DOI: 10.5061/dryad.qh5js47
title: Data from: High throughput sequencing combined with null model tests reveals specific plant-fungi associations linked to seedling establishment and survival

description: 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.
description: Seedling establishment
 dataSeedling 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.csvSeedling survival dataSeedling 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.csvOTU Abundance tablePer plot abundance of each OTU.dryad_data_otu_table.csv