Effects of mechanical weeding on soil fertility and microbial community structure in star anise (Illicium verum Hook.f.) plantations.

Recently, the effects of weed control on crop yield, quality and soil fertility have been increasingly investigated. However, soil microorganism diversity under weed control, especially for aromatic plants, is little studied. Mechanical weeding effects on soil fertility and microbial diversity in star anise plantations remain unknown, limiting improvements in crop quality and yield through weed control. Therefore, mechanical weeding (MW) and no weeding (NW) zones were randomly designed in the same star anise plantation to study the mechanical weeding impacts on soil biological properties and microbial diversity. The phosphatase activity of MW soil was significantly higher than that of NW soil; however, aminopeptidase activity was significantly lower than that under NW. There was no significant difference in β-glucosidase activity between MW and NW. Moreover, soil microbial biomass C and N in MW soil were significantly higher than those of NW, but soil microbial biomass P was significantly lower than that of NW. Proteobacteria, Acidobacteria, Actinobacteria, Chloroflexi, Planctomycetes, WPS-2, Firmicutes and Verrucomicrobia were the predominant bacterial phyla in MW and NW soils. Specifically, Bacteroidetes was enriched in MW soil, being the unique dominant bacteria. Ascomycota, Basidiomycota, unclassified_k_Fungi, Rozellomycota and Mortierellomycota were the predominant fungi in MW and NW soils. The numbers of dominant bacterial genera (> 1%) were 26 and 23 for NW and MW soils, respectively. Among them, norank_f__norank_o__norank_c__Subgroup_6, 1921-2 and norank_f__norank_o__B12-WMSP1 went undetected in MW soil. Moreover, the numbers of dominant fungi in soils of star anise plantations were 11 and 9 for NW and MW, respectively. Among them, only unclassified_f__Clavicipitaceae and Mortierella went undetected in MW soils. Thus, soil microbial community structures are not significantly altered by mechanical weeding. The above results suggest that soil fertility can be improved and soil heath can be maintained by mechanical weeding in star anise plantations. Moreover, soil-borne diseases maybe easily occurred under NW treatment in star anise plantation.

Introduction

In agricultural systems, weeds are defined as plants growing in unwanted places and are related to crop damage through direct nutrition competition or parasitism. Moreover, weeds also cause indirect damage by harboring pests and crop pathogens. The direct losses caused by weeds are related to the different crop types and agroecological zones [1]. In China, more than 1,400 kinds of weeds have been reported, 30 of which are the most troublesome. More than 3 million tons of grain are lost every year due to weeds in China [2].

Star anise (Illicium verum Hook.f.) is an aromatic evergreen tree native to western China, Vietnam, Cambodia, Myanmar, Indonesia, the Philippines and other subtropical regions. Its fruits are not only an important Chinese medicine, treating vomiting, stomachache, insomnia, skin inflammation and rheumatism [3, 4], but also a common spice in cooking [5], being introduced into Europe in the 17th century. Its unique licorice flavors are the result of a compound called anisole [4, 6]. Moreover, its bark, seeds, leaves, branches and fruits are rich in fennel oil with antibacterial [7], antiviral [8], and antioxidant [9] functions. In the modern pharmaceutical industry, star anise is used as an industrial source of shikimic acid and an important ingredient of the antiviral drug Tamiflu (oseltamivir phosphate) [10].

Guangxi Province, located in southwestern China, is the native production area of star anise. The star anise yield in Guangxi accounts for 80% and more than 85% of its total production every year worldwide and throughout China, respectively [11]. However, the yield per unit area of star anise in Guangxi is very low and unstable due to inappropriate management, including weed control. Recently, this has become a limiting factor for the sustainable development of the star anise industry in Guangxi. As weeds interfere with tree growth at any time and any stage of production, they can compete for nutrients, water, space, light and even harbor pests and pathogens, causing problems for mechanized harvesting and potentially changing the final crop quality [12]. Therefore, weed control is an important problem to consider for the sustainable development of star anise production. To improve the yield and profit margins of the star anise industry, weeding in star anise plantations must be correctly established and properly maintained. That is, a good weed management practice is essential. Previous studies have shown that weeding is an effective practice for tree plantation management [13] because it promotes the growth of planted trees [14] by reducing competition between planted trees and weeds [15].

