Disentangling the multi-faceted growth patterns of primary Picea abies forests in the Carpathian arc

Abstract

A tree’s radial growth sequence can be thought of as an aggregate of different growth components such as age and size limitations, presence or absence of disturbance events, continuous impact of climate variability and variance induced by unknown origin. The potentially very complex growth patterns with prominent temporal and spatial variability imply that our understanding of climate-vegetation feedbacks essentially benefits from the expansion of large tree ring networks into data-poor regions, and our ability to disentangle growth constraints by comparing ring series at multiple scales. In this study, we analyze Central-Eastern Europe’s most substantial assemblage of primary Norway spruce forests found in the Carpathian arc. The vast data set, >10,000 tree-ring series, is stratified along a prominent gradient in climate response space over four separate landscapes. We integrated curve intervention detection and dendroclimatic standardization to decompose tree growth variance into climatic, disturbance and residual components to explore the behavior of the components over increasingly larger spatial hierarchies. We show that the residual variance of unknown origin is the most prominent variance in individual Carpathian spruce trees, but at larger spatial hierarchies, climate variance dominates. The variance induced by climate was further explored with common correlation analyses, growth response to extreme climate years and forward modeling of tree growth to identify leading modes of climate response, and potentially non-linear and mixed climate response patterns. We find that the climatic response of the different forest landscapes overall can be described as an asymptotic response to June and July temperatures, most likely intermixed with influence from winter precipitation. In the collection of landscapes, Southern Romania stands out as being the least temperature sensitive and most likely exhibiting the most complicated mixed temperature and moisture limitation.