Soil microclimate is a potentially important regulator of the composition of plant-associated fungal communities in climates with significant drought periods. Here, we investigated the spatio-temporal dynamics of soil fungal communities in a Mediterranean Pinus pinaster forest in relation to soil moisture and temperature. Fungal communities in 336 soil samples collected monthly over 1 year from 28 long-term experimental plots were assessed by PacBio sequencing of ITS2 amplicons. Total fungal biomass was estimated by analysing ergosterol. Community changes were analysed in the context of functional traits. Soil fungal biomass was lowest during summer and late winter and highest during autumn, concurrent with a greater relative abundance of mycorrhizal species. Intra-annual spatio-temporal changes in community composition correlated significantly with soil moisture and temperature. Mycorrhizal fungi were less affected by summer drought than free-living fungi. In particular, mycorrhizal species of the short-distance exploration type increased in relative abundance under dry conditions, whereas species of the long-distance exploration type were more abundant under wetter conditions. Our observations demonstrate a potential for compositional and functional shifts in fungal communities in response to changing climatic conditions. Free-living fungi and mycorrhizal species with extensive mycelia may be negatively affected by increasing drought periods in Mediterranean forest ecosystems.
Multiple-use forestry requires comprehensive planning to maximize the utilization and sustainability of many forest resources whose growth and productivity are interconnected. Forest fungi represent an economically important nonwood forest resource that provides food, medicine, and recreation worldwide. A vast majority of edible and marketed forest mushrooms belong to fungi that grow symbiotically with forest trees. To respond to the need for planning tools for multiple-use forestry, we developed empirical models for predicting the production of wild mushrooms in pine forests in the South-Central Pyrenees using forest stand and site characteristics as predictors. Mushroom production and species richness data from 45 plots were used. A mixed modelling technique was used to account for between-plot and between-year variation in the mushroom production data. The most significant stand structure variable for predicting mushroom yield was stand basal area. The stand basal area associated with maximum mushroom productivity (15–20 m2·ha–1) coincides with the peak of annual basal area increment in these pine forests. Other important predictors were slope, elevation, aspect, and autumn rainfall. The models are aimed at supporting forest management decisions and forecasting mushroom yields in forest planning.
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