Growth responses to climate in a multi-species tree-ring network in the Western Carpathian Tatra Mountains, Poland and Slovakia

We analyzed growth responses to climate of 24 tree-ring width and four maximum latewood density chronologies from the greater Tatra region in Poland and Slovakia. This network comprises 1183 ring-width and 153 density measurement series from four conifer species (Picea abies (L.) Karst., Larix decidua Mill., Abies alba (L.) Karst., and Pinus mugo (L.)) between 800 and 1550 m a.s.l. Individual spline detrending was used to retain annual to multi-decadal scale climate information in the data. Twentieth century temperature and precipitation data frorn 16 grid-boxes covering the 48-50 degrees N and 19-21 degrees E region were used for comparison. The network was analyzed to assess growth responses to climate as a function of species, elevation, parameter, frequency and site ecology. Twenty ring-width chronologies significantly correlated (P < 0.05) with June-July temperatures, whereas the latewood density chronologies were correlated with the April-September temperatures. Climatic effects of the previous-year summer generally did not significantly influence ring formation, whereas site elevation and frequency of growth variations (i.e., inter-annual and decadal) were significant variables in explaining growth response to climate. Response to precipitation increased with decreasing elevation. Correlations between summer temperatures and annual growth rates were lower for Larix decidua than for Picea abies. Principal component analysis identified five dominant eigenvectors that express somewhat contrasting climatic signals. The first principal component contained highest loadings from I I Picea abies ring-width chronologies and one Pinus mugo ring-width chronology and explained 42% of the network's variance. The mean of these 12 high-elevation chronologies was significantly correlated at 0.62 with June-July temperatures, whereas the mean of three latewood density chronologies, which loaded most strongly on the fourth principal component, significantly correlated at 0.69 with April-September temperatures (P < 0.001 over the 1901-2002 period in both cases). These groupings allow for a robust estimation of June-July (1661-2004) and April-September (1709-2004) temperatures, respectively. Comparison with reconstructions from the Alps and Central Europe supports the general rule of the dominant influence of growing season temperature on high-elevation forest growth.