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Soil Biology and Biochemistry 177 (2023) 108922
Available online 22 December 2022
0038-0717/© 2022 Elsevier Ltd. All rights reserved.
Long-term organic fertilization promotes the resilience of soil
multifunctionality driven by bacterial communities
Jipeng Luo
a
, Guangcheng Liao
a
, Samiran Banerjee
b
, Shaohua Gu
c
, Jiabin Liang
a
, Xinyu Guo
a
,
Heping Zhao
a
, Yongchao Liang
a
, Tingqiang Li
a
,
d
,
e
,
*
a
Ministry of Education Key Laboratory of Environmental Remediation and Ecological Health, College of Environmental and Resource Sciences, Zhejiang University,
Hangzhou, 310058, China
b
Department of Microbiological Sciences, North Dakota State University, Fargo, ND, USA
c
Center for Quantitative Biology and Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
d
Zhejiang Provincial Key Laboratory of Agricultural Resources and Environment, Hangzhou, 310058, China
e
National Demonstration Center for Experimental Environment and Resources Education, Zhejiang University, Hangzhou, 310058, China
ARTICLE INFO
Keywords:
Long-term fertilization
Temporal resilience
Soil multifunctionality
Copiotrophic taxa
Biodiversity loss
Microbial community
ABSTRACT
Long-term intensive fertilization is a practice common around the world and gradually alters soil microbiome,
however, its inuences on the temporal resilience of soil multifunctionality to biodiversity loss and biodiversity-
multifunctionality relationships remain poorly understood. Here, we manipulated soil biodiversity using the
dilution-to-extinction approach to examine the temporal variability in individual functions, soil multi-
functionality and their relationships with bacterial and fungal communities under different fertilization treat-
ments during a 90-day re-colonization process. We found that organic fertilization accelerated the resilience of
single functions and soil multifunctionality to biodiversity loss compared with mineral fertilization and unfer-
tilized control. The fungal community was less resilient than bacterial community to disturbances caused by
fertilization and dilution. Bacterial but not fungal diversity was signicantly and positively related to multi-
functionality, and the strength of the diversity-multifunctionality relationships in organic fertilized soil was 3-
and 67-fold higher than that in unfertilized and mineral fertilized soil, respectively. Both organic and mineral
nutrient inputs promoted copiotroph-dominated bacterial assemblages (including Proteobacteria and Bacteroidetes
members) and suppressed oligotrophs (mostly Acidobacteria and Chloroexi), which paralleled multifunctionality
resilience patterns in fertilized soils. β-Diversity of bacterial copiotrophs alone or in combination was signi-
cantly related to changes in multifunctionality. Random forest analysis and structural equation modeling indi-
cated that bacterial community diversity and composition along with soil carbon and nitrogen basically
determined soil multifunctionality, with 70% of the variance in multifunctionality being explained. Rare taxa
from the bacterial copiotrophs were particularly important for maintaining multifunctionality. Our results un-
derline the importance of fertilization-induced shifts in microbial ecophysiological strategies for promoting the
resilience of soil multifunctionality to biodiversity loss, and the need to preserve the diversity of rare copio-
trophic taxa for stable provision of ecosystem functions under future environmental change.
1. Introduction
The soil microbial world is extremely complex and diverse, with
estimates of up to 10
9
bacterial cells (Gans et al., 2005), 10
4
species
(Curtis et al., 2002), and approximately 200 m fungal hyphae inhabiting
1 g of soil (Bardgett and van der Putten, 2014). This vast and hidden
diversity contributes to a large fraction of terrestrial ecosystem biomass
(Fierer et al., 2009) and is critically important for maintaining multiple
ecosystem functions and services simultaneously (i.e. multi-
functionality) by supporting processes, such as nutrient cycling, litter
decomposition and climate mitigation (van der Heijden et al., 2008;
Wagg et al., 2014; Jansson and Hofmockel, 2020). Nowadays, agricul-
tural ecosystems are suffering from increasing anthropogenic pressures
and environmental disturbances, such as land use intensication,
* Corresponding author. Ministry of Education Key Laboratory of Environmental Remediation and Ecological Health, College of Environmental and Resource
Sciences, Zhejiang University, Hangzhou, 310058, China.
E-mail address: litq@zju.edu.cn (T. Li).
Contents lists available at ScienceDirect
Soil Biology and Biochemistry
journal homepage: www.elsevier.com/locate/soilbio
https://doi.org/10.1016/j.soilbio.2022.108922
Received 23 November 2021; Received in revised form 13 December 2022; Accepted 17 December 2022
Soil Biology and Biochemistry 177 (2023) 108922
2
nitrogen enrichment, climate change and accumulation of pollutants in
soils (Cleland and Harpole, 2010; Trenberth et al., 2014; Huang et al.,
2019). These longstanding disturbances and pressures can severely
impact multifunctionality in agricultural ecosystems through regulating
soil microbial community diversity and abundance (Soliveres et al.,
2016; Jiao et al., 2019). In addition, evidence is mounting that con-
ventional agricultural management practices, such as intensive fertil-
ization, soil tillage and crop rotation, can cause irreversible impacts on
microbial community diversity and interactions and their responses to
changing environmental conditions (Dai et al., 2018; Zhang et al., 2019;
Na et al., 2021). However, we know little about the consequences of
these practices for soil multifunctionality and stability. Given that the
agricultural intensication is predicted to increase to meet the
increasing global food demand, it is vital to determine the effect of
agricultural practices on microbial communities and the soil multi-
functionality they govern following potential shifts in biodiversity.
Routine inputs of organic and mineral fertilisers are important land
management practices for improving nutrient bioavailability and ulti-
mately increased crop yield. Previous lab- and eld-based studies have
discovered the distinct impacts of organic and inorganic fertilisers on
soil abiotic and biotic properties (Hartmann et al., 2015; Xun et al.,
2016). For instance, organic fertilisers can elevate the soil contents of
nutrient and organic carbon, and also lead to the increase in soil pH (Li
et al., 2015; Blanchet et al., 2016). Inorganic fertilisers can similarly
improve nutrient availability, but typically cause soil acidication and
negative effects on soil physical structure (Guo et al., 2010; Zhang et al.,
2016). Moreover, fertilization strategy is expected to alter the soil mi-
crobial community structure, diversity and activity (Bünemann et al.,
2006; Dai et al., 2018). As a whole, organic inputs (e.g. manure,
compost) can support high levels of bacterial diversity and richness, and
promote soil carbon cycling more than the mineral fertilisers (Lori et al.,
2017; Luo et al., 2018a,b). Mineral fertiliser applications can reduce
richness in soil microbiota and suppress protistan functional groups
(Hartmann et al., 2015; Zhao et al., 2020). These studies illuminate that
organic fertilisers tend to be more environmentally friendly than inor-
ganic fertilisers because of their roles in improving soil nutrients, and
maintaining and promoting microbial community diversity and activity.
To date, however, how fertilization practices modulate the response of
soil multifunctionality and its relationships with microbial communities
to changes in biodiversity, remains poorly understood.
