Abstract: This study addresses a critical gap in forest management by introducing a Universal Transfer-Response Function (UTRF) to predict Lodgepole Pine (Pinus contorta var. latifola Dougl.) maximum height under varying climate conditions in British Columbia. Using long-term provenance trial data, we developed a two-stage modeling approach: first, fitting a logistic height-age curve to estimate individual tree growth potential, and second, applying a cubic polynomial UTRF incorporating site, provenance, and climate transfer variables. The model explained approximately 62% of variation in maximum height and was used to simulate future growth under multiple climate scenarios. Results indicate that southern lodgepole pine populations will experience severe declines in height growth under warming conditions, while northern populations may benefit temporarily, reflecting a northward shift in the species’ climatic niche. Spatial predictions further highlight regions becoming unsuitable for lodgepole pine by 2100, emphasizing the urgency of climate-based seed transfer and assisted migration strategies. By integrating UTRF into operational growth and yield models, forest managers can simulate adaptive strategies to mitigate timber yield losses. This finding represents a significant advancement in climate-sensitive forestry modeling and provides a foundation for sustainable management under future climate uncertainty.

Key words: Forestry, Climate change, Genecology, Growth and yield