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\begin{document}

\title{Native and commercial microbial inoculants show equal effects on plant
growth in dryland ecosystems}



\author[1]{Frederick Dadzie}%
\author[2]{Miriam Muñoz-Rojas}%
\author[2]{Eve Slavich}%
\author[2]{Patrice Pottier}%
\author[1]{Karen Zeng}%
\author[2]{Angela Moles}%
\affil[1]{University of New South Wales - Kensington Campus}%
\affil[2]{University of New South Wales}%


\vspace{-1em}



  
  \date{June 18, 2024}


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\selectlanguage{english}
\begin{abstract}
There are a wide variety of microbial inoculant types available to
restoration practitioners, but little information as to which performs
best under field conditions in dryland ecosystems. We used a
meta-analysis of 62 dryland studies to provide the first quantitative
comparison of native vs commercial, diverse vs single species, and
fungal vs bacterial microbial inoculants. We found that while microbial
inoculation increases plant growth compared to uninoculated
counterparts, contrary to our expectations, the magnitude of effect was
statistically similar for all the inoculant pairs. Our results suggest
that land managers should use inoculant types that are readily available
and easy to handle rather than complicated and expensive inoculants that
combine multiple taxa of local origin microbes.%
\end{abstract}%



\sloppy


\textbf{Introduction}

Microbial inoculants can allow land managers to increase plant growth
while avoiding the negative impact of fertilizer application
(Soozandehfar et al., 2023). The use of microbial inoculants is now well
established in mesic agricultural settings (Fox, 2015; Timmusk et al.,
2017; Waltz 2017), and there is growing interest in using microbial
inoculation to assist with the restoration of degraded dryland
ecosystems (Kaushal and Wani, 2016; Zhu et al., 2014). However,
systematic studies examining the effect of microbial inoculants on plant
growth at the field scale in drylands are lacking (Hart et al., 2017).
In this study, we conduct a meta-analysis of dryland ecosystems to
quantify the effect of microbial inoculation on plant growth and
increase understanding of which types of inoculants are most effective.

Our first hypothesis is that plants inoculated with microorganisms in
drylands will have higher growth than uninoculated plants.
Microorganisms are thought to facilitate plant growth by increasing
access to water and nutrients (Canbolat et al., 2006; Lai et al., 2008),
and may also produce phytohormones that stimulate plant growth (Jaral et
al., 2012; van der Heijden et al., 2008; Ruzi and Aroca, 2015 van der
Putten et al., 2016). For example, biomass production in tomatoes was
doubled when inoculated with microorganisms (Almaghrabi et al., 2013).
Also, inoculating wheat with microorganisms increased the shoot and root
biomass by increasing phosphorus uptake from the soil (Karimzadeh et
al., 2021). However, the efficacy of microbial inoculation in field
situations varies substantially (Hart et al., 2018; Ryan et al., 2018;
O'Callaghan, 2016), and it is unclear whether microbial inoculation is
likely to be effective in drylands. High temperatures can reduce
microbial activity (Fang, 2022), so benefits may be reduced in dryland
ecosystems with challenging environmental conditions. Conversely, there
is some suggestion that microbial inoculation is more likely to be
successful in drylands due to organisms shifting to facilitative
strategies in high-stress environments (Bertness and Callaway, 1994).
For instance, inoculating with microorganisms increased seedling
emergence (Dadzie et al., 2022) and biomass production (Shirmohammadi et
al., 2020) in drylands suggesting a facilitation effect of microbial
inoculation on plant growth.

Our second hypothesis is that inoculation with native microorganisms
yields greater growth than inoculation with commercial microorganisms.
The dominant theory is that because native microorganisms have
co-evolved with native plants and are adapted to local conditions, they
will result in greater plant growth than commercial inoculants (Dadzie
et al., 2022; Emam, 2016; Koziol et al., 2022; Middleton et al., 2015).
Some studies have supported the hypothesis that native microorganisms
enhance plant growth better than exotic microorganisms (Koziol et al.,
2022; Chaudhary et al., 2020). However, the massive development of
bio-fertilizers in ecological domains (Timmusk et al., 2017; Islam et
al., 2021) compels a systematic evaluation of the magnitude of effect
between native and commercial inoculants under dryland field conditions.
This information will help ecologists and restoration managers to select
appropriate inoculants within their economic means.

