Consistent predictors of microbial community composition across spatial scales in grasslands reveal low context-dependency

Radujkovic, Dajana1 ; Vicca, Sara1; van Rooyen, Margaretha2; Wilfahrt, Peter3; Brown, Leslie4; Jentsch, Anke5; Reinhart, Kurt O.6; Brown, Charlotte7; De Gruyter, Johan1; Jurasinski, Gerald8; Askarizadeh, Diana9; Bartha, Sandor10; Beck, Ryan11; Blenkinsopp, Theodore7; Cahill, James7; Campetella, Giandiego12; Canullo, Roberto12; Chelli, Stefano12; Enrico, Lucas13; Fraser, Lauchlan14; Hao, Xiying11; Henry, Hugh A. L.15; Hohn, Maria16; Jouri, Mohammad Hassan17; Koch, Marian18; Lawrence Lodge, Rachael19; Li, Frank Yonghong20; Lord, Janice M.19; Milligan, Patrick21; Minggagud, Hugjiltu20; Palmer, Todd21; Schröder, Birgit18; Szabó, Gábor22; Zhang, Tongrui20; Zimmermann, Zita10; Verbruggen, Erik1

Published Aug 30, 2023 on Dryad. https://doi.org/10.5061/dryad.0k6djhb4z

Abstract

Environmental circumstances shaping soil microbial communities have been studied extensively. However, due to disparate study designs, it has been difficult to resolve whether a globally consistent set of predictors exists, or context-dependency prevails. Here, we used a network of 18 grassland sites (11 of those containing regional plant productivity gradients) to examine i) if similar abiotic or biotic factors predict both large-scale (across sites) and regional-scale (within sites) patterns in bacterial and fungal community composition, and ii) if microbial community composition differs consistently at two levels of regional plant productivity (low vs high). We found that bacteria were consistently associated with certain soil properties and both bacteria and fungi were consistently associated with plant community composition within different sites. Moreover, there was a microbial community signal that clearly distinguished high and low-productivity soils that was shared across different grasslands independent of their location in the world. In this study, we show that there is high congruence between predictors of bacterial and fungal community composition at different spatial scales and that regional productivity differences are typified by characteristic soil microbial communities across the grassland biome. These results suggest that it might be feasible to predict the overall effects of global changes on soil microbial community composition in different grasslands, as well as to discriminate fertile from infertile systems using generally applicable microbial indicators.

README: Consistent predictors of microbial community composition across spatial scales in grasslands reveal low context-dependency

Summary of methods:
Data were collected from 18 Herbaceous Diversity Network (HerbDivNet) grassland sites located in 12 countries.
Each of the 18 sites contained between two and six 8 × 8 m plots: 11 sites contained six plots, one site contained four plots, one site three plots and five sites contained two plots; giving a total of 83 plots.
Most sites were chosen to represent a site-specific gradient in productivity based on their plant biomass production;
A clear gradient in biomass production (low vs. high) was captured in 11 sites.
For each plot within a site, five soil subsamples to a depth of 10 cm were taken from four corners and the centre of the plot.
Subsamples for microbial analyses were analysed separately (83 x 5), and soil properties were analysed from one composite sample per plot (n = 83).

The dataset includes the following files:

otu_b.txt - rarefied OTU table for bacterial communities (with 5 samples per plot)
map_b.txt - metadata file linked to the bacterial OTU table
tax_b.txt - table containing taxonomic information for bacterial OTUs
otu_f.txt - rarefied OTU table for fungal communities (with 5 samples per plot)
map_f.txt - metadata file linked to the fungal OTU table
tax_f.txt - table containing taxonomic information for fungal OTUs
plant_genera_abundance.txt - table with the abundances of plant genera per plot
map_general.txt - an overall map data table with information about sites, soil properties, climate, biomass, coordinates, bacterial and fungal biomass per plot
map_prod_levels.txt - a map data table with the same information as before, specifically for the sites that contain plant productivity gradient
R_script_full - R script describing the steps taken in the analyses

