Abstract
High-resolution carbon isotope ratio (δ13C) measurements of tree rings have the potential to provide seasonal environmental information. However, due to the complexity of the wood formation processes, the reliability of this method for intra-seasonal reconstruction of growing conditions remains unclear. We therefore investigated the intra-annual variation of δ13C in tree rings of three conifer species (Pinus sylvestris L., Picea abies (L.) H. Karst., Abies alba Mill.) across sites from the Swiss Alps to assess their response to seasonal variation of soil water potential (SWP) and vapour pressure deficit (VPD). Intra-annual δ13C values at a resolution of 10 points per year were assessed using laser-ablation isotope-ratio mass spectrometry. Seasonal δ13C patterns were analysed for synchronicity across trees and species, and their correlation with on-site environmental variables was used to determine the driving factors of δ13C, to reconstruct growing-season dynamics, and to estimate the timings of the growth dynamics and the allocation of carbon to xylem formation. The δ13C patterns showed high synchronicity between species, with characteristic maxima in wet and dry years occurring in the middle of the ring and at the end of the ring, respectively. Seasonal δ13C variations reliably reflected atmospheric dryness. Higher than normal soil dryness hindered the integration of further fresh assimilates into the xylem, thus allowing the identification of species- and site-specific threshold conditions that disrupt wood formation. The δ13C of Scots pine shows the strongest correlations with VPD and SWP, making it an excellent indicator of environmental variability. Silver fir appeared to integrate carbon into xylem structural material over a longer season than the other conifers, whilst Norway spruce shows more plastic, site-specific responses to environmental conditions. In conclusion, we identify how atmospheric and soil drought jointly impact tree growth and intra-annual δ13C patterns across conifer species, offering valuable insights for climate reconstructions and wider applications in forest dynamics.