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\begin{document}

\title{Divergent changes in microbial communities and nutrients upon forest
floor humus layer of the sandy Pinus sylvestris var. mongolica
plantation in Northeast of China}



\author[1]{Yawei Wei}%
\author[1]{Mengge Wu}%
\author[1]{Zhiping Cheng}%
\author[1]{Chunlin Jing}%
\author[1]{Lingyu Yan}%
\author[1]{Deling Meng}%
\author[1]{Wenxu Zhu}%
\author[1]{Zhenju Chen}%
\affil[1]{Shenyang Agricultural University}%


\vspace{-1em}



  
  \date{June 13, 2024}


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\selectlanguage{english}
\begin{abstract}
The sandy \emph{Pinus sylvestris} var. \emph{mongolica} plantation that
as the boundary part of the Three North Shelterbelt Project in Northeast
China has been well protected and prohibited disturbance more than ten
years, and thus bring about lots of forest floor litter and then humus
layer. While humus layer accumulation that could change the interface
between litter and soil, its effects on litter and soil, and especially
the interaction among them were still poorly understood. Hence, three
different treatments that included remove all forest floor litter and
humus, double forest floor litter and humus layer, and retain forest
floor litter and humus original (no treatment) were conducted, and the
physicochemistry properties and microbial communities were monitored.
Results showed that the humus layer increased forest floor litter
decomposition rate and its total carbon, total nitrogen and total
phosphorus significantly, while it changed soil pH and nutrients
differently and slightly. The abundances of bacterial groups at
different taxonomic levels increased and while its diversity indexes
decreased in litter when the humus layer existed, however, the fungi
community both in litter and soil varied insignificantly. The humus
layer not only increased remarkably the proportions of common OTUs
between humus and litter, humus and soil compared to litter and soil
both for fungi and bacteria, but also decreased the differences of the
number of fungal and bacterial taxa statistics between litter and soil.
It implied that the humus layer could act an important role in the
recover process of degraded forest ecosystem.%
\end{abstract}%



\sloppy


\textbf{Divergent changes in microbial communities and nutrients upon
forest floor humus layer of the sandy \emph{Pinus sylvestris}
var.\emph{mongolica} plantation in Northeast of China}

Mengge Wu\textsuperscript{a,b}, Zhiping Cheng\textsuperscript{a,b},
Chunlin Jing\textsuperscript{a,b}, Lingyu Yan\textsuperscript{a,b},
Deling Meng\textsuperscript{a,b}, Wenxu Zhu\textsuperscript{a,b}, Yawei
Wei \textsuperscript{a,b}11Corresponding author. E-mail address:
ywei@syau.edu.cn, Zhenju Chen\textsuperscript{a,b}

\textsuperscript{a} College of Forestry, Shenyang Agricultural
University, 120 Dongling Road, Shenyang 110866, China

\textsuperscript{b} Research Station of Liaohe-River Plain Forest
Ecosystem, Chinese Forest Ecosystem Research Network, Changtu, Liaoning,
112500, China

\textbf{Abstract}

The sandy \emph{Pinus sylvestris} var. \emph{mongolica} plantation that
as the boundary part of the Three North Shelterbelt Project in Northeast
China has been well protected and prohibited disturbance more than ten
years, and thus bring about lots of forest floor litter and then humus
layer. While humus layer accumulation that could change the interface
between litter and soil, its effects on litter and soil, and especially
the interaction among them were still poorly understood. Hence, three
different treatments that included remove all forest floor litter and
humus, double forest floor litter and humus layer, and retain forest
floor litter and humus original (no treatment) were conducted, and the
physicochemistry properties and microbial communities were monitored.
Results showed that the humus layer increased forest floor litter
decomposition rate and its total carbon, total nitrogen and total
phosphorus significantly, while it changed soil pH and nutrients
differently and slightly. The abundances of bacterial groups at
different taxonomic levels increased and while its diversity indexes
decreased in litter when the humus layer existed, however, the fungi
community both in litter and soil varied insignificantly. The humus
layer not only increased remarkably the proportions of common OTUs
between humus and litter, humus and soil compared to litter and soil
both for fungi and bacteria, but also decreased the differences of the
number of fungal and bacterial taxa statistics between litter and soil.
It implied that the humus layer could act an important role in the
recover process of degraded forest ecosystem.