Our third hypothesis is that bulk inoculation of different microbial
species will affect plant growth more than inoculation of single
microbial species. One of the most prominent theories in ecology is the
idea that increasing biodiversity leads to increased resource use
efficiency and functional redundancy, whereas the loss of an organism
will cause a reduction in ecosystem function (Bender et al., 2016;
Philippot et al., 2013; Wagg et al., 2014). This idea has readily been
adopted from plant ecology into microbial ecology with little testing,
despite studies showing that microbial activities and trends do not
follow patterns of macroecological theories (Fierer et al., 2011;
Hendershot et al., 2017). Some studies show a greater effect of
biodiverse microbial inoculants than single taxon inoculants (Brad\selectlanguage{ngerman}á\selectlanguage{polish}č\selectlanguage{english}ov\selectlanguage{ngerman}á
et al., 2019; Devi et al., 2022; Jain et al., 2015; Lally et al., 2017).
Other studies have shown a similar magnitude of effect from
single-strain microbial inoculation as from multi-species microbial
inoculations (Bhatia et al., 1998; Onwuchekwa et al., 2014;
Shirmohammadi et al., 2020). Here, we provide a systematic evaluation of
the effect of single-strain and multiple-strain microbial effect on
plant growth in drylands.

Our final objective was to test the hypothesis that inoculation with
fungi will yield greater plant growth than inoculation with bacteria in
dryland ecosystems. Bacteria and fungi are the most widely used
microbial organisms for inoculation studies. Both taxa have been found
to enhance plant growth when inoculated with plants (Coleine et al.,
2022; Zhang et al., 2019). Some previous work suggests that inoculation
with fungi will have greater effects on plant growth due to their
ability to ameliorate stress (Porter et al., 2020) and ability to thrive
in soils with a high carbon: nitrogen ratio (Güsewell and Gessner,
2009). On the other hand, the quick turnover of bacteria can cause them
to perform better than fungi (Hasheem et al., 2016). By understanding
the differences in the effect of fungal and bacterial inoculants on
dryland soils, we can inform future dryland restoration projects to
direct their limited resources more effectively.

\textbf{Material and Methods}

We conducted a systematic literature search following the general PRISMA
EcoEvo guidelines (O'Dea et al. 2021) to find a representative sample of
all published literature testing the impact of microbial inoculation on
plant growth in dryland ecosystems. We searched Scopus and ISI Web of
Science databases using UNSW Sydney's institution subscriptions for all
studies published before 1\textsuperscript{st} April, 2022 using the
search terms: (inocula*) AND (''plant growth'' OR ''plant biomass'' OR
''plant development'') AND (''dryland*'' OR ''arid land*'' OR
''semi-arid land*'') AND (``restor*'' OR ``remediat*'' OR
``rehabilita*''). Our search resulted in 923 publications for Web of
Science and 850 for Scopus. The total number of publications was reduced
to 1235 after 538 duplicates were removed (Table S1). We additionally
included one study from the author, Dadzie et al. (2022).

We selected studies based on five main eligibility criteria. First, we
only considered peer-reviewed primary studies, thus excluding books,
review papers, and theses. Second, the study must have been conducted in
a dryland ecosystem. We defined drylands as areas with annual
precipitation under 600 mm where potential evapotranspiration was
greater than the annual precipitation. When studies did not provide
climate information, we used location information to obtain approximate
climate information within the study duration via cross-checking with
historical WorldClim data (version 2.1, 30 seconds resolution
\textasciitilde{} 1 km square grid; Fick and Hijmans, 2017). Third, only
field studies were considered. Studies that were conducted in pots
(mesocosms) and left in the field were not included since the pots
provided a microclimatic condition. Fourth, studies must have compared
microbially inoculated and non-inoculated plants. We defined microbial
inoculation as bacteria and fungi that are purposefully added to plants
to improve their growth. Finally, studies must have reported
above-ground biomass as a metric for plant growth and development.
Studies that reported plant growth with other metrics were not included.
For studies that reported plant growth in consecutive years, only the
last year of the growing season was considered since we were interested
in the overall effect of microbial inoculation on plant growth.

