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Transcript of Integrating Climate Change into Landscape Planning Modeling climate and management interactions...
![Page 1: Integrating Climate Change into Landscape Planning Modeling climate and management interactions within the ILAP framework April 23, 2013 Jessica Halofsky.](https://reader037.fdocuments.us/reader037/viewer/2022110210/56649e675503460f94b6272d/html5/thumbnails/1.jpg)
Integrating Climate Change into Landscape Planning
Modeling climate and management interactions within the ILAP framework
April 23, 2013Jessica Halofsky
Emilie Henderson
![Page 2: Integrating Climate Change into Landscape Planning Modeling climate and management interactions within the ILAP framework April 23, 2013 Jessica Halofsky.](https://reader037.fdocuments.us/reader037/viewer/2022110210/56649e675503460f94b6272d/html5/thumbnails/2.jpg)
Modeling
• “Essentially, all models are wrong, but
• some are useful.” – Box & Draper 1987
“It’s Only a Model.” – Patsy, 1975
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Projects behind today’s talks
• Integrated Landscape Assessment Project (ILAP)– Climate Change Module– Central Oregon Study Area
• Climate, Management and Habitat
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How might climate and land management interact to shape vegetation and habitat?
Coastal Washington
Southwest Oregon Southeast Oregon
Northern Spotted Owl Greater Sage Grouse
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Scenarios
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General Topics for today’s talk:
• Starting conditions • STMs without climate• Climate impacts modeling
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Modeling Strata
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The overall picture:
Not locally precise.Useful for describing landscape-to regional
trends.
![Page 9: Integrating Climate Change into Landscape Planning Modeling climate and management interactions within the ILAP framework April 23, 2013 Jessica Halofsky.](https://reader037.fdocuments.us/reader037/viewer/2022110210/56649e675503460f94b6272d/html5/thumbnails/9.jpg)
Current Vegetation
• GNN = Gradient Nearest Neighbor
– A spatial depiction of the FIA plots. – Structured by an ordination model.
• Gives us information on current vegetation within each modeling stratum.
Janet Ohmann, Matthew Gregory, Heather Roberts
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General Topics
• Starting Conditions • State Transition Modeling, without
accounting for climate• Climate impacts modeling
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State and Transition Modeling
Early Successional Young Forest
Mature Forest
Old Growth Forest
GrowthFireRegeneration Harvest
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State and Transition Modeling:Dry Douglas-fir
Grass-Forb
Giant TreesModerate CanopyMulti-Layered
Pole-stage, single-story, post-disturbance
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ILAP Potential Vegetation Types
PROBLEM:
Basic framework assumes that this map doesn’t change.
When climate shifts, sowill potential vegetation.
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State and Transition Modeling
Early Successional Young Forest
Mature Forest
Late Successional Old Growth
GrowthFireRegeneration Harvest
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Estimated harvests from the LANDSAT record inSouthwest Oregon
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Thanks to Robert Kennedy for the LandTrendr maps of disturbance history
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Current Fire
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PROBLEM:
Fire regimes are set to resemble the recent past.
They will probably change with shifting climate.
Extracted from Monitoring Trends in Burn Severity dataset: mtbs.gov
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Preliminary results for Southwestern Oregon: Current management
Area with Large and Giant TreesNo Climate Change
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General Topics
• Starting Conditions• State Transition Modeling, without accounting
for climate• Climate impacts modeling
– ILAP extension – Central Oregon Study Area
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What about climate change?
• Climate controls ecosystem processes, including:
– Plant establishment, growth, and mortality
– Disturbance• Drought• Fire • Insect outbreaks
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Dynamic Global Vegetation Models (DGVMs):
• Link state-of-the-art knowledge of: – plant physiology– biogeography – biogeochemistry– biophysics
• Simulate changes in vegetation structure and composition and ecosystem function through time
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*adapted from: Bachelet, D., J. M. Lenihan, C. Daly, R. P. Neilson, D. S. Ojima, and W. J. Parton. 2001. MC1: A Dynamic Vegetation Model for Estimating the Distribution of Vegetation and Associated Ecosystem Fluxes of Carbon, Nutrients, and Water. USDA Forest Service General Technical Report PNW-GTR-508.