\textbf{Keywords}

the sandy \emph{Pinus sylvestris} var. \emph{mongolica} plantation,
humus layer, litter decomposition, soil physicochemical properties,
microbial community, forest rehabilitation

\textbf{INTRODUCTION}

The plantation plays an important role in China 's carbon sinks,
especially in recent years due to the implementation of many forestry
ecological projects and protection policies. On the other hand, lots of
forest floor litter and humus layer were emerged and accumulation, which
not only changes the interface and micro-environment between soil and
litter but also is crucial to the soil aggregate and nutrient return
(Lu, 2022). Some studies have demonstrated that soil humus is a complex
polymer decomposed and synthesized by animal and plant residues under
the action of microorganisms (Zavarzina et al., 2021), and the
substances that resist degradation provide the building blocks for the
synthesis of soil humus, thereby promoting its formation (Scarciglia et
al., 2020). Humus has a unique structural pattern different from other
soil compounds and can be used as a representative of natural organic
matter in terms of chemical composition (Dou et al., 2020), furthermore,
it encompasses all the essential chemical elements required by
terrestrial plants and serves as a source of nutrients for both mineral
and non-mineral nutrition. Hence, the humification and its process of
forest litter plays a crucial role in enhancing soil fertility and
ensuring ecosystem stability (Qiu et al., 2023).

Microorganisms has been demonstrated that play a crucial role in the
material cycle between plants and soil, influencing soil physical and
chemical properties as well as plant growth and development (Toledo et
al., 2023). Moreover, soil microorganisms have the ability to rapidly
respond to the changed environment and reflect soil fertility (Yu et
al., 2019), and its diversity and structure often be used as indicators
for soil nutrient availability, soil ecosystem stability, and soil
ability to withstand ecological deterioration (Sun et al., 1997; Jiang
et al., 2016). While humus is a result of the interactions between
microorganisms and forest litter, it also could act as an energy source
and release nutrients for plants and microorganisms under specific
conditions (Wang et al., 2023; Wang et al., 2021a). However, the effect
of humus (forest floor humus layer) on microbial community in litter and
soil, especially their interaction is still unclearly.

The sandy Mongolian pine (\emph{Pinus sylvestris} var. \emph{mongolica}
) plantation of northwestern Liaoning which as the important part of the
Three North Shelterbelt Project play an important role in wind breaking,
sand fixing and carbon sequestration. Lots of forest floor litter and
humus were accumulated in recent ten years. Hence, this study selected
this Mongolian Scots pine plantation to monitor the variation of soil
and litter nutrient and microbial community when the humus layer existed
and aimed to enhance the understanding of forest soil and litter
nutrient cycle. Besides, it also expected to provide new data and
theoretical support for sustainable forest management in China.

\textbf{MATERIALS AND METHODS}

\textbf{2.1. Study site}

This study relies on the Liaohe-River Plain Field Safeguarding Forest
Ecosystem Research Station (123\selectlanguage{ngerman}°38\selectlanguage{english}'52''E,43deg23\selectlanguage{english}'23''N, Figure 1), which
is situated in the northwest of Liaoning Province and at the
southeastern edge of Horqin Sandy land in northeastern China. This area
belongs the part of the Three-North Shelterbelt Project of China. The
region has a temperate semi-humid semiarid continental monsoon climate.
The winters are long and cold, and summers are short and hot. The annual
temperature changes from -32\selectlanguage{english}\textasciitilde{}35.6\selectlanguage{english}, and the annual
precipitation is 450mm\textasciitilde{}550mm, which is mostly
concentrated from July to August. The annual evaporation is nearly
1800mm, which is 3-4 times the annual precipitation. The growing season
is from the beginning of May to the beginning of October. The soil type
of this region is sandy soil (primosols), characterized by low nutrient
content.

