Stand Structural Characteristics Derived from Combined TLS and Landsat Data Support Predictions of Mushroom Yields in Mediterranean Forest

Forest fungi provide recreational and economic services, as well ecosystem biodiversity. Wild mushroom yields are difficult to estimate; climatic conditions known trigger temporally localised yields, forest structure also affects productivity. In this work, we analyse the capacity of remotely sensed variables estimate wild biomass production in Mediterranean Pinus pinaster forests Soria (Spain) using generalised additive mixed models (GAMMs). addition climate variables, multitemporal NDVI derived from Landsat data, structural measured with mobile Terrestrial Laser Scanner (TLS), considered. Models built for all species a single pool Lactarius deliciosus individually. Our results show that, autumn precipitation, interaction vegetation most explanatory productivity models. When analysing deliciosus, between canopy cover minimum temperature, basal area (BA) becomes relevant, indicating an optimal BA range development species. These findings contribute improvement knowledge about productivity, helping meet Goal 15 2030 UN Agenda.