Data from: Aridity amplifies soil microbial influences and dampens plant diversity effects on lakeshore wetland multifunctionality
Data files
Mar 18, 2026 version files 46.55 KB
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data_of_JoE.csv
44.65 KB
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README.md
1.90 KB
Abstract
Lakeshore wetlands support multiple functions and services, including primary productivity, carbon storage, and nutrient cycling. However, empirical evidence on how ecosystem multifunctionality (EMF) in these intrazonal systems is regulated by climatic aridity, and how plant and microbial diversity jointly regulate EMF, remains scarce. In this study, we surveyed 15 natural lakeshore wetlands across the Mongolian Plateau, spanning a ~2,400 km gradient in climatic aridity, comprising 7 arid (aridity index > 0.8) and 8 semiarid (aridity index < 0.8) sites. Across these wetlands, we measured 12 ecosystem functions representing carbon, nitrogen, and phosphorus cycling, soil fertility, and productivity. We then assessed the relative importance of biotic (plant, bacterial, and fungal diversity at local α- and regional β-scales) and abiotic (soil moisture, pH, and seasonal climate) drivers of EMF. We found that most individual functions were negatively associated with increasing aridity, leading to a decline in EMF along the aridity gradient. In arid regions, both bacterial and fungal diversity increased with aridity at local (α) and regional (β) scales, thereby amplifying their positive contributions to EMF. In contrast, in semiarid regions, both plant and soil microbial diversity declined with aridity, while EMF was more jointly influenced by soil moisture, pH, and seasonal climatic variation. Our study shows that EMF in lakeshore wetlands reflects the interplay between local biodiversity and regional aridity. Biodiversity contributes to EMF in different ways across arid and semiarid regions, demonstrating that the strength and direction of biodiversity effects depend on climatic context. Together, these findings reveal that intrazonal wetlands, often overlooked in biodiversity–function research, maintain multifunctionality through region-specific mechanisms and offer practical guidance for restoring ecosystem functions in degraded wetlands.
Dataset DOI: 10.5061/dryad.x69p8czz8
Description of the data and file structure
Functional indicators, biodiversity data, and environmental factor data of the lakeshore wetland. It includes data on plants, soil microorganisms, soil properties, and climate.
Files and variables
File: data_of_JoE.csv
Description:
Variables
- ID: Number
- Lake: lake names
- Lake1: lake names
- site: sampling sites
- TN: soil total nitrogen (mg/g)
- AP: soil available phosphorus (mg/g)
- S_UE: soil urease (U/g)
- S_SC: soil saccharase (U/g)
- S_AKP: Soil alkaline phosphatase (U/g)
- SOC: soil organic carbon (mg/g)
- Plant_N: total nitrogen content of plants (mg/g)
- Plant_P: total phosphorus content of plants (mg/g)
- AGB: above-ground biomass (g/m²)
- BGB: below-ground biomass (g/m²)
- FluxCO2: soil CO2 flux (mg CO₂·m⁻²·h⁻¹)
- FluxN2O: soil N2O flux (mg CO₂·m⁻²·h⁻¹)
- pH: soil pH
- EC: soil electrical conductivity (μs/cm)
- AI: aridity index of climate indicators
- bacSimpson: bacterial Simpson index
- bacMPD: bacterial mean pairwise distance
- funSimpson: fungal Simpson index
- funMPD: fungal mean pairwise distance
- pltSimpson: plant Simpson index
- pltMPD: plant mean pairwise distance
- beta_pltMPD: plant beta mean pairwise distance
- beta_bacMPD: bacterial beta mean pairwise distance
- beta_funMPD: fungal beta mean pairwise distance
- beta_pltbray: plant Bray-Curtis index
- beta_bacbray: bacterial Bray-Curtis index
- beta_funbray: fungal Bray-Curtis index
Notes: The NA cells in the table indicate that the corresponding data were not calculated in this study.
Code/software
Excel
RStudio
All analyses and figures were calculated and drawn in R 4.5.1
