1. No category

ANDY HANSEN
Montana State University
Vulnerability of Tree Species and Biome Types
to Climate Change in the U.S. Northern Rocky
Mountains and Yellowstone
Andy Hansen, Linda Phillips, Tony Chang, Nathan Piekielek,
Katie Ireland
Montana State University and Penn State University
NASA Applied Sciences Program
(NNH10ZDA001N - BIOCLIM)
GNLCC Webinar
March 18 2015
Which tree species and biome types are most vulnerable to
climate change and how can management help?
Studies Summarized
•
Meta-analysis of tree species and biome climate
suitability across the US Northern Rockies.
Hansen, Phillips. 2015. Forest Ecology and Mgt.
•
Habitat suitability of tree species in Greater
Yellowstone.
Piekielek, Hansen, Chang. In Review. EcoInformatics.
•
Climate suitability modeling for whitebark pine in
Yellowstone.
Chang, Hansen, Piekielek. 2014. Plos ONE.
•
Implications for management: WBP in the GYE.
Hansen et al. In Review. Biol. Cons.;
Ireland et al. In Prep.
Landscape Climate Change Vulnerability Project
Principle Researchers
A Hansen, C Whitlock, E Shanahan: Montana
State Univ
S Goetz, P Jantz: Woods Hole Research
Center
B Monihan, J Gross: NPS I&M Program
T Olliff: NPS / Great Northern LCC
F Melton: CSU Monterey Bay / NASA Ames
D Theobald: Conservation Science Partners
Goal: Understand and manage
wildland ecosystems under climate
change
Agency Collaborators
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Study Areas
•
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NASA Applied Sciences Program
North Central Climate Sciences
Center
MT EPSCoR
Western US
NPS I&M Greater Yellowstone Network: K Legg
NPS I&M Rocky Mountain Network: M Britten
GYCC: V. Kelly
GYCC Whitebark Pine Subcom: K Buermeyer
Grand Teton National Park: D. Reinhart
Yellowstone National Park: A Rodmann
Rocky Mountain National Park: B Bobowski
Eastern US
NPS I&M Appalachian Highlands Network: R
Emmott
NPS I&M Eastern Rivers and Mountains
Network: M Marshall
NPS I&M Mid-Atlantic Network: J Comiskey
Delaware Water Gap National Recreational Area:
R Evans, L Morelock
Great Smoky Mountains National Park: J Renfro
Shenandoah National Park: J Schaberl
Collaborative Approach to Climate Adaptation
Glick et al. 2011. Scanning the Conservation Horizon.
John Gross, NPS Climate Scientist
Ben Bobowski, Chief of Resources, Rocky
Mountain National Park
Scientific Assessment
Scientific Assessment
N. Zimmerman 2014
Climate Envelope Modeling
Latitude (Y)
Identify places where future climate is projected to be suitable for a species.
Longitude (X)
2. Obtain climate data for these locations
Ppres = f (climate)
Temperature
1. Identify where the species is present
Moisture
4. Project presence under future conditions
3. Statistically relate presence to climate
Climate Envelop Modeling
Ignores Change in
• Disturbance / pests
•
Competition with other
species
Ignores
• Adaptive capacity: dispersal,
genetic variation, etc.
Utility
• Climate suitability is a strong
indicator of where viable
populations may be able to
exist.
•
Other controlling factors can
be manipulated through
management.
•
Thus, knowledge of climate
suitability is a first filter for
prioritizing research and
management.
Meta-analysis for US Northern Rockies
Study
Statistical modeling
method
Reference and
Scenarios / GCMs
Vegetation
future projection
units
periods
Biomes
1961-1990
A1, B2 /
2030, 2060, 2090 Consensus of CGCM3,
GFDLCM21, HADCM3
Rehfeldt et al.
2012
Random Forests
Crookson et al.
2010
Random Forests
1961-1990
A1, B2 /
2030, 2060, 2090 CGCM3, GFDLCM21,
HADCM3
Coops and
Waring 2011
Decision Tree
Regression
1950-1975
2020’s, 2050’s,
2080’s
1961-1990
2020s, 2050s,
2080s
Gray & Hamann Random Forests
2013
Bell et al. 2014
Baysian Logistic
Regression
1981-2010
2070-2099
A1, B2 /
CGCM3
Tree species
Tree species
Consensus of AIFI, A2, Tree species
B1, B2 under
CGCM, CSIRO2,
HADCM3, ECHAM4,
PCM
A1, B2 /
Tree species
Average of 16 GCMs
Selected based on: GNLCC or wider in extent; used comparable GCMs, scenarios, methods;
grain size projection results available.
