Early-Warning Signals of Individual Tree Mortality Based on Annual Radial Growth

Maxime Cailleret, Vasilis Dakos, Steven Jansen, Elisabeth M. R. Robert, Tuomas Aakala, Mariano M. Amoroso, Joe A. Antos, Christof Bigler, Harald Bugmann, Marco Caccianaga, Jesus-Julio Camarero, Paolo Cherubini, Marie R. Coyea, Katarina Cufar, Adrian J. Das, Hendrik Davi, Guillermo Gea-Izquierdo, Sten Gillner, Laurel J. Haavik, Henrik HartmannAna-Maria Heres, Kevin R. Hultine, Pavel Janda, Jeffrey M. Kane, Viachelsav Kharuk, Thomas Kitzberger, Tamir Klein, Tom Levanic, Juan-Carlos Linares, Fabio Lombardi, Harri Makinen, Ilona Meszaros, Juha M. Metsaranta, Walter Oberhuber, Andreas Papadopoulos, Any Mary Petritan, Brigitte Rohner, Gabriel Sanguesa-Barreda, Jeremy M. Smith, Amanda B. Stan, Dejan B. Stojanovic, Maria-Laura Suarez, Miroslav Svoboda, Volodymyr Trotsiuk, Ricardo Villalba, Alana R. Westwood, Peter H. Wyckoff, Jordi Martinez-Vilalta

Research output: Contribution to journalArticlepeer-review

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 similar to 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.

Original languageEnglish
Article number1964
Number of pages14
JournalFrontiers in Plant Science
Volume9
DOIs
StatePublished - 8 Jan 2019

All Science Journal Classification (ASJC) codes

  • Plant Science

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