The relationship between biodiversity and biomass is a long-standing ecological debate, initially explored in plant communities. Resource availability is a key regulator, often resulting in a unimodal (humped-back) relationship between plant diversity and productivity. This pattern is explained by resource stress at low biomass levels, leading to positive associations, and competitive exclusion at high biomass levels, resulting in negative correlations. While the diversity and biomass of soil microbial communities are crucial for ecosystem functions like organic matter decomposition and nutrient cycling, their interrelationship across global biomes remains poorly understood. Previous studies have suggested that competitive exclusion might be less important in belowground communities due to spatial separation, but recent research challenges this view. Soil carbon (C) content is a key driver of belowground productivity and microbial biomass. Studies have shown a strong correlation between soil organic C content and microbial diversity. Given the vulnerability of soil C to climate change and land-use intensification, understanding the diversity-biomass relationship is crucial. This study hypothesizes that soil C content is a major driver of this relationship across global biomes and that the microbial diversity-to-biomass ratio serves as an integrative proxy for understanding their interlinkage. Two hypotheses are explored: the Stress Gradient Hypothesis, suggesting higher diversity relative to biomass in stressful, low C environments; and competitive exclusion, predicting a humped-back relationship and reduced diversity-to-biomass ratio in C-rich environments. The study aims to examine the relationships between microbial diversity and biomass, their effects on ecosystem functions, and the environmental factors controlling these relationships across various biomes, focusing on bacteria and fungi due to their abundance and diversity.

The introduction extensively reviews the existing literature on the biodiversity-biomass relationship, primarily focusing on plant communities and highlighting the 'humped-back' model and its underlying mechanisms (resource stress and competitive exclusion). It then transitions to the soil microbial context, noting the limited understanding of the diversity-biomass relationship in this area and the influence of factors like soil carbon content. The review also discusses contrasting views on the role of competitive exclusion in belowground communities and cites studies supporting a correlation between soil organic carbon and microbial diversity.

A global field survey was conducted between 2016 and 2017, collecting 435 soil samples from 87 locations across five continents. The locations encompassed diverse ecosystems (cold forests, dry forests, grasslands, etc.) and climates. A standardized sampling protocol was followed, collecting five composite soil samples per location to account for within-plot heterogeneity. Soil properties (pH, texture, available phosphorus, soil organic carbon) were measured using standard protocols. Microbial biomass was estimated using phospholipid fatty acid (PLFA) analysis, while microbial diversity (bacterial and fungal) was assessed through amplicon sequencing (Illumina MiSeq) targeting the 16S and 18S rRNA genes. Bioinformatics analysis was performed using QIIME, USEARCH, and UNOISE3 to identify amplicon sequence variants (ASVs). The data were rarefied to ensure even sampling depth. A richness-to-biomass ratio, standardized between 0 and 1, was calculated for both bacterial and fungal communities. Statistical analyses included PERMANOVA, ANOVA, Random Forest analysis, linear/quadratic regression, structural equation modeling (SEM), and Cubist regression for global prediction mapping. SEM was used to explore the relationships among abiotic (pH, soil C, texture), biotic (microbial biomass, vegetation type, plant cover), and climatic factors (mean annual temperature and precipitation) on microbial richness and the richness-to-biomass ratio. Cubist regression was used to predict the global distribution of microbial biomass and the richness-to-biomass ratios using environmental covariates from global databases (SoilGrids, WorldClim, Globcover2009).

The study revealed a unimodal (humped-back) relationship between soil microbial biomass and diversity across global biomes, even when excluding tropical soils with high biomass. SEM analysis indicated that soil C content indirectly influences microbial diversity through changes in microbial biomass. Soil C content was a key driver of the diversity-to-biomass ratio for both bacterial and fungal communities. Soil C content correlated positively with both microbial biomass and diversity, but the correlation was stronger for biomass. The slope of the linear relationship between soil C and microbial biomass was higher than that between soil C and microbial richness. This suggests that soil C content has a stronger effect on biomass than richness, contributing to the negative relationship between soil C content and the richness-to-biomass ratio. The negative relationship between soil C content and the richness-to-biomass ratio held across different ecosystems, except for fungal communities in moss heaths. The study also found that while soil pH and texture influence microbial richness, soil C content has a greater impact on regulating the richness-to-biomass ratio. Global prediction mapping using Cubist regression illustrated the geographical distribution of microbial biomass and the richness-to-biomass ratios.

The findings support the hypotheses that soil C content is a crucial driver of the microbial diversity-biomass relationship and that the diversity-to-biomass ratio is a useful indicator of this relationship. The observed patterns can be explained by the Stress Gradient Hypothesis and competitive exclusion. In stressful, low C environments, facilitation and niche partitioning promote higher diversity relative to biomass. Conversely, in C-rich environments, increased biomass may lead to competitive exclusion, reducing diversity. The study's results have significant implications for understanding how changes in soil C content, due to land-use change and climate change, may drastically alter microbial community structure and function. The stronger influence of soil C on microbial biomass compared to richness suggests that these changes could have more pronounced effects on biomass, potentially altering ecosystem processes.

This study demonstrates the crucial role of soil carbon content in shaping the relationship between soil microbial diversity and biomass across global biomes. The diversity-to-biomass ratio serves as a valuable indicator of this relationship and its sensitivity to environmental changes. Future research should explore the functional consequences of altered diversity-biomass ratios in response to ongoing environmental change, focusing on specific ecosystem processes and functional groups.

The study acknowledges that causal relationships between soil C content and microbial biomass are complex, as soil C originates from multiple sources, and microbial activity contributes to soil C stabilization. The use of a single fatty acid (18:206) as a fungal biomass indicator is also a limitation, as this fatty acid can originate from other eukaryotic cells. The global prediction mapping relies on existing databases with limitations in resolution and data coverage, warranting future validation efforts.