The influence of tree genus, phylogeny, and richness on the specificity, rarity, and diversity of ectomycorrhizal fungi.

Partner specificity is a well-documented phenomenon in biotic interactions, yet the factors that determine specificity in plant-fungal associations remain largely unknown. By utilizing composite soil samples, we identified the predictors that drive partner specificity in both plants and fungi, with a particular focus on ectomycorrhizal associations. Fungal guilds exhibited significant differences in overall partner preference and avoidance, richness, and specificity to specific tree genera. The highest level of specificity was observed in root endophytic and ectomycorrhizal associations, while the lowest was found in arbuscular mycorrhizal associations. The majority of ectomycorrhizal fungal species showed a preference for one of their partner trees, primarily at the plant genus level. Specialist ectomycorrhizal fungi were dominant in belowground communities in terms of species richness and relative abundance. Moreover, all tree genera (and occasionally species) demonstrated a preference for certain fungal groups. Partner specificity was not related to the rarity of fungi or plants or environmental conditions, except for soil pH. Depending on the partner tree genus, specific fungi became more prevalent and relatively more abundant with increasing stand age, tree dominance, and soil pH conditions optimal for the partner tree genus. The richness of partner tree species and increased evenness of ectomycorrhizal fungi in multi-host communities enhanced the species richness of ectomycorrhizal fungi. However, it was primarily the partner-generalist fungi that contributed to the high diversity of ectomycorrhizal fungi in mixed forests.

Harmonised statistics and maps of forest biomass and increment in Europe.

Forest biomass is an essential resource in relation to the green transition and its assessment is key for the sustainable management of forest resources. Here, we present a forest biomass dataset for Europe based on the best available inventory and satellite data, with a higher level of harmonisation and spatial resolution than other existing data. This database provides statistics and maps of the forest area, biomass stock and their share available for wood supply in the year 2020, and statistics on gross and net volume increment in 2010-2020, for 38 European countries. The statistics of most countries are available at a sub-national scale and are derived from National Forest Inventory data, harmonised using common reference definitions and estimation methodology, and updated to a common year using a modelling approach. For those counties without harmonised statistics, data were derived from the State of Europe's Forest 2020 Report at the national scale. The maps are coherent with the statistics and depict the spatial distribution of the forest variables at 100 m resolution.

Highly comparable metabarcoding results from MGI-Tech and Illumina sequencing platforms.

With the developments in DNA nanoball sequencing technologies and the emergence of new platforms, there is an increasing interest in their performance in comparison with the widely used sequencing-by-synthesis methods. Here, we test the consistency of metabarcoding results from DNBSEQ-G400RS (DNA nanoball sequencing platform by MGI-Tech) and NovaSeq 6000 (sequencing-by-synthesis platform by Illumina) platforms using technical replicates of DNA libraries that consist of COI gene amplicons from 120 soil DNA samples. By subjecting raw sequencing data from both platforms to a uniform bioinformatics processing, we found that the proportion of high-quality reads passing through the filtering steps was similar in both datasets. Per-sample operational taxonomic unit (OTU) and amplicon sequence variant (ASV) richness patterns were highly correlated, but sequencing data from DNBSEQ-G400RS harbored a higher number of OTUs. This may be related to the lower dominance of most common OTUs in DNBSEQ data set (thus revealing higher richness by detecting rare taxa) and/or to a lower effective read quality leading to generation of spurious OTUs. However, there was no statistical difference in the ASV and post-clustered ASV richness between platforms, suggesting that additional denoising step in the ASV workflow had effectively removed the 'noisy' reads. Both OTU-based and ASV-based composition were strongly correlated between the sequencing platforms, with essentially interchangeable results. Therefore, we conclude that DNBSEQ-G400RS and NovaSeq 6000 are both equally efficient high-throughput sequencing platforms to be utilized in studies aiming to apply the metabarcoding approach, but the main benefit of the former is related to lower sequencing cost.