Ecosystem stability represents the capability of ecosystem to resist
environmental disturbances (resistance) and to recover from perturba-
tions (resilience) (Allison and Martiny, 2008; Shade et al., 2012). The
soil microbial communities are usually resistant and/or resilient to
perturbations and recover quickly to its original state. Generally, resis-
tance and resilience are two main mechanisms responsible for the sta-
bility of microbial ecosystems in facing of environmental disturbances
(Allison and Martiny, 2008). The phylotypes within a microbiome and
microbial assemblages from the distinct soil environments (e.g. organic
v.s. inorganic fertilized soils) may use different adaptive mechanisms to
adapt to disturbed environments (Delgado-Baquerizo et al., 2020).
Therefore, understanding how fertilization strategies inuence the sta-
bility of microbial communities and multiple soil functions in response
to a decline in biodiversity is critical for sustainable management aimed
at enhancing the adaptability of agroecosystems to ongoing environ-
mental changes.
Recent studies have linked the stabilizing effect of soil microbial
diversity to the asynchrony among microbial taxa whereby different
microbes support functions at different times (Wagg et al., 2021). The
asynchronous temporal uctuations among species in their abundance
and contribution to various ecosystem functions in more diverse com-
munities could ensure greater performance in overall ecosystem func-
tioning (Isbell et al., 2011). In addition, changes in the temporal
abundance of different species within a community will likely vary if the
species possess different fundamental niches and life histories (Chesson,
2000; Loreau and de Mazancourt, 2008), which may result in distinct
contributions of different soil microorganisms to the maintenance of
multiple ecosystem functions (Delgado-Baquerizo et al., 2020). Empir-
ical studies assessing microbial life strategies have noted that intensied
land use induces shifts from fungi-dominated to bacteria-dominated
communities associated with altered C turnover (Bardgett, 2005; de
Vries et al., 2012). The fungi-dominated communities tend to be more
resistant (that is, have greater ability to withstand a disturbance) (Pimm,
1984), but less resilient (that is, have lower rate of recovery after a
disturbance) to climate-related and intra-annual environmental distur-
bances than the bacteria-dominated communities due to their distinct
physiological responses or adaptability (de Vries et al., 2012). However,
it is still unclear whether bacterial communities will dominate the arable
soils receiving long-term fertilizers treatments, the typical intensively
managed ecosystems, and bacterial diversity will play a dominant role in
regulating multiple soil functions. We posit that the shifts in bacterial
diversity and abundance will be linked to the resilience of soil multi-
functionality to a greater extent than fungal counterparts, and the
relative contribution of different microbial taxa to multifunctionality
stability would vary across fertilization regimes as temporal variability
in microbial composition is greatly inuenced by land management
practices (Lauber et al., 2013).
In this study, we constructed a series of soil microbial communities
with a gradient of biodiversity by inoculating progressively diluted soil
suspensions into original sterilized soils, and the resilience of soil mul-
tifunctionaliy and its relationships with microbial communities across a
90-day incubation from replicated, experimental plots representing
three long-term fertilization regimes were monitored by several
methods. We used 16S rRNA gene and fungal ITS (internal transcribed
spacer) sequencing to compare bacterial diversity, fungal diversity and
their relations to soil multifunctionality within and between fertilization
regimes. Specically, we aimed to (i) examine the impact of long-term
fertilization treatments on the resilience of both the microbial commu-
nities and soil multifunctionality they carried out to biodiversity loss,
(ii) evaluate the relative contributions of the composition and diversity
of bacterial and fungal communities to the resilience of multi-
functionality and (iii) identify microbial taxa that had a prominent
contribution to the recovery of soil multifunctionality. Given the bene-
ts that organic amendments provide for soil nutrients and microbial
communities, we hypothesized that organic fertilization would enhance
the resilience of soil microbiomes and the multifunctionality compared
to mineral fertilization. We also hypothesized that bacterial community
with fast growth rate would be more important than fungal community
for multifunctionality resilience.
2. Materials and methods
2.1. Fertilization experiment and soil sampling
Soil samples were collected in May 2019 from a 15-year fertilization
experimental site in Anji city, Zhejiang Province, China (30.6◦N, 119.4◦
E), with the annual mean precipitation of 1420 mm and annual mean
temperature of 16.1 ◦C. The experimental soil at this site is haplic alisol
with 48% sand, 29% silt and 23% clay. The fertilization experiment was
initiated in 2004 and included annual rotations of winter rape and
summer rice to examine the impacts of the substitution of chemical
fertiliser with organic fertiliser on the crop yield and soil ecosystem
functioning. A total of three fertilization regimes were implemented
with ve replicates in a random block design, including (i) control (CK),
no added fertiliser, (ii) chemical fertiliser (combination of nitrogen,
phosphorus and potassium; NPK), (iii) manure chemical combined
fertilization (NPKM). The NPK treatment was fertilized with nitrogen,
phosphorus and potassium at 150, 35 and 65 kg ha
−2
year
−1
as urea,
double superphosphate, and potassium chloride, respectively. The
NPKM treatment was NPK combined with pig manure applied at 1300
kg ha
−2
year
−1
.
Soil samples were collected from the upper 15-cm soil horizons of
J. Luo et al.
Soil Biology and Biochemistry 177 (2023) 108922
3
each fertilization treatment as a combined sample of ve soil cores
randomly distributed across each replicate. A subset of the collected
soils were stored at −80 ◦C until the biological processes, enzymatic
activities and microbial community analyses (referred to as the initial
soils). The remaining soils were air-dried at room temperature, ho-
mogenized and passed through a 2 mm sieve, and the physico-chemical
properties were analyzed before storage at −4 ◦C.
2.2. Microcosm incubation experiment
Microcosms were established by placing 100 g of sterilized soil
(γ-irradiation exposure, 35 kGy) with different fertilization treatments
into a 250 ml glass ask. Sterile soil microcosms were inoculated with
progressively diluted suspensions of the same soil that was not sterilized
(Philippot et al., 2013; Maron et al., 2018) to examine the resilience of
microbial communities and soil multifunctionality under different
long-term fertilizations. An initial soil suspension for inoculation was
made by mixing 100 g of dry soil aliquots with 300 ml of sterile distilled
water with a blender for 10 min at maximum speed. This was regarded
as the undiluted soil suspension, i.e. 10
0
dilution (D0). Subsequently,
this suspension was then sequentially diluted to obtain the further di-
lutions of 10
−3
(D1) and 10
−6
(D2), and these soil suspensions were
homogeneously added to asks with the sterilized soils. The sterility was
tested by spreading 0.5 g of the inoculated soil onto Luria-Bertani (LB)
and trypticase soy agar media. No bacterial and fungal growth for the
soils was detected on agar plates during 7 days of incubation. The design
of the microcosm experiment included three dilutions with ve repli-
cates each for different fertilizations. The moisture content of the soils
was determined every two days by using the gravitation method and was
adjusted to 50% water-holding capacity with sterile water. Subse-
quently, the microcosms were sealed with the breathable Bemis Paralm
(Oshkosh, USA) to avoid exogenous microbial contamination and were
incubated at 25 ◦C for 90 days to allow the soil recolonization by the
inoculated microorganisms. Soil samples were taken in the clean bench
with a UV hood at 7, 15, 30 and 90 days after incubation, and soil
physico-chemical properties, enzyme activities, N
2
O concentrations and
net N mineralization rate were measured to evaluate the temporal shifts
in soil multifunctionality. The initial soils (undisturbed) and at day 90
soil samples were subjected for DNA sequencing to assess microbial
community resilient effectiveness.