Future Climate Projection: Scenarios
Story Line
IPCC CMIP4 (2007)
IPCC CMIP5 (2013)
“Business as usual emissions”
A2
RCP 8.5
“Global reductions in emissions”
B1
RCP 4.5
Future Climate
GYE PACE
CMIP5, 8 GCM ensemble average
Reference period: 1980-2005 average
Change in temperature by 2100 (°C)
Change in PPT (mm) by 2100
RCP 4.5
RCP 8.5
RCP 4.5
RCP 8.5
3.0
7.0
60 (7.5%)
130 (16.3%)
Context: Mean July temperature across North America since the end
of the last ice age 14 000 years ago varied ~5 0C (Viau et al. 2006).
Future Climate
GYE PACE
CMIP5, 8 GCM ensemble average, 800 m
Aridity Index (PET/PPT)
RCP 4.5
RCP 8.5
Biome Types
A2 , B1, 3 GCM
consensus
Current
2090
Percent of GNLCC Suitable in Climate
Biome Types
A2, B1, 3 GCM
consensus
A2 Scenario
Tree Species
Coops & Waring
Crookston et al.
Gray & Hamann
Bell et al.
Subalpine
Montane
Mesic
Western redcedar
Western hemlock
Percent of GNLCC Suitable in Climate, Reference Period to 2100
Change in Spatial Patterns
A2 Scenario
Change in Spatial Patterns
A2 Scenario
Vulnerability Assessment Based on Potential Impact
Time Period
Current
Period
Metric
Area of suitable habitat
Units
Percent of study area
Late century
(e.g., 20702090)
Loss of reference-period
suitable habitat
Percent loss of area from the
reference period
Naturally colonizable
newly suitable habitat by
2070-2090
% gain in suitable habitat
<=30 km from ref suitable)
Newly suitable habitat by
2070-2090 requiring
assisted migration
Percent gain in suitable
habitat >30 km from ref
suitable)
Vulnerability Ranking
5: Very high (<10% of area)
4: High (10<30% of area)
3: Medium (30<50% of area)
2: Low (50<75% of area)
1: Very low (>=75% of area)
5: Very high (>75%)
4: High (>50-75%)
3: Medium (>30-50%)
2: Low (>10-30%)
1: Very low (<=10%)
0: very low gain (0<10%)
-1: low gain (10<50%)
-2: mod gain (50<100%)
-3: large gain (100<150%)
-4: very large gain (>=150%)
0: low gain (0<20%)
-1: mod gain (20<100%)
-2: large gain (>100%)
Vulnerability Assessment Based on Potential Impact
Average among
studies for A2
scenario
Habitat Suitability Modeling: Greater Yellowstone
Methods
Chang et al. 2014; Piekielek et al. in review
Response Data
2,569 data points from FIA, GYCC, WLIS, GYRN I&M
Predictor Data
• PRISM climate (19 variables)
• Monthly water balance using Thornthwaite equation (10
variables)
• Parent material, topography (10 variables)
Random Forests
Species
Sagebrush spp., Juniper spp. Limber pine, Aspen, Douglas
fir, Lodgepole Pine, Subalpine fir, Engleman spruce,
Whitebark pine
Analyses
• NC CSC Software for Assisted Habitat Modeling (SAHM)
VisTrails package
• Boosted Regression Trees, Logistic Regression, Multivariate
Adaptive Regression Splines, and Random Forest
• Model validation based on ROC for withheld data
GCMs
• Best 9 CHIP5 GCMs
WBP Suitability under 9 GCMs
2010 – 2100
RCP 8.5
scenario
Greater Yellowstone
Douglas fir
N
Suitable to
Suitable
Suitable to
Unsuitable
Unsuitable
to suitable
2010 – 2100
RCP 8.5
scenario
Greater Yellowstone
Juniper
Suitable to
Suitable
Suitable to
Unsuitable
Unsuitable
to suitable
2010 – 2100
RCP 8.5
scenario
Greater Yellowstone
Lodgepole pine
YNP Photo Archives
Suitable to
Suitable
Suitable to
Unsuitable
Unsuitable
to suitable
2010 – 2100
RCP 8.5
scenario
Greater Yellowstone
Subalpine fir
Suitable to
Suitable
Suitable to
Unsuitable
Unsuitable
to suitable
Greater Yellowstone
Whitebark Pine
RCP 8.5
scenario
Prob. Presence > 0.42
N
2010
Greater Yellowstone
Whitebark Pine
RCP 8.5
scenario
Prob. Presence > 0.42
N
2040
Greater Yellowstone
Whitebark Pine
RCP 8.5
scenario
Prob. Presence > 0.42
N
2070
Greater Yellowstone
Whitebark Pine
RCP 8.5
scenario
Prob. Presence > 0.42
N
2099
Greater Yellowstone
Whitebark Pine
RCP 8.5
scenario
Prob. Presence > 0.42
N
% 1950-80 Suitable Habitat
2010
2099
RCP 4.5 91.3
17.8
RCP 8.5 91.3
3.0
2099
Climate Envelope Modeling Conclusions
In the Northern Rockies and Yellowstone, subalpine forests are high in
vulnerability to climate change and lower treeline forests are pushed
substantially upslope.
