Response of radial growth to climate change for Larix olgensis along an altitudinal gradient on the eastern slope of Changbai Mountain, Northeast China

Abstract

Aims: To further understand the sensitivity of tree growth to climate change and its variation with altitude, particularly the growth-climate relationship near the timberline, the radial growth of Larix olgensis in an oldgrowth forest along an altitudinal gradient on the eastern slope of Changbai Mountain was investigated. Methods: The relationships between climate factors and tree-ring index were determined using bootstrapped response functions analysis with the software DENDROCLIM2002. Redundancy analysis, a multivariate "direct" gradient analysis, and its ordination axes were constrained to represent linear combinations with meteorological elements. The analysis was used to clarify the relationship between tree-ring width indexes at different elevations and climate factors during the period 1959-2009. Important findings: Results indicated: (1) Tree ring chronologies from high altitudes were more superior than other samples in terms of growth-climate relationship, revealing that trees at high altitudes are more sensitive to climate variation than at low sites, (2) Tree growth was mainly affected by temperatures of from before and through growing season in previous year, especially in June and August. In comparison, tree growth in the low elevation was regulated by the combination of precipitation of August and Palmer drought severity index (PDSI) of September in current year, (3) Trees growing below timberline appeared to be more sensitive to climate warming; small extents of habitat heterogeneity or disturbance events beyond timberline may have masked the response, hence the optimal sites for examining growth trends as a function of climate variation are considered to be just below timberline, and (4) Redundancy analysis between the three chronologies and climate factors showed the same results as that of the correlation analysis and response function analysis, and this is in support of previous conclusion that redundancy analysis is also effective in quantifying the relationship between tree-ring indexes and climate factors.