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Predicting Current and Future Tree Diversity in the Pacific Northwest

This study examines the impacts of climate variation on tree mortality and species distribution in the Pacific Northwest. By analyzing temperature and precipitation patterns, as well as physiological models, the researchers predict changes in leaf area index and the distribution of major tree species in the region.

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Predicting Current and Future Tree Diversity in the Pacific Northwest

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  1. I R S S Predicting Current and Future Tree Diversity in the Pacific Northwest Richard Waring1 Nicholas Coops2 1 Oregon State University 2 University of British Columbia

  2. Pinyon pine in New Mexico stressed by multi-year drought & killed by bark beetles

  3. Drought-induced mortality in southern Californiaexcept along ephemeral streams

  4. Lodgepole pine killed by mt. pine beetle in British Columbia not related to drought

  5. Extensive bark beetle outbreaksover the last few decades Raffa et al. 2008, BioSci. 58:219-284

  6. Questions: I. Has climatic variation increased tree mortality? II. If so, where do we expect changes in a species’ distribution and why?

  7. Approach: Compare recent changes in temperature and precipitation patterns Translate climatic variables as they affect tree growth Determine where conditions cause stress on different species Predict future (potential) distributions of major tree species

  8. SEA TEMPERATURE AFFECTS LAND CLIMATE Pacific Decadal Oscillations warm and cool phases Pacific Decadal Oscillation assessment calibration

  9. Seasonal Changes in Precipitation (1976-2006)- (1950-1975) Spring Precip. Winter Precip. Summer Precip. Fall Precip.

  10. Seasonal Changes in Temperature (1976-2006)- (1950-1975) Winter Temp. Spring Temp. Summer Temp. Fall Temp.

  11. Use a physiologically- based model to define how seasonal variations in climate affect Douglas-fir Solar Radiation (50% PAR) Precipitation VPD Temp Canopy Interception Light absorbed canopy (APAR) Stomatal Conductance Canopy Quantum Efficiency Soil Fertility Transpiration GPP Soil Water Growth Partitioning LAI NPPA NPPB

  12. Predicted Mean Leaf Area Index 1950-1975 (Range: 1 to 9) Predicted Mean Leaf Area Index 1976-2006 (Range: 1 to 9)

  13. Predicted Change in Leaf Area Index (1976-2006)-(1950-1975) (Range:  3.0)

  14. Comparison of predicted changes in Leaf Area Index for Level 1 Ecoregion

  15. More optimum conditions Less optimum conditions Relative change in environmental constraints on Douglas-fir growth(1976 to 2006) – (1950-1975) Winter Temperature Spring Frost Fall Soil H20

  16. Principal Drivers for change in LAI (1976 to 2006) – (1950-1975)

  17. Tree species differ in their abilities to compete, based on seasonal variation in frost (FRT), available soil water (SW), humidity deficits (vpd), and temperature Size of slice = rel. importance Size of slice = rel. importance

  18. Decision tree analysis After Coops & Waring. 2010. Climatic Change (in press)

  19. Predicted range with Decision Tree Model & Mean climate 1950-75 73%  3% accuracy Recorded field records (red) Distribution of Douglas-fir General map (Little)

  20. Douglas-fir ponderosa pine lodgepole pine Predicted stressed (red) and improved areas (green) since 1950-1975 period

  21. Predicted lodgepole pine distributions Current 2020 2050 Coops, N.C. & R.H. Waring. 2010. Climatic Change (in press)

  22. Conclusions • We are in a period where sea temperatures are as warm as they have been in the last 100 years, and likely to increase. • Where our model predicts a reduction in leaf area index for Douglas-fir, an increase in tree mortality can be expected with more drought-prone species favored (e.g.,ponderosa pine). • Where an increase in leaf area index for Douglas-fir is predicted, lodgepole pine and other subalpine species are likely to be replaced in time. • Trends are predicted to continue, and to accelerate

  23. Additional Information R.H. Waring http://www.fsl.orst.edu/~waring N.C. Coops http://farpoint.forestry.ubc.ca/FP Project http://www.pnwspecieschange.info/

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