Simulating silver fir provenance responses to climate change: A forest modelling approach in the Northern Apennines

Understanding how genetic variation within forest species influences growth responses under climate change is essential for improving the accuracy of forest models and guiding adaptive management strategies. This study models the dynamics of Italian silver fir (Abies alba) forests under varying climate change scenarios using the forest gap model FORMIND. Focusing on three distinct silver fir provenances (Western Alps, Northern Apennines, and Southern Apennines), the study simulates forest growth in the Tuscan-Emilian Apennine National Park under different representative concentration pathways (RCPs). The individual-based model FORMIND was parameterized and validated with field data for each of the provenances, demonstrating its ability to accurately reproduce key forest metrics and dynamics. Our results reveal significant differences in expected growth patterns, productivity, metabolism, and carbon storage capacity among the silver fir provenances in pure and mixed stands. In the simulations, the Northern Apennines provenance showed higher biomass production (biomass >10% ​± ​1%) and carbon uptake (net primary productivity, NPP >8% ​± ​1%) at the end of the century compared to the Western Alps provenance in the pure provenance (PP) and no regeneration scenario. Conversely, the Southern Apennines provenance showed higher biomass (biomass >5%–10%) and NPP (>15%–18%) in mixed provenance (MP) and regeneration scenarios. These results show that genetic diversity strongly affects forest growth and resilience to environmental changes. Hence, it should be included as a predictor variable in forest models. The study also demonstrates the resilience of silver fir to climatic stressors, emphasizing its potential as a robust species in multiple forest contexts. The integration of forest provenance data into the FORMIND model represents a significant advancement in forest modelling, enabling more accurate and reliable predictions under climate change scenarios. The study's findings advocate for a greater understanding and consideration of genetic diversity in forest management and conservation strategies, in support of assisted migration strategies aiming to enhance the resilience of forest ecosystems in a changing climate.