To increase the comparability of our estimates, we ensured that the
conditions applied to each treatment were equally applied to the control
in each study. For example, when studies reported on the application of
fertilizer to the field before planting seeds, we ensured that the
controls were given similar fertilizer treatment else they were
excluded. In studies that reported both fertilizer application and
microbial inoculations as individual treatments, we selected controls
that were unfertilized and uninoculated, whereas only treatments that
were unfertilized but inoculated with microbial were considered for the
response measure. Where there was a crop rotation, we only included data
from the first rotation season since subsequent rotations were not
receiving direct inoculation and were confounded with plough-back
remnant crops.

\textbf{Data extraction and effect size estimation}

From each study, we extracted the mean above-ground biomass with its
associated measure of dispersion (i.e. standard deviations or standard
errors) for control and inoculated plants, the number of replicates per
treatment, the duration of plant growth, the environmental condition of
the site, the type of inoculated microorganism (i.e. bacteria or fungi),
the composition of the inoculated microorganisms (i.e. individual or in
a consortium), and the source of microbial inoculum (i.e. native,
foreign or commercial inoculant). Native microbial inoculants were
defined as microbes that were isolated from soils within the local study
area. Foreign microbes were those obtained from the same country but in
a different study area. Commercial microbes were those obtained from
commercial companies. Commercial microorganisms were separated from
foreign microbes in that the former often has additional plant
growth-associated components in addition to the microbial communities.
Therefore, in the analysis comparing effects between commercial and
native inoculation inoculants, foreign microbial communities were
excluded.

\textbf{Data Analysis}

To estimate the overall effect of microbial inoculants on above-ground
biomass, we used the natural log response ratio as our effect size,
calculated as lnRR = ln (V\textsubscript{i}/V\textsubscript{c}) (Hedges
et al., 1999), where V\textsubscript{i} is the mean of the treatments
(inoculated) and V\textsubscript{c} is the mean of the control
(uninoculated). Thus, the lnRR is positive when the magnitude of the
above-ground plant biomass of inoculated plants is greater than the
biomass of uninoculated plants, and vice versa. Statistical significance
was determined when 95\% confidence intervals did not overlap with zero.

We used hierarchical meta-analytic models using the
\emph{rma.mv}function from the \emph{metafor} package (Viechtbauer,
2010; version 3.0.2) to test for the mean effect of microbial
inoculation on plant growth. Study type, site, and species were found to
be non-independent so we included them as random variables in the
analyses.

We performed a meta-analytic model to determine the overall mean effect
of inoculation on plant growth, using an intercept-only model with
random effects for study type, site, and species. We then performed
meta-regressions using the moderators; microbial source (either native
or commercial), microbial type (either bacteria or fungi), and microbial
composition (single or multiple inoculants) in separate models to test
our hypotheses. All statistical analyses were conducted in R version
4.2.1 (2022). Statistical significance was determined when 95\%
confidence intervals did not overlap with zero. We reported
back-transformed effect sizes converted to the percentage scale to
facilitate interpretation (a percentage increase in plant growth in
inoculated plants versus non-inoculated plants). We also reported 95\%
prediction intervals (PI), which represent 95\% of the expected values
from future empirical studies, and also to put the result in perspective
to climate-specific comparisons (Moles, 2018). Plots were created with
the \emph{orchaRd} package (Nakagawa et al., 2021) supported under
the\emph{ggplot2} package (Wickham 2016).