biomass mortality
nutrient loss and release
Biogeography Biogeochemistry
Fire
fireoccurrence
lifeformmixture
carbon poolssoil moisture
lifeform mixture
live biomass
(MAPSS) (CENTURY)
(MCFire)
The MC1 Dynamic Global Vegetation Model
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A Linked Model Approach
Dry Mixed Conifer
Xeric Ponderosa PineJuniper woodland
Moist Mixed Conifer
MC1STMs
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Central Oregon Study Area
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Historical vegetation in the study area
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Vegetation type crosswalks
MC1 Functional Vegetation Type
STM Potential Vegetation Type
Subalpine forest Mountain hemlock and subalpine fir forests
Cool needle-leaved forest Moist mixed conifer and white fir forests
Temperate needle-leaved forest Ponderosa pine, lodgepole pine, and dry mixed conifer forests
Temperate needle-leaved woodlandMountain big sage – western juniper woodland and shrubland
Temperate shrubland Wyoming big sage shrubland
Xeromorphic shrubland Salt desert shrubland
Temperate grasslandBluebunch wheatgrass – Sandberg bluegrass grassland
Warm-season grassland Warm-season grassland
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Climate Scenarios
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MC1 Functional Vegetation Type Projections
MIROC CSIRO
Hadley
Halofsky et al. in review
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MC1 fire projectionsMIROC CSIRO
Hadley
Halofsky et al. in prep
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Linked model results
MIROC CSIRO
Hadley
Halofsky et al. in prep
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Central Oregon Management Scenarios
• Fire suppression only– Fire frequencies same as the last 25 years under
fire suppression– No other active management
• Resilience– Light to moderate levels of thinning and some
prescribed fire in dry forest types
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Effects of management on dry forests
Fire suppression
only
Resilience
MeanMin to maxRandomly selected simulations
Halofsky et al. in prep
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Fire suppression only
Resilience
Halofsky et al. in prep
Effects of management on:dry forests with large trees and open canopy
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Land
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Fire suppression
only
Resilience
Trends in dry forest structure<12.7 cm12.7-50.8 cm>50.8 cm
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Conclusions for Central Oregon
• Linked DGVM-STM output suggests greater vegetation resilience than DGVM alone.
• Dry ponderosa pine and mixed conifer forests will likely maintain dominance in the central Oregon study area.
• In some cases, management may dampen the magnitude of forest change under changing climate.
Halofsky et al. in prep
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Technical Thoughts
• All models are wrong, ours could be useful• These models provide big-picture projections• The linked model process is data-, labor-, and
software-intensive
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Getting to Landscape Planning
• We haven’t described the planning process itself, which involves conversations and people.– Stakeholders – Decision Makers
• Our models are useful storytelling tools. – Enable the asking of questions.– Realistic and plausible stories. – Enhance the role of science in conversations about
planning.
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• Half of science is asking the right questions. -- Roger Bacon (c. 1214 – 1294)1
• Emilie, you really need to refine your questions!-- Dr. David Mladenoff, numerous times throughout my
career as a PhD student in his lab.1Wikiquotes
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What activities?e.g., partial harvestregeneration harvestrestoration harvestprescribed fire
At what rates?
Where should they be applied?
Groups we have spoken with:
•The Nature Conservancy•Bureau of Land Management•US Forest Service personnel – regional and local•Local chapters of the Society of American Foresters•Washington Department of Natural Resources•Oregon Department of Forestry•Consulting foresters who serve nonindustrial private landowners•County commissioners
•4 activities
• 24 ownership/allocation categories
• ∞ variations in rates
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Save the world!
Our Hope for our Work
• Tell informative stories that are grounded in science about how different landscape management policies and plans may lead to different futures.
• Relevance and credibility beyond the science community.
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Funding:
Dominique Bachelet Emilie HendersonDavid Conklin James KaganMegan Creutzburg Becky KernsJessica Halofsky Anita MorzilloJoshua Halofsky Janine SalwasserMiles Hemstrom
ResearchTeam: