Cover crop mixtures enhance multiple ecosystem functions: A global meta-analysis
Data files
May 30, 2025 version files 179.21 KB
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Aboveground_biomass.csv
27.40 KB
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Acidic_PH.csv
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Actinomycetes_abundance.csv
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Alkaline_PH.csv
4.04 KB
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Available_nitrogen.csv
7.55 KB
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Available_phosphorus.csv
9.45 KB
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Available_potassium.csv
8.99 KB
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Bacteria_abundance.csv
2.46 KB
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Bacteria_Chao1.csv
1.07 KB
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Bacteria_Shannon.csv
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Bulk_density.csv
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Carbon_accumulation.csv
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Catalase_activity.csv
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Crop_yield.csv
12.73 KB
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Electrical_conductivity.csv
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Fungal_abundance.csv
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Fungal_Chao1.csv
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Fungal_Shannon.csv
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Microbial_biomass_carbon.csv
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Microbial_biomass_nitrogen.csv
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Nitrogen_accumulation.csv
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Organic_matter.csv
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Phosphatase_activity.csv
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Phosphorus_accumulation.csv
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Polyphenol_Oxidase_activity.csv
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Potassium_accumulation.csv
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README.md
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Soil_moisture_content.csv
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Sucrase_activity.csv
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Total_nitrogen.csv
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Total_phosphorus.csv
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Total_porosity.csv
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Total_potassium.csv
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Urease_activity.csv
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Abstract
Cover crop mixtures have been increasingly adopted across agroecosystems worldwide thanks to their potential to improve soil health and ecosystem functioning. However, it is not clear whether and how cover crop mixtures vs. single cover crops might influence different ecosystem functions.
Here, we selected 1,895 paired data from 61 studies worldwide to evaluate the role of cover crop mixtures in affecting biomass production, soil properties, and subsequent main crop yields in comparison with single cover crops. We also assessed whether the number of plant species in cover crop mixtures, crop field types, and cover crop combinations could affect ecosystem functioning.
Multi-species mixtures increased cover crop aboveground biomass by 21.7%, carbon and nutrient accumulation (C: +27.7%, N: +27.7%, P: +22.8%, K: +24.1%), and subsequent crop yields by 4.9% compared to single cover crops. These benefits were most pronounced in paddy fields (e.g., a 35.3% increase in biomass), as well as in specific species combinations such as milk vetch-rapeseed (32.8%) and milk vetch-ryegrass (36.0%).
Also, multi-species cover crop mixtures increased subsequent soil moisture content (+1.5%), total soil nitrogen (+5.8%), soil microbial carbon (+37.8%), soil microbial nitrogen (+37.6%), Chao1 index of fungi (+12.6%), and decreased soil bulk density (-7.0%), soil electrical conductivity (-9.5%), and polyphenol oxidase activity (-7.0%). However, effects on soil pH, organic matter, and most nutrients were neutral unless specific combinations.
Synthesis and applications. Multi-species cover crop mixtures significantly enhance agroecosystem productivity and soil health, particularly in paddy systems and when combining functionally complementary species (e.g., legumes with Cruciferae, legumes with Gramineae). Farmers and policymakers should prioritize tailored mixtures over monocultures to optimize biomass production, nutrient cycling, and yield resilience. For maximum impact, mixtures should align with local conditions—such as using milk vetch-rapeseed or milk vetch-ryegrass in humid regions—to advance sustainable agriculture and climate adaptation goals globally.
Dataset DOI: 10.5061/dryad.m37pvmdf3
Description of the data and file structure
This global meta-analysis dataset comprises 1,895 paired observations extracted from 61 peer-reviewed articles across 55 experimental sites worldwide. Data were systematically organized into specialized CSV files corresponding to specific ecosystem response variables (e.g., microbial biomass, nutrient cycling, soil physical properties). For each pairwise comparison between cover crop mixtures and monocultures, we extracted:
Mean values (Xmixtures, Xmonocultures)
Standard deviations (SDmixtures, SDmonocultures)
Replicate counts (Nmixtures, Nmonocultures)
Data classification was implemented through four key dimensions:
Cover crop complexity: Binary classification by species count (mix2 = 2-species mixtures, mix3 = 3+-species mixtures)
Crop field types: Agricultural systems categorized as paddy fields, wheat fields, tobacco fields, corn fields, orchards, or other systems
Botanical taxonomy: Cover crop family combinations (e.g., Fabaceae-Poaceae pairings)
Species-specific mixtures: Identified combinations used in pairwise analyses (e.g., Vicia faba + Secale cereale)
Methodologically, numerical data were extracted from figures using GetData Graph Digitizer 2.26, with soil organic carbon values converted to organic matter via the van Bemmelen factor (1.724). To support advanced statistical modeling, we implemented a hierarchical identification system where:
Study = Unique publication identifier
Experiment = Site-year combination code (e.g., Brazil_2019)
These identifiers enable proper accounting of random effects in meta-analytic models, ensuring robust quantification of cover crop mixture impacts on ecosystem functions. The file-per-variable structure optimizes reusability while maintaining cross-file consistency in core metadata columns.
