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Abstract The timing and intensity of precipitation varies from year‐to‐year and is expected to change in the future. Assessing the impacts of this moisture delivery variability on tree growth is important both for future forest health and for our interpretation of pre‐instrumental tree‐ring records. Here, we used the Vaganov‐Shashkin model to investigate how changes in precipitation delivery impact tree growth at five sites representing four species in two North American river basins with high precipitation variability but different seasonal cycles. Evenly distributed precipitation increased tree growth in the Lower Sacramento watershed, while the water‐limited South Platte benefited from concentrated precipitation early in the growing season. Although most experimental simulations retained the pattern of high‐ and low‐growth years, tree growth was reduced with fewer, more intense precipitation events, which could affect interpretation of past climate extremes. Under the RCP4.5 scenario, projected warming offset the potential benefits of increased precipitation on tree growth.
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This content will become publicly available on July 1, 2026
Identifying the Climate Conditions Associated With Extreme Growth States in Trees Across the Western United States
ABSTRACT Climate extremes—e.g., drought, atmospheric rivers, heat waves—are increasing in severity and frequency across the western United States of America (USA). Tree‐ring widths reflect the concurrent and legacy effects of such climate extremes, yet our ability to predict extreme tree growth is often poor. Could tree‐ring data themselves identify the most important climate variables driving extreme low‐ and high‐growth states? How does the importance of these climate drivers differ across species and time? To address these questions, we explored the spatial synchrony of extreme low‐ and high‐growth years, the symmetry of climate effects on the probability of low‐ and high‐growth years, and how climate drivers of extreme growth vary across tree species. We compiled ring widths for seven species (four gymnosperms and three angiosperms) from 604 sites in the western USA and classified each annual ring as representing extreme low, extreme high, or nominal growth. We used classification random forest (RF) models to evaluate the importance of 30 seasonal climate variables for predicting extreme growth, including precipitation, temperature, and vapor pressure deficit (VPD) during and up to four years prior to ring formation. For four species (three gymnosperms, one angiosperm) for which climate was predictive of growth, the RF models correctly classified 89%–98% and 80%–95% of low‐ and high‐growth years, respectively. For these species, asymmetric climate responses dominated. Current‐year winter hydroclimate (precipitation and VPD) was most important for predicting low growth, but prediction of high growth required multiple years of favorable moisture conditions, and the occurrence of low‐growth years was more synchronous across space than high‐growth years. Summer climate and temperature (regardless of season) were only weakly predictive of growth extremes. Our results motivate ecologically relevant definitions of drought such that current winter moisture stress exerts a dominant role in governing growth reductions in multiple tree species broadly distributed across the western USA.
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- Award ID(s):
- 2213599
- PAR ID:
- 10616991
- Publisher / Repository:
- Wiley
- Date Published:
- Journal Name:
- Global Change Biology
- Volume:
- 31
- Issue:
- 7
- ISSN:
- 1354-1013
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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