1. New lines in tree ring research
- Author
-
Pellizzari, Elena
- Subjects
juniper ,dendrochronology, climate, juniper, wood anatomy, conifer ,dendrochronology ,wood anatomy ,conifer ,Settore AGR/05 - Assestamento Forestale e Selvicoltura ,AGR/05 Assestamento forestale e selvicoltura ,climate - Abstract
Natural archives, and tree-rings in particular, are fundamental tools to investigate on pre-instrumental climate variability. Tree-ring research, indeed, covers a wide field of applications, however several woody species are still overlooked and investigating just at yearly resolution, we might miss important intra-annual information. To fill these gaps, the main objective of this thesis is to undertake new lines in tree-ring research testing i) the dendrochronological potential of a marginal species to detect different climatic signal respect the usual tree species and ii) a quantitative wood anatomy approach to investigate whether with multiple cell traits is possible to extract information not visible at annual level in tree-ring series. With the new species, the common juniper (Juniperus communis, L.), I found a clear winter precipitation signal in ring-width series in the Alps, and a decoupling in the tree-ring to climate responses and growth between trees and shrubs across all the biomes investigated (Mediterranean, Alpine and Polar). With wood anatomy, I assessed the importance to use several related proxies as a diagnostic tool to detect hydraulic deterioration and mortality due to drought stress in Scots pine (Pinus sylvestris L.) and Silver fir (Abies alba) in Spain. In addition, at high latitudes, still on Scots pine I was built a 1000-year long chronology with anatomical parameters which could permit to investigate long-term temperature fluctuations. This work highlights the importance to use different species and different approaches to extract new information out of the tree-ring series. These first analysis show the possibility to reconstruct winter precipitation in the Alps and to adopt anatomical data as a surrogate of densitometric measurements or as a valid diagnostic tool for a retrospective assessment of trees health. Prediction on the future status of our forests would benefit from such an information.
- Published
- 2017