Pattern & Process of Tree Mortality Waves in the Mountains of the Southwestern United States [Alison Macalady]
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Pattern & Process of Tree Mortality Waves in the Mountains of the Southwestern United States. Presented by Alison Macalady at the "Perth II: Global Change and the World's Mountains" conference in Perth, Scotland in September 2010.
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Pattern & Process of Tree Mortality Waves in the Mountains of the Southwestern United States [Alison Macalady]
- 1. Pattern & Process of Tree Mortality Waves in the Mountains of the Southwestern United States Alison Macalady1 & Harald Bugmann2,1 1 Laboratory of Tree-Ring Research, University of Arizona 2 Forest Ecology, ETH Zürich, Switzerland Photo: Craig Allen
- 3. Mortality in the 1950s and 2000s 1950s 2000s Allen and Breshears (1998), PNAS Breshears et al. (2005), PNAS
- 4. Mortality mechanisms McDowell et al. (2008), New Phyto
- 5. Growth-mortality models 1 Mortality Probability ? 0 Index based on radial growth CCR >80%, (e.g. Bigler & Bugmann 2004, Ecol Appl) – growth level over past few years – growth trend over past years to decades – growth sensitivity
- 6. Research questions Can the probability of piñon mortality under drought be accurately modeled using indices derived from diameter growth? What do growth-mortality models reveal about the drivers of tree mortality through space and time?
- 7. Field sites
- 9. Tree growth – typical patterns Large Low growth SEV 2000s release/recovery before death of L trees! Divergence of L TRP 2000s and D trees incited by 1950s drought
- 10. Fitting mortality models: one site Sevilleta, 1950s Internal validation: 60% fitting, 40% testing 500 simulations
- 11. Fitting mortality models: all sites Site/period Variable AU ROC CCR mean SEV 1950s 0.89 78.7% sensitivity 50 mean BNM 1950s 0.92 82.0% sensitivity 25 recent SEV 2000s 0.83 75.3% growth 3 BNM 2000s – – – growth TRP 2000s 0.67 59.6% difference 15
- 12. Validating mortality models Calibration data [shown is CCR] Validation SEV 1950s BNM 1950s SEV 2000s SEV 1950s – 73.1 77.4 BNM 1950s 77.4 – 60.0 SEV 2000s 55.9 61.7 – BNM 2000s 31.6 16.7 14.3 TRP 2000s 53.4 55.9 52.5
- 13. What’s going on? High model accuracies associated with 1950’s and SEV 2000’s data reflect a chronic stress signal associated with mortality risk •Best predictors reflect the resource status of the trees over different time periods. •Supports carbon starvation mechanism of mortality Lack of fit in N 2000’s models suggests other processes. •Acute drought stress •Increased temps driving accelerated bark beetle/fungi dynamics? •Carbon allocation to defensive compounds (Kane and Kolb 2010, Oikos)?
- 14. Conclusions Strong influence of acute drought stress and/or bark beetle/fungi dynamics at northern sites in the 2000’s Differences in space and time an early indicator of global change? Challenges of predicting mortality under drought
- 15. Acknowledgements… Acknowledgements Craig Allen, Julio Betancourt, Tom Swetnam, Dave Breshears, Kay Beeley, Collin Haffey, Greg Pederson, Derek Murrow, Chris Baisan, Rex Adams, Alex Arizpe, Christof Bigler Financial support Science Foundation Arizona, US DOE GREF (AM) ETH Zürich, UA Lab. Tree-Ring Research, Haury Fellowship (HB)