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.