Publication bias implies that statistically significant findings are
more likely to be published than non-statistically significant findings.
We assessed publication bias in our dataset by using hierarchical
meta-regressions using standard error or sampling variance as moderators
in our models (Nakagawa et al., 2022) and assessed it using Egger's
regression test (Figure Appendix 2). We also assessed the robustness of
our findings by performing sensitivity analysis (leave one out
analysis), where each study from the 62 studies was iteratively removed,
and the resulting data were fitted in an intercept-only meta-analytic
model.

We obtained a total of 172 effect sizes comparing inoculated from
uninoculated plants from 62 studies across the globe (Figure S1).
Ninety-four of the effect sizes were from restoration studies, 63 from
agriculture, and 15 from phytoremediation studies. The most commonly
used genus of fungi in plant inoculation was \emph{Rhizophagus} spp.
(N=34) while \emph{Pseudomonas} spp. (N=20) was the most abundant genus
of bacteria used in plant inoculation.

We found no strong evidence for publication bias nor an association
between plant responses to inoculation and either standard error (slope
= -0.48, CI = -0.78 - 1.11, N = 172). Our results were also robust to
the iterative removal of one study at a time. Across all models, the
inoculated increased plant biomass by 43.76\% (CI = 29.69\% - 58.8\%),
which is consistent with the overall effect previously reported (43.3\%,
CI = 29.69\% - 58\%, Figure 1A).

\textbf{Results}

Overall plant growth was increased by an average of 43.3\% when
inoculated with microorganisms (p = 0.0001, CI = 29.69\% - 58\%, Figure
1A). Most studies reported positive effects of microbial inoculation on
plant growth (N = 158, 92\%), with only 13 of the 172 observations (7.5
\%) reporting negative effects of microbial inoculation and a single
record finding no statistically significant effect of inoculation on
plant growth.

Native microbial inoculants increased plant growth on average by 53\%
(CI = 31\% - 80\%, replicates (N) = 78) while commercial inoculants
increased plant growth by 40\% (CI = 9\% - 78\%, replicates (N) = 23).
However, we found no statistically significant difference between the
two types of inoculants (p = 0.57, CI = -0.18 -- 0.37, Figure 1B).

Single microbial inoculants increased plant biomass by an average of
39\% (CI = 24\% - 55\%, replicates (N) = 108) while multiple strain
inoculants (biodiverse microbes) increased plant biomass by 49\% (CI =
32\% - 68\%, N = 64). This difference was not statistically significant
(p = 0.27, CI = -16.71\% -- 5.12\%, Figure 1C).

Fungal inoculation increased plant biomass by 39\% (CI = 28\% - 61\%, N
= 88) while bacteria inoculation increased plant biomass by 43\% (CI =
23\% - 58\%, N = 77). We found no statistically significant difference
between the effect of bacteria and the effect of fungi on plant growth
(p = 0.69, CI = -15.6\% - 11\%, Figure 1D).

\textbf{Discussion}

Our study confirms that even in harsh dryland soils, microbial
inoculation improves plant growth (Fig 1). The results suggest a
mutualistic relationship between microorganisms and plants, where the
plants benefit from an increase in growth as has been found in mesic
systems (Hoeksema et al., 2010; Nuenkamp et al., 2019; Rubin et al.,
2017; Schutz et al., 2018). The magnitude of the effect seen in drylands
(a 43\% increase in plant growth with inoculation) is similar to the
study of Rubin et al. (2017), who found that the effect of microbial
inoculation on plant growth under drought conditions is higher than
under well-watered conditions. Thus, our findings are consistent with
the stress-facilitation hypothesis of community interactions which
suggests that environmental stress increases facilitative interactions
between organisms (Bertness and Callaway 1994; Hammerlund and Harcombe
2019).

