Abstract
The year-to-year variability of precipitation has significant consequences for water management and forest health. “Whiplash” describes an extreme mode of this variability in which hydroclimate switches abruptly between wet and dry conditions. In this study, a pool of total-ring-width indices from five conifer species (Abies magnifica, Juniperus grandis, Pinus ponderosa, Pinus jeffreyi, and Tsuga mertensiana) in the Sierra Nevada is used to develop reconstructions of water-year precipitation using stepwise linear regression on lagged chronologies, and the reconstructions are analyzed for their ability to track whiplash events. A nonparametric approach is introduced to statistically classify positive and negative events, and the success of matching observed events with the reconstructions is evaluated using a hypergeometric test. Results suggest that reconstructions can effectively track whiplash events, but that tracking ability differs among species and sites. Although negative (dry-to-wet) events (1921–1989) are generally tracked more consistently than positive events, Tsuga stands out for strong tracking of positive events. Tracking ability shows no clear relationship to variance explained by reconstructions, suggesting that efforts to extend whiplash records with tree-ring data should consider optimizing reconstruction models for the whiplash signal.
Original language | English (US) |
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Article number | 12 |
Journal | Environments - MDPI |
Volume | 10 |
Issue number | 1 |
DOIs | |
State | Published - Jan 2023 |
Keywords
- Sierra Nevada
- climate variability
- dendroclimatology
- reconstruction
- tree rings
ASJC Scopus subject areas
- Ecology, Evolution, Behavior and Systematics
- Renewable Energy, Sustainability and the Environment
- General Environmental Science