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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.
Methods using environmental DNA to explore and analyze biodiversity from previously unexplored habitats and ecosystems have become increasingly popular in recent years. This is particularly due to the potential reduction in necessary taxonomic expertise, the opportunity to assess microorganismal communities, and decreased time investments required to cover large spatial extents. In forests, the surface of tree bark is an important habitat for epiphytic diversity. Because of the large surface area rich in micro-niches, the seasonal stability of the substrate, and the longevity of trees, tree bark surfaces provide an ideal habitat for many species. Yet, we lack a comprehensive understanding of their communities and the environmental drivers behind the community assembly. These missing links hinder the exploration of the forest microbiome as a whole and limits our understanding of functions of a large forest habitat and its connections to other forest microbiomes. With a holistic eDNA metabarcoding approach, encompassing samples of three major taxonomic groups (e.g. bacteria, fungi, and green algae), as well as simultaneous collections from multiple forest habitats we can contribute to closing these gaps and increase our knowledge of the forest microbiome.
My dissertation is set within the framework of the Biodiversity Exploratories and was conducted in four parts: I. the establishment of an eDNA metabarcoding workflow to reveal the local diversity of the bark surface microbiome; II. the upscaling of the method to large geographic and environmental gradients to uncover the drivers of the microbiome; III. the integration of soil and bark samples to investigate compositional differences in two important forest habitats; IV. the evaluation of eDNA metabarcoding as a tool for biodiversity assessments of lichen diversity in forests.
In the first part, I developed a simple, cost-effective and fast sampling strategy to acquire eDNA samples from the bark of trees in forest ecosystems. Using readily available medical-specimen-collection swabs I sampled bark surfaces of individual trees in Central German forests and used metabarcoding to amplify marker genes of green algae, fungi and bacteria. From the sequencing reads I calculated the first diversity estimates of the major organismal groups of bark surface microbiomes from Central European forests. Overall the methodology produced reliable results, allowing for an expanded sampling in the second part.
In the second part of the dissertation, I expanded the sampling based on the results of part one. I collected bark surface samples from the three regions of the Biodiversity Exploratories covering large spatial and environmental gradients representative for Central European forests. The collection included composite samples from 150 plots and over 750 trees. Utilizing measurements of climatic and forest structure variables provided by the Biodiversity Exploratories, as well as my own community data, I identified the biotic and abiotic drivers behind alpha and beta diversity of the bark surface microbiome.
In the third part, I studied the differences between the bark surface as an unexplored and the soil as an example of a well characterized forest microbiome. Using only the fungal part of the large sampling campaign and soil samples obtained from the same plots at the same time, I assessed the commonalities and differences of the micro-communities of these distinct forest niches. Furthermore, I included two coniferous and one deciduous tree species to examine, if the effect of tree species, previously shown for soil microbiomes, also holds true for the bark surface.
In the last part of my dissertation, I used eDNA in a more applied way as a tool in biodiversity assessments of lichenized fungi. I compared the results from eDNA metabarcoding to an expert floristic mapping conducted in the same plots in 2007/2008. I assigned functional guilds to the fungal taxa obtained in the large sampling campaign and used a subset that was assigned as lichenized fungi.
In conclusion, I showed that eDNA metabarcoding is a valuable tool to reveal the unknown diversity of microorganisms in forest ecosystems. In particular, my results advance our understanding of the bark surface microbiome, an underexplored habitat within forests. The tightly linked interactions of the three major microbial groups underline that studies need to take holistic approaches across multiple taxonomic groups to deepen our understanding of processes governing the assembly of microbiomes. Results from my dissertation may serve as a foundation to inform hypotheses addressing the functions of forest microbiomes. The massive diversity data collected may also contribute to closing the gap in our understanding of macro-organisms and micro-organisms with respect to diversity distributions and patterns of richness, and serve as a baseline for predictions of biodiversity responses under future anthropogenic change.
Tree bark constitutes 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 focussed on agriculturally relevant systems and on single taxonomic groups. Here we implemented a multi-kingdom metabarcoding approach to analyse 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 towards 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.