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Climatic gradients and Douglas-fir growth: Water limits growth from stand to region

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. Douglas-fir and climate.

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Climatic gradients and Douglas-fir growth: Water limits growth from stand to region

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  1. 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

  2. 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.

  3. High elevation / northern mountain hemlock Photo: J. Littell Low elevation / southern mountain hemlock Photo: C. Webber Interior ponderosa pine Photo: C. Woodhouse

  4. Why an emphasis on tree growth? • Compared to biogeography, we know relatively little about long-term, 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

  5. 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

  6. CLIMET (Climate-Landscape Interactions on a Mountain Ecosystem Transect)

  7. Climate Change Highest Elevation Local climate Climate Variability Physiography Topography South North Lowest Elevation

  8. 411 cm 199 cm 219cm 115cm Quinault North (ONP) Gray Wolf South (ONP) Thornton North (NCNP) Stehekin South (NCNP) 121cm 72 cm 118cm 170cm Trout Ck. North (IPNF) Robinson South (IPNF) Park Ck. North (GNP) Belly River South (GNP)

  9. Climate Dimensions of the Sample Transect

  10. 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)

  11. Standard Chronology (mod. Z index) 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

  12. 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 • Assumed non-linear declining availability function • Estimated PET - AET = deficit • Milne et al. surplus water: PPT- ET / PPT

  13. General patterns of growth-climate correlations are similar for divisional and VIC PPT and T climate. GNP relationship stronger • PPT • (M) JJ Year-of • JA (S) Year-prior • 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

  14. 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)

  15. 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)

  16. 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

  17. 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.

  18. 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.

  19. Summary: Growth-Climate Relationships • Most frequent patterns of correlations point to combined influence of (-) temperature and (+) precipitationduring 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

  20. Spencer Wood Mike Case, Mike Tjoelker, Sarah Gobbs, Sean Hill Melissa Hornbein 2003-2004 Field Crews Alex Karpoff Greg Pederson Sam Cushman Carson Sprenger

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