LAUSR

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