ClimateFVS Version 0'1: Description of Content and Example Outputs

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• Climate-FVS Version 0.1 Description of Content
  and Example Outputs
• Nicholas L. Crookston
• Gary Dixon, Jerry Rehfeldt and many more
• Rocky Mountain Research Station Moscow
• National Silviculture Workshop
• June 15-19, 2009

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Contents

• Introduction
• Climate change makes a difference
• Modeling species climate-profiles
• Future climate and species distributions
• Elements of Climate-FVS
• Three examples
• Pros and cons regarding the modeling.
• Next steps

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Douglas-fir climate profile location
change (current to 2060)
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Aspen climate profile location change (current to
2060)
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Black Mesa Western Colorado
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Modeling species climate-profiles

• Build contemporary climate surfaces
• Get predictions of climate for each FIA plot in
  the western United States.
• Use Random Forest classification to build a
  predictive model of the species climate profile
  (climate-based species viability).
• To map the profile predict the viability for
  each 1 km pixel in the Western United States.

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Douglas-fir contemporary climate
Mapped at 1 km2 grid
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Future climate and species distributions

• Build future climate surfaces using outputs from
  3 global circulation models (GCM), run using 2 or
  3 scenarios to form 7 futures.
• Predict and map the species viability for the
  future climates.

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GCM General circulation model

• There are many, we used these three
• CGCM3 Canadian Center of Climate Modeling and
  Analysis, SRES scenarios A1B, A2, B1
• HADMC3 Met Office Hadley Centre (UK), SRES
  scenarios A2, B1
• GFDLCM21 Geophysical Fluid Dynamics Laboratory
  (Princeton University, NOAA Research), SRES
  scenarios A2, B2

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2090 GDFL
2000
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2090 GDFL
2000
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Douglas-fir climate profile location
change (current to 2060)
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Details in Rehfeldt et al. 2006. Empirical
analysis of plant-climate relationships for the
western United States. Int. J. Plant Sci.
167(6)11231150.
http//forest.moscowfsl.wsu.edu/gems/Biogeography.
pdf
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Elements of Climate-FVS

• Architecture and input
• Site carrying capacity
• Species composition
• Mortality
• Establishment
• Tree growth
• Genetics
• Site

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Architecture and input

• The architecture of FVS was not changed.
• Existing outputs and management actions
• Input climate and species viability scores for
  each stand and GCM/scenario combination.
• These data will be available from an internet
  site. You need to supply the location and
  elevation of each stand.

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Site carrying capacity

• Measured as max BA or max SDI
• FVS contains species max BA or SDI.
• A viability-weighed average is computed for
  contemporary climate and future climate. A ratio
  of these is used to adjust the FVS-estimate of
  carrying capacity.
• Conversion from forest to non-forest and visa
  versa is supported by this logic.

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Species composition

• Mortality rates increase when the viability score
  fall below 0.50.
• Establishment
• Triggered by low stocking.
• Add the most viable species.
• Add more trees per acre of the most viable
  species.

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Tree growth Site

• Site changes are modeled as a function of change
  in annual dryness index (ADI).
• Proportional change future/current.
• An increasing ADI results in corresponding growth
  reductions and visa versa.

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Tree growth Genetics

• Basic idea use common garden data to calibrate
  growth models as a function of climate transfer
  distance the difference in climate at the
  planting site and the seed source.

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Laura Leites, University of Idaho
Douglas-fir height growth
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Tree growth Genetics

• The change in relative growth is used to adjust
  growth.
• computed by replacing space with time in these
  models
• the effects are strongest for genetic
  specialists.
• We have preliminary models for Larch and
  Douglas-fir, they are used for all species based
  on a ranking of genetic specialization.

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Three examples
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First example Clearwater

• 135 stands on the Clearwater National Forest
• One hundred year simulation
• Output total basal area and trees per acre by
  species
• Eight results
• Base FVS (use the modified model with
  contemporary climate fixed over time)
• 7 GCM/SRES model/scenario combinations

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Second example Black Mesa

• Recall the talk introduction.
• 214 stands on the Grand Mesa, Uncompahgre,
  Gunnison National Forest (Black Mesa)

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Third example West Cascades

• 310 stands on the Gifford Pinchot National Forest
• For this area a additional element is include
  that represents change in growth depending on
  transfer distance, measured on climatic scales.

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Differences between examples

• Impact differs between locations
• Black Mesa IPCC A2 scenarios from the Canadian
  and GFDL models exhibit greatest impact.
• Clearwater Hadley model for A2 and B2 scenarios
  exhibit the greatest impact.
• West Cascades Low impact (but maybe false!).

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Reasons for using the approach

• Based on direct observations of the relationship
  between climate and species distributions
• It places reasonable bounds on the spatial
  distribution of species
• It is a consistent method over all species and
  regions

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Proscontinued

• Provides a framework for modeling what happens to
  forests when mature trees die and are replaced by
  small trees.
• We can start to understand the scale of the
  variance between GCMs and IPCC scenarios.

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Problems with the approach

• For genetic specialists, (such as Douglas-fir and
  lodgepole), the method likely underestimates the
  effect climate change will have on mortality
  rates of existing trees.
• Species migration rates are not represented.
• The effect of climate change on growth rates
  (site index) is represented using the results of
  a limited analysis.

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Cons continued

• Physiological processes are not directly
  represented. We have tried 3PG to model changes
  in carrying capacity.
• The climate model down-scaling does not represent
  fine-scale topographical elements that control
  micro climate.

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Cons continued

• Mortality will likely be caused by fire, insects,
  diseases, or these in combination. These
  simulations do not represent these episodic
  mortality causes, but they do, perhaps, represent
  the net effects of these events.
• Many more!

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Next steps

• Get this model in your hands for testing,
  evaluation, and feed back.
• Contact me or Dave Cawrse if you want to be a
  tester, ask questions, or make comments.
• dcawrse_at_fs.fed.us
• ncrookston_at_fs.fed.us

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Acknowledgements

• Funded by USFS Global Climate Change Research
  Program and the Rocky Mountain Research Station.
• Many people who attended workshops where ideas
  were openly discussed Aaron Weiskittel,
  Abdel-Azim Zumrawi, Albert Stage, Ann Abbot, Bill
  Wykoff, Bob Monserud, Brad StClair, Bryce
  Richardson, Colin Daniel, Dave Cawrse, Dave
  Marshall, David Loftis, Dennis Ferguson, Don
  Robinson, Doug Berglund, Doug Maguire, Erin
  Smith-Mateja, Fred Martin, Glenn Howe, John
  Goodburn, John Marshall, Kelsey Milner, Laura
  Leites, Linda Joyce, Mee-Sook Kim, Megan
  Roessing, Mike Bevers, Mike Ryan, Peter Gould,
  Phil Radtke, Robert Froese, and Stephanie Rebain.