Microbial diversity in temperate forest soils under different tree species
Background: This study analyses the influence of three deciduous tree species - small-leaved lime (Tilia cordata), common beech (Fagus sylvatica) and sessile oak (Quercus petraea) - on soil microbial diversity in temperate forest ecosystems. Conducted on loess soils of southern Poland, it helps to clarify species-specific effects on microbial diversity and soil chemistry. By analysing both fungal and bacterial communities, it provides new insights into species-specific microbial interactions in temperate forests. To determine microbial diversity, the samples were analysed using NGS technology.  Results: Significant differences in soil chemical properties were observed between tree species. Lime soils had the highest pH (5.1–7.0) and calcium content (18.9 cmol(+)·kg?¹), while beech soils were the most acidic (pH: 3.8–5.7) with the lowest calcium (8.0 cmol(+)·kg?¹). Fungal communities were dominated by Basidiomycota (54.7% in beech, 53.2% in oak, 32.9% in lime), Ascomycota (34.8% in lime, 23.5% in beech, 24.2% in oak), and Mortierellomycota (22.6% in lime, 19.8% in oak, 17.0% in beech). Bacterial diversity was highest in lime (342–382 genera) and oak (337–358 genera) soils, with Actinobacteriota (34.9% in lime, 33.7% in oak, 29.1% in beech), Proteobacteria (33.9% in beech, 31.6% in oak, 29.0% in lime), and Acidobacteriota (16.7% in beech, 11.7% in oak, 11.0% in lime) as dominant phyla. Each tree species supported a distinct microbial community, demonstrating that stand composition influences soil properties and microbial diversity.  Conclusions: The composition and diversity of soil microbial communities in temperate forests are significantly shaped by tree species. These findings highlight the ecological importance of selecting the right tree species for forest management. Incorporating microbial data into soil management could enhance ecosystem services, conserve biodiversity and boost forests' resilience to climate change. Future studies should address spatial variability by taking samples from multiple stands of each species across a broader geographical area.