Ecological drivers of fine-scale distribution of arbuscular mycorrhizal fungi in a semiarid Mediterranean scrubland.

BACKGROUND AND AIMS: Arbuscular mycorrhizal (AM) fungi enhance the uptake of water and minerals by the plant hosts, alleviating plant stress. Therefore, AM fungal-plant interactions are particularly important in drylands and other stressful ecosystems. We aimed to determine the combined and independent effects of above- and below-ground plant community attributes (i.e. diversity and composition), soil heterogeneity and spatial covariates on the spatial structure of the AM fungal communities in a semiarid Mediterranean scrubland. Furthermore, we evaluated how the phylogenetic relatedness of both plants and AM fungi shapes these symbiotic relationships. METHODS: We characterized the composition and diversity of AM fungal and plant communities in a dry Mediterranean scrubland taxonomically and phylogenetically, using DNA metabarcoding and a spatially explicit sampling design at the plant neighbourhood scale. KEY RESULTS: The above- and below-ground plant community attributes, soil physicochemical properties and spatial variables explained unique fractions of AM fungal diversity and composition. Mainly, variations in plant composition affected the AM fungal composition and diversity. Our results also showed that particular AM fungal taxa tended to be associated with closely related plant species, suggesting the existence of a phylogenetic signal. Although soil texture, fertility and pH affected AM fungal community assembly, spatial factors had a greater influence on AM fungal community composition and diversity than soil physicochemical properties. CONCLUSIONS: Our results highlight that the more easily accessible above-ground vegetation is a reliable indicator of the linkages between plant roots and AM fungi. We also emphasize the importance of soil physicochemical properties in addition to below-ground plant information, while accounting for the phylogenetic relationships of both plants and fungi, because these factors improve our ability to predict the relationships between AM fungal and plant communities.

The role of root community attributes in predicting soil fungal and bacterial community patterns.

Roots are assumed to play a major role in structuring soil microbial communities, but most studies exploring the relationships between microbes and plants at the community level have only used aboveground plant distribution as a proxy. However, a decoupling between belowground and aboveground plant components may occur due to differential spreading of plant canopies and root systems. Thus, soil microbe-plant links are not completely understood. Using a combination of DNA metabarcoding and spatially explicit sampling at the plant neighbourhood scale, we assessed the influence of the plant root community on soil bacterial and fungal diversity (species richness, composition and ß-diversity) in a dry Mediterranean scrubland. We found that root composition and biomass, but not richness, predict unique fractions of variation in microbial richness and composition. Moreover, bacterial ß-diversity was related to root ß-diversity, while fungal ß-diversity was related to aboveground plant ß-diversity, suggesting that plants differently influence both microbial groups. Our study highlights the role of plant distribution both belowground and aboveground, soil properties and other spatially structured factors in explaining the heterogeneity in soil microbial diversity. These results also show that incorporating data on both plant community compartments will further our understanding of the relationships between soil microbial and plant communities.

Estimating belowground plant abundance with DNA metabarcoding.

Most work on plant community ecology has been performed above ground, neglecting the processes that occur in the soil. DNA metabarcoding, in which multiple species are computationally identified in bulk samples, can help to overcome the logistical limitations involved in sampling plant communities belowground. However, a major limitation of this methodology is the quantification of species' abundances based on the percentage of sequences assigned to each taxon. Using root tissues of five dominant species in a semi-arid Mediterranean shrubland (Bupleurum fruticescens, Helianthemum cinereum, Linum suffruticosum, Stipa pennata and Thymus vulgaris), we built pairwise mixtures of relative abundance (20%, 50% and 80% biomass), and implemented two methods (linear model fits and correction indices) to improve estimates of root biomass. We validated both methods with multispecies mixtures that simulate field-collected samples. For all species, we found a positive and highly significant relationship between the percentage of sequences and biomass in the mixtures (R2  = .44-.66), but the equations for each species (slope and intercept) differed among them, and two species were consistently over- and under-estimated. The correction indices greatly improved the estimates of biomass percentage for all five species in the multispecies mixtures, and reduced the overall error from 17% to 6%. Our results show that, through the use of post-sequencing quantification methods on mock communities, DNA metabarcoding can be effectively used to determine not only species' presence but also their relative abundance in field samples of root mixtures. Importantly, knowledge of these aspects will allow us to study key, yet poorly understood, belowground processes.