Yield models for predicting aboveground ectomycorrhizal fungal productivity in Pinus sylvestris and Pinus pinaster stands of northern Spain
| Autor: | Isabel Cañellas, Juan Andrés Oria-de-Rueda, Pablo Martín-Pinto, María Pasalodos-Tato, Fernando Martínez-Peña, Juan Martínez de Aragón, Mariola Sánchez-González, Sergio de-Miguel, José Antonio Bonet |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
0106 biological sciences
Productos forestales no leñosos Ectomicorrizas 010504 meteorology & atmospheric sciences Mushrooms Forest product Forest management 01 natural sciences Hongos Basal area Ectosymbiosis Hurdle models lcsh:QH540-549.5 Ecosystem Mixed models Ecology Evolution Behavior and Systematics 0105 earth and related environmental sciences Nature and Landscape Conservation 2. Zero hunger Mushroom Productividad Ecology biology Fungi Forestry 15. Life on land biology.organism_classification Productivity (ecology) Non-wood forest products Pinus pinaster Environmental science lcsh:Ecology 010606 plant biology & botany |
| Zdroj: | Recercat. Dipósit de la Recerca de Catalunya instname Zaguán: Repositorio Digital de la Universidad de Zaragoza Universidad de Zaragoza Repositorio Abierto de la UdL Universitad de Lleida Forest Ecosystems, Vol 6, Iss 1, Pp 1-13 (2019) Zaguán. Repositorio Digital de la Universidad de Zaragoza |
| ISSN: | 2018-0993 |
| Popis: | 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 of the weather variables (mainly precipitation) on mushroom yields as well as the relevance of the basal area of the forest stand that follows a right-skewed unimodal curve with maximum predicted yields at stand basal areas of 30–40 m2∙ha− 1. Conclusion: These models are the first empirical models for predicting the annual yields of ectomycorrhizal mushrooms in Pinus sylvestris and Pinus pinaster stands in northern Spain, being of the highest resolution developed to date and enable predictions of mushrooms productivity by taking into account weather conditions and forests’ location, composition and structure. This work was partially supported by the Spanish Ministry of Science, Innovation and Universities (grant number RTI2018-099315-A-I00), by the Spanish Ministry of Economy and Competitivity (MINECO) (Grant number AGL2015–66001-C3), by the Cost action FP1203: European Non-Wood Forest Products Network, and by the European project StarTree – Multipurpose trees and non-wood forest products (Grant number 311919). Sergio de Miguel and José Antonio Bonet benefited from a Serra-Húnter Fellowship provided by the Generalitat of Catalunya. |
| Databáze: | OpenAIRE |
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