Data from: Soil pathogen and mutualist mediation of productivity response to biodiversity: candidate mechanisms and evidence
Data files
Jul 02, 2026 version files 470.50 KB
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Experimental_Design.csv
11.64 KB
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Predicted_biomass.csv
454.88 KB
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README.md
3.98 KB
Abstract
Microbiome feedbacks likely contribute to positive productivity responses to plant diversity through multiple mechanisms. Pathogen dilution may enhance productivity, whereas mutualists could strengthen or weaken diversity effects depending on the degree of host specialization. We tested candidate mechanisms in grassland plots varying in plant richness and family composition that received one of three soil microbiome treatments: post-agricultural microbes, prairie arbuscular mycorrhizal (AM) fungi, or whole prairie soil containing whole microbiome communities. Positive productivity responses to diversity (overyielding) depended on interactions between plant family composition and initial microbiomes. Overyielding, measured by the complementarity effect, increased strongly with host pathogen specialization, consistent with dilution of specialist pathogens. In contrast, AM fungal specialization reduced overyielding, consistent with positive plant-soil feedback. Pathogen dilution effects were strongest when AM fungal specialization was low. Neither rhizobial specialization nor symbiont diversity mediated overyielding. These results demonstrate opposing and interactive microbial controls on biodiversity–productivity relationships.
Dataset DOI: 10.5061/dryad.c866t1gnx
Description of the data and file structure
A large-scale biodiversity manipulation was conducted near Lawrence, KS, USA. Plots were planted to one of the following species richness levels: 1, 2, 3, 6, or 18 species. Each multi-species plot consisted of either 1, 2, or 3 representative plant families (Poaceae, Fabaceae, and Asteraceae). Plots were inoculated with one of three soil microbiomes: prairie AM fungi, whole prairie soil, or sterile soil. In years 1-5, percent cover of planted species was visually estimated within each plot. Beginning in year 2, biomass was harvested and separated by species. These values were then used to predict year 1 biomass. Biomass was not harvested in year 1, so as not to hinder plant establishment.
Files and variables
File: Experimental_Design.csv
Description: This file lays out the overarching experimental design of the large-scale field experiment. The total experimental design consisted of 432 plots ("Plot") divided into 2 blocks ("BLOCK"). Each block contained three sub-blocks ("SUBBLOCK"). Plots were inoculated with one of three soil inoculations ("INOC"; codes described below). Plots were planted to one of five species richness levels (SPPNO), containing either 1, 2, 3, 6, or 18 species. Each multi-species plots consisted of either 1, 2, or 3 representative plant families (Poaceae, Fabaceae, and Asteraceae), represented by "PHYLO4". "DISPERSION" represents binary over- (multiple families) or under-dispersion (single family). "DISPERSIONNUM" represents number of families present, as multi-family plots could contain two or three plant families.
Variables
- Plot
- BLOCK
- SUBBLOCK
- INOC
- SPPNO
- DISPERSION
- DISPERSIONNUM
- PHYLO4
Soil inoculation codes (INOC):
AMF = Native arbuscular mycorrhizal fungi;
PR = whole prairie soil, containing entire suite of soil microbiome (i.e. filed AMF, bacteria, pathogens, etc.);
ST = steam-pasteurized field soil
File: Predicted_biomass.csv
Description: This file lays out the data collected from the large-scale field experiment. The total experimental design consisted of 432 plots ("PLOTNO"). "PERCENTCOVER" represents the canopy cover of that species within the plot, whereas "PLOTCOVER" represents sum cover of planted species within each plot. For example, Plot 1 contains two planted species ("SPPID"=CORTIN and DALCAN; species codes described below); CORTIN has a "PERCENTCOVER" of 10 and DALCAN has a "PERCENTCOVER" of 5; therefore, "PLOTCOVER" is 15. "BIOMASS" and "PLOTBIOMASS" (in grams) operate in a similar manner. Beginning in year 2 (2019), biomass was harvested from strips within plots to estimate plot-level productivity and then correlated with "PERCENTCOVER". These data were then used to predict SppBiomass in year 1 (2018).
Variables
- PLOTNO
- SPPID
- PLOTSPP
- PERCENTCOVER
- PLOTCOVER
- BIOMASS
- PLOTBIOMASS
- SppBiomass.g
- YEAR
Species codes (SPPID):
CORTIN = Coreopsis tinctoria (Asteraceae);
ECHPAL = Echinacea pallida (ASTERACEAE);
EUPALT = Eupatorium altissimum (Asteraceae);
HELMOL = Helianthus mollis (Asteraceae);
LIAPYC = Liatris pycnostachya (Asteraceae);
SILINT = Silphium integrifolium;
AMOCAN = Amorpha canescens (Fabaceae);
CHAFAS = Chamaecrista fasciculata (Fabaceae);
DALCAN = Dalea candida (Fabaceae);
DALPUR = Dalea pupurea (Fabaceae);
DESCAN = Desmodium canadense (Fabaceae);
DESILL = Desmanthus illinoensis (Fabaceae);
ANDGER = Andropogon gerardii ;
BOUGRA = Bouteloua gracilis;
ELYCAN = Elymus canescens;
PANVIR = Panicum virgatum;
SCHSCO = Schizachyrium scoparium
Code/software
All data was analyzed in R
Access information
Other publicly accessible locations of the data:
- N/A
Data was derived from the following sources:
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