2.3. Analysis of soil properties
Soil pH and electrical conductivity (EC) were measured in a 1:2.5
(w/v) soil-water suspension with the glass electrode method and DDS-
307A conductivity meter (INESA, Shanghai, China). Total nitrogen
(TN) was determined using Kjeldahl method. The K
2
Cr
2
O
7
–H
2
SO
4
oxidation-reduction colorimetric method was used to measure soil total
organic carbon (TOC). Soil NH
4
+
and NO
3
−
were extracted using 0.5 M
K
2
SO
4
solution (1:5 w/v), and then were determined with continuous
flow analysis (AQ-2 Discrete Automated Analyzer, Seal Analytical, UK).
N mineralization rate was estimated as the differences between initial
and nal inorganic N (sum of NH
4
+
and NO
3
−
) before and after incubation
(Delgado-Baquerizo et al., 2016). Total phosphorus (TP) and available
phosphorus (AP) were determined using the mo-blue method and
Olsen’s method (Watanabe and Olsen, 1965), respectively. Soil acid
phosphatase activity (P mineralization) was assayed through measuring
the release of mg p-nitrophenyl phosphate (PNP) per gram soil in 1 h
(Tabatabai and Bremner, 1969). β-Glucosidase activity (sugar degrada-
tion) was determined by measuring the production of p-nitrophenol
(Dick et al., 1996). The activity of β-1,4-N-acetylglucosaminidase (chitin
degradation) was measured from 1 g of soil using uorometry (Bell
et al., 2013). Gas samples (10 ml) were taken from the headspace of ask
with a syringe at the four sampling points, and N
2
O concentration was
measured with a gas chromatography (Shimadzu Corporation, Japan)
tted with an ECD detector.
2.4. DNA extraction and analysis of microbial communities
Genomic DNA was extracted from 0.25 g soil using the DNeasy®
PowerSoil® DNA isolation kit (QIAGEN, Hilden, Germany), and the
concentration and quality of DNA was checked with a Nanodrop 2000
UV–vis spectrophotometer (Wilmington, USA). To assess the bacterial
and fungal communities, the bacterial V3–V4 regions of the 16S rRNA
gene and fungal ITS2 region were amplied using the primer pairs of
338F (5′-ACTCCTACGGGAGGCAGCA-3′) and 806R (5′-GGAC-
TACHVGGGTWTCTAAT-3′) (Srinivasan et al., 2012), and ITS3-F:
5′-GCATCGATGAAGAACGCAGC-3′and ITS4-R: 5′-TCCTCCGCTTAT
TGATATGC-3′(Mckay et al., 1999), respectively. These primers con-
tained a set of dual-index barcodes sequence unique to each sample,
enabling sequencing of pooled (equimolar) amplicons (HiSeq platform;
Illumina) and downstream assignment of amplicons to treatments.
A total of 1605088 and 2890331 high-quality sequences were ob-
tained for bacteria and fungi, respectively, with their median read
counts per sample of 30723 (range: 22632-47642) and 53525 (range:
9210–71156). Raw sequence data were processed within the QIIME 2
environment (release 2020.6), denoising sequences with the available
DADA2 pipeline (Callahan et al., 2016). We assembled the remaining
quality-ltered reads into error-corrected amplicon sequence variants or
ASVs (at 100% sequence identity), which represent unique bacterial
taxa. Representative sequences of the generated bacterial and fungal
ASVs were aligned against the SILVA 132 database and the UNITE
reference database using an open-reference Naïve Bayes feature classi-
er, respectively. The resultant ASV abundance table were ltered to
remove ASVs without a phylum assignment, or assigned to archaea, or
mitochondria using the R ‘phyloseq’ package (McMurdie and Holmes,
2013). To facilitate downstream composition and differential abun-
dance analyses, we applied a prevalence and abundance threshold for
ltered ASVs, in which taxa were retained only if they were found in 2%
of samples and at a frequency of 20 sequences reads per sample. Shan-
non index, phylogenetic diversity (Faith’s pd) and richness of both
bacteria and fungi were estimated using the normalized ASV table by
rarefying to 15000 and 16000 reads per sample, respectively. In this
study, the ASVs with a relative abundance of <0.1% were referred to as
the potential rare taxa. Sequence data were submitted to the NCBI
Sequence Read Archive under Bioproject PRJNA776660 and BioSample
accession numbers from SAMN22814164 to SAMN22814271.
2.5. Assessing multifunctionality and their relationships with microbial
α
-diversity
Multifunctionality, a human construct rather than a single measur-
able process, involves quantifying the provision of multiple ecosystem
processes and services simultaneously (Byrnes et al., 2014; Delgado--
Baquerizo et al., 2016; Han et al., 2021). These include, among other,
nutrient cycling, organic matter decomposition and gases emission. We
assessed nine soil variables related to C cycling (β-1,4-N-acetylglucosa-
minidase, β-glucosidase, DNA concentration), N cycling (NO
3
−
, N
mineralization, N
2
O emission) and P cycling (TP, AP, acid phosphatase).
Among them, DNA concentration has previously been used as a proxy of
surface soil biomass and the ability of microorganisms to decompose
organic matter (Johnson et al., 2012; Delgado-Baquerizo et al., 2016).
Soil multifunctionality was quantied according to previously described
method (Delgado-Baquerizo et al., 2016, 2020; Fanin et al., 2018; Hu
et al., 2021). In brief, data were tested for normal distribution by
Shapiro-Wilk test prior to analyses, and the non-normally distributed
data were log-transform when necessary. For the calculation of multi-
functionality, we standardized (z-score) each of the nine
above-mentioned soil variables measured, and then took the average of
these standardized variables to obtain a multifunctionality index. Or-
dinary least squares (OLS) linear regression model was used to test the
relationships between soil multifunctionality and microbial diversity
indexes.
J. Luo et al.
Soil Biology and Biochemistry 177 (2023) 108922
4
Meanwhile, a threshold approach was used to calculate the multi-
threshold multifunctionality (Byrnes et al., 2014), which can display the
effects of diversity on multifunctionality across the full range of
thresholds (some percentage of the maximum observed value of each
function) between 0% and 100%. In this approach, every function was
normalized rst, and then, observations with function were transformed
into a percentage of the maximum performance of each function. Then
regressions between the number of functions surpassing a threshold and
the diversity throughout thresholds from 0 to 99% were performed with
the “multifunc” package (Byrnes et al., 2014). Each threshold is repre-
sentative of a level of functional performance and the regressions indi-
cate whether diversity is able to increase the number of functions
working beyond that level of performance.
