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Predicting Current and Future Tree Diversity in the Pacific Northwest I R S S Richard Waring 1 Nicholas Coops 2 1 Oregon State University 2 University.

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Presentation on theme: "Predicting Current and Future Tree Diversity in the Pacific Northwest I R S S Richard Waring 1 Nicholas Coops 2 1 Oregon State University 2 University."— Presentation transcript:

1 Predicting Current and Future Tree Diversity in the Pacific Northwest I R S S Richard Waring 1 Nicholas Coops 2 1 Oregon State University 2 University of British Columbia Richard Waring 1 Nicholas Coops 2 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 California except along ephemeral streams

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

5 Extensive bark beetle outbreaks over 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 Pacific Decadal Oscillation Pacific Decadal Oscillations warm and cool phases calibration assessment SEA TEMPERATURE AFFECTS LAND CLIMATE

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

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

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

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 Relative change in environmental constraints on Douglas-fir growth (1976 to 2006) – (1950-1975) Spring Frost Fall Soil H 2 0Winter Temperature More optimum conditions Less optimum conditions

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

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

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

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

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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