Aim Climate variability is an important mediating agent of ecosystem dynamics in cold, semi-arid regions such as the mountains of western North America. Climatically sensitive tree-ring chronologies offer a means of assessing the impact of climate variability on tree growth across temporal scales of years to centuries and spatial scales of metres to subcontinents. Our goal was to bring practices from landscape ecology that highlight the impact of landscape heterogeneity on ecological pattern and processes into a dendroclimatic study that shows that the biophysical setting of target trees affects ring-width patterns.
Location This study was conducted at two sites near alpine treeline in the Sequoia National Park, USA (36°30′ 00′ N, 118°30′ 00′ W).
Methods We collected stand information and increment cores from foxtail pines (Pinus balfouriana Grev. et Balf.) for eight tree-ring chronologies in four extreme biophysical settings at two sites using proxies for soil moisture and radiation derived from a digital elevation model.
Results Biophysical setting affected forest age–class structure, with wet and bright plots showing high recruitment after 1900 ad, but had no obvious effect on immature stem density (e.g. seedlings). Biophysical setting strongly affected ring-width patterns, with wet plots having higher correlation with instrumental temperature records while dry plots correlated better with instrumental precipitation records. Ring-width chronologies from the wet plots showed strong low-frequency variability (i.e. hundreds of years) while ring-width chronologies from the dry plots showed strong variability on multidecadal scales.
Main conclusions There was a strong association between biophysical setting and age-class structure, and with ring-width patterns in foxtail pine. The mediation of ring widths by biophysical setting has the potential to further the understanding of the expression of synoptic-scale climate across rugged terrain. When combined with remotely sensed imagery, a priori GIS modelling of tree growth offers a viable means to devise first-order predictions of climatic impacts in subalpine forest dynamics and to develop flexible and powerful monitoring schemes.