2.6. Statistical analysis
Testing for statistical differences in microbial
α
-diversity, multi-
functionality and soil phyico-chemical parameters were performed
using analysis of variance (ANOVA) with post hoc comparisons by
Tukey’s HSD. A classication Random Forest (RF) modeling (Breiman,
2001) was used to identify the main predictors of soil multifunctionality.
The importance of each predictor variable is determined by evaluating
the decrease in prediction accuracy (that is, increase in the mean square
error (MSE) when the data for that predictor is randomly permuted. The
importance and statistical signicance of each predictor were calculated
using “frPermute” package in R. Signicance of the models and
cross-validated R
2
values was assessed with 5000 permutations of the
response variable, by using the “A3” package. Also, we used RF
modeling to identify the most important bacterial taxa as predictors of
soil multifunctionality. Similarity percentage analysis (SIMPER) was
conducted using the “vegan” package (Philip, 2003) to quantify the
contribution of individual phyla to the overall community dissimilarity.
Differences in microbial community composition were assessed using
principal coordinate analyses (PCoAs) performed on Weighted UniFrac
(WUF; accounting for ASV abundances and phylogenetic distances) with
the “ape” package, and the signicance of differences was calculated
using permutational multivariate analysis of variance (PERMANOVA)
performed with the ‘adonis’ test. We independently correlated the
β-diversity (WUF) of bacteria and fungi to the dissimilarity matrices
(Euclidean distance) from soil multifunctionality using Mantel correla-
tions (Pearson). We also assessed Mantel correlations (Pearson) among
soil multifunctionality to Bray-Curtis (accounting for ASV abundances
but not phylogenetic distances) dissimilarity matrices of bacterial
copiotrophs (Proteobacteria, Bacteroidetes, Firmicutes alone and in com-
bination) and the three most abundant fungal phyla.
Structural equation models (SEMs) were used to evaluate the direct
and indirect relationships between fertilization type, dilution, soil
properties, microbial Shannon diversity (bacteria and fungi), commu-
nity composition and soil multifunctionality using the AMOS software
(IBM SPSS AMOS, Chicago, USA 21.0.0). To improve the accuracy of the
model, only the signicant (P <0.05) predictors acquired from RF
models were included. To address multicollinearity, kappa test (R “base”
package) and variance ination factor were conducted between selected
soil properties and multifunctonality. NH
4
+
, TOC, pH that contain small
multicollinearity were retained for SEM analyses. The maximum-
likelihood estimation method was applied to t the model. Parameters
including Chi-square (
χ
2
), P value, and the root mean square error of
approximation (0 ≤RMSEA ≤0.05) were used to test the overall good-
ness of t of the model. The net inuence of one variable upon another is
calculated by synthesizing all direct and indirect pathways between the
two variables.
3. Results
3.1. Abiotic properties and resilience of single functions among distinct
fertilized soils
The NPK and NPKM soils had a signicantly (P <0.05) higher pH
than the CK soil, and electrical conductivity in NPKM soil was obviously
lower than in the CK and NPK soils. Long-term organic fertiliser appli-
cation markedly (P <0.05) increased soil organic carbon (TOC) and
total nitrogen (TN) contents compared with the CK and NPK fertiliser.
The soil NO
3
−
, total phosphorus and available phosphorus were
sequentially decreased from the NPKM to NPK and then to CK soil (P <
0.05; Table S1).
All the soil properties and biological processes were strongly altered
by fertilization type (ANOVA, F =22.4–195.2, P <0.001), dilution
(ANOVA, F =23.8–516.1, P <0.001) and incubation time (TN was the
exception; ANOVA, F =2.5–6860, P <0.001), respectively (Table S2).
Of the soil properties and processes that increased with time, they ten-
ded to recover faster in the NPKM soil than in the CK and NPK soils, and
in undiluted (D0) samples than in the diluted samples (D1 and D2)
(Fig. 1a–e and h). DNA concentration, β-glucosidase, acid phosphatase
and N mineralization were higher in NPKM than in the CK and NPK soils
over the course of the incubation (Fig. 1a, b and d).
3.2. Soil multifunctionality was more closely related to bacterial diversity
than to fungal diversity
Two-way ANOVA showed that dilution had a stronger inuence than
fertilization type on Shannon and phylogenetic diversity of bacterial
communities, with their interactive effects were also signicant while
only the fungal phylogenetic diversity was affected by fertilization type
(P <0.05; Figs. S1a and b). The signicant and negative effect of dilu-
tion on bacterial but not fungal diversity was also found in each soil
(Figs. S1c and d and Table S3). Similar to the diversity indexes, multi-
functionality of each soil decreased along the dilution gradient, and was
signicantly (P <0.05) impacted by fertilization type, incubation time
and their interactions (Fig. 2). The extent of decrease in multi-
functionality was smaller for NPKM than for the CK and NPK soils
following dilution. Soil multifunctionality observed at 30 and 90 days
were basically higher in NPKM than in the CK and NPK soils (Fig. 2).
The average approach showed that soil multifunctionality was
signicantly and positively related to bacterial diversity, estimated with
the Shannon index, but not to fungal diversity (Fig. 3a and b). The sig-
nicant and positive relationships between bacterial diversity and
multifunctionality were also maintained when using other diversity
metrics including phylogenetic diversity and richness (Figs. S2a and c).
However, none of the fungal diversity indexes were signicantly linked
to soil multifunctionality (Figs. S2b and d). Notably, the signicant and
positive associations between multifunctionality and bacterial di-
versity/richness were found in NPKM and NPK soils but not in CK soil,
and the slope of the biodiversity-multifunctionality relationship in
NPKM soil was steeper than that in the NPK soil (Fig. S3). When rean-
alyzed by using the multiple-threshold approach, the results indicated
that the effect of bacterial diversity on the number of functions sur-
passing different thresholds of multifunctionality was mainly positive,
whereas a large proportion of fungal diversity effect was negative
(Fig. 3c and d). Moreover, bacterial diversity had a signicant effect on
the maintenance of multiple soil functions operating at higher perfor-
mance levels compared with fungal diversity (peaks at ~52% and 43%
thresholds in Fig. 3e and f, respectively).
3.3. Variation in soil microbial community composition and their linkages
with multifunctionality
Bacterial communities in fertilized soils were primarily composed of
Proteobacteria (~25% of the total reads), Bacteroidetes (~24%),
J. Luo et al.
Soil Biology and Biochemistry 177 (2023) 108922
5
Firmicutes (~14%) and Acidobacteria (~9%) (Fig. S4a). Fungal com-
munities were dominated by Ascomycota (~62%), Basidiomycota
(~16%) and Chytridiomycota (~15%) (Fig. S4b). The enriched bacterial
groups related to higher dilution levels (D1 and D2) mainly belonged to
Bacteroidetes, whereas the depleted bacteria were afliated with Acid-
obacteria, Actinobacteria, Chloroexi and Patescibacteria (Kruskal-Wallis
test, P
FDR
<0.05) (Fig. S4a). Only the Actinobacteria differed signi-
cantly in abundance among soils (Kruskal-Wallis test, P
FDR
<0.05). The
fungal phyla Ascomycota were signicantly enriched and
Chytridiomycota were depleted in the high dilution treatments, respec-
tively (Kruskal-Wallis test, P
FDR
<0.05) (Fig. S4b). Bacteroidetes, Firmi-
cutes and Proteobacteria explained on average 56% of the overall
bacterial community dissimilarities (Table S4), and Ascomycota, Chy-
tridiomycota and Basidiomycota explained 87% of the overall fungal
community dissimilarities among fertilization treatments (Table S5).
