Tree growth sensitivity to climate varies across a seasonal precipitation gradient

Yocom, Larissa, Ogle, Kiona, Peltier, Drew, Szejner, Paul, Liu, Yao and Monson, Russell K. (2022) Tree growth sensitivity to climate varies across a seasonal precipitation gradient. Oecologia, 198 (4). pp. 933-946. ISSN 0029-8549

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Spatial patterns of precipitation in the southwestern United States result in a complex gradient from winter-to-summer moisture dominance that influences tree growth. In response, tree growth exhibits seasonal-to-annual variability that is evident in the growth of whole tree rings, and in sub-annual sections such as earlywood and latewood. We evaluated the influence of precipitation and temperature on the growth of Pinus ponderosa trees in 11 sites in the southwestern US. Precipitation during the year of growth and the prior year accounted for about half of the climate influence on annual growth, with the other half reflecting conditions 2–4 years prior to growth, indicating that individual trees do indeed exhibit multi-year “memory” of climate. Trees in wetter sites exhibited weaker influence of past precipitation inputs, but longer memory of climatic variability. Conversely, trees in dry sites exhibited shorter memory of long-term climatic variability, but greater sensitivity to past precipitation effects. These results are consistent with the existence of complex interactions between endogenous (phenotype) effects and exogenous (climate) effects in controlling climate memory in trees. After accounting for climate, residual variability in latewood growth was negatively correlated with earlywood growth, indicating a potential tradeoff between latewood versus earlywood growth. This study provides new insights that will assist the accurate prediction of woody biomass growth and forest carbon sequestration across a southwestern US precipitation gradient.

Item Type: Article
Additional Information: Funding information: The majority of the work conducted in this study was funded by a National Science Foundation-Advances in Biological Informatics grant to K. Ogle (#1458867). P. Szejner and R. Monson acknowledge financial support from the Macrosystems Program in the Emerging Frontiers Section of the U.S. National Science Foundation (#1065790) and the Ecosystems Program in the Division of Environmental Biology (#1754430), which enabled much of the sampling and data collection. Y. Liu was partly supported by the U.S. Department of Energy contract DE-AC05-00OR22725.
Uncontrolled Keywords: Bayesian, Dendrochronology, Memory, Monsoon, Pinus ponderosa
Subjects: C100 Biology
F800 Physical and Terrestrial Geographical and Environmental Sciences
Department: Faculties > Engineering and Environment > Geography and Environmental Sciences
Depositing User: Elena Carlaw
Date Deposited: 12 May 2022 11:53
Last Modified: 17 Apr 2023 08:00

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