Forecasting Variations in Profitability and Silviculture under Climate Change of Radiata Pine Plantations through Differentiable Optimization

Climate change might entail significant alterations in future forest productivity, profitability and management. In this work, we estimated the financial (Soil Expectation Value, SEV) of a set radiata pine plantations northwest Spain under climate change. We optimized silvicultural interventions using differentiable approach projected productivity machine learning model basing on climatic predictions 11 Global Models (GCMs) two Representative Concentration Pathways (RCPs). The forecasted mean SEV for was lower than current (∼22% RCP 4.5 ∼29% 6.0, with interest rate = 3%). dispersion distribution very high, alternatively forecasting increases decreases depending chosen GCM. Silvicultural optimization considering projections effectively mitigated potential economic losses due to change; however, its ability perform mitigation strongly dependent rates. conclude that region be significantly reduced change, though further research is necessary clearing uncertainties regarding high projections.