1. Plant-fungal interactions are important for plant community assembly, but quantifying these relationships remains challenging. High throughput sequencing of fungal communities allows us to identify plant-fungal associations at a high level of resolution, but often fails to provide information on taxonomic and functional assignment of fungi.
2. We transplanted seeds of Pinus cembra across an elevational gradient (1850-2250 m a.s.l.) and identified environmental factors and known fungal associates important for seedling establishment and survival. We then applied null model tests to identify taxonomically unassigned fungi associated with pine recruitment.
3. Early seedling establishment was positively associated with multiple abiotic factors, while seedling survival was positively associated with the absence of a known pathogenic fungus and other biotic factors. Null model tests identified known mycorrhizal partners and a large number of unassigned operational taxonomic units (OTUs) associated with seedling survival, including mycorrhizal, saprotrophic and pathogenic species.
4. Synthesis: We conclude that high throughput metabarcoding paired with null model tests, is a valuable approach for identifying hidden plant-fungal associations within large and complex DNA metabarcoding datasets. Such an approach can be an important tool in illuminating the black box of plant-microbe interactions, and thus understanding ecosystem dynamics.
Seedling establishment data
Seedling establishment data. Abbreviated column names are as follows: "canopy_open_calc" = % of canopy openness, "distance_to_fertile_tree" = m of distance to P. cembra, "ecm_shannon" = Shannon diversity of ECM fungi, "germinated" = Proportion of established seeds, "ID_replicate" = ID, "Mean_daily_max_hot_3m" = mean daily maximum temperature (°C )for the hottest three months, "Mean_daily_max_Jul" = mean daily maximum temperature (°C) for the hottest month (i.e. July), "Mean_daily_mean_hot_3m" = mean daily mean temperature (°C ) for the hottest three months, "Mean_daily_mean_Jul" = mean daily maximum temperature (°C) for the hottest month, "mean_soil_mean" = % of soil moisture, "not_germinated" = Proportion of unestbalished seedlings, "otu_1198_abund" = Plot abundance of OTU 1198, "otu_282_abund" = Plot abundance of OTU 282, "plot_ID" = plot ID, "reg" = valley (D = Flüela, S = Sertig), "season" = sampling year, "shrubs" = % of ground vegetation cover.
dryad_data_germ.csv
Seedling survival data
Seedling survival data. Abbreviated column names are as follows: "canopy_open_calc" = % of canopy openness,
"distance_to_fertile_tree" = m of distance to P. cembra, "ecm_shannon" = Shannon diversity of ECM fungi, "ID_replicate" = ID, "Mean_daily_max_hot_3m" = mean daily maximum temperature (°C )for the hottest three months, "Mean_daily_max_Jul" = mean daily maximum temperature (°C) for the hottest month (i.e. July), Mean_daily_mean_cold_3m" = mean daily mean temperature (°C) for the coldest three months, "Mean_daily_mean_hot_3m" = mean daily mean temperature (°C ) for the hottest three months,
"Mean_daily_mean_Jan" = mean daily mean temperature (°C) for the coldest month (i.e. January), "Mean_daily_mean_Jul" = mean daily maximum temperature (°C) for the hottest month, "Mean_daily_min_cold_3m" = mean daily minimum temperature (°C) for the coldest three months, "Mean_daily_min_Jan" = mean daily minimum temperature (°C) for the coldest month (i.e. January), "mean_soil_mean" = % of soil moisture, "otu_1198_abund" = Plot abundance of OTU 1198, "otu_282_abund" = Plot abundance of OTU 282, "plot_ID" = plot ID, "reg" = valley (D = Flüela, S = Sertig),"season" = sampling year, "shrubs" = % of ground vegetation cover, "surviving_seedling" = seedling survived until the second year (1) or not (0).
dryad_data_surv.csv
OTU Abundance table
Per plot abundance of each OTU.
dryad_data_otu_table.csv