Fungal Interactions Matter: Tricholoma matsutake Domination Affect Fungal Diversity and Function in Temperate Deciduous Forest Soils

Tricholoma matsutake forms a symbiotic association with coniferous trees, developing mycelial aggregations, called ‘shiro’, which are characterized by distinct chemical and physical properties from nearby forest bulk soil. The fungal diversity living in shiro soil play key roles in nutrient cycles for this economically important mushroom, but have not been profiled across large spatial and environmental gradients. Samples of shiro and non-shiro (nearby bulk soil) were taken from five field sites where sporocarps naturally formed. Phospholipid fatty acids (PLFA) and Illumina MiSeq sequencing were combined to identify fungal biomass and community structure. Matsutake dominated in the shiro, which had a significantly reduced saprotrophic fungi biomass compared to non-shiro soil. Fungal diversity was negatively correlated with the relative abundance of T. matsutake in the shiro soil. The fungal community in the shiro was characterized by similar fungal species composition in most samples regardless of forest types. Matsutake coexisted with a specific fungal community due to competition or nutrient interactions. Oidiodendron was positively correlated with the abundance of T. matsutake, commonly cohabitant in the shiro. In contrast, Helotiales and Mortierella were negatively correlated with T. matsutake, both of which commonly inhabit the non-shiro soil but do not occur in shiro soils. We conclude that T. matsutake generate a dominance effect to shape the fungal community and diversity in shiro soil across distinctive forest types.

Can vegetation index track the interannual variation in gross primary production of temperate deciduous forests?

Background Vegetation indices (VIs) by remote sensing are widely used as simple proxies of the gross primary production (GPP) of vegetation, but their performances in capturing the inter-annual variation (IAV) in GPP remain uncertain. Methods We evaluated the performances of various VIs in tracking the IAV in GPP estimated by eddy covariance in a temperate deciduous forest of Northeast China. The VIs assessed included the normalized difference vegetation index (NDVI), the enhanced vegetation index (EVI), and the near-infrared reflectance of vegetation (NIRv) obtained from tower-radiometers (broadband) and the Moderate Resolution Imaging Spectroradiometer (MODIS), respectively. Results We found that 25%–35% amplitude of the broadband EVI tracked the start of growing season derived by GPP (R2: 0.56–0.60, bias < 4 d), while 45% (or 50%) amplitudes of broadband (or MODIS) NDVI represented the end of growing season estimated by GPP (R2: 0.58–0.67, bias < 3 d). However, all the VIs failed to characterize the summer peaks of GPP. The growing-season integrals but not averaged values of the broadband NDVI, MODIS NIRv and EVI were robust surrogates of the IAV in GPP (R2: 0.40–0.67). Conclusion These findings illustrate that specific VIs are effective only to capture the GPP phenology but not the GPP peak, while the integral VIs have the potential to mirror the IAV in GPP.