Abstract

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.

Highlights

  • Fungal-bacterial interactions play a key role in the functioning of many ecosystems

  • Nonmetric multidimensional scaling (NMDS) ordinations show that the filters to remove rare operational taxonomic units (OTUs) altered overall community structure very little, and, the set of wood physical and chemical characteristics that significantly correlated with main trends in community structure remained the same (Fig. 1)

  • We proceeded to hierarchical modeling of species communities (HMSC) using the community data sets filtered to bigger data sets (452 fungal and 570 bacterial OTUs) and smaller data sets (103 fungal and 51 bacterial OTUs)

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Summary

Introduction

Fungal-bacterial interactions play a key role in the functioning of many ecosystems. understanding their interactive dynamics is of central importance for gaining predictive knowledge on ecosystem functioning. 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. Fungi and bacteria are core members of communities driving biogeochemical cycles, and interactions between the groups play a key role in the functioning of numerous ecosystems [1]. Understanding their interactive dynamics is of central importance for gaining predictive knowledge on ecosystem functioning. Fungal-bacterial interactions might be mainly modulated through fungal communities influencing bacterial communities

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