Evaluation of mushroom production potential by combining spatial optimization and LiDAR-based forest mapping data

Abstract

High-resolution forest mapping technology is a powerful data source to assess the production capacity of forests regarding wood and non-wood ecosystem services. The study shows how to evaluate the potential benefits from forest management treatments devoted to increase mushroom supply. The study was developed in Central Spain, over a forest with important cultural and economic values attached to mushrooms. Airborne laser scanning (ALS), mushroom production models and mathematical programming as spatial optimization method are used to sequence, spatially and temporally, silviculture-oriented actions to enlarge mushroom provisioning. We present a tactical forest planning solution to incentivize mushroom yield driven by clustered silvicultural treatments applied to fine-grained segments derived from ALS data, and along a 5-year plan while embedding temporal and spatial dependencies. Mushroom yield can increase up to 18 % from current conditions if all area is treated. Our model integrates constraints to optimize the selection of segments yielding the highest benefits in terms of mushroom yield and timber removals during the treatments. The temporal sequencing was successful, so the annual interventions are scheduled aligned in space and in time to ease the actionability and realism of model outputs. The assessment of production potential is an informative, spatially and temporally explicit exercise to inform decision-makers on investment opportunities to enhance the supply of non-wood ecosystem services, tested with mushroom in this study but extendable to more non-wood ecosystem services.

Keywords: Decision-making; Forest planning; Mathematical programming; Non-wood ecosystem services.