Significant mean and extreme climate sensitivity of Norway spruce and silver fir at mid-elevation mesic sites in the Alps.

Abstract

Climate forcing is the major abiotic driver for forest ecosystem functioning and thus significantly affects the role of forests within the global carbon cycle and related ecosystem services. Annual radial increments of trees are probably the most valuable source of information to link tree growth and climate at long-term time scales, and have been used in a wide variety of investigations worldwide. However, especially in mountainous areas, tree-ring studies have focused on extreme environments where the climate sensitivity is perhaps greatest but are necessarily a biased representation of the forests within a region. We used tree-ring analyses to study two of the most important tree species growing in the Alps: Norway spruce (Picea abies) and silver fir (Abies alba). We developed tree-ring chronologies from 13 mesic mid-elevation sites (203 trees) and then compared them to monthly temperature and precipitation data for the period 1846-1995. Correlation functions, principal component analysis and fuzzy C-means clustering were applied to 1) assess the climate/growth relationships and their stationarity and consistency over time, and 2) extract common modes of variability in the species responses to mean and extreme climate variability. Our results highlight a clear, time-stable, and species-specific response to mean climate conditions. However, during the previous-year's growing season, which shows the strongest correlations, the primary difference between species is in their response to extreme events, not mean conditions. Mesic sites at mid-altitude are commonly underrepresented in tree-ring research; we showed that strong climatic controls of growth may exist even in those areas. Extreme climatic events may play a key role in defining the species-specific responses on climatic sensitivity and, with a global change perspective, specific divergent responses are likely to occur even where current conditions are less limited.