Global temperature rise and extremes accompanying drought threaten forests and their associated climatic feedbacks. Our ability to accurately simulate drought-induced forest impacts remains highly uncertain in part owing to our failure to integrate physiological measurements, regional-scale models, and dynamic global vegetation models (DGVMs). Here we show consistent predictions of widespread mortality of needleleaf evergreen trees (NET) within Southwest USA by 2100 using state-of-the-art models evaluated against empirical data sets. Experimentally, dominant Southwest USA NET species died when they fell below predawn water potential (Ψpd) thresholds (April–August mean) beyond which photosynthesis, hydraulic and stomatal conductance, and carbohydrate availability approached zero. The evaluated regional models accurately predicted NET Ψpd, and 91% of predictions (10 out of 11) exceeded mortality thresholds within the twenty-first century due to temperature rise. The independent DGVMs predicted ≥50% loss of Northern Hemisphere NET by 2100, consistent with the NET findings for Southwest USA. Notably, the global models underestimated future mortality within Southwest USA, highlighting that predictions of future mortality within global models may be underestimates. Taken together, the validated regional predictions and the global simulations predict widespread conifer loss in coming decades under projected global warming.
McDowell, N. G., et al. "Multi-scale predictions of massive conifer mortality due to chronic temperature rise." Nature Climate Change, vol. 6, no. 3, Dec. 2015. https://doi.org/10.1038/nclimate2873
McDowell, N. G., Williams, A. P., Xu, C., Pockman, W. T., Dickman, L. T., Sevanto, S., Pangle, R., Limousin, J., Plaut, J., Mackay, D. S., Ogee, J., Domec, J. C., Allen, C. D., Fisher, R. A., Jiang, X., Muss, J. D., Breshears, D. D., Rauscher, S. A., & Koven, C. (2015). Multi-scale predictions of massive conifer mortality due to chronic temperature rise. Nature Climate Change, 6(3). https://doi.org/10.1038/nclimate2873
McDowell, N. G., Williams, A. P., Xu, C., et al., "Multi-scale predictions of massive conifer mortality due to chronic temperature rise," Nature Climate Change 6, no. 3 (2015), https://doi.org/10.1038/nclimate2873
@article{osti_1492529,
author = {McDowell, N. G. and Williams, A. P. and Xu, C. and Pockman, W. T. and Dickman, L. T. and Sevanto, S. and Pangle, R. and Limousin, J. and Plaut, J. and Mackay, D. S. and others},
title = {Multi-scale predictions of massive conifer mortality due to chronic temperature rise},
annote = {Global temperature rise and extremes accompanying drought threaten forests and their associated climatic feedbacks. Our ability to accurately simulate drought-induced forest impacts remains highly uncertain in part owing to our failure to integrate physiological measurements, regional-scale models, and dynamic global vegetation models (DGVMs). Here we show consistent predictions of widespread mortality of needleleaf evergreen trees (NET) within Southwest USA by 2100 using state-of-the-art models evaluated against empirical data sets. Experimentally, dominant Southwest USA NET species died when they fell below predawn water potential (Ψpd) thresholds (April–August mean) beyond which photosynthesis, hydraulic and stomatal conductance, and carbohydrate availability approached zero. The evaluated regional models accurately predicted NET Ψpd, and 91% of predictions (10 out of 11) exceeded mortality thresholds within the twenty-first century due to temperature rise. The independent DGVMs predicted ≥50% loss of Northern Hemisphere NET by 2100, consistent with the NET findings for Southwest USA. Notably, the global models underestimated future mortality within Southwest USA, highlighting that predictions of future mortality within global models may be underestimates. Taken together, the validated regional predictions and the global simulations predict widespread conifer loss in coming decades under projected global warming.},
doi = {10.1038/nclimate2873},
url = {https://www.osti.gov/biblio/1492529},
journal = {Nature Climate Change},
issn = {ISSN 1758-678X},
number = {3},
volume = {6},
place = {United States},
publisher = {Nature Publishing Group},
year = {2015},
month = {12}}