Interannual climatic suitability based on species distribution models predicts European beech growth at its southern range margin

Understanding how climatic variability influences forest growth is essential for anticipating species responses under a warming climate. Species distribution models (SDMs) are widely used to assess climatic suitability, yet they typically rely on long-term climatic averages that may hinder short-term fluctuations relevant to population dynamics. In this study, we integrated annual SDM-derived climatic suitability (hereafter, suitability) with tree-ring data to test whether interannual variation in suitability explains radial growth patterns of European beech, ( Fagus sylvatica , hereafter, beech) across its southern range margin. Occurrence data across Europe (>17 000 plots) and yearly climate layers (1979–2019) were used to estimate annual suitability with Maximum Entropy algorithm (MaxEnt). Then, these suitability estimates were related to tree growth from Mediterranean beech chronologies through hierarchical mixed-effects models. Long-term suitability showed no significant association with tree growth, but both annual suitability and within-site deviations were positively and significantly correlated with ring-width variation. These results indicate that year-to-year climatic fluctuations, rather than average climatic conditions, may modulate growth responses in marginal beech populations. Our findings highlight the importance of incorporating temporal climatic variability into niche modelling frameworks and demonstrate the potential of combining SDMs with dendroecological data to more realistically infer population performance under climate change. • SDMs reflect demographic performance beyond spatial presence/absence. • Interannual variation in climatic suitability positively predicts radial growth. • Temporal fluctuations in climatic suitability capture growth patterns overlooked by long-term climatic averages. • Integrating dendro data with SDMs enhances predictions of species performance.