Responding to hurricane disruptions: salvage decisions under uncertain timber supply
| Authors: | Ian Pereira Sartorio, Bruno Kanieski da Silva, Shaun M. Tanger, Jesse Henderson, Mohammad Marufuzzaman, Yun Yang, Adam Polinko, Christine Fortuin |
| Year: | 2026 |
| Type: | Scientific Journal |
| Station: | Southern Research Station |
| DOI: | https://doi.org/10.1080/14942119.2026.2646802 |
| Source: | International Journal of Forest Engineering |
Abstract
Hurricanes are increasingly frequent and intense disturbances that cause substantial economic and ecological damage to forested landscapes worldwide. Following such events, multiple stakeholders – including timberland owners, forest management organizations, logging and transportation providers, and wood-processing mills – face urgent salvage decisions under uncertain and spatially heterogeneous timber supply conditions. This study presents a scenario-based stochastic optimization framework for post-hurricane salvage logging that explicitly accounts for uncertainty in timber volume loss and quality degradation. Using Hurricane Michael (2018) as a case study in the southeastern United States, forest inventory data, remotely sensed damage indices, species-specific yield curves, and market information are integrated into a spatial optimization model that jointly determines salvage harvest locations and wood transportation decisions. Uncertainty in salvageable supply is represented through multiple simulated damage scenarios with varying levels of sawtimber downgrade to pulpwood. The framework compares risk-neutral and risk-averse strategies, including a mean – risk formulation based on Conditional Value-at- Risk (CVaR), and evaluates sensitivity to key economic and logistical parameters. Results indicate that risk- averse and performance-stable salvage strategies reduce transportation costs and mitigate losses in timber value relative to deterministic approaches, particularly under high uncertainty in damage severity and downgrade rates. Overall, the findings demonstrate that representing post-hurricane timber supply uncertainty through scenario-based simulations and evaluating alternative downgrade and risk prefer-ences materially influence salvage location choices, transportation costs, and economic outcomes. The proposed framework provides a decision-support tool for assessing trade-offs between expected returns and downside risk across a wide range of plausible post-disturbance conditions.