Tree species and individual tree lifespan is a fundamental yet understudied ecological pattern crucial to determine forest maturity, functioning, and carbon sink capacity. The timescale of forest demographics, spanning centuries to millennia, makes the study of maximum tree longevity methodologically challenging. As a consequence, the most relevant factors for the evolution of old-living specie and the emergence of old individuals within-species remains largely unstudied. Theories, such as the relationship between metabolic rate and longevity (or ‘live fast, die young’ hypothesis), have been proposed, but we still lack large-scale, long-term, multi-species assessments of tree longevity to support these efforts. Here, we used the largest tree-ring database, the International Tree Ring Data Bank, to investigate the relationship between maximum tree age and environment. This database is ideal for the study of longevity thanks to the keen interest of dendrochronologists on old trees. We constructed random forest and structural equation models for two longevity variables: (i) maximum age, linked to the evolution of long-lived species; and (ii) species-normalized maximum age, related to the maximum age of individuals within each species. We included both macroenvironment (climate, disturbances, productivity, diversity, density, and stability), and internal (relative growth, competition, and size) variables in our models.
Results/Conclusions
Our models explained a large fraction of the variability in longevity between species, suggesting an approximately equal role of macroenvironment and internal factors on species maximum longevity, macroenvironment explaining roughly 45% of the variance. Extrapolating this model highlighted global locations with high potential for hosting long-lived species, which may deserve further dendrochronological exploration. Elevation, precipitation seasonality, and minimum temperature were the most relevant variables for the model.
Individuals older than their species’ averages were more complex to model, resulting in much lower predictive ability using only macroclimate, and suggesting a stronger role of local conditions and variable interactions. Structural equation models suggested that maximum longevity within-species is influenced by a complex interaction between temperature, seasonality, maximum size (defined by the ecosystems’ productivity), and human influence.
This represent the first attempt at modelling tree maximum longevity at large-scale and across species, hopefully improving our understanding of the response of longevity to future environmental change. If ecosystem productivity and minimum temperatures increase in temperate areas, this may result in a rise in maximum longevity in multiple species and thus enhanced carbon sink capacity. However, increasing human and natural disturbances, and changes in forest density, can counteract this potential outcome.