\textbf{2.2. Sample plots and experimental design}

The sandy Mongolian pine plantation of more than 50 years was selected,
and three 5m x5m plots were established at the beginning of May in 2021.
Then three sub-plots of 2m x2m were arranged in each 5m x5m plot, and
the three sub-plots were designated for remove all the forest floor
humus and litter (RT), double the forest floor humus and litter (humus
and litter from treatment (1), DT), retain the existing forest floor
humus and litter (no treatment, CT), respectively. Additionally, the
understorey vegetation within the sub-plots was cleared periodically to
exclude effects of shrub and herbal. The litterbag method was applied to
compare the effect of humus layer on litter decomposition,
physicochemical and microbial community. Then eight litterbags (size:20
x15cm) with a pore size of 0.01mm (150 mesh, exclude soil animals) and
within 10g (based on dry weight) of the current year's withered leaves
of this pine were deployed on the top of soil surface (RT) and humus
layer (DT and CT) in each sub-plot and fasted using 10cm long legs of
stainless steel, respectively. Moreover, the temperature sensor of HOBO
was placed with the decomposed litterbags.

\textbf{2.3 Sample collection and processing}

Samples of soil, forest floor humus and litter (decomposed litterbags)
were collected in each sub-plot at early August 2022, respectively. Soil
were obtained using the multi-point mixed sampling method. A soil auger
was used to collect samples from a depth of 0-5cm, and humus were
collected between soil and undecomposed aboveground litter only in the
DT and CT sub-plots. At the same time, eight decomposed litterbags were
taken back and cleaned carefully in each sub-plot. One half of the soil,
humus and litter samples were stored in sterile labeled zip lock bags
and transported to the laboratory in an ice box for microorganisms
tested, and the other were taken back and air-dried for basic
physicochemical properties tested.

Soil pH (1:2.5 soil: deionized water slurries) was measured with a Leici
PHS-3C pH meter (Zhang et al., 2021). Determination total carbon (TC)
and nitrogen (TN) by the elemental analyzer (Elementar Vario EL III,
Hanau, Germany). Total phosphorus (TP) was measured with an AA3 flow
analyzer (AA3, Hamburg, Germany). Determination of soil ammoniacal
nitrogen, nitrate nitrogen, and available phosphorus were measured using
a spectrophotometer, following the method described by Lu (2000).

\textbf{2.4. DNA extraction and sequencing of litter and soil
microorganisms}

Soil, humus and litter genetic material was extracted from 0.25g of
fresh soil and litter using OMEGA Mag-bind Soil DNA Kit (Omega M5636-02)
(Omega Bio-Tek, Norcross, GA, USA). Follow-up steps follow the
instructions of DNA Isolation Kit. After extraction, the DNA extraction
quality (purity and integrity) was checked by 1\% agarose gel
electrophoresis, and the concentration and p-urity of the DNA extract
were checked with a nucleic acid quantifier NanoDr-op ND-1000(Thermo
Fisher Scientific, Waltham, MA, USA). The fungal ITS r-egion was
amplified with primers ITS1F(5'-CTTGGTCATTTAGAGGAAGTAA-3') and
ITS2R(5'-GCTGCGTTCTTCATCGATGC-3'); The V3-V4 regions of ba-cterial 16S
rRNA gene was amplified with primers 338F (5'-ACTCCTACGGGAGGCAGCA-3')
and 806R (5'-GGACTACHVGGGTWTCTAAT-3'). PCR ampli-fication products were
detected by 2\% agarose gel electrophoresis, and then re-covered using
AXYGEN's gel recovery kit. The products were sent to Shangh-ai Paisenuo
Biotechnology Co., Ltd (Shanghai, China), and the sequencing libr-ary
was prepared using TruSeq Nano DNA LT Library Prep Kit (Illumina,
Bei-jing, China).

