Abstract

Maritime pine (Pinus pinaster Ait) is a very important forest species in Portugal. Nevertheless, both revenues and timber flows from the pine forests are substantially impacted by forest fires. We present a methodology for integrating fire risk in Maritime pine stand-level management optimization in Portugal. The objective is to determine the optimal prescription for a stand where fire risk is related to its structure and fuel load. The study optimizes the thinning treatments and the rotation length, as well as the fuel treatment schedule, i.e., reduction of understory cover during the rotation. Two components of wildfire risk—occurrence and damage—are considered. Fire damage was treated as an endogenous factor depending on the stand management schedule while fire occurrence was considered exogenous. A preliminary model that relates the expected loss to stand basal area, mean tree diameter and fire severity was used for this purpose. The article demonstrates how a deterministic stand-level growth and yield model may be combined with wildfire occurrence and damage models to optimize stand management. The Hooke-Jeeves direct search method was used to find the optimal prescription. In addition, population-based direct search methods (e.g. differential evolution and particle swarm optimization) were used for further testing purposes. Results are presented for Maritime pine stand management in Leiria National Forest in Portugal. They confirm that fuel treatments improve profitability and reduce the expected damage.

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