Climatic gradients and Douglasfir growth: Water limits growth from stand to region

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Climatic gradients and Douglas-fir growth Water
limits growth from stand to region
Jeremy Littell JISAO CSES Climate Impacts Group
UW College of Forest Resources David L.
Peterson, USFS PWFSL Michael Tjoelker, UW College
of Forest Resources
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Douglas-fir and climate

• Bio-climatic range of Douglas-fir fairly well
  understood
• But presence/absence ? life history - growth is
  also important
• Climatic limitations on growth should vary
  substantially across range

Thompson et al.
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High elevation / northern mountain hemlock
Photo J. Littell
Low elevation / southern mountain hemlock
Photo C. Webber
Interior ponderosa pine
Photo C. Woodhouse
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Why an emphasis on tree growth?

• Compared to biogeography, we know relatively
  little about long-term(centuries), broad-scale
  climatic controls on life-history processes of
  trees
• Especially true in non-plantation, mountain
  ecosystem settings where topography, soils, etc.
  interact with climate
• Establishment, growth, and mortality are the
  mechanisms of species range changes and are tied
  to climate these are the ecological mechanisms
  behind productivity, carbon sequestration, and
  ecohydrology

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Scales of Climatic Influence

• Global - hemispheric climate change
• Hemispheric to regional climatic variability
• Regional to local physiographic
• Local topographic
• Goal exploit network of tree ring chronologies
  to understand local vs. large scale controls on
  growth

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CLIMET (Climate-Landscape Interactions on a
Mountain Ecosystem Transect)
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Climate Dimensions of the Sample Transect
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First Detrending Negative exponential, negative
linear, or zero slope fit
Mean standardized chronology
Second Detrending Cubic smoothing spline
(preserves 50 variance at 128yr frequency, 99
at 41 yr)
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ONP
Within each park, the variability in tree-growth
is similar across low, middle, and high
elevations. Main differences between west and
east (note 2000s drought)
NCNP
IPNF
GNP
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Correlating Tree-growth and Climate

• Two scales of monthly climate data
• Climatological divisional climate (1895-2002)
• Year-of-growth and year-prior PPT, Avg. T, PDSI
  calculated water balance deficit
• Biological (1/8 x 1/8 ) VIC climate
  (1915-2002)
• Year-of-growth and year-prior PPT, T (Avg., Max.,
  Min.), Soil Moisture, ET, SWE
• Seasonal climate variables
• Climate division ANN, H2OANN, NDJFM, AMJ, MJJAS,
  JJA, JA for all PPT, T, PDSI
• VIC Selected combinations of months for
  different variables
• Water balance deficit
• Gridded Bouwman 30cm field capacity data set 50
  and 100mm (coarse ½ degree resolution)
• Assumed non-linear declining availability
  function
• Estimated PET - AET deficit
• Milne et al. surplus water PPT- ET / PPT total
  surplus water available to site

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General patterns of growth-climate correlations
are similar for divisional and VIC PPT and T
climate.

• PPT
• (M) JJ Year-of
• JA (S) Year-prior-to grwoth
• Avg. T
• JJ Year of, JA prior
• Apr and Nov prior
• Important differences
• VIC precipitation and divisional temperature
  are better correlates in most chronologies.
• Seasonality relationships different VIC
  captures a longer season of sensitivity to
  precipitation.

ONP relationship stronger
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Prior JS results similar to divisional average T
JJ results weak in other analyses
Nov. results similar to VIC and divisional
average T

• VIC allows separation of the influence of minimum
  and maximum temperature
• VIC Min/Max T
• JJ year of (esp. GNP and ONP), - JA year prior
  for maximum temperature (esp. IPNF and NCNP) (hot
  summers)
• ON year prior for minimum temperature (warmer
  autumns)

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Deficit (Div.) -JJ year of growth -JAS year
prior PDSI (Div.) May.-Sep ASO year
prior Soil Moisture (VIC) Entire year
prior Evapotransp. (VIC) Mixed (AET context
varies with PET)
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• Seasonal Aggregation
• Divisional Climate
• Prior JA temperature
• Prior JA precipitation
• VIC Climate
• Prior JA precipitation
• Prior JJAS max. temp.
• current AMJJ precip.
• current AMJJ max. temp.
• Prior ANN. soil moisture

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The magnitude of the correlation between seasonal
hydrological variables and tree-growth depends on
the position of the plot along a gradient of
surplus water in the environment.
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The portion of the tree-growth signal that is
common to all plots is closely related to
independent reconstructions of PDSI. However,
there are differences across the transect in
fidelity to that signal.
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Summary Growth-Climate Relationships

• Most frequent patterns of correlations point to
  combined influence of (-) temperature and ()
  precipitation during summer
• Underscored by PDSI () and water balance deficit
  (-), esp. in IPNF and GNP.
• Some cool season () temp. and (-) snow
  relationships, primarily in ONP and NCNP.

Bonsai PSME, Saint Mary, Glacier National Park
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Spencer Wood
Mike Case, Mike Tjoelker, Sarah Gobbs, Sean
Hill
Melissa Hornbein
2003-2004 Field Crews
Alex Karpoff
Greg Pederson
Sam Cushman
Carson Sprenger