\textbf{2.5. Statistical analysis}

The fitting effect of the amplicon sequence variant (ASV) partitioning
method and the environment is better than that of the OTU partitioning
method, which can more accurately capture the community information.
Therefore, in this study, the DADA2 method was used to perform the steps
of depriving (Callahan et al. ,2016) quality filtering, denoise,
splicing and decimalization to generate ASVs. ASVs were extracted using
QIIME2 (2021) to obtain the bacterial and fungal community composition
of each sample at the phylum and genus, and displayed as a relative
abundance heatmap. Alpha diversity analysis was performed on ASVs
including Good's coverage, Chao1, Shannon, Simpson index and Observed
species. In samples with high diversity, the ASV method would reduce the
Chao1 indices to a certain extent (Zhong et al., 2022), so the above
four indices are selected for alpha diversity analysis in this study.
Differences in soil \selectlanguage{greek}β-\selectlanguage{english}diversity were analyzed based on the Operational
Taxonomic Units (OTU) table, and APE package in R (R v.3.4.4) (New
Zealand). Common and unique OTUs of soil microbial communities in each
sample were analyzed in R (R v.3.4.4). The Bray--Curtis distance was
used to analyze the differences in microbial community structure among
different soil and litter samples (Bray et al., 1957), and visualized by
principal coordinate analysis (PCoA) (Ramette et al., 2007) and
non-metric multidimensional scaling (NMDS). Venn diagrams were generated
using the ``Venn diagram'' package. Stacked histograms of species
composition were the most commonly used means of characterizing the
species composition of multiple samples. IBM SPSS Statistics
22.0(Chicago, IL, USA) was used to analyze the correlation between soil
and litter nutrients and the relative abundance of bacteria, fungi at
the phylum and genus. Redundancy analysis (RDA) was performed through
Canoco5 and the gene cloud tool of the free online data analysis
platform (\emph{https://www.genescloud.cn/login} (accessed on 10 May
2023) was used to construct a correlation heatmap.

\textbf{RESULTS}

\textbf{3.1. Effects of humus layer on soil and litter physicochemical
properties}

Both soil and litter physicochemical properties were changed differently
due to humus layer (Table 1). All contents of total carbon (TC), total
nitrogen (TN), total phosphorus (TP) and litter decomposition rate in RL
were decreased significantly compared to CL and DL, similarly, both C/P
and N/P ratio also exhibited the same trend. On the other hand, contents
of TC and TN among RS, CS and DS varied slightly, while TP in DS
increased remarkable. In addition, the presence of humus layer also
changed soil VWC, pH, AP, NH\textsuperscript{4+-}N and
NO\textsuperscript{3-}-N to varying degrees. Moreover, the contents of
TC, TN, C/P and N/P in humus layer were significantly higher than those
in litter and soil, and TP was significantly lower than that in litter.

\textbf{3.2. Effects of humus layer on soil and litter microbial
community characteristics}

3.2.1. Distribution characteristic of microorganisms at each taxonomic
level

The classification levels of microorganisms in litter and soil were
varied differently due to the forest floor humus layers (Table 2). The
abundance of fungi groups in DL and RL increased compared to CL, except
in phylum level. Conversely, the bacterial groups in DL and RL all
decreased compared to CL, except phylum level in DL and species levels
in RL. Similarly, the bacteria groups in soil showed the same trend like
it exhibited in litter. The fungi groups in soil changed slightly, it
decreased in DS and RS at the genus and species levels while it
increased in DS and RS at order level.

3.2.2. Analysis of taxonomic composition at the phylum level

The community structures of fungal and bacterial phyla varied
differently in litter and soil (Figure 2). The relative abundance of
each prevalent fungal phylum was lower in litter compared to soil. The
dominant fungal phyla at the classification level were Ascomycota,
Basidiomycota, Rozellomycota, Chytridiomycota and Mortierellomycota both
in litter and soil, but their relative abundances were lower noticeable
in litter than in soil. While both Ascomycota and Basidiomycota
abundances increased in RL and DL compared to CL, only Basidiomycota
abundances increased in DS and RS compared to CS (Figure 2a; 2b).