These three bacterial phyla along with Acidobacteria explained on
average 61% of the total community dissimilarities (Table S6), and these
three fungal phyla together with Mortierellomycota explained 93% of the
Fig. 1. Changes in soil DNA concentration (a), β-glucosidase (b), acid phosphatase (c), N-acetylglucosaminidase (d), net N mineralization rate (e), N
2
O production
(f), total nitrogen (g), total organic carbon (h) and available phosphorus (i) over incubation times. Data are in the form of mean ±standard error (S.E.).
Fig. 2. Dynamics of average multifunctionality index in fertilized soils of the three dilutions over incubation time. Effects of fertilization type (F), incubation time (T)
and their interaction (F ×T) on the multifunctionality index were determined by two-way ANOVA. Lowercase letters indicate signicant differences in multi-
functionality between times within a given fertilization. Data are in the form of mean ±S.E.
J. Luo et al.
Soil Biology and Biochemistry 177 (2023) 108922
6
total community dissimilarities among dilutions (Table S7).
Principal coordinate analyses of the weighted UniFrac metric
showed that reconstructed bacterial community compositions were
more different among dilutions (ANOSIM, R =0.77, P <0.001) and
fertilization types (ANOSIM, R =0.10, P <0.005) compared with the
fungal community compositions (ANOSIM, R =0.22, P <0.005 for
dilution; R =0.03, P >0.05 for fertilization types) (Figs. 4a and b).
Bacterial communities in D1 samples were clustered more closely to D2
samples than to D0 samples, with these samples being separated from
the initial soils (Fig. 4a). On the basis of the associated R values, bac-
terial communities of the three dilutions clustered more closely in the
NPKM soil (R =0.59, P <0.001) than in the CK (R =0.78, P <0.001)
and NPK soils (R =0.86, P <0.001) (Fig. 4c–e), whereas differences in
fungal communities among dilutions were larger in the NPKM soil (R =
0.53, P <0.001) than in the NPK (R =0.45, P <0.001) and CK soils (R =
0.20, P <0.001) (Fig. 4f–h). PERMANOVA analysis supported similar
trends and detected notable effects of fertilization and dilution on the
fungal community compositions (Table S8). Moreover, the dissimilar-
ities in the NPKM bacterial communities between the initial and day 90
samples signicantly (P <0.05) decreased from D0 to D2 samples, and
that in the total and NPK bacterial communities followed an opposite
trend (Fig. 4i-l). The WUF dissimilarities in D1 and D2 bacterial com-
munities between the initial and day 90 samples were signicantly (P <
0.05) lower for NPKM than for CK and NPK soils, suggesting that bac-
terial community with a reduced
α
-diversity recovered more quickly to
its initial composition (higher stability) in NPKM soil. In comparison, the
dissimilarities in fungal communities between the initial and day 90
samples did not change signicantly across dilution levels (Fig. 4m-p).
Based on Mantel test, soil multifunctionality was strongly correlated
with the β-diversity of bacterial community (r =0.56, P <0.001), and
then with that of fungal community (r =0.15, P =0.031) (Fig. 5a and b).
The signicant associations of multifunctionality and single functions
with community β-diversity were maintained for bacteria but not for
fungi when examined each soil separately (Fig. 5c–h; Table S9).
Furthermore, β-diversity of the copiotrophic bacterial assemblages,
Proteobacteria and Bacteroidetes was signicantly and positively corre-
lated with soil multifunctionality (P <0.05; Fig. 6a–c). However, no
signicant correlations among β-diversity of the three most abundant
fungal phyla and the soil multifunctionality were observed (Fig. 6e–g).
Fig. 3. Relationship between the bacterial (a) and
fungal Shannon diversity (b) and soil multi-
functionality. The solid line is the tted line from OLS
regression. Relationships between bacterial (c) and
fungal (d) Shannon diversity and the number of
functions at or above a threshold (in %) of the
maximum observed functions. Lines signify the slope
between diversity and the number of functions
greater than or equal to a threshold value ranging
from 0 to 100% of maximum for each function. The
dotted curves indicate the changes in number of
functions per unit increment of Shannon diversity of
bacteria (e) and fungi (f), and shadowed area in-
dicates the slope and the 95% condence interval of
the regression showed in (c) and (d).
J. Luo et al.
Soil Biology and Biochemistry 177 (2023) 108922
7
3.4. The direct and indirect effects of multiple soil multifunctionality
drivers
Random forest (RF) modeling was used to identify the most impor-
tant predictors of soil multifunctionality (Fig. S5). Our RF models pre-
dicted 70% of the variance in soil multifunctionality, with soil DNA,
NH
4
+
and acid phosphatase being the most important predictors. Other
factors such as TN, TOC, pH, fertilization type, bacterial diversity and
composition were also signicant predictors of soil multifunctionality.
Structural equation modeling results showed that TOC, pH, NH
4
+
and
microbial diversity explained 70% of the variance found in multi-
functionality (Fig. 7a), and that these soil properties together with the
bacterial and fungal community compositions explained a comparable
proportion of the variance (Fig. 7b). TOC had direct positive effect, and
fertilization type and dilution had indirect negative effects on multi-
functionality by regulating bacterial diversity. SEM also supported the
RF analysis in that bacterial rather than fungal diversity strongly and
positively regulated multifunctionality when account simultaneously for
selected soil properties (Fig. 7). Bacterial community composition had a
greater direct effect than TOC and fungal composition on multi-
functionality. Notably, TOC had largest integrated effects on soil mul-
tifunctionality among the selected abiotic predictors (Fig. 7c and d). Soil
pH had a consistent negative inuence on soil multifunctionality.
3.5. Microbial taxa predicting soil multifunctionality
We further performed RF modeling to identify the most important
microbial taxa predicting soil multifunctionality. As a result, 37 bacte-
rial ASVs were identied as the signicant predictors (P <0.05), with
68% of them were afliated with the members of Bacteroidetes and
Proteobacteria. Of these 37 ASVs, the abundance of 29 was positively
correlated with the soil multifunctionality (Spearman correlation;
Table S10). Of the nine signicant predictors (ASVs) with a mean rela-
tive abundance less than 0.5% (Fig. 8a), their abundances were pro-
nouncedly correlated to multifunctionality (Spearman’s
ρ
≥0.32; P <
0.05; Fig. 8b). Six of these nine were relatively rare with a relative
abundance less than 0.1%. The top four bacterial taxa that exhibited
strongest correlation with multifunctionality were Bacillus (Firmicutes),
Gemmatimonadaceae (Gemmatimonadetes), Sphingomonas (Proteobac-
teria), and Flavitalea (Bacteroidetes) (Fig. 8). Fungal ASVs, however,
exhibited poor predictive power for soil multifunctionality. Taken
together, the rare copiotrophic bacteria with a low relative abundance
(<0.1%) were especially important for promoting the resilience of
multiple soil functions to biodiversity loss.