Missing data codes: NA

Description of the data and file structure

Data-specific information for otu_b.txt - Number of rows = 485 (5 replicate samples collected from 83 plots including technical replicates and failed/repeated samples) - Number of columns = 19248 (bacterial OTUs)
Data-specific information for map_b.txt - Number of rows = 461 (5 replicate samples collected from 83 plots including technical replicates) - row names to be matched with row names of otu_b.txt - Number of columns = 9 continent - where the sites are located short_site - short names of the site plot - the number of the plot within the site site_plot - combination of the site name and plot number sample - 1 to 5 samples taken per plot rep - 1 = used in the analysis, r = technical replicate (not used in the analyses) real - 1 = samples used in the analyses, 2 = samples not used in the analyses upsam - samples that were upsampled during rarefaction (yes), and the other samples (no) site_long - full name of the countries where the sites were located
Data-specific information for tax_b.txt - Number of rows = 19248 (OTUs) - to be matched with otu_b.txt - Number of columns = 7 Domain Phylum Class Order Family Genus
Species
Data-specific information for otu_f.txt - Number of rows = 462 (5 replicate samples collected from 83 plots including technical replicates and failed/repeated samples) - Number of columns = 13967 (fungal OTUs)
Data-specific information for map_f.txt - Number of rows = 451 (5 replicate samples collected from 83 plots including technical replicates) - row names to be matched with otu_f.txt - Number of columns = 8 continent - where the sites are located short_site - short names of the site plot - the number of the plot within the site site_plot - combination of the site name and plot number sample - 1 to 5 samples taken per plot rep - 1 = used in the analysis, r = technical replicate (not used in the analyses) real - 1 = samples used in the analyses, 2 = samples not used in the analyses site_long - full name of the countries where the sites were located
Data-specific information for tax_f.txt - Number of rows = 13967 (OTUs) - to be matched with otu_f.txt - Number of columns = 12 OTU phylum class order family genus
species trophicMode - possible trophic status (includes combinations of different possibilities) troph1 - the first possible trophic status (used in the study) troph2 - the second possible trophic status guild guild_long
Data-specific information for plant_genera_abundance.txt - Number of rows = 83 - row names to be matched with plot aggregated data of otu_b\, otu_f (site_short) and site_short of map_general.txt - Number of columns = 566 - plant genera
Data-specific information for map_general.txt - Number of rows = 83 - Number of columns = 38 site_short - short names of the site plot - the number of the plot within the site site_plot - combination of the site name and plot number Ndep - atmospheric nitrogen deposition derived from Ackerman et al. (2018). [kg/ha/yr] Biomass - average peak biomass production per plot [g/m2] Litter - per plot [g/m2] Total_biomass - per plot [g/m2] Sp_richness - species richness per plot Latitude - plot latitude [decimal degrees] Longitude - plot longitude [decimal degrees] Elevation [m] prec - mean annual precipitation [mm/year] derived from the CHELSA database temp - mean annual temperature [°C] derived from the CHELSA database ph_KCl - pH measured in KCl H - hydrogen H+ [meq/100g] Ca - calcium [meq/100g] K - potassium [meq/100g] Mg - magnesium [meq/100g] Na -sodium [meq/100g] Al - aluminium [meq/100g] Fe - iron [meq/100g] Mn - manganese [meq/100g] CEC - cation exchange capacity [meq/100g] BS - base saturation [%] P_Olsen - extractable phosphorus Olsen [mg/kg - ppm] P_Bray - extractable phosphorus Bray [mg/kg - ppm] P - total phosphorus [mg/kg - ppm] N - total nitrogen [%] C - total carbon [%] CN_ratio - C:N SOM - soil organic matter [%] BD - bulk density [kg/m3] Sand [%] Clay [%] Silt [%] Fcopies_g - number of fungal gene copies per gram of dry soil Bcopies_g - number of bacterial gene copies per gram of dry soil F_B - ratio of fungal to bacterial copies
Data-specific information for map_prod_levels.txt - Number of rows = 44 - Number of columns = 38 contains the same variables as in the previous file f_group - productivity level (l-low, h-high)

Sharing/Access information

Links to other publicly accessible locations of the data:
NA

Data was derived from the following sources:

N deposition: https://doi.org/10.1029/2018GB005990
Climatic variables: https://chelsa-climate.org/
Plant biomass and richness: DOI: 10.1126/science.aab3916

Code/Software

Methods

Data were collected from 18 Herbaceous Diversity Network (HerbDivNet) grassland sites located in 12 countries. Each of the 18 sites contained between two and six 8 × 8 m plots: 11 sites contained six plots, one site contained four plots, one site three plots and five sites contained two plots; giving a total of 83 plots. Most sites were chosen to represent a site-specific gradient in productivity based on their plant biomass production; with six plots (two replicates of low, medium and high productivity) located within the same region with little to no variation in climatic conditions. However, some sites contained fewer plots and did not show a prominent productivity gradient. A clear gradient in biomass production was captured in 11 sites. For each plot within a site, five soil subsamples to a depth of 10 cm were taken from four corners and the centre of the plot. Subsamples for microbial analyses were analysed separately, and soil properties were analysed from one composite sample per plot (n=83).

Plant species presence and total aboveground biomass were measured from each m² of each 64 m² plot in a single event at the peak of the growing season. Mean annual precipitation (MAP) and temperature (MAT) were derived from the CHELSA database on the geographical position (latitude and longitude) of each plot. Data on total inorganic nitrogen deposition [kg/ha/yr] were derived from Ackerman et al. (2018). We analysed 14 soil properties: soil organic matter (SOM), total nitrogen (N), total carbon (C), total phosphorus (P), available P, base saturation (BS), cation exchange capacity (CEC), pH, soil texture (sand, clay, silt), extractable Ca, Mg and K. The bacterial 16S V4 region was amplified using the 515F-806R primer pair and the fungal ITS1 region was amplified using general fungal primers ITS1 and ITS2. The abundance of bacterial and fungal gene copies per sample was quantified using qPCR targeting the 16s V4 region for bacteria and the 18s region for fungi.