Integrating economic and ecological drivers in forest product yield forecasting: A Finnish case study

Abstract

As global climate change intensifies, sustainable forest resource management is essential for carbon storage, climate regulation, and providing forest products. This study integrates the Cobb-Douglas function with the random forest model to predict forest product yields. The Cobb-Douglas-random forest model achieves high accuracy, predicting 96 % of historical data (P < 0.001). Our analysis highlights the significant role of solar radiation (52 %) and the interaction between environmental factors (62 %) and societal factors (38 %) in forest production. While the photoperiod remains unchanged, our findings show that forest yield can be influenced by policies, especially in the face of climate change. Under different Shared Socioeconomic Pathway (SSP) scenarios, Finnish forest products remain stable under SSP126, demonstrating the benefits of stringent environmental policies. However, under SSP370 and SSP585, significant declines in forest products occur, especially in high-emission scenarios. Spatial variability in forest responses to climate change is observed, with northern Finland being more vulnerable. This study introduces an innovative model for predicting future forest product yields, essential for long-term sustainable forest management. We emphasize the importance of sustainable forest management that balances economic development with ecological protection, yet also considering region-specific contexts in Finland. This case study serves as a solid foundation for the global application of our model.