Climate effects on tree diameter growth: a multi-species modelling approach using permanent sample plot data in Quebec, Canada

Abstract Accurately predicting forest growth under changing climate conditions is essential for sustainable forest management and carbon accounting. Yet, many empirical growth models still lack climate sensitivity, limiting their relevance in a warming world. In this study, we leveraged a large network of permanent sample plots across Quebec, Canada, to develop climate-sensitive models of diameter increment for 29 tree species. Starting from a general model based on tree- and site-level variables, we incorporated tree-level random effects and tested three climate-related hypotheses: (H1) longer growing periods increase growth, (H2) increased atmospheric dryness reduces growth, and (H3) limited soil water availability reduces growth. For 21 species, models including climate variables significantly outperformed general and mixed-effects models. Hypothesis H1 was most frequently supported, followed by hypotheses H3 and H2. Only one species showed support for all three hypotheses simultaneously. Our findings highlight the value of integrating climate variables into empirical growth models, while also revealing limitations related to the spatial and temporal resolution of climate data. Future improvements may come from refining climate metrics and combining tree-ring and inventory data to better capture climate-growth relationships.