The prominent bacterial phyla were Proteobacteria, Actinobacteria,
Acidobacteria, and Bacteroidetes, and their abundances were higher
slightly in litter than in soil (Figure 2c; 2d). The Proteobacteria
abundance increased in DL while it decreased in RL, and Actinobacteria
abundance increased in RL and decreased in DL compared to CL. The
relative abundance of bacterial phyla changed slightly in soil.

3.2.3. Analysis of taxonomic composition at the genus level

The community structures and dominant fungal and bacterial genera both
in litter and soil varied differently due to the humus layer (Figure 3).
The dominant fungal genera at the classification level
were\emph{Xenopolyscytalum} , \emph{Mycena} , \emph{Trechispora}
and\emph{Knufia} in litter, while they were \emph{Amphinema} ,
and\emph{Mortierella} , \emph{Tomentella} , and \emph{Fusarium} in soil
(Figure 3a; 3b). The relative abundance of the two dominant fungi in
litter was lower than that in soil. The relative abundance
of\emph{Xenopolyscytalum} in RL was significantly higher than it in DL
and CL, while the relative abundance of \emph{Mycena} in DL was
significantly higher than it in RL and CL. The relative abundance
of\emph{Amphinema} both in RS and DS were increased remarkably compared
to CS, and \emph{Sebacina} abundance was significantly reduced in RS.
Besides, the other fungal genera abundances changed unnoticeable in
soil.

The relative abundances of all prominent bacterial genera were
remarkably low both in litter and soil (Figure 3c; 3d). The dominant
bacterial genera were \emph{Sphingomonas} , \emph{Actinoplanes}
,\emph{Methylobackterium} and \emph{Allorhizobium} in litter, while they
were \emph{Subgroup-6} , \emph{Bacillus} , \emph{Subgroup-2}
and\emph{Bradyrhizobium} in soil. Moreover, the abundances of prominent
bacterial genera increased in RL while it increased in DS compared to
litter and soil, respectively.

3.2.4. Analysis of alpha diversity

As Figure 4 demonstrates that the box plot gradually becomes more
compressed while the number of samples increases, which supports that
there are approximately 4000 fungal species, and 35000 bacterial species
present in abundance. Moreover, the Goods coverage index indicates all
samples have a probability greater than 0.995 (Table 3), which
indicating a high level of accuracy in the measurement of sequences and
the sequencing outcomes have effectively covered the majority of species
in the test samples.

The diversity and richness of microbial communities both in litter and
soil changed differently due to the forest floor humus layers (Table 3).
The Chao 1 index, Shannon index and Simpson index of litter fungi all
increased significantly in DL and RL, especially in DL, while all the
three indexes decreased in DS and RS compared to soil. On the other
hand, the Chao1 index of litter bacteria increased in RL and decreased
in DL, while both the Shannon index and Simpson index increased in RL
and DL compared to CL. Similarly, the three indexes also changed in
soil, but these differences were not statistically significant.

3.2.5. Analysis of beta diversity

As Figure 5 showed that the first principal component (PCo1) and the
second principal component (PCo2) jointly contributed 59.4\%, 45.5\%,
40.2\%, and 39.1\% to the variation in litter fungi (Figure 5a), litter
bacteria (Figure 5b), soil fungi (Figure 5c) and soil bacteria (Figure
5d), respectively, which demonstrates that the axes provide a
comprehensive understanding of the microbial community's structure. The
NMDS analysis revealed that all Stress values were below 0.2, indicating
a reliable scoring model. In terms of the microbial community structure,
the fungus showed closer proximity between DL and RL (Figure 5a), while
the bacteria showed closer proximity between DL and CL (Figure 5c). On
the other hand, the community structure of fungus exhibited disperse and
the bacteria centralize in soil (Figure 5b; 5d).

