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<dc:title>Primary productivity and climate control mushroom yields in Mediterranean pine forests</dc:title>
<dc:creator>Olano Mendoza, José Miguel</dc:creator>
<dc:creator>Martínez Rodrigo, Raquel</dc:creator>
<dc:creator>Altelarrea, José Miguel</dc:creator>
<dc:creator>Ágreda, Teresa</dc:creator>
<dc:creator>Fernández Toirán, Luz Marina</dc:creator>
<dc:creator>García Cervigón, Ana I.</dc:creator>
<dc:creator>Rodríguez Puerta, Francisco</dc:creator>
<dc:creator>Agueda Hernández, Beatriz</dc:creator>
<dc:description>Mushrooms play a provisioning ecosystem service as wild food. The abundance of this resource shows high&#xd;
annual and interannual variability, particularly in Mediterranean ecosystems. Climate conditions have been&#xd;
considered the main factor promoting mushroom production variability, but several evidences suggest that forest&#xd;
composition, age and growth play also a role.&#xd;
Long-term mushroom production datasets are critical to understand the factors behind mushroom productivity.&#xd;
We used 22 and 24 year-long time series of mushroom production in Pinus pinaster and Pinus sylvestris&#xd;
forests in Central Spain to evaluate the effect of climate and forest productivity on mushroom yield. We combined&#xd;
climatic data (precipitation and temperature) and remote sensing data (soil moisture and the Normalized&#xd;
Difference Vegetation Index, NDVI, a surrogate of primary productivity) to model mushroom yields for each&#xd;
forest and for the main edible species of economic interest (Boletus edulis and Lactarius deliciosus).&#xd;
We hypothesized that mushroom yield would be related to (i) forest primary productivity inferred from NDVI&#xd;
affects mushroom yields, that (ii) soil moisture inferred from remote sensors will equal the predictive power&#xd;
precipitation data, and that (iii) combining climatic and remote sensing will improve mushroom yield models.&#xd;
We found that (i) previous year NDVI correlated (r =0.41–0.6) with mushroom yields; (ii) soil moisture from&#xd;
remote sensors rivaled the predictive power of precipitation (r = 0.63–0.72); and (iii) primary production and&#xd;
climate variances were independent, thus the combination of climatic and remote sensing data improved models&#xd;
with mean R2&#xd;
adj as high as 0.629.&#xd;
On the light of these results, we propose as a working hypothesis that mushroom production might be&#xd;
modelled as a two step process. Previous year primary productivity would favour resource accumulation at tree&#xd;
level, potentially increasing resources for mycelia growth, climatic conditions during the fruiting season control&#xd;
the ability of mycelia to transform available resources into fruiting bodies</dc:description>
<dc:description>Junta de Castilla y León [project VA026P17]; and the Spanish Ministry of Science, Innovation and Universities [grant numbers DI-17-09626, PTQ-16-08411 and IJCI- 2017-34052 to RMR, BÁ, and AIGC, respectively].</dc:description>
<dc:date>2025-01-15T08:05:24Z</dc:date>
<dc:date>2025-01-15T08:05:24Z</dc:date>
<dc:date>2020</dc:date>
<dc:type>info:eu-repo/semantics/article</dc:type>
<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
<dc:identifier>Agricultural and Forest Meteorology 288-289: 108015.</dc:identifier>
<dc:identifier>https://uvadoc.uva.es/handle/10324/73839</dc:identifier>
<dc:identifier>10.1016/j.agrformet.2020.108015</dc:identifier>
<dc:identifier>1</dc:identifier>
<dc:identifier>7</dc:identifier>
<dc:language>spa</dc:language>
<dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
<dc:rights>Elsevier</dc:rights>
<dc:format>application/pdf</dc:format>
<europeana:object>https://uvadoc.uva.es/bitstream/10324/73839/3/Primary-productivity-and-climate-control-mushroom-_2020_Agricultural-and-For.pdf.jpg</europeana:object>
<europeana:provider>Hispana</europeana:provider>
<europeana:type>TEXT</europeana:type>
<europeana:rights>http://rightsstatements.org/vocab/CNE/1.0/</europeana:rights>
<europeana:dataProvider>UVaDOC. Repositorio Documental de la Universidad de Valladolid</europeana:dataProvider>
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