Revealing hidden drivers of macrofungal species richness by analyzing fungal guilds in temperate forests, West Hungary

Verification study on how macrofungal fruitbody formation can be predicted by artificial neural network

The occurrence and regularity of macrofungal fruitbody formation are influenced by meteorological conditions; however, there is a scarcity of data about the use of machine-learning techniques to estimate their occurrence based on meteorological indicators. Therefore, we employed an artificial neural network (ANN) to forecast fruitbody occurrence in mycorrhizal species of Russula and Amanita, utilizing meteorological factors and validating the accuracy of the forecast of fruitbody formation. Fungal data were collected from two locations in Western Hungary between 2015 and 2020. The ANN was the commonly used algorithm for classification problems: feed-forward multilayer perceptrons with a backpropagation algorithm to estimate the binary (Yes/No) classification of fruitbody appearance in natural and undisturbed forests. The verification indices resulted in two outcomes: however, development is most often studied by genus level, we established a more successful, new model per species. Furthermore, the algorithm is able to successfully estimate fruitbody formations with medium to high accuracy (60-80%). Therefore, this work was the first to reliably utilise the ANN approach of estimating fruitbody occurrence based on meteorological parameters of mycorrhizal specified with an extended vegetation period. These findings can assist in field mycological investigations that utilize sporocarp occurrences to ascertain species abundance.

Exploring the Relationships between Macrofungi Diversity and Major Environmental Factors in Wunvfeng National Forest Park in Northeast China

In this paper, we analyze the macrofungi communities of five forest types in Wunvfeng National Forest Park (Jilin, China) by collecting fruiting bodies from 2019–2021. Each forest type had three repeats and covered the main habitats of macrofungi. In addition, we evaluate selected environmental variables and macrofungi communities to relate species composition to potential environmental factors. We collected 1235 specimens belonging to 283 species, 116 genera, and 62 families. We found that Amanitaceae, Boletaceae, Russulaceae, and Tricholomataceae were the most diverse family; further, Amanita, Cortinarius, Lactarius, Russula, and Tricholoma were the dominant genera in the area. The macrofungi diversity showed increasing trends from Pinus koraiensis Siebold et Zuccarini forests to Quercus mongolica Fischer ex Ledebour forests. The cumulative species richness was as follows: Q. mongolica forest A > broadleaf mixed forest B > Q. mongolica, P. koraiensis mix forest D (Q. mongolica was the dominant species) > Q. mongolica and P. koraiensis mix forest C (P. koraiensis was the dominant species) > P. koraiensis forest (E). Ectomycorrhizal fungi were the dominant functional group; they were mainly in forest type A and were influenced by soil moisture content and Q. mongolica content (p < 0.05). The wood-rotting fungus showed richer species diversity than other forest types in broadleaf forests A and B. Overall, we concluded that most fungal communities preferred forest types with a relatively high Q. mongolica content. Therefore, the deliberate protection of Q. mongolica forests proves to be a better strategy for maintaining fungal diversity in Wunvfeng National Forest Park.

Environmental drivers of forest biodiversity in temperate mixed forests - A multi-taxon approach

Harmonization of timber production and forest conservation is a major challenge of modern silviculture. For the establishment of ecologically sustainable forest management, the management-related environmental drivers of multi-taxon biodiversity should be explored. Our study reveals those environmental variables related to tree species diversity and composition, stand structure, litter and soil conditions, microclimate, landscape, and land-use history that determine species richness and composition of 11 forest-dwelling organism groups. Herbs, woody regeneration, ground-floor and epiphytic bryophytes, epiphytic lichens, terricolous saprotrophic, ectomycorrhizal, and wood-inhabiting macrofungi, spiders, carabid beetles, and birds were sampled in West Hungarian mature mixed forests. The correlations among the diversities and compositions of different organism groups were also evaluated. Drivers of organism groups were principally related to stand structure, tree species diversity and composition, and microclimate, while litter, soil, landscape, and land-use historical variables were less influential. The complex roles of the shrub layer, deadwood, and the size of the trees in determining the diversity and composition of various taxa were revealed. Stands with more tree species sustained higher stand-level species richness of several taxa. Besides, stands with different dominant tree species harbored various species communities of organism groups. Therefore, landscape-scale diversity of dominant tree species may enhance the diversity of forest-dwelling communities at landscape level. The effects of the overstory layer on forest biodiversity manifested in many cases via microclimate conditions. Diversity of organism groups showed weaker relationship with the diversity of other taxa than with environmental variables. According to our results, the most influential drivers of forest biodiversity are under the direct control of the actual silvicultural management. Heterogeneous stand structure and tree species composition promote the different organism groups in various ways. Therefore, the long-term maintenance of the structural and compositional heterogeneity both at stand and landscape scale is an important aspect of ecologically sustainable forest management.