Fig. 4. Compositions of the re-constructed soil microbial communities among fertilization treatments and dilution levels. PCoAs of the weighted UniFrac distance
metric for the total bacterial (a) and fungal (b) communities, and the sub bacterial communities from the CK (c), NPK (d) and NPKM (e) soils, and the sub fungal
communities from the CK (f), NPK (g) and NPKM (h) soils. Ellipses represent the condence interval at 95% probability, only statistically signicant correlations at P
<0.05 level are displayed. Dissimilarities of β-diversity between the initial and day 90 samples of the total, CK, NPK and NPKM soil bacterial (i–l) and fungal (m–p)
communities, as estimated by the tted ordinary or quadratic linear regression models.
J. Luo et al.
Soil Biology and Biochemistry 177 (2023) 108922
8
4. Discussion
4.1. Organic fertilization facilitates the recovery of individual soil
functions
By examining the temporal changes of individual soil functions along
decreasing diversity gradient, we showed that decrease in diversity
negatively affected the resilience of many functions during soil re-
colonization (Fig. 1). These ndings coincide with eld studies that
underscore the crucial role of microbial diversity in supporting soil
functioning (Jing et al., 2015; Delgado-Baquerizo et al., 2016). As ex-
pected, temporal shifts in individual functions of dilution samples varied
among fertilized soils, suggesting that the effects of biodiversity on
ecosystem functioning is strongly resource dependent (Fanin et al.,
2018). This probably can be explained by the prediction of the ‘species
sorting theory’, stipulating that if different ecosystems differ in resource
supply, the identity of the species that maximize ecosystem functions
would vary for each ecosystem (Leibold et al., 2017). Previous
Fig. 5. Relationship between community dissimilarity for community composition of the total bacterial community (a), total fungal community (b), bacterial and
fungal communities of the CK (c, d), NPK (e, f) and NPKM soils (g, h) and soil multifunctionality. The statistically signicant (P <0.05) and non-signicant (P >0.05)
linear regression ts are shown in solid and dashed lines, respectively.
J. Luo et al.
Soil Biology and Biochemistry 177 (2023) 108922
9
biodiversity manipulation experiments have revealed that the strength
and even the direction of biodiversity changes effect on individual
functions varied across ecosystem types because of differences in soil
abiotic properties (notably soil fertility and water availability), plant
functional traits or biological communities (Fridley, 2002; Fanin et al.,
2018). These were also conrmed in the present study by the fact that
fertilization has induced large shifts in the soil properties (e.g. TN, TOC,
available phosphorus), microbial community diversity and enzyme ac-
tivities (Table S2). In line with studies revealing that organic amend-
ments usually promote the functioning of agroecosystems (Luo et al.,
2018a,b; Chen et al., 2019), the temporal patterns in soil functions
across soils indicated that organic fertiliser application can increase the
recovery of individual functions from a decline in biodiversity (Fig. 1),
and thus contributing to ensuring the stability of soil ecosystems
following disturbances. The rapid increase in single soil functions
revealed the high inux of new functional traits, which may be due to
the high growth rate and/or rapid resilient ability of functional microbes
that connect many ecosystem functions (Allison and Martiny, 2008).
Collectively, organic inputs have the potential to improve the adapt-
ability and resilience of multiple soil functions in agroecosystem to
biodiversity loss through regulating microbial communities.
4.2. Contrasting responses in bacterial and fungal diversity and
compositions
The substantially stronger inuences of fertilization and dilution on
Fig. 6. Relationship between community dissimilarity for community composition of the total copiotrophic bacterial communities composed of Proteobacteria,
Bacteroidetes and Firmicutes (a), Proteobacteria (b), Bacteroidetes (c), Firmicutes (d), Ascomycota (e), Basidiomycota (f), and Chytridiomycota (g) and dissimilarity matrix
for multifunctionality. The signicant (P <0.05) and non-signicant (P >0.05) linear regression ts are shown in solid and dashed lines, respectively.
J. Luo et al.
Soil Biology and Biochemistry 177 (2023) 108922
10
bacterial diversity than on fungal diversity over time reect the higher
resistance of fungal diversity in arable soils to environmental pertur-
bations (Fig. S1). In comparison, the higher bacterial diversity compared
with fungal diversity observed after 90 days of incubation may indicate
the higher resilience of bacterial communities to biodiversity loss
(Table S3). These results supported previous studies showing that
fungal-based food webs are more resistant (that is, have greater ability
to withstand a disturbance), but less resilient (that is, have lower rate of
recovery after a disturbance) than bacterial-based food webs to drought-
related disturbances (Pimm, 1984; de Vries et al., 2012). This consis-
tency indicated that the response patterns of bacterial and fungal com-
munities to many abiotic stressors are common across diverse
conditions. The differential ability of bacteria and fungi to maintain
stability (i.e. resistance and resilience) in response to environmental
perturbations may be ascribed to the many differences in phenotype,
phylogeny, and life strategy that could cause distinct succession patterns
during microbial recovery (Sun et al., 2017). For instance, soil fungal
growth rate appears to be 10-fold lower than that of soil bacteria, which
can recover faster close to its original state after a disturbance (Rousk
and Bååth, 2007). It is possible that 90 days of incubation for multi-
functionality measurements may capture mainly bacterial growth, and
the majority of changes in fungal diversity and recovery of fungal
abundance will occur over longer time than for bacteria. Additionally,
fungi were shown to be more dispersal limited than bacteria due to their
larger size and thus may be less homogeneously distributed (Cole-
man-Derr et al., 2016), resulting in the less altered fungal diversity
following dilution (Fig. S1). Based on these ndings, the role bacteria
and fungi play in sustaining the biodiversity-functions relationships and
stability of soil multifunctionality is expected to be different.
Unlike fungi, bacterial community recovered close to the composi-
tions of the undiluted communities but differed from the original com-
munity compositions. Shade et al. (2012) have provided insights into
microbial community responses to press (long-term) and pulse (short--
term) disturbances in a variety of habitats. In response to a disturbance,
a microbial community may be resistant, resilient or move to a different
but stable status following potential perturbation. The dissimilarities in
Fig. 7. Structural equation models (SEMs) indicate
potential direct and indirect effects of soil variables
and bacterial and fungal Shannon diversity (a) and
communities (b) on soil multifunctionality. We
grouped the edaphic properties into the same box in
the model for graphical simplicity, which did not
represent latent variables. Numbers adjacent to ar-
rows are indicative of the effect-size of the relation-
ship, *P <0.05, **P <0.01, ***P <0.001.
