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Dynamic responses of tree-ring growth to multiple dimensions of drought.

Global Change Biology 2018 November
Droughts, which are characterized by multiple dimensions including frequency, duration, severity, and onset timing, can impact tree stem radial growth profoundly. Different dimensions of drought influence tree stem radial growth independently or jointly, which makes the development of accurate predictions a formidable challenge. Measurement-based tree-ring data have obvious advantages for studying the drought responses of trees. Here, we explored the use of abundant tree-ring records for quantifying regional response patterns to key dimensions of drought. Specifically, we designed a series of regional-scaled "natural experiments," based on 357 tree-ring chronologies from Southwest USA and location-matched monthly water balance anomalies, to reveal how tree-ring responds to each dimension of drought. Our results showed that tree-ring was affected significantly more by the water balance condition in the current hydrological year than that in the prior hydrological year. Within the current hydrological year, increased drought frequency (number of dry months) and duration (maximum number of consecutive dry months) resulted in "cumulative effects" which amplified the impacts of drought on trees and reduced the drought resistance of trees. Drought events that occurred in the pregrowing seasons strongly affected subsequent tree stem radial growth. Both the onset timing and severity of drought increased "legacy effects" on tree stem radial growth, which reduced the drought resilience of trees. These results indicated that the drought impact on trees is a dynamic process: even when the total water deficits are the same, differences among the drought processes could lead to considerably different responses from trees. This study thus provides a conceptual framework and probabilistic patterns of tree-ring growth response to multiple dimensions of drought regimes, which in turn may have a wide range of implications for predictions, uncertainty assessment, and forest management.

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