Global change alters the abundance and community structure of arbuscular mycorrhizal fungi and influences plant mycorrhizal benefit
Data files
Nov 19, 2025 version files 762.99 KB
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data_and_code.zip
760.32 KB
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README.md
2.67 KB
Abstract
Arbuscular mycorrhizal (AM) fungi play critical roles in ecosystem services and exhibit sensitivity to global change factors (GCFs). However, the interactive effects of multiple GCFs on AM fungal communities, and whether changes in AM fungal have a feedback effect on plant mycorrhizal benefits under global change remain poorly understood. We synthesized 1,646 observations of arbuscular mycorrhizal (AM) fungal communities from field experiments to evaluate how manipulated GCFs affect their abundance and community structure and to determine the potential consequences for outcomes of plant-mycorrhizal fungal relationships. The interactive effects among GCFs were mainly additive rather than synergistic or antagonistic. AM fungal diversity was not consistently sensitive to the individual effects of GCFs; however, a significant shift in community structure occurred under individual or concurrent GCFs. When multiple factors were imposed simultaneously, their negative effect on AM fungal colonization was strengthened, while their effects on community structure were diminished. Moreover, plant performance was closely linked to changes in abundance and community structure of AM fungi under GCFs. Experimental duration and environmental variables emerged as the most important predictors of AM fungal responses to GCFs. Reordering or replacement of AM fungal species has been identified as the key mechanism driving community responses to GCFs. Our study highlights the need to monitor AM fungal community structure and associated functional consequences for plant communities under ongoing global change.
This data_and_code.zip contains the data and R scripts associated with "Global change alters the abundance and community structure of arbuscular mycorrhizal fungi and influences plant mycorrhizal benefit" by Ren et al. These files include basic data, R scripts.
Description of the data and file structure
The data and code folder contains all files and data related to analyses run using the R package. The files include:
R scripts:
code.txt--R Script for Data Visualization (Figure 2; Figure 4; Figure 5; Figure 6).
The first row of both the CSV and Excel files has been annotated to define all abbreviations used in the tables. Additionally, the specific figure that each table corresponds to has been indicated.
csv files:
colonization.csv--This dataset, along with the accompanying code, allows for the reproduction of Figure 2. Primary focus on associations between global change factors and their effects on arbuscular mycorrhizal (AM) fungal.
env.csv and rich.csv --This dataset, along with the accompanying code, allows for the reproduction of Figure 6. Primarily displays the matrix of correlation coefficients between multiple metrics of AM fungi and a series of abiotic factors.
paraglomus1.csv--This dataset, along with the accompanying code, allows for the reproduction of Figure 5. Primarily investigates the relationships between global change factors and parameters of arbuscular mycorrhizal fungi.
xlsx files:
original dataset.xlsx--Raw Data Extracted for Meta-Analysis. Includes soil chemical characteristics (pH, available P g/kg, nitrate-nitrogen g/kg, ammonium-nitrogen g/kg, organic carbon g/kg, total N g/kg, total P g/kg), environmental mean annual temperature (MAT), latitude and longitude, mean annual precipitation (MAP)), AM fungal abundance (including root colonization, extraradical hyphae length, and spore density), richness (the total number of species or taxa present, based on morphology [spore taxonomy] or genetics [OTU numbers]), Shannon diversity index, beta diversity (the magnitude of similarity in species composition among different sites) and the community structure.
Code and software
R version 4.3.3 was used to run analyses and create all figures. Annotations are provided in all scripts to guide data loading, analyses, and figure creation. The following packages are required:
Matrix; rJava; glmulti; metafor; readxl; vegan; rfPermute; psych; reshape2; pheatmap; jokergoo/ComplexHeatmap (built from GitHub, script contains code for install).