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New Phytologist
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New Phytologist
Article . 2020 . Peer-reviewed
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New Phytologist
Article . 2021
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Understanding and predicting forest mortality in the western United States using long‐term forest inventory data and modeled hydraulic damage

Authors: Martin D. Venturas; Henry N. Todd; Anna T. Trugman; William R. L. Anderegg;

Understanding and predicting forest mortality in the western United States using long‐term forest inventory data and modeled hydraulic damage

Abstract

Summary Global warming is expected to exacerbate the duration and intensity of droughts in the western United States, which may lead to increased tree mortality. A prevailing proximal mechanism of drought‐induced tree mortality is hydraulic damage, but predicting tree mortality from hydraulic theory and climate data still remains a major scientific challenge. We used forest inventory data and a plant hydraulic model (HM) to address three questions: can we capture regional patterns of drought‐induced tree mortality with HM‐predicted damage thresholds; do HM metrics improve predictions of mortality across broad spatial areas; and what are the dominant controls of forest mortality when considering stand characteristics, climate metrics, and simulated hydraulic stress? We found that the amount of variance explained by models predicting mortality was limited (R2 median = 0.10, R2 range: 0.00–0.52). HM outputs, including hydraulic damage and carbon assimilation diagnostics, moderately improve mortality prediction across the western US compared with models using stand and climate predictors alone. Among factors considered, metrics of stand density and tree size tended to be some of the most critical factors explaining mortality, probably highlighting the important roles of structural overshoot, stand development, and biotic agent host selection and outbreaks in mortality patterns.

Related Organizations
Keywords

Climate, Climate Change, Forests, United States, Droughts, Trees

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
59
Top 1%
Top 10%
Top 1%
hybrid