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

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.Peer reviewe

A dendroecological reconstruction of disturbance in an old-growth Fagus-Abies forest in Slovenia

The scarcity of large old-growth forests has made it challenging to quantify disturbance regimes in Central Europe. The objective of this study was to reconstruct the history of disturbance in an old-growth Fagus-Abies forest reserve in Slovenia using a dendroecological approach. We extracted cores from canopy trees blown down during a recent windthrow event and identified growth releases in the tree-ring series using boundary-line release criteria to infer past disturbances. A total of 216 release events were identified from 88 trees. Between 1790 and 1990, moderate, asynchronous release events were present in nearly every decade of the disturbance chronology, suggesting a history of frequent, low severity disturbance. However, there were also peaks in the chronology corresponding to synchronous release events in a large proportion of the trees, suggesting that less frequent, intermediate severity disturbance events played an important role in forest development. These events are likely caused from wind damage associated with local thunderstorms, which seem to occur at intervals between 20–80 years on the study site. Thus, in addition to the small-scale gap phase processes operating in the forest, the results indicate that periodic intermediate severity disturbance events are an important component of the disturbance regime in mountain forests of Central Europe.Reconstruction dendroécologique des perturbations dans une hêtraie sapinière ancienne en Slovénie. Le faible nombre de forêts anciennes suffisamment étendues rend difficile la quantification des régimes de perturbation en Europe centrale. L'objectif de cette étude est de reconstituer l'histoire de ces perturbations dans une hêtraie-sapinière ancienne mise en réserve en Slovénie en utilisant une approche dendroécologique. Des carottes ont été extraites du tronc d'arbres dominants renversés lors d'un récent chablis. Les séries temporelles de cernes ont été analysées pour identifier des périodes de relâchement de contraintes de croissance et pour en déduire l'intensité des perturbations passées. Un total de 216 évènements de relâchement de contrainte a été identifié pour 88 arbres. Entre 1790 et 1990, des évènements d'intensité modérée et asynchrones ont été détectés dans les séries chronologiques au cours de pratiquement toutes les décennies. Cela suggère une fréquence élevée de perturbations de faible intensité. Cependant, des pics d'enregistrement d'évènements synchrones ont été identifiés dans la chronologie dans une proportion importante d'arbres. Cela suggère que des perturbations de sévérité intermédiaire ont joué un rôle important dans le développement de la forêt, malgré leur plus faible fréquence. Ces évènements ont probablement été causés par des chablis provoqués par des orages locaux violents, qui semblent se produire à des intervalles de 20 à 80 ans sur le site d'étude. Les résultats montrent ainsi qu'en sus de perturbations locales de faible intensité conduisant à la formation de petites trouées, les perturbations périodiques de sévérité intermédiaire constituent une composante importante du régime de perturbations dans les montagnes en Europe centrale

Tree growth and needle dynamics of P. nigra and P. sylvestris and their response to climate and fire disturbances

201

A Machine Learning Approach To Analyzing The Relationship Between Temperatures And Multi-Proxy Tree-Ring Records

Machine learning (ML) is a widely unexplored field in dendroclimatology, but it is a powerful tool that might improve the accuracy of climate reconstructions. In this paper, different ML algorithms are compared to climate reconstruction from tree-ring proxies. The algorithms considered are multiple linear regression (MLR), artificial neural networks (ANN), model trees (MT), bagging of model trees (BMT), and random forests of regression trees (RF). April-May mean temperature at a Quercus robur stand in Slovenia is predicted with mean vessel area (MVA, correlation coefficient with April-May mean temperature, r = 0.70, p 0.05 (ns)) chronologies. The predictive performance of ML algorithms was estimated by 3-fold cross-validation repeated 100 times. In both spring and summer temperature models, BMT performed best respectively in 62% and 52% of the 100 repetitions. The second-best method was ANN. Although BMT gave the best validation results, the differences in the models' performances were minor. We therefore recommend always comparing different ML regression techniques and selecting the optimal one for applications in dendroclimatology.This item is part of the Tree-Ring Research (formerly Tree-Ring Bulletin) archive. For more information about this peer-reviewed scholarly journal, please email the Editor of Tree-Ring Research at [email protected]

Pervasive decreases in living vegetation carbon turnover time across forest climate zones

Forests play a major role in the global carbon cycle. Previous studies on the capacity of forests to sequester atmospheric CO2 have mostly focused on carbon uptake, but the roles of carbon turnover time and its spatiotemporal changes remain poorly understood. Here, we used long-term inventory data (1955 to 2018) from 695 mature forest plots to quantify temporal trends in living vegetation carbon turnover time across tropical, temperate, and cold climate zones, and compared plot data to 8 Earth system models (ESMs). Long-term plots consistently showed decreases in living vegetation carbon turnover time, likely driven by increased tree mortality across all major climate zones. Changes in living vegetation carbon turnover time were negatively correlated with CO2 enrichment in both forest plot data and ESM simulations. However, plot-based correlations between living vegetation carbon turnover time and climate drivers such as precipitation and temperature diverged from those of ESM simulations. Our analyses suggest that forest carbon sinks are likely to be constrained by a decrease in living vegetation carbon turnover time, and accurate projections of forest carbon sink dynamics will require an improved representation of tree mortality processes and their sensitivity to climate in ESMs

Site- and species-specific responses of forest growth to climate across the European continent

International audienc

Forest condition and environmental drivers in Europe: Recent evidence from selected studies

202

Pervasive decreases in living vegetation carbon turnover time across forest climate zones

Forests play a major role in the global carbon cycle. Previous studies on the capacity of forests to sequester atmospheric CO2 have mostly focused on carbon uptake, but the roles of carbon turnover time and its spatiotemporal changes remain poorly understood. Here, we used long-term inventory data (1955 to 2018) from 695 mature forest plots to quantify temporal trends in living vegetation carbon turnover time across tropical, temperate, and cold climate zones, and compared plot data to 8 Earth system models (ESMs). Long-term plots consistently showed decreases in living vegetation carbon turnover time, likely driven by increased tree mortality across all major climate zones. Changes in living vegetation carbon turnover time were negatively correlated with CO2 enrichment in both forest plot data and ESM simulations. However, plot-based correlations between living vegetation carbon turnover time and climate drivers such as precipitation and temperature diverged from those of ESM simulations. Our analyses suggest that forest carbon sinks are likely to be constrained by a decrease in living vegetation carbon turnover time, and accurate projections of forest carbon sink dynamics will require an improved representation of tree mortality processes and their sensitivity to climate in ESMs