
handle: 20.500.12831/25940
This study presents a novel, structured optimization approach for incorporating multiple ecosystem services (ES) into long-term strategic and tactical forest management planning. We provide a new and improved framework for forest planning based on ecosystem values of education, aesthetics, cultural heritage, recreation, carbon, water regulation, and water supply. First, the suitability values of seven ecosystem services (ES) were estimated to produce timber harvest and store carbon under fifty potential treatment schedules over a 100-year planning horizon. Then optimization was applied to maximize future utility values derived from values of ES that can be developed with treatment schedules and using the weights of the Sustainable Development Goals (SDG). Finally, the model defined ES functions that were weight-adjusted to select a successful scenario. Thus, we demonstrated that our approach could generate the optimal future suitability value of ES for long-term forest planning compared to the current value of ES. The results showed that the ES that is most affected when harvest demand and harvest flow constraints change is carbon. The value of other ES did not change when scheduled timber volume changed, and as a result we suggest that standing volume and growth increment be considered as criteria used to determine the future value of other ES. We found that the development of suitable value-effective management strategies for securing forest ES values in future stand developments was possible while also achieving other goals and while also being constrained by operational considerations. Our study therefore contributes to ongoing debates about the management of ES.
forest harvest scheduling, mixed-integer programming, treatment schedules, ecosystem services, ecosystem services, forest harvest scheduling, optimization, treatment schedules, mixed-integer programming, optimization
forest harvest scheduling, mixed-integer programming, treatment schedules, ecosystem services, ecosystem services, forest harvest scheduling, optimization, treatment schedules, mixed-integer programming, optimization
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