Files and variables
File list:
- Microbial_biomass_carbon.csv:Measurements of soil microbial biomass carbon
- Total_phosphorus.csv:Total phosphorus content in soil samples
- Microbial_biomass_nitrogen.csv:Measurements of soil microbial biomass nitrogen
- Total_potassium.csv :Total potassium content in soil samples
- Phosphatase_activity.csv :Soil phosphatase enzyme activity levels
- Fungal_Chao1.csv :Fungal community richness (Chao1 index)
- Urease_activity.csv: Soil urease enzyme activity levels
- Phosphorus_accumulation.csv: Phosphorus accumulation in plant tissues
- Potassium_accumulation.csv: Potassium accumulation in plant tissues
- Soil_moisture_content.csv: Volumetric soil water content measurements
- Sucrase_activity.csv: Soil sucrase enzyme activity levels
- Polyphenol_Oxidase_activity.csv: Soil polyphenol oxidase enzyme activity levels
- Total_nitrogen.csv: Total nitrogen content in soil samples
- Fungal_abundance.csv: Absolute abundance of soil fungal communities
- Total_porosity.csv: Total pore space measurements in soil
- Nitrogen_accumulation.csv: Nitrogen accumulation in plant tissues
- Organic_matter.csv: Soil organic matter content measurements
- Fungal_Shannon.csv: Fungal community diversity (Shannon index)
- Electrical_conductivity.csv: Soil electrical conductivity measurements
- Crop_yield.csv :Crop yield measurements under different cover crop treatments
- Bulk_density.csv :Soil bulk density measurements
- Bacteria_Shannon.csv :Bacterial community diversity (Shannon index)
- Catalase_activity.csv: Soil catalase enzyme activity levels
- Carbon_accumulation.csv: Carbon accumulation in plant tissues
- Bacteria_Chao1.csv :Bacterial community richness (Chao1 index)
- Bacteria_abundance.csv :Absolute abundance of soil bacterial communities
- Available_nitrogen.csv: Plant-available nitrogen content in soil
- Available_potassium.csv :Plant-available potassium content in soil
- Available_phosphorus.csv :Plant-available phosphorus content in soil
- Alkaline_PH.csv: Soil pH measurements in alkaline conditions
- Actinomycetes_abundance.csv: Absolute abundance of soil actinomycetes communities
- Aboveground_biomass.csv: Aboveground plant biomass measurements
- Acidic_PH.csv: Soil pH measurements in acidic conditions
Variables
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Study:Publication identity
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Experiment:A unique combination of site and year
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Mixtures:Number of cover crop species (mix2 = 2 species, mix3 = 3 species)
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Crop Field Types:the type that crops field classified by their species (paddy fields, wheat fields, tobacco fields, corn fields, orchards, and others)
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Cover Crop Families:the family which plant belongs to
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Cover Crop Species:specific cover crop species mixtures in the pairwise analysis
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Xmixtures:the mean value of the response variable under multi-species cover crop mixtures
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SDmixtures:refer to the standard deviation for the mixtures groups
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Nmixtures:the number of replicates with multi-species cover crop mixtures
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Xmonocultures:the mean value under the corresponding monocultures of each species included in the mixture
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SDmonocultures:refer to the standard deviation for the monocultures groups
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Nmonocultures:the number of replicates with mono-species cover crops
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\:The symbol\indicates missing standard deviation (SD) values where:\ in SDmixtures columns = Original publications did not report SD for cover crop mixture treatments
\ in SDmonocultures columns = Original publications did not report SD for monoculture control treatments
This notation applies uniformly across all data files.