Continuous lines indicate signicant relationships,
and light grey lines indicate non-signicant. The
width of arrows is proportional to the strength of path
coefcients. R
2
denotes the proportion of variance
explained. Standardized total effects (direct plus in-
direct effects) derived from the respective structural
equation models depicted above (c, d).
Fig. 8. Important bacterial ASVs (family or genus level) as the signicant
predictors of soil multifunctionality identied by Random Forest regression and
spearman correlation analysis. Figure (a) shows the Random Forest mean pre-
dictor importance (% of increase of MSE) of bacterial ASVs on soil multi-
functionality. Signicance levels of each predictor are as follows: *P <0.05,
**P <0.01, ***P <0.001. Figure (b) shows the Spearman correlations between
the signicant ASVs (predictors) and multifunctionality. Signicance levels of
spearman’s
ρ
are as follows: *P <0.05, **P <0.01, ***P <0.001.
J. Luo et al.
Soil Biology and Biochemistry 177 (2023) 108922
11
bacterial communities between the initial and day 90 samples were
smaller for NPKM than for CK and NPK soils, suggesting that bacterial
communities in the former soil rebound faster (higher stability) than the
latter two from a decline in biodiversity (Grifths and Philippot, 2013).
This can be explained by the fact that organic fertilisers are not only
nutrient-rich, but also longer lasting in the provision of carbon, nitrogen
and energy for microbial growth than mineral fertilisers (Zhen et al.,
2014), which should increase the stability of microbial communities in
response to environment disturbances.
4.3. Organic fertilization promotes soil multifunctionality resilience to
biodiversity loss
The notable inuence of fertilization on soil multifunctionality was
discernible across each dilution level (Fig. 2), supporting the ndings
that land-management practices can alter both biological traits and
ecosystem functioning (de Vries et al., 2012; Rodrigues et al., 2013).
Importantly, organic fertilization has increased multifunctionality and
strengthened its positive relationships with bacterial diversity relative to
the control and mineral fertilization (Fig. S3). Recent eld surveys
showed that organic fertilisers promoted soil multifunctionality by
enhancing regulating and supporting services related to biodiversity
preservation, soil quality, and climate mitigation, while inorganic fer-
tilisers exhibited the opposite trend (Chen et al., 2020; Wittwer et al.,
2021). The promoting effect of organic fertilisers on multifunctionality
was likely due to the increases in functional bacterial diversity resulting
from higher nutrient availability (Chen et al., 2020) (Fig. 7). The in-
crease in TOC and TN, and suitable pH range in organically-fertilized
soils could have directly increased the bacterial community diversity
(Table S9 and Fig. 7) because improved resource availability and pH
condition can favor the growth and metabolism of bacteria (Rousk et al.,
2010; Banerjee et al., 2020), and promote supports on ecosystem
functioning.
A majority of prior studies examining the effects of land management
practices on the diversity-multifunctionality relationships were based on
a single sampling point (Delgado-Baquerizo et al., 2016; Luo et al.,
2018a,b; Zheng et al., 2019; Chen et al., 2020), and this may hamper our
ability to predict the true responses of multifunctionality to disturbances
and harness microbiome functionality. Our ndings add to this view by
demonstrating that 15 years of organic fertiliser application increased
the resilience of soil multifunctionality to biodiversity loss to a greater
extent than non-fertilization and mineral fertilization (Fig. 2). This
nding implicated that organic fertilization has the potential to offset
the negative effects caused by land intensication, such as physical
damage on microbial composition, reduction in functional redundancy
and biodiversity (Lalibert ˜
A et al., 2010), by introducing not only nu-
trients but also large amount of exogenous microbes in soil (Durso et al.,
2011). A regrettable thing is that our experimental design did not allow
us to causally distinguish between biostimulation (i.e. adding growth
substrates) and bioaugmentation (i.e. adding organisms) as the mecha-
nisms underlying the increased multifunctionality resilience. Never-
theless, a biodiversity manipulation experimental study indicated that if
it is possible to add a species to an ecosystem, it would likely increase
some ecosystem functions (Meyer et al., 2018). Therefore, organic
fertilization is recommended in agricultural production as the approach
buffering negative effects of biodiversity loss caused by environmental
disturbance, such as land use and global environmental change.
In contrast to fungi, bacterial diversity with a faster recovery rate
after incubation (i.e., higher resilience) was more important in driving
the resilience of multifunctionality (Fig. 3 and Table S3). Actually, the
importance of bacterial diversity for maintenance of soil multi-
functionality and stability in face of environmental stresses, such as
drought, land use and changing climate, has previously been identied
(Jing et al., 2015; Delgado-Baquerizo et al., 2016; Zheng et al., 2019).
For example, the positive associations between soil multifunctionality
and bacterial diversity rather than fungal diversity have been detected in
a eld survey in the Chinese Tibetan Plateau where climate
change-related disturbances are ubiquitous (Jing et al., 2015). These
studies have frequently attributed the positive effects of bacterial di-
versity on multifunctionality to the differences in microbial life strate-
gies (i.e., r-vs. K-strategists) and niche complementarity (De
Keersmaecker et al., 2016; Chen et al., 2020). In addition, soil bacteria
are relatively broad taxonomic groupings with more diverse associated
traits and functions than fungi, and thus increasing biodiversity of broad
taxonomic groups of free-living soil, such as bacteria, should increase
the diversity of available substrates that are decomposed in the soil
(Torsvik et al., 2002), which should promote soil multifunctionality.
Notably, our study is the rst to show that organic fertilization-induced
shifts in microbial life-history strategies, with copiotrophic microbes
such as Ohtaekwangia and Flavitalea (Bacteroidetes) and Sphingomonas
(Proteobacteria) prevailing in the fertilized soils, could account for the
observed increase in the resilience of soil multifunctionality to biodi-
versity loss. The reported positive responses of Proteobacteria and Bac-
teroidetes to increased soil TOC suggested that members of these phyla
are copiotrophic bacteria (Fierer et al., 2007) (Table S11), which have
fast growth rates and rapid C cycling, and thus, a higher resilience of soil
multifunctionality they govern to loss in biodiversity. These results
accorded with a eld observation revealing that the diversity of het-
erotrophic microbes involved in the decomposition of organic material
and nutrient cycling had a particularly important role in regulating in-
dividual functions and soil multifunctionality (Schuldt et al., 2018),
probably because the activity of these groups directly or indirectly
connects many ecosystem functions. Microorganisms that rapidly utilize
C resources can promote organic material decomposition and C turn-
over, which strongly affect nutrient availability for plant growth and
higher trophic levels (Wardle et al., 2004). Conversely, Acidobacteria,
Verrucomicrobia and Chloroexi displaying poor or negative relation-
ships with TOC were more oligotrophic, with the relative abundance of
acidobacterial taxa being negatively related to multifunctionality, and
therefore exhibited low resilience of soil multifunctionality following
perturbations (Table S11). Moreover, shifts in the compositions of
abundant fungal phyla Ascomycota, Basidiomycota and Chytridiomycota
were less linked to multifunctionality (Fig. 6e–g and Table S12). This
pointed to the low fungal activity and the weak dependence of fungal
growth on labile C during the 90-day incubation, and thus may be less
important for the resilience of soil multifunctionality in comparison with
bacteria. Our ndings provide evidence that nutrient enrichment
through organic fertiliser input could induce a shift in microbial
ecophysiological strategies, favoring a more active and copiotrophic
bacterial community, a pattern that was tightly linked to the resilience
of soil multifunctionality to biodiversity loss.
