INTRODUCTION
The relationship between plant diversity and ecosystem functioning (BEF) has been a long-standing interest in ecology, driven by the need to understand the consequences of biodiversity decline in the face of global change on ecosystem functions, services, and human well-being . Recent studies have also highlighted the role of soil biodiversity in supporting multiple ecosystem functions and services , including soil nutrient cycling, carbon storage, and erosion prevention . Furthermore, several factors influencing belowground functioning have gained substantial attention within the scientific, geopolitical, and public attention . Recent evidence suggests that the relationship between plant and soil biodiversity and their function is context- dependent , however the biotic and environmental factors shaping these relationships are not well understood. For instance, the influence of soil biodiversity on function may depend on ecosystem water availability . Moreover, growing evidence indicates that microbial diversity significantly co-shapes the positive relationship between plant diversity and ecosystem function . Nevertheless, experimental studies that consider the interplay between plant and soil biodiversity in influencing function under varying climatic conditions, such as water availability, remain scarce. Therefore, incorporating above-belowground interactions into BEF research is essential to achieve a mechanistic understanding of BEF relationships in the context of climate change.
The interplay between plants and microbes involves numerous above- and belowground interactions (e.g., mutualisms and pathogenesis), which have substantial implications for BEF relationships . On one hand, soil microbial diversity can independently have a positive impact on plant nutrient uptake by promoting nutrient cycling . However, the relative contribution of soil microbial diversity to nutrient availability may depend on the functional groups within the plant community. Indeed, plant functional groups (PFGs) sharing similar ecological traits, such as nitrogen fixation or photosynthetic pathways, are known to influence the soil microbiome and associated soil functions . For instance, nitrogen (N)-fixing plants are known to promote keystone microbial taxa, such as Rhizobium spp. and Frankia spp. . Similarly, grasses and forbs, exhibit discernible traits and occupy specific ecological niches . Compared to forbs, perennial grasses have a higher belowground biomass leading to dense root systems . As a result, grass-dominated communities exhibit accelerated rates of litter decomposition and enhanced soil nutrient cycling . Consequently, variations in PFGs are likely to influence the composition of associated microbial communities , raising the question of how PFGs regulate soil microbial communities and their functions, and how this relationship varies across gradients of microbial diversity. However, the effects of plant functional richness and individual functional groups on soil microbial diversity and ecosystem processes remain unclear. Further, global change drivers and human activities threaten biodiversity and functioning, including potentially the relationships between plant and microbial diversity and soil processes in complex but unknown ways . Yet, there is a critical paucity of studies on the biotic interactions when assessing the effects of global change drivers on ecosystem functions . Lack of understanding of the relative contributions of plant functional richness, PFGs, and/or microbial diversity, and their interactions with environmental stresses on soil functions is a critical knowledge gap that constrains our predictive capacity and informed management strategies to mitigate the negative impacts of global change.
To bridge these knowledge gaps, we conducted an integrative experiment, simultaneously manipulating plant and soil microbial diversity while explicitly considering PFGs and plant functional diversity. We established a microcosm experiment with six plant species, categorized into three functional types (C3 grasses, C4 grasses, and legumes) in three levels of richness (1, 3, 6 species) and three levels of microbial diversity (high, intermediate, low), all under induced drought conditions. We formulated two primary hypotheses: (1) Soil microbial diversity loss will directly impact soil functions, undermining the linkage between plant diversity and function, particularly under drought conditions. (2) Plant functional groups will play a more significant role in buffering soil functions during drought than plant diversity. This effect arises from the varying capacity of different functional groups (C3 vs. C4 vs. legumes) to withstand abiotic stresses associated with drought conditions. Overall, this study investigates the complex interplay between soil microbial diversity, plant diversity, and PFGs, seeking to decipher their critical role in shaping plant-soil microbiome interactions under drought stress.
MATERIAL AND METHODS
Experimental design
We employed a factorial design to investigate the interactive effects of soil microbial diversity, plant functional diversity, and PFGs on various soil N and P pools and processes prior, during and after induced drought. Briefly, the design involved three dilution levels of soil microbial diversity (D0, D2, and D6) and three levels of plant species richness (1, 3, and 6 species). The plant species used wereChloris gayana , Digitaria eriantha (C4 grasses),Lolium perenne , Phalaris aquatica (C3 grasses),Biserrula pelecinus and Medicago sativa (legumes) (Figure S1). This design is considered incomplete because pots with 3 and 6 species composed of all PFGs were not included for logistic reasons. The plant diversity treatments were replicated six times and were identical for D0 (10-0 High), D2 (10-2 Intermediate) and D6 (10-6 Low) microbial diversity treatments, with no-plant controls included for each microbial diversity level. To account for airborne contamination throughout the experiment, the study also included five pots with sterile soil inoculated only with phosphate buffer saline (PBS) solution. In total, there were 33 treatments, for a total of 203 microcosms and five sampling events (Figure 1).
