Abstract
Tree mortality is a key driver of forest dynamics and its occurrence is projected to increase in the future due to climate change. Despite recent advances in our understanding of the physiological mechanisms leading to death, we still lack robust indicators of mortality risk that could be applied at the individual tree scale. Here, we build on a previous contribution exploring the differences in growth level between trees that died and survived a given mortality event to assess whether changes in temporal autocorrelation, variance, and synchrony in time-series of annual radial growth data can be used as early warning signals of mortality risk. Taking advantage of a unique global ring-width database of 3065 dead trees and 4389 living trees growing together at 198 sites (belonging to 36 gymnosperm and angiosperm species), we analyzed temporal changes in autocorrelation, variance, and synchrony before tree death (diachronic analysis), and also compared these metrics between trees that died and trees that survived a given mortality event (synchronic analysis). Changes in autocorrelation were a poor indicator of mortality risk. However, we found a gradual increase in inter-annual growth variability and a decrease in growth synchrony in the last ∼20 years before mortality of gymnosperms, irrespective of the cause of mortality. These changes could be associated with drought-induced alterations in carbon economy and allocation patterns. In angiosperms, we did not find any consistent changes in any metric. Such lack of any signal might be explained by the relatively high capacity of angiosperms to recover after a stress-induced growth decline. Our analysis provides a robust method for estimating early-warning signals of tree mortality based on annual growth data. In addition to the frequently reported decrease in growth rates, an increase in inter-annual growth variability and a decrease in growth synchrony may be powerful predictors of gymnosperm mortality risk, but not necessarily so for angiosperms.
Highlights
Episodes of tree mortality associated with drought and heat stress have been reported in many forested biomes over the last decades (Allen et al, 2010; Hartmann et al, 2018), and are expected to increase under ongoing climate change in many regions (Allen et al, 2015)
The residual AR1 was higher than zero in the final 20-year period preceding tree death. This was mostly true for gymnosperms, and such level of positive resAR120 values was not exclusive to the end of a to detect which combinations of temporal trends in standard deviation (SD) and AR1 can be expected when growth rates gradually decrease, we generated theoretical RW time series based on simple growth models that included (i) an autocorrelation component, (ii) a long-term change in the mean, and (iii) some noise reflecting the environmental stochasticity (Supplementary Appendix E)
We found a gradual increase in inter-annual growth variability and a decrease in growth synchrony during the ∼20-year period before mortality
Summary
Episodes of tree mortality associated with drought and heat stress have been reported in many forested biomes over the last decades (Allen et al, 2010; Hartmann et al, 2018), and are expected to increase under ongoing climate change in many regions (Allen et al, 2015). Evaluating individual tree mortality risk requires reliable indicators that reveal temporal changes in tree vitality (Allen et al, 2015; Hartmann et al, 2018) Such information can be provided by physiological and anatomical data. In association with low whole-plant conductivity, reduced carbon assimilation and depletion of stored carbohydrates may occur due to the decline in stomatal conductance and leaf area, for gymnosperms (Galiano et al, 2011; Pangle et al, 2015; Adams et al, 2017). The determination of such mechanistic indicators is, costly, and temporally and spatially limited. Ring-width (RW) data are especially suitable, as they provide retrospective and long-term information about tree radial growth at an annual resolution, and can be applied effectively at an affordable cost to a large number of trees, sites, and species
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