These results might suggest that upper and lower treeline forests are
least resilient to climate change, beetles, fire.
In these zones of forest decline, ecosystem services relating to
snowpack, runoff, and food and habitat for other species will be
reduced.
Climate suitability for tree species is an important filter for prioritizing
research and management.
YNP Photo Archives
Collaborative Approach to Climate Adaptation
Glick et al. 2011. Scanning the Conservation Horizon.
John Gross, NPS Climate Scientist
Ben Bobowski, Chief of Resources, Rocky
Mountain National Park
Informing implementation of the Greater Yellowstone Coordinating
Committee’s Whitebark Pine Strategy based on climate sciences
MSU and UM: Andrew Hansen, Tom Olliff, Cathy Whitlock et al.
GYCC WBP Subcommittee: Karl Buermeyer, Kelly McClosky, Dan Reinhart, Kristen Legg
Funding: North Central
Climate Sciences Center
Management Implications for Whitebark Pine
RCP 4.5
Core Habitat. Manage to retain the
species in these vitally important
zones.
Deteriorating Habitat.
• Give up?
• Manage towards Scenarios of
Viability?
RCP 8.5
Future habitat. Manage for natural
colonization and assisted
colonization.
Adaptive Management Opportunities
Adaptive Management Opportunities
Adaptive Management Opportunities
Informing implementation of the Greater Yellowstone Coordinating
Committee’s Whitebark Pine Strategy based on climate sciences
MSU and UM: Andrew Hansen, Tom Olliff, Cathy Whitlock et al.
GYCC WBP Subcommittee: Karl Buermeyer, Kelly McClosky, Dan Reinhart, Kristen Legg
Objectives
1.
Ecological forecasting under alternative
IPCC climate and land use scenarios.
2.
Analyzing WBP response to climate and
extreme climate events over the past
15,000 years.
3.
Develop spatially explicit WBP
management alternatives.
4.
Evaluate the management alternatives
under future climate scenarios:
• WBP goals
• Ecosystem services derived from
WBP
• Cost of implementation.
5.
Draw recommendations for
implementation of the GYCC WBP
strategy under climate change.
Funding: North Central
Climate Sciences Center
Workshop Prospectus
Vegetation Vulnerability across the Greater Yellowstone Ecosystem: Managing
under Climate Change
Date and Venue
April 9, 2015: USGS Science Center, Bozeman, MT
Objectives
1. Synthesize results from the NASA Landscape Climate Change Vulnerability
Project (LCCVP)* study on climate change, ecological response,
vulnerability assessment.
2.
Identify management-relevant issues for vegetation in the GYE based on
LCCVP, Northern Rockies Adaptation Partnership, Greater Yellowstone
Coordinating Committee, and related activities.
3.
Attempt to “close the loop” on the Climate Smart Cycle by outlining
approaches for developing/evaluating/implementing/monitoring climate
adaptation strategies.
Acknowledgements
NASA Applied Sciences Program (Grant 10-BIOCLIM10-0034)
NSF EPSCoR Track-I EPS-1101342 (INSTEP 3)
NASA Land Cover Land Use Change Program
North Central Climate Sciences Center
Federal agency collaborators
Literature Cited
Hansen, A.J. and L.B. Phillips, 2015. Which tree species and biome types are most
vulnerable to climate change in the US Northern Rocky Mountains?, Forest Ecology
and Management, 338: pp. 68-83.
Chang, T., A.J. Hansen, N. Piekielek. 2014. Patterns and variability of projected
bioclimate habitat for Pinus albicaulis in the Greater Yellowstone Ecosystem. PLOS
One. November 05, 2014.
Piekielek, N., A.J. Hansen, T. Chang. In Review. Using custom scientific workflow
software and GIS to inform protected area climate adaptation planning across
Greater Yellowstone. EcoInformatics.
Hansen, A.J., K. Ireland, K. Legg, E. Barge, M. Jenkis, M. Pillet. In Review. Can
whitebark pine persist in Greater Yellowstone? Exploring Scenarios of Viability for
species under deteriorating climates. Biological Conservation.