Understanding the functional organization of ecological communities is essential for predicting their succession in stable and changing environments and designing effective strategies to control it. Functioning of terrestrial ecosystems strongly depends on the rate of organic matter turnover and fungi are the main drivers of this complex process in forests. In this work, based on ecological network analysis and functional predictions from amplicon sequences, we characterized between-species interactions in wood-decay fungal communities and mapped functional attributes to their biological networks. The analysis is based on fungal abundance profiles obtained with high-throughput sequencing of rRNA gene internal transcribed spacer (ITS2). Ecological networks were inferred with SPRING (semi-parametric rank-based correlation and partial correlation estimation). Copy numbers of gene families, encoding extracellular enzymes involved in decomposition of plant biopolymers (e.g., cellulose, hemicellulose, and lignin degrading CAZymes) were reconstructed with PICRUSt2 based on the JGI MycoCosm database of reference genomes. We compare the predicted functional profiles of undisturbed and degraded communities of wood-decay fungi and estimate the consequences of species loss for biotic interactions. We classify functional elements by their vulnerability to chemical pollution and by the importance in wood decomposition.
The work was funded by Russian Foundation for Basic Research (grant 18-29-05042).
