Dataset Information

Determinants of Deadwood-Inhabiting Fungal Communities in Temperate Forests: Molecular Evidence From a Large Scale Deadwood Decomposition Experiment.

ABSTRACT: Despite the important role of wood-inhabiting fungi (WIF) in deadwood decomposition, our knowledge of the factors shaping the dynamics of their species richness and community composition is scarce. This is due to limitations regarding the resolution of classical methods used for characterizing WIF communities and to a lack of well-replicated long-term experiments with sufficient numbers of tree species. Here, we used a large scale experiment with logs of 11 tree species at an early stage of decomposition, distributed across three regions of Germany, to identify the factors shaping WIF community composition and Operational Taxonomic Unit (OTU) richness using next generation sequencing. We found that tree species identity was the most significant factor, corresponding to (P < 0.001) and explaining 10% (representing 48% of the explainable variance) of the overall WIF community composition. The next important group of variables were wood-physicochemical properties, of which wood pH was the only factor that consistently corresponded to WIF community composition. For overall WIF richness patterns, we found that approximately 20% of the total variance was explained by wood N content, location, tree species identity and wood density. It is noteworthy that the importance of determinants of WIF community composition and richness appeared to depend greatly on tree species group (broadleaved vs. coniferous) and it differed between the fungal phyla Ascomycota and Basidiomycota.

SUBMITTER: Purahong W

PROVIDER: S-EPMC6158579 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Determinants of Deadwood-Inhabiting Fungal Communities in Temperate Forests: Molecular Evidence From a Large Scale Deadwood Decomposition Experiment.

Purahong Witoon W Wubet Tesfaye T Lentendu Guillaume G Hoppe Björn B Jariyavidyanont Katalee K Arnstadt Tobias T Baber Kristin K Otto Peter P Kellner Harald H Hofrichter Martin M Bauhus Jürgen J Weisser Wolfgang W WW Krüger Dirk D Schulze Ernst-Detlef ED Kahl Tiemo T Buscot François F

Frontiers in microbiology 20180920

Despite the important role of wood-inhabiting fungi (WIF) in deadwood decomposition, our knowledge of the factors shaping the dynamics of their species richness and community composition is scarce. This is due to limitations regarding the resolution of classical methods used for characterizing WIF communities and to a lack of well-replicated long-term experiments with sufficient numbers of tree species. Here, we used a large scale experiment with logs of 11 tree species at an early stage of deco ...[more]

PMID: 30294306

Similar Datasets

Project description:Fungal-bacterial interactions play a key role in the functioning of many ecosystems. Thus, understanding their interactive dynamics is of central importance for gaining predictive knowledge on ecosystem functioning. However, it is challenging to disentangle the mechanisms behind species associations from observed co-occurrence patterns, and little is known about the directionality of such interactions. Here, we applied joint species distribution modeling to high-throughput sequencing data on co-occurring fungal and bacterial communities in deadwood to ask whether fungal and bacterial co-occurrences result from shared habitat use (i.e., deadwood's properties) or whether there are fungal-bacterial interactive associations after habitat characteristics are taken into account. Moreover, we tested the hypothesis that the interactions are mainly modulated through fungal communities influencing bacterial communities. For that, we quantified how much the predictive power of the joint species distribution models for bacterial and fungal community improved when accounting for the other community. Our results show that fungi and bacteria form tight association networks (i.e., some species pairs co-occur more frequently and other species pairs co-occur less frequently than expected by chance) in deadwood that include common (or opposite) responses to the environment as well as (potentially) biotic interactions. Additionally, we show that information about the fungal occurrences and abundances increased the power to predict the bacterial abundances substantially, whereas information about the bacterial occurrences and abundances increased the power to predict the fungal abundances much less. Our results suggest that fungal communities may mainly affect bacteria in deadwood.IMPORTANCE Understanding the interactive dynamics between fungal and bacterial communities is important to gain predictive knowledge on ecosystem functioning. However, little is known about the mechanisms behind fungal-bacterial associations and the directionality of species interactions. Applying joint species distribution modeling to high-throughput sequencing data on co-occurring fungal-bacterial communities in deadwood, we found evidence that nonrandom fungal-bacterial associations derive from shared habitat use as well as (potentially) biotic interactions. Importantly, the combination of cross-validations and conditional cross-validations helped us to answer the question about the directionality of the biotic interactions, providing evidence that suggests that fungal communities may mainly affect bacteria in deadwood. Our modeling approach may help gain insight into the directionality of interactions between different components of the microbiome in other environments.

Project description:Forests accumulate and store large amounts of carbon (C), and a substantial fraction of this stock is contained in deadwood. This transient pool is subject to decomposition by deadwood-associated organisms, and in this process it contributes to CO2 emissions. Although fungi and bacteria are known to colonize deadwood, little is known about the microbial processes that mediate carbon and nitrogen (N) cycling in deadwood. In this study, using a combination of metagenomics, metatranscriptomics, and nutrient flux measurements, we demonstrate that the decomposition of deadwood reflects the complementary roles played by fungi and bacteria. Fungi were found to dominate the decomposition of deadwood and particularly its recalcitrant fractions, while several bacterial taxa participate in N accumulation in deadwood through N fixation, being dependent on fungal activity with respect to deadwood colonization and C supply. Conversely, bacterial N fixation helps to decrease the constraints of deadwood decomposition for fungi. Both the CO2 efflux and N accumulation that are a result of a joint action of deadwood bacteria and fungi may be significant for nutrient cycling at ecosystem levels. Especially in boreal forests with low N stocks, deadwood retention may help to improve the nutritional status and fertility of soils.IMPORTANCE Wood represents a globally important stock of C, and its mineralization importantly contributes to the global C cycle. Microorganisms play a key role in deadwood decomposition, since they possess enzymatic tools for the degradation of recalcitrant plant polymers. The present paradigm is that fungi accomplish degradation while commensalist bacteria exploit the products of fungal extracellular enzymatic cleavage, but this assumption was never backed by the analysis of microbial roles in deadwood. This study clearly identifies the roles of fungi and bacteria in the microbiome and demonstrates the importance of bacteria and their N fixation for the nutrient balance in deadwood as well as fluxes at the ecosystem level. Deadwood decomposition is shown as a process where fungi and bacteria play defined, complementary roles.

Dataset Information

Determinants of Deadwood-Inhabiting Fungal Communities in Temperate Forests: Molecular Evidence From a Large Scale Deadwood Decomposition Experiment.

Publications

Determinants of Deadwood-Inhabiting Fungal Communities in Temperate Forests: Molecular Evidence From a Large Scale Deadwood Decomposition Experiment.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets