1. NADEF 2007 Winter Temperatures Influence Annual Growth of Conifers in the Great Smoky Mountains, Tennessee, USA Group Leader: Henri Grissino-Mayer Participants: Bill Brenton, Pete Clark, Susan Mortenson, Mark Spond, Park Williams

3. Objectives Evaluate differential climate response between two pine species in GSMNPEvaluate differential climate response between two pine species in GSMNP Shortleaf Pine (Pinus echinata P. Miller)Shortleaf Pine (Pinus echinata P. Miller) Table Mountain Pine (Pinus pungens Lamb.)Table Mountain Pine (Pinus pungens Lamb.) Evaluate the effectiveness of different standardization techniquesEvaluate the effectiveness of different standardization techniques Evaluate the influence of oceanic-atmosphere teleconnections on the growth of pine speciesEvaluate the influence of oceanic-atmosphere teleconnections on the growth of pine species

4. Tennessee Table Mountain Pine Shortleaf Pine at Gold Mine Trail Table Mountain Pine

5. Shortleaf Pine at Gold Mine Trail Table Mountain Pine Low elevation (400 – 650 m) Low elevation (400 – 650 m) Located on dry western section of GSMNP Located on dry western section of GSMNP Some resident tree species: shortleaf pine, red maple, eastern white pine, chestnut oak Some resident tree species: shortleaf pine, red maple, eastern white pine, chestnut oak Xeric, nutrient poor soils Xeric, nutrient poor soils Significant damage from southern pine beetle infestation. Significant damage from southern pine beetle infestation. Changes in species composition and stand density (anthropogenic fire suppression) Changes in species composition and stand density (anthropogenic fire suppression) Mid-elevation (800 – 1200 m) Mid-elevation (800 – 1200 m) Located on dry, south-facing slopes and ridges Located on dry, south-facing slopes and ridges Habitat is dependent on periodic surface fires Habitat is dependent on periodic surface fires Some resident tree species: red maple, pitch pine, and black gum Some resident tree species: red maple, pitch pine, and black gum Site Description

8. Climograph of Tennessee Climate Eastern Division

9. Methods Sampling and Chronology Development Established PlotsEstablished Plots Sampled all trees within plotsSampled all trees within plots Targeted trees exhibiting longevityTargeted trees exhibiting longevity Remnant wood collected when availableRemnant wood collected when available Standard processing procedures (Stokes and Smiley 1968)Standard processing procedures (Stokes and Smiley 1968) Crossdate: Skeleton plot and COFECHACrossdate: Skeleton plot and COFECHA Cross-checked against other regional chronologiesCross-checked against other regional chronologies Standardization using ARSTANStandardization using ARSTAN Negative Exponential / LinearNegative Exponential / Linear

10. Crossdating Statistics Number of series (radii): 99 Number of trees 64 Master series: 1729 - 2006 (278 yrs) Series intercorrelation: 0.526 Average mean sensitivity: 0.268 Number of series (radii) : 61 Number of trees: 46 Master series: 1837 - 2001 (165 yrs) Series intercorrelation: 0.538 Average mean sensitivity: 0.258 Average mean sensitivity: 0.258 Shortleaf Pine Table Mountain Pine

11. Indices Table Mountain Pine Standard Chronology (STD) (1837 – 2001) Shortleaf Pine Standard Chronology (STD) (1729 – 2006) Sample Depth

12. Methods Climate Response Tennessee Eastern Climate DivisionTennessee Eastern Climate Division Beginning 1930Beginning 1930 Palmer Drought Severity Index (PDSI)Palmer Drought Severity Index (PDSI) TemperatureTemperature PrecipitationPrecipitation Correlation AnalysisCorrelation Analysis Between Monthly Climate Data and Pine ChronologiesBetween Monthly Climate Data and Pine Chronologies Previous May – Current December (20 Months)Previous May – Current December (20 Months)

13. Correlation coefficients between Shortleaf Pine Standard Chronology and Monthly Climate R Values Months 0.5 0.42 * p < 0.05** p < 0.01*** p < 0.001

14. Correlation coefficients between Table Mountain Pine Standard Chronology and Monthly Climate ** *** ** * * * * * * * * * * * R Values Months 0.42 0.37 * p < 0.05** p < 0.01*** p < 0.001

15. Correlation strength of 158 ITRDB Tree-ring Chronologies versus Shortleaf Pine Standard Chronology Shortleaf Pine Random Local Chronology ( White Oak )

16. Methods Standardization Trials Evaluated twelve standardization techniques: Spline lengths of 10,15, 25, 50,100, 200, 300, 400 years Linear, Horizontal Line, 50% Freq. Response of 67% Series Length Negative Exponential Curve / Linear Detrending

17. Correlation coefficients for Shortleaf Pine Standardization trials January TemperatureFebruary Temperature * * * ** * *** ** *** ** *** ** *** ** *** ** *** Correlation Coefficients Trials * p < 0.05** p < 0.01*** p < 0.001

18. Does tree growth tell us about non-local temperature? Monthly Correlations between Shortleaf Pine STD Chronology and United States Land Temperatures

19. During which range of months does temperature effect tree rings the most? Data taken from: Newport Weather Station, TN

20. Narrow Ring Widths Wide Ring Widths Winter Temperature (Jan + Feb) Anomalies

21. Does tree growth tell us about anything else besides temperature? Monthly Correlations between Ring-widths and Sea Level Pressure

22. Winter Sea Level Pressure (Jan + Feb) Narrow Ring Widths Wide Ring Widths Pa

23. Winter Sea Level Pressure (Jan + Feb) Anomalies Narrowest Ring Widths Widest Ring Widths

24. Winter Sea Surface Temperature (Jan + Feb) Anomalies Narrow Ring Widths Wide Ring Widths

25. Correlation coefficients for Shortleaf Pine STD with select Teleconnections ** * * * ** * ** * * *** ** *** * * p < 0.05** p < 0.01*** p < 0.001 r Value Month * *

26. *** * * * * * * * * * Correlation coefficients for the Table Mountain Pine STD with select Teleconnections * p < 0.05** p < 0.01*** p < 0.001 r Value Month

27. Fig.: (a) Shortleaf Pine STD. (b) The wavelet power spectrum. The contour levels are chosen so that 75%, 50%, 25%, and 5% of the wavelet power is above each level, respectively. (c) The global wavelet power spectrum.

28. Fig.: (a) Fall Sea Surface Temperature Anomalies (1856 – 1991). (b) The wavelet power spectrum. The contour levels are chosen so that 75%, 50%, 25%, and 5% of the wavelet power is above each level, respectively. (c) The global wavelet power spectrum.

29. Fig. 1: (a) Table Mountain Pine STD. (b) The wavelet power spectrum. The contour levels are chosen so that 75%, 50%, 25%, and 5% of the wavelet power is above each level, respectively. (c) The global wavelet power spectrum.

30. Year Temperature (F) Winter Temperature (Jan + Feb) Calibration using Shortleaf Pine Standard Chronology Predicted Jan + Feb Temps = (10.01927 x Index)+29.24597 r 2 = 0.33, F = 36.16, p < 0.0001

31. Year Temperature (F) Winter Temperature (Jan + Feb) Reconstruction using Shortleaf Pine Standard Chronology 1729 - 2006

32. Acknowledgments Thanks to: Jim Speer, Hank, Lisa and Jess, Dr. Chuckles, Stephen, Muffin, Le Paris, IGA, All NADEF Participants (we have our best eye on you…) Special thanks to GSM Tremont Institute and all of the Funding agencies for supporting NADEF