risk (magnitude, likelihood) Species Magnitude of effects Ponderosa Pine-east Low Aspen Moderate Cottonwood Moderate Engelmann spruce Moderat Grand fir Moderate Green ash Moderate Limber pine Moderate Lodgepole pine Moderate Mountain hemlock Moderate Ponderosa Pine-west Moderate Subalpine fir Moderate Western hemlock Moderate Western red cedar Moderate Alpine larch High Western larch High Western white pine High Whitebark pine High Douglas-fir High Species Likelihood of effects Ponderosa Pine-east Low Cottonwood Moderate Engelmann spruce Moderate Grand fir Moderate Limber pine Moderate Lodgepole pine Moderate Mountain hemlock Moderate Ponderosa Pine-west Moderate Subalpine fir Moderate Western hemlock Moderate Western red cedar Moderate Alpine larch High Aspen High Green ash High Western white pine High Whitebark pine High Douglas-fir High Western larch Very High Species Exposure Grand fir Low Subalpine fir Low Engelmann spruce Low Mountain hemlock Low Ponderosa Pine-east Moderate Ponderosa Pine-west Moderate Western white pine Moderate Aspen Moderate Western red cedar Moderate Western hemlock Moderate Lodgepole pine Moderate Green ash Moderate Cottonwood Moderate Limber pine High Douglas-fir High Whitebark pine High Alpine larch High Western larch High
- 55. NRAP Vulnerability Assessment Vulnerability Rating Alpine larch 1 Whitebark pine 2 Western white pine 3 Western larch 4 Douglas-fir 5 Western red cedar 6 Western hemlock 7 Grand fir 8 Engelmann spruce 9 Subalpine fir 10 Lodgepole pine 11 Mountain hemlock 12 Cottonwood 13 Aspen 14 Limber pine 15 Ponderosa Pine-west 16 Ponderosa Pine-east 17 Green ash 18
- 56. Vulnerability Assessment Vulnerability Rating Comparison Species NRAP Rating Alpine larch 1 Whitebark pine 2 Western white pine 3 Western larch 4 Douglas-fir 5 Western red cedar 6 Western hemlock 7 Grand fir 8 Engelmann spruce 9 Subalpine fir 10 Lodgepole pine 11 Mountain hemlock 12 Cottonwood 13 Aspen 14 Limber pine 15 Ponderosa Pine-west 16 Ponderosa Pine-east 17 Green ash 18 Species PNW Vuln Rating Whitebark pine 1 Subalpine fir 2 Engelmann spruce 3 Alpine larch 4 Grand fir 5 Aspen 6 Mountain hemlock 7 Lodgepole pine 8 Western hemlock 10 Douglas-fir 11 Western larch 12 Western white pine 13 Ponderosa Pine-east 14 Ponderosa Pine-west 14 Western red cedar 15 Cottonwood 17 Limber pine 18 Green ash 19
- 57. Vulnerability Assessment Vulnerability Rating Comparison Species NRAP Rating Alpine larch 1 Whitebark pine 2 Western white pine 3 Western larch 4 Douglas-fir 5 Western red cedar 6 Western hemlock 7 Grand fir 8 Engelmann spruce 9 Subalpine fir 10 Lodgepole pine 11 Mountain hemlock 12 Cottonwood 13 Aspen 14 Limber pine 15 Ponderosa Pine-west 16 Ponderosa Pine-east 17 Green ash 18 Species Hansen Vulnerability Whitebark pine 1 Mountain hemlock 2 Lodgepole pine 3 Subalpine fir 4 Engelmann spruce 5 Western hemlock 6 Western red cedar 7 Western larch 8 Douglas-fir 9 Ponderosa Pine-east 10 Ponderosa Pine-west 10 Grand fir 11 Aspen NA Alpine larch NA Western white pine NA Cottonwood NA Limber pine NA Green ash NA
- 58. Vulnerability Assessment Exposure, Risk (magnitude, likelihood) Forest Vegetation type Exposure Risk Assessment Magnitude of effects Risk Assessment Likelihood of effects NR Vulnerability Ranking 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
- 59. Biome Types A2, B1, 3 GCM consensus PercentofGNLCCSuitableinClimate Whitebark/fir/spruce Ponderosa/Dougfir Mesic cedar/fir/hemlock
- 60. Vulnerability Assessment Exposure, Risk (magnitude, likelihood) Resource Concern Exposure Risk Assessment Magnitude of effects Risk Assessment Likelihood of effects NR Vulnerability 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
- 61. 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