Simulated and predicted responses of tree stem radial growth to climate change—A case study in semi-arid north central China

Abstract

Precise knowledge how tree growth will respond to future climate change is essential for the adapted management of forest ecosystems. By conducting sensitivity tests, tree-ring process-based cambial growth models can provide an innovative way to better understand wood formation under different climate change scenarios. As a case study in semi-arid north central China, we used artificially increased or decreased daily climatic data as input to the Vaganov-Shashkin dynamic growth model to investigate the response of wood formation to climatic change. By calibrating the tree-ring model using daily climate data over the period 1951–2010, we found that 81% of radial growth was driven by soil moisture, while 13% of growth was controlled by temperature. During the main growing season June–August, significant differences in the integral growth rate occurred after changing precipitation by ± 30% or by decreasing temperature by 3.0°C (p< 0.05). However, increasing temperature showed only modest effects on tree radial growth rate. During the past 60 years, a significant advancement of the starting dates of growth was detected, whereby non-significant variability was found for the ending dates of growth. Contemporaneously, the effect of previous winter temperature (previous December to current January) on cambial growth initiation declined after 1980. Significant differences in the growth onset dates only occurred when temperature was reduced by 4.5 °C or increased by 5.5 °C. Moreover, both the onset and ending dates of growth in the study region were more sensitive to cooling rather than to warming. If temperature will increase by 2°C and precipitation will increase by 30% at the end of this century as predicted by some Earth system models, tree radial growth might increase by 19% in the study region, compared to the average during the period 1952–2010. Consequently, tree stem radial growth is expected to increase under a warming and wetting climatic scenario, but will decrease under drying conditions.