\textbf{3.3. Role of humus layer between litter and soil}

3.3.1. Analysis of microbial communities using species differences

As Figure 6 depicted that the number of microbial OTUs varied
differently between litter and soil due to humus layer. For example, the
proportions of fungal OTUs in common were only 138 and its account for
27.77\% and 9.22\% of total RL and RS, respectively (Figure 6a; Table
4), and it increased to 36.32\%\textasciitilde{}41.50\% and
11.87\%\textasciitilde{}14.20\% of total litter and soil OTUs when humus
layer emerged (Figure 6a; Table 4). The similar trends of OTUs in common
between litter and soil were also existed in bacteria community,
although its proportions were decreased distinguished compared to fungal
(Figure 6b; Table 4).

3.3.2. Statistics on the quantity of taxonomic units

Both the number of fungal and bacteria taxa statistics increased from
litter to soil, and the differences between litter and soil were
distinguished, especially for fungal (Figure 7), the humus layer
decreased this differences while it existed. For example, the
differences between litter and humus, humus and soil were relative
slightly both in fungal and bacteria taxonomic statistics.

\textbf{3.4. Correlation analysis of microbial community composition and
soil physicochemical properties}

Spearman's correlation analysis was conducted to examine the
relationship between the physicochemical properties of each sample and
the top ten microorganisms at the phylum (Figure 8) and genus (Figure 9)
taxonomic level, respectively. It illustrates the combination of RDA1
and RDA2 achieved 83.83\% and 90.67\% for fungi (Figure 8a) and bacteria
(Figure 8b), respectively, indicating the effectiveness of the sorting
axis in capturing the relationship between physicochemical properties
and microorganism. Fungal phylum was significantly associated with TC
(60.3, P=0.002) and TN (23.5, P=0.002). Among them, Ascomycota,
Mortierellomycota, Glomeromycota and Mucoromycota were significantly
negatively correlated with TC and TN, while Basidiomycota was
significantly negatively correlated with TN (Figure 8a). In addition,
bacterial phylum was significantly correlated with C/P (77.7, P=0.002)
and TP (19.7, P=0.002). Among them, Proteobacteria and Bacteroidetes
were significantly positively correlated with TP, Acidobacteria,
Firmicutes and Gemmatimonadetes were significantly negatively correlated
with TP, while Firmicutes, Gemmatimonadetes and Patescibacteria were
significantly positively correlated with C/P (Figure 8b).

As shown in Figure 9, the combined percentages of RDA1 and RDA2 for
fungi (Figure 9a) and bacteria (Figure 9b) were 74.32\% and 67.12\%,
respectively. This indicates that the ordination axis effectively
captures the relationship between environmental factors and communities.
There was a significant correlation between fungal genera and N/P (53.7,
P=0.002) and TP (22.4, P=0.002), and \emph{Xenopolyscytalum}
,\emph{Amphinema} , \emph{Tomentella} , \emph{Fusarium}
,\emph{Penicillium} , \emph{Pseudogymnoascus} and \emph{Trichoderma}
were significantly negatively correlated with N/P and TP (Figure 9a).
Bacterial genera were strongly correlated with TP (57.1, P=0.002) and TN
(19.8, P=0.002), and \emph{Sphingomonas} , \emph{Actinoplanes}
,\emph{Methylobacterium} , Allorhizobium and \emph{Mycobacterium} were
significantly positively correlated with TP and TN,
while\emph{Bradyrhizobium} , \emph{Subgroup\_6} and \emph{Bacillus} were
significantly negatively correlated with TP and TN (Figure 9b).

