Yield models for predicting aboveground ectomycorrhizal fungal productivity in Pinus sylve

Yield models for predicting aboveground ectomycorrhizal fungal productivity in Pinus sylvestris and Pinus pinaster stands of northern

Spain

Mariola Sánchez-González; Sergio de-Miguel; Pablo Martin-Pinto; Fernando Martínez-Pe?a; María Pasalodos-Tato; Juan Andrés Oria-de-Rueda; Juan Martínez de Aragón; Isabel Ca?ellas; JoséAntonio Bonet

【期刊名称】《森林生态系统：英文版》 【年(卷),期】2024(006)004

【摘要】Background: Predictive models shed light on aboveground fungal yield dynamics and can assist decision-making in forestry by integrating this valuable non-wood forest product into forest management planning. However, the currently existing models are based on rather local data and, thus, there is a lack of predictive tools to monitor mushroom yields on larger scales.Results: This work presents the first empirical models for predicting the annual yields of ectomycorrhizal mushrooms and related ecosystem services in Pinus sylvestris and Pinus pinaster stands in northern Spain, using a long-term dataset suitable to account for the combined effect of meteorological conditions and stand structure.Models were fitted for the following groups of fungi separately: all ectomycorrhizal mushrooms, edible mushrooms and marketed mushrooms. Our results show the influence