First, star anise growers mostly rely on the application of chemical herbicides and mechanical mowing in their production fields. However, frequent application of chemical herbicides not only causes negative environmental issues, such as herbicide leaching, drift and run-off, but also induces severe phytotoxic injuries to star anise trees, including stunted growth, chlorosis, burning and dropping of leaves, and even complete death of the tree. Due to these issues surrounding chemical herbicide use and increasing concern among star anise consumers related to herbicide and pesticide applications, many star anise producers are interested in strategies to reduce or even eliminate chemical weed management. Currently, mechanical mowing with a brush cutter is commonly conducted once or twice per year by operators in Guangxi star anise plantations. However, the effect of current weed control practices on soil quality, such as soil health and fertility in star anise plantations, has been seldom reported.

Soil quality is influenced by the interplay of physical, chemical and biological soil factors [16]. Soil physical and chemical indicators are commonly used by farmers and researchers to assess soil quality, and biological indicators are frequently underrepresented [17]. However, previous studies have shown that biological indicators, such as soil organisms, particularly soil microbial activity and community structure, can be sensitive to the quality and health of soil ecosystems [18]. In other words, biological indicators can help to better elucidate the soil response to management as well as the underlying relationships. The purpose of this manuscript is to provide a theoretical direction for nonchemical weed control strategies in star anise plantations and identify areas where current practices could potentially support the sustainable development of star anise production.

Materials and methods

Study area and sampling

Soil samples were collected from the Paiyangshan forest farm (107°5′E, 22°1′N), Ningming County, Guangxi Zhuang Autonomous Region, Southwest China. This region is in the subtropical monsoon climate zone with an annual average temperature of 22 °C, and the mean annual precipitation rainfall ranges from 1400 to 2400 millimeters.

The soil type of the study area was acid red loam with a pH of 5.46 and an organic matter content of 12.9 g kg-1. The total contents of nitrogen, phosphorus and potassium in the topsoil were 0.81, 0.39 and 2.68 g kg-1, respectively. Moreover, the contents of alkaline nitrogen, available phosphorus and potassium were 53.7, 9.1 and 89.0 mg kg-1, respectively.

Weed control approaches were arranged randomly with mechanical weeding (MW) and no weeding (NW) zones in the same star anise plantation. The experiment comprised three replicate blocks each with three plots (50 × 50 m each) assigned to two treatment combinations: MW and NW. Weeding with a brush cutter was conducted in early July 2019, and all the cut plant materials were left on the ground.

One month later, in August, soil samples were collected from the MW and NW blocks. First, we removed the litter on the soil surface and collected three disturbed soil subsamples from the 0–20 cm soil layer. Three samples were selected from each species in soil of star anise with different treatments, and one soil sample was taken from each tree. All soil samples were collected in separate sterile bags, which were sealed and placed in an incubator with ice packs until they were taken to the laboratory for processing. In the laboratory, the soil attached to the plant’s fine roots was defined as rhizosphere soil, and the remaining soil was classified as bulk soil. The rhizosphere soil samples were used for DNA extraction and enzyme activity analysis, and the remaining soil samples were used for soil property determination.

Soil biological property analysis

The activities of three soil enzymes involved in the C cycle (β-glucosidase), N cycle (aminopeptidase) and P cycle (phosphatase) were determined. The β-glucosidase activity was measured using the method described by Hayano [19]. Aminopeptidase activity was measured using the method described by Ladd [20]. Phosphatase activity was measured using the method described by Tabatabai and Bremner [21].

The soil microbial biomass carbon was determined by the chloroform fumigation extraction-volumetric analysis method [22], soil microbial biomass nitrogen was determined by ninhydrin colorimetry [23], and soil microbial biomass phosphorus was determined by the phosphorus molybdenum blue colorimetric method [24].

Analysis of soil microbial diversity

Microbial community genomic DNA was extracted from samples using the FastDNA® Spin Kit for Soil (MP Biomedicals, U.S.) according to manufacturer′s instructions. The DNA extract was checked on a 1% agarose gel, and DNA concentration and purity were determined with a NanoDrop 2000 UV-vis spectrophotometer (Thermo Scientific, Wilmington, USA). The V3-V