We did not find evidence to support the hypothesis that inoculation with
native microbes is more effective than commercially available
inoculants. Our results suggest that any advantage native microbes have
as a result of being adapted to the abiotic conditions of the site might
be counterbalanced by the fact that commercial inoculants have
presumably been developed to contain highly effective strains (Tsoi et
al., 2019). The lack of difference between native and commercial
inoculants (Fig 1) presents an opportunity for more effective dryland
restoration programs. Currently, commercial inoculants are more
expensive than native microorganisms (Kaminski et al., 2019), but have a
much lower barrier to entry compared to developing native inoculants
(Bell et al., 2019). Our results suggest that restoration practitioners
who have low technical knowledge of microbial isolation and culturing
can simply use readily available commercial inoculants.

Our hypothesis that inoculating biodiverse microorganisms will show a
stronger effect on plant growth than inoculating a single microbial
inoculum was not supported (Figure 1C). This observation is contrary to
the idea that increasing biodiversity enhances ecosystem function
through complementary and synergistic associations between individuals
(Wagg et al., 2014). However, there is evidence that microorganisms'
effects on ecosystem functionality are more strongly correlated with
microbial functional diversity than with species richness (Kitz et al.,
2015; Nielsen et al., 2011; Zhou et al., 2020). That is, increasing
species richness without concern for functional diversity might not
provide extra benefits to plant growth (Bender et al., 2016).

Our results show no clear benefit to the added expense and complexity of
including more diverse species in the inoculant (Fig 1). That is,
single-species inoculum provides a cost-effective and simple approach to
improving plant growth in dryland ecosystems. Maybe instead of
developing complex inoculants, we should be focusing our efforts on
identifying groups of inoculants that perform similar functions first.
By understanding individual functional groups of inoculants that produce
similar effects, we can avoid redundant diversity and create more
effective inoculant combinations with known results.

We found no evidence to support our hypothesis that the magnitude of the
effect from fungal inoculation is stronger than that of bacteria
inoculation. This result is contrary to the previous studies of Porter
et al. (2020) and Morris et al. (2007), who found that fungi had a
greater effect on plant growth than bacteria. However, there is evidence
that greenhouse studies maximise fungal effects on plant growth leading
to an overestimation of results when compared to field studies (Hart et
al., 2018; Rubin et al., 2017). This example highlights how caution must
be exercised when interpreting glasshouse studies in the context of
microbial influence on plant growth, especially within environments that
differ greatly from typical greenhouse climates.

\textbf{Conclusion}

Our work shows that microbial inoculation strongly increases plant
growth in drylands, and that different types of microbial inoculants
have broadly similar effects. Our work will help restoration
practitioners and also agriculturalists select affordable and effective
inoculants to enhance plant growth in drylands.

\textbf{Acknowledgments}

We would like to extend thanks to Joe Atkinson for his helpful
discussions in meta-analysis. We also appreciate the University of New
South Wales for facilitating open-access publications as part of the
Wiley - University of New South Wales agreement via the Council of
Australian University Librarians

\textbf{Conflict of Interest}

Authors had no conflicts of interest.

\textbf{Data Availability}

Data and codes will be stored publicly at Open Science Framework upon
acceptance of this manuscript.

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Figure 1: Effect size of microbial inoculation on plant growth in
drylands. Panel A demonstrates the overall effect of all microbial
inoculants on plant growth while Panel B compares the effect sizes
between native and commercial inoculants on plant growth. Panel C
compares the effect sizes between inoculating a single microbial strain
and inoculating multiple microbial strains. Panel D compares the effect
sizes of inoculating with fungi and inoculating with bacteria on plant
growth in dryland systems. The thicker horizontal line next to the
meta-analytic mean shows the confidence interval at 95 \% while the
thinner horizontal line shows the 95 \% prediction intervals (where you
expect individual effect sizes to be within this range). The letter K
represents the number of observations used for the analysis while the
number in parenthesis represents the total number of studies from which
the data was collected. An effect size of zero means there is no
treatment effect compared to the control while an effect size less or
greater than zero means there is a negative or positive effect on plant
growth respectively.\selectlanguage{english}
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