Tree Size Drives Diversity and Community Structure of Microbial Communities on the Bark of Beech (Fagus sylvatica)

Abstract

Tree bark constitutes an ideal habitat for microbial communities, because it is a stable substrate, rich in micro-niches. Bacteria, fungi, and terrestrial microalgae together form microbial communities, which in turn support more bark-associated organisms, such as mosses, lichens, and invertebrates, thus contributing to forest biodiversity. We have a limited understanding of the diversity and biotic interactions of the bark-associated microbiome, as investigations have mainly focused on agriculturally relevant systems and on single taxonomic groups. Here we implemented a multi-kingdom metabarcoding approach to analyze diversity and community structure of the green algal, bacterial, and fungal components of the bark-associated microbial communities of beech, the most common broadleaved tree of Central European forests. We identified the most abundant taxa, hub taxa, and co-occurring taxa. We found that tree size (as a proxy for age) is an important driver of community assembly, suggesting that environmental filtering leads to less diverse fungal and algal communities over time. Conversely, forest management intensity had negligible effects on microbial communities on bark. Our study suggests the presence of undescribed, yet ecologically meaningful taxa, especially in the fungi, and highlights the importance of bark surfaces as a reservoir of microbial diversity. Our results constitute a first, essential step toward an integrated framework for understanding microbial community assembly processes on bark surfaces, an understudied habitat and neglected component of terrestrial biodiversity. Finally, we propose a cost-effective sampling strategy to study bark-associated microbial communities across large spatial or environmental scales.

Biotic interactions outweigh abiotic factors as drivers of bark microbial communities in Central European forests

“…The dominant tree species in the final subset of 133 plots were beech ( Fagus sylvatica ), pine ( Pinus sylvestris ), or spruce ( Picea abies ). Following a previous study [ 10 ], the composite sample included two small (5–15 cm diameter at 150 cm height), two medium (15–30 cm), and two large (> 30 cm) trees. When no equal sampling was possible, we chose the size class that best represented the surrounding forest (36 of 133 plots, ~27%).…”

“…The sampling technique is described in detail in [ 10 ] with the only difference that all swabs from one plot were pooled together. In brief: we sampled the microbial community of the bark surface by swabbing with nylon-flocked swabs (FLOQSwabs™, Copan, Brescia, Italy) once around the stem at 150-cm height.…”

“…For example, a previous study on bark microalgae from Mediterranean forests showed a higher abundance and diversity compared to those of temperate forests, likely due to differences in temperature and precipitation [ 32 ]. However, additional factors may contribute to shaping the unique communities on bark surfaces [ 7 ], for example, the age of the host tree [ 10 , 33 ].…”

“…Only few studies about natural bark micro-communities exist (e.g. [ 7 , 8 , 35 ]), and although they often included only single organismal groups [ 16 , 36 , 37 ], we already know parts of the diversity in bark surface communities [ 10 ]. However, to gain insights into how the whole community of microorganisms responds to present environmental change, and to model future changes, we need a comprehensive overview of the drivers behind community structure [ 1 , 10 ].…”

“…[ 7 , 8 , 35 ]), and although they often included only single organismal groups [ 16 , 36 , 37 ], we already know parts of the diversity in bark surface communities [ 10 ]. However, to gain insights into how the whole community of microorganisms responds to present environmental change, and to model future changes, we need a comprehensive overview of the drivers behind community structure [ 1 , 10 ]. Since diversity is multifaceted we need to go beyond alpha diversity and consider multiple diversity dimensions [ 38 ] to fully understand which biotic and abiotic factors shape community responses.…”