SEM analyses also supported the above-mentioned results showing
that bacterial diversity and bacterial/fungal composition had largest
standardized total effects among all regulators (Fig. 7), conrming the
critical role of bacterial communities in the resilience of multi-
functionaliy once again. Despite these, our RF models revealed that soil
abiotic variables, such as TOC, NH
4
+
, TN and pH, were signicant pre-
dictors of soil multifunctionality (Fig. S5). The role of soil environmental
variables as predictors of multiple soil functions is well known (Jing
et al., 2015; Delgado-Baquerizo et al., 2016; Zheng et al., 2019)
(Table S9). Soil pH is often linked to substrate and nutrient availability
and is expected to co-vary with many soil properties and affect micro-
bially driven soil C and N processes (Jing et al., 2015; Li et al., 2019).
Here the pH has a low impact on microbial diversity and multi-
functionality. One possible explanation might be the larger variation in
TOC and NH
4
+
than pH caused by fertilization and incubation time,
which exhibited greater impacts on microbial diversity and multi-
functionality (Fig. S1 and Table S2). On the other hand, the dominant
inuence of bacterial diversity on multifunctionality may mask soil pH
effect. NH
4
+
is an available N form in soil and together with TN had
regulatory effects on multifunctionality (Fig. 7 and Table S9). Among
these soil properties, TOC had a largest standardized total effect on soil
J. Luo et al.
Soil Biology and Biochemistry 177 (2023) 108922
12
multifunctionality (Fig. 7c and d). This was congruent with two recent
surveys investigating the biodiversity-ecosystem function relationships
in global natural and continental scale agricultural ecosystems (Delga-
do-Baquerizo et al., 2020; Jiao et al., 2021), highlighting the important
role of TOC in regulating the responses of soil multifunctionality to
disturbances in managed ecosystems. Soil C content is closely associated
with soil texture and subsequently inuences the nutrient availability
and soil process rates (Kallenbach et al., 2016). Also, Zheng et al. (2019)
showed that soil C content correlated with N mineralization and also
affected multiple soil enzyme activities. Therefore, scientists and policy
makers can buffer the negative inuence of biodiversity loss on the
stability of soil multifunctionality through improving TOC status.
4.4. Rare bacterial taxa play a disproportional role in driving
multifunctionality
In this study, bacterial taxa with a relative abundance less than 0.1%
were the major drivers of changes in soil multifunctionality (Fig. 8).
Rare species are increasingly recognized as key drivers of multiple
ecosystem functions in terrestrial and aquatic ecosystems and host-
associated microbiomes (Chen et al., 2020; Xiong et al., 2021), indi-
cating their ecological relevance is common across different habitats.
Jousset et al. (2017) indicated that rare species may have an
over-proportional role in driving multifunctionality, which to some
extent can explain why fertilization affected multifunctionality re-
sponses to biodiversity loss (Fig. 8). Our results support the hypothesis
that rare taxa may contribute to the resilience of microbial community,
and also to the maintenance of microbially driven functions under
non-favorable conditions as they are supposed to be highly tolerant to
stress/disturbance and functionally overlapped (Jousset et al., 2017;
Ziegler et al., 2018). Among the rare taxa observed, members of Bac-
teroidetes could rapidly recover from gamma-irradiation treatment
(Muehe et al., 2015). Sphingomonas were previously reported to tolerate
abiotic stresses such as salinity, drought and heavy metal (Asaf et al.,
2020). Bacillus is considered to be mostly aerobic or facultatively
anaerobic heterotrophs that grow rapidly in response to available
organic C possibly due to their high competitive capacity (Pitombo et al.,
2016). Although abundant taxa basically exhibited a lower contribution
to the resilience of multifunctionality than rare taxa during the
re-colonization process, several abundant taxa might have played a
non-negligible role, including members of Subgroup 7, Gemmatimona-
daceae and Comamonadaceae (Fig. 8). Environmental disturbances may
have stronger impacts on abundant taxa, as they may keep the large
population size and perform the main functions through rapid growth
(Xue et al., 2018). Besides, early studies demonstrated that abundant
taxa have the capability of utilizing a broad range of resource and
combating biotic and abiotic stresses, and thus are able to adapt to
different habitats through active growth and high competitive ability
(Jing et al., 2015; Xiong et al., 2021) and affect the soil
multifunctionality.
The functional importance of the rare taxa might be grounded in
their disproportional role in soil multifunctionality or via the provision
of insurance effects (Jousset et al., 2017). Notably, the rarity of micro-
bial taxa may not be always constant, an estimated 1.5–28% of all mi-
crobes are ‘conditionally rare taxa’, which are rare in most conditions
but become dominant occasionally (Shade et al., 2014). Species that are
considered functionally non-relevant under a given condition may
become important by offering indispensable traits or functions when
optimal conditions arise (Shade et al., 2014). Therefore, rare species are
proposed to provide a pool of genetic resources that may be activated
under the appropriate conditions. Furthermore, high species activity
was considered as another mechanism by which rare microbes perform
the main ecosystem functions (Jousset et al., 2017). Organic fertilisers
can increase the activity of soil microbes, particularly the copiotrophs
belonging to Firmicutes, Proteobacteria, Bacteroidetes (Balota et al., 2014;
Luo et al., 2018a,b). In this study, approximate 76% of the observed
multifunctionality predictors were afliated with bacterial copiotrophs
(Table S10), thus rare taxa in organically-fertilized soil may play a more
important role in the maintenance of multifunctionality than those in
the mineral fertilized and unfertilized soils. Consequently, rare yet
highly active microbes can contribute more to ecosystem functioning
than expected based on their abundance. Future works are required to
incorporate
13
C isotope technique to provide in-depth evidences evalu-
ating the contribution of carbon-assimilating active microbes to micro-
bial community resilience following biodiversity loss, and the
consequence of microbial resilience on ecosystem functions. If
conrmed, our ndings hold the great potential in targeted microbiome
manipulation to minimize the negative impacts of future global change
on biodiversity loss to ensure the stable provision of ecosystem services.
Declaration of competing interest
The authors declare that they have no known competing nancial
interests or personal relationships that could have appeared to inuence
the work reported in this paper.
Data availability
Data will be made available on request.
Acknowledgements
This research is nancially supported by the National Natural Sci-
ence Foundation of China (41977017, 42107009, 42177008), the
fellowship of China Postdoctoral Science Foundation (2022M712770),
Zhejiang Provincial Science and Technology Plan Project
(2022C02022), National Postdoctoral Program for Innovative Talents
(BX20200293), and the Fundamental Research Funds for the Central
Universities.
Appendix A. Supplementary data
Supplementary data to this article can be found online at https://doi.
org/10.1016/j.soilbio.2022.108922.
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