Soil microbial diversity manipulation
To manipulate indigenous soil microflora, we utilized the robust dilution-to-extinction approach, following well-established procedures . In brief, we collected soil from the top 15 cm of a regional grassland. Soil microbial inoculums representing high, intermediate, and low microbial diversity were created using a 10-fold dilution approach with phosphate buffer saline (PBS) as the buffer. Sterile soil was inoculated with a 9:1 ratio of soil to microbial inoculum, and a portion of the sterile soil was maintained with no microbial diversity (PBS solution only). Over 18 weeks of incubation, microbial colonization and biomass recovery were monitored and validated using amplicon sequencing and qPCR for bacterial 16S rRNA gene and fungal internal transcribed spacer (ITS) .
Microcosms and plant diversity establishment
To create the grassland microcosms, pots with an inner diameter of 14 cm and a height of 15 cm (1.9 L) were filled with (~1.9 kg) soil from the respective microbial diversity levels and subsampled (prior to planting, T0). Monoculture, three-species, and six-species microcosms were established using ~5 weeks old seedlings grown in sterile conditions. The allocation of seedlings was executed according to a pre-designed plant diversity pattern, ensuring consistency and replication across the experiment (Figure S1). All microcosms were arranged randomly in a climate-controlled glasshouse (temperature of 20/15℃ day/night, with a day length of 12 h day/night) .
Drought treatment and sampling
The microcosms were kept well-watered, at initial plant establishment period (T1) and early flowering stage (pre-drought, T2), and intermediate soil sampling was done using one soil core taken from each pot. The experiment was carried out in a glasshouse room with corresponding Spring and Summer temperatures from monthly averages up to 28/18℃ day/night, from September to January, based on the last 10-year monthly average data from Meteorological Bureau Station 067021 (http://www.bom.gov.au). After 16 weeks of plant establishment, a 2-week drought treatment was applied to half of the pots by reducing watering to 30% of water holding capacity (WHC), while the remaining pots were watered to maintain 60% of WHC. Gravimetric moisture was monitored daily during the drought period, and soil samples were collected (drought, T3) after 2 weeks of drought to assess the effects on soil functions. The final harvest of plant and soil samples (after-recovery, T4) was performed after a 4-week recovery period. This approach allowed us to assess the resilience of belowground functions to drought, providing realistic scenarios of areas with increasing dry periods .
Soil physiochemical, functional and diversity measurements
Measurements of soil properties (see Note S1 for methodological details) included moisture content, pH, extractable nitrate (NO3), ammonium (NH4), extractable phosphate (PO4), total carbon (C), and total nitrogen (N). Additionally, we determined the rate of mineralized N and potential acid phosphatase (PHOS) enzyme activity. Total genomic DNA was extracted from soil samples, and microbial biomass was quantified prior to planting (T0), by measuring bacterial and fungal RNA copy number (bacteria: 16S rRNA; fungi: ITS rRNA) using qPCR (see Note S2 for methodological details) and amplicon sequencing for 16S rRNA gene and ITS (see Note S3 for methodological details). This allowed us to validate the dilution-to-extinction approach (Note S4) and obtain insights into the composition of microbial communities in response to our experimental manipulations.
Statistical analysis
Two-way analysis of variance (ANOVA) followed by Tukey’s multiple comparison test was used to assess the effects of dilution-to-extinction approach on microbial abundance, and microbial richness (observed OTUs and Chao1) and diversity (Shannon index). A Šídák’s multiple comparison test was used to compare between sampling points or otherwise mentioned in the figure legends. Permutational multivariate analysis of variance (PERMANOVA) was employed to test the significance of changes in microbial composition (number of permutations: 999) based on Bray-Curtis distances using the web-based MicrobiomeAnalyst platform . Spearman correlation coefficients (ρ) were used to determine the positive or negative relationships between microbial and plant diversity with soil functions across soil diversity and plant richness levels. Multiple linear regression models (R function, lm() ) were used to compare the relative contributions of soil microbial communities, plant species richness, PFGs, drought and their interactions in respect to soil N and P nutrient pools (NH4, NO3 and PO4) and processes (rate of mineralized N and PHOS activity). To evaluate the relative contributions of these variables as drivers of soil functions, we expressed the importance of each predictor as the percentage of explained variance, based on their individual regression coefficients (R2) compared to the absolute values of the total of regression coefficients. Further, a stepwise regression (R function, StepAIC() ) was performed to select the best fit models based on AIC values to explore the contribution of individual PFGs on microbial diversity-soil function relationships. A value of p < 0.05 was considered to be statistically significant. All tests and statistical models were constructed and visualized by R 4.1.2 and GrapPad Prism 9.0 software (Boston, Massachusetts USA, www.graphpad.com). This approach allowed us to quantify the importance of each predictor in explaining the variation in soil N and P pools and processes, providing valuable insights into the underlying mechanisms.