The objective of this research is to evaluate the potential of remote sensing data for the modelling of mushroom yields in forests at large spatial scales. Specifically, we want to see if combining remote sensor-based data could represent more accuracy to the current models which are based on climate observations. Showing the potential of remote sensing to model mushroom yields is a first step for the future development of small-scale predictive models.
In 2008, we installed 14 mushroom inventory plots of 100 m2 size in Pinus pinaster forests. The plots were selected to include a range of geographical features (altitude, slope, aspect) as well as variation in tree density and basal area in the conservation area of Poblet. A second set of plots were installed in 2009 paired to the first set of plots. The second set of plots was thinned removing 26 to 77% of the basal area. Mushroom yields were monitored on a weekly basis in the Autumn Season of the years 2008 to 2010 to analyze the effects of forest thinning on the yields of Lactarius delicious group.