\textbf{DISCUSSION}

\textbf{4.1. Effect of forest floor humus layer on litter and soil}

Humus provides a conducive environment for interactions among plants,
soil, and microorganisms, which are crucial in forest ecosystems
(Sohrabi et al., 2022). This study also found that the divergent changes
in nutrients and microbial communities both in litter and soil due to
the forest floor humus layer emerged in sandy Mongolian Scots pine
plantation in the Three North Shelterbelt Project of Northeastern China.
For example, the forest floor litter decomposition rate and its
nutrients i.e. the contents of total organic carbon, total nitrogen,
total phosphorus all increased when humus layer emerged (Table 1) in
this study. It identified with the former studies that humus accelerated
the processes of decomposition and nutrient cycling in forest ecosystems
(Sohrabi et al., 2022; Zhao et al., 2023). As the higher carbon and
nitrogen content in the humus layer, which creates favorable conditions
for microbial growth, resulting in a more abundant microbial community
and stronger microbial activity (Wang, 2021b), and the increased
microbial activity contributes to the litter decay and nutrient cycling.
On the other hand, both soil total phosphorus and available phosphorus
reduced significantly in RS compared to DS (Table 1), which implied that
the forest floor humus layer could enhance soil nutrients (Zhao et al.,
2023), and especially phosphorus that was very poor in this sandy land
of northeastern China (Zhang et al., 2023).

The composition and distribution of microbial communities that are
highly sensitive to environmental changes can significantly impact
ecosystem functioning (Gao et al., 2023), and microbial community and
taxonomic composition were changed differently in soil and litter due to
the humus layer existed in this study. Both the litter fungi groups at
different taxonomic levels and its community diversity indexes were
mostly increased when the humus layer removed or doubled (Table 2 and
4), especially the diversity indexes increased significantly, while soil
fungi diversity indexes decreased, it means that the effects of humus on
litter and soil fungi were distinct, and fungi communities were affected
easily by disturbance activities. Additionally, the litter bacteria
community at different taxonomic levels increased while its diversity
indexes decreased with the humus layer emerged (Table 2 and 3), on the
other hand, soil bacteria community changed differently with litter. It
primarily due to differences in carbon and nitrogen sources input
resulting from the addition of humus layers (Cleveland and Townsend,
2006), which could lead to structural changes in microbial communities
(Wang et al., 2022a; Gillespie et al., 2021; Xiao et al., 2022).
Ascomycota and Basidiomycota are the primary fungal groups responsible
for decomposing the cell wall structure and other complex substances of
litter (Gong et al., 2023; Qu et al., 2023), and they are primarily
associated with humic environments and are essential decomposers of
nutrients in soil (Yu et al., 2022). The dominant fungal phyla observed
in this study were Ascomycota and Basidiomycota both in litter and soil,
which aligns with the findings of Shen et al. (2023), and their relative
abundance increased obviously in litter when the humus layer existed or
not, but they varied slightly in soil (Figure 2 and 3). On the other
hand, the main bacterial phyla identified in this study are
Proteobacteria and Actinobacteria, which were demonstrated capable of
breaking down complex biological macromolecules, such as lignin and
cellulose (Llad\selectlanguage{ngerman}ó, 2016), and play a crucial role in humus formation.
Interestingly, the relative abundance of Proteobacteria was increased
and Actinobacteria was decreased in litter with the humus layer emerged.
Wang (2022b) has suggested that Proteobacteria thrive by absorbing
nutrients like ammonia and methane produced during humus formation,
whereas Actinobacteria can flourish in environments rich in
high-molecular compounds, including cellulose, hemicellulose, and fungal
hyphae (Gousia et al., 2023).

\textbf{4.2. The linkages of forest floor humus layer between litter and
soil}

The former studies found that plant leaves carry unique species-specific
and universal microorganisms and can be transmitted through seeds or
animals (Wagner et al., 2016), or share a considerable proportion of
fungi with soil (Massoni et al., 2021), which was supported in this
observation that litter and soil have few microbial communities in
common (Figure 6). But while the humus layer existed the jointly
microbial communities increased distinguished between litter and humus,
humus and soil compared to litter and soil (Figure 6, Table 4), which
implied that the forest floor humus layer maybe act the role of
transition between litter and soil. On the other hand, the proportions
of jointly microbial communities between litter and humus were higher
noticeable than it between soil and humus, it was related to the process
that humus was formed from aboveground litter. Moreover, the proportions
of jointly fungi OTUs were significantly higher than bacteria OTUs in
common (Table 4), which demonstrated that the fungal community has a
significant impact on plant litter decay while the bacterial community
has a relatively smaller effect (Heinen et al., 2020). Moreover, adding
litter to the soil has been found to enhance the abundance of existing
microorganisms and introduce new microorganisms. This is attributed to
the fact that these foliar microorganisms can have positive and negative
effects on soil microorganisms. Similar to the release of chemical
substances from plant roots to soil, litter also releases chemical
substances, affecting the chemical properties of humus layer and soil
(Veen et al., 2019). Besides, similarly to the former result (Yang et
al., 2023) the number of fungal and bacterial taxa increased gradually
from litter to humus to soil (except for bacteria at the genus and
species levels) in this study, which further proved the bridge role of
the forest floor humus.

\textbf{4.3. The influencing factors on microbial community}

Former studies have demonstrated that microbial community was affected
by a variety of environment factors (Ji et al., 2020; Lin et al., 2023),
and this study also showed that the fungal community was mainly affected
by TC and N/P ratio, while the bacterial community was mainly affected
by TP and C/P ratio. Moreover, microbial community at the genus level
also exhibited significantly correlation-ships with C/N and C/P ratios,
that as the former study showed that the C/N and C/P ratios play a
crucial role in the process of litter decomposition and nutrient release
(Liu, 2023).

\textbf{CONCLUSIONS}

Soil and litter microbial communities and physicochemical properties
were changed differently when the forest floor humus layer emerged.
Firstly, total carbon, total nitrogen and total phosphorus of litter all
increased when forest floor humus layer existed, simultaneously, the
litter decomposition rate were also increased significantly. On the
contrary, soil pH and nutrients changed slightly. Secondly, litter
bacteria groups at different taxonomic levels (except species) all
increased while its diversity indexes decreased when the humus layer
existed, on the other hand, both soil and litter fungal community and
soil bacterial communities changed differently and undistinguished.
Thirdly, the humus layer increased the proportions for its jointly
number of microbial OTUs with litter and soil compared to litter and
soil, moreover, it decreased the differences on the quantity of both
fungi and bacteria taxonomic units between litter and soil. General,
soil and litter nutrients and microbial communities changed differently
when the forest floor humus layer emerged, moreover, it reduced the
differences between litter and soil, which means the forest floor humus
layer could play a more important role in forest carbon cycle that was
neglected in former recognized. However, it should be pay more attention
deeply on the effects of humus layer and its interaction between soil
and litter.

\textbf{DATA AVAILABLITY STATEMENT}The authors will supply the relevant
data in response to reasonable requests.\textbf{CREDIT AUTHORSHIP
CONTRIBUTION STATEMENT}

\textbf{Mengge Wu:} Conceptualization, Methodology, Software,
Writing--original Draft, Visualization. \textbf{Zhiping
Cheng:}Conceptualization, Validation, Formal Analysis,
Investigation.\textbf{Chunlin Jing:} Conceptualization, Software,
Validation, Investigation. \textbf{Lingyu Yan:} Conceptualization,
Validation, Data curation. \textbf{Deling Meng:} Conceptualization,
Validation, Data curation. \textbf{Wenxu Zhu:} Resources, Supervision.
\textbf{Yawei Wei:} Conceptualization, Writing--review \& editing,
Supervision\selectlanguage{english},Project administration, Funding acquisition. \textbf{Zhenju
Chen:} Project administration, Funding acquisition.

\textbf{DECLARATION OF COMPETING INTEREST}

The authors declare that they have no known competing financial
interests or personal relationships that could have appeared to
influence the work reported in this paper.

\textbf{ACKNOWLEDGEMENTS}

This research was supported by the National Natural Science Foundation
of China (NSFC, No.32271843, 41888101, 41871027) and the project of
forestry science and technology innovation platform operation subsidy
(No.2022132224).

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