Understanding tree growth in relation to environmental conditions is essential, particularly in the context of climate change, where rising temperatures, frequent droughts, and disturbances threaten forest health and productivity. This study uses high-resolution data from four intensively monitored Picea abies stands in Austria (2010–2020), with dendrometers recording hourly stem increments on 10 trees per site, allowing for detailed analysis of growth responses to environmental changes. For this purpose we tested dierent generalized additive mixed models (GAMs) using environmental data collected on site. The best model consisted of combinations of soil moisture (SM) and soil temperature (ST) data. Furthermore we analyzed how the relationships established differ for three different times during the growing season. We found that high SM consistently had a positive effect on tree growth, wheras the effect of ST varied depending on the timing. Our findings underscore the importance ofmonitoring soil conditions, particularly for species like Picea abies, which are known for their sensitivity to environmental changes due to their shallow rooting systems and vulnerability to drought. Keywords: dendrometer, tree growth, soil moisture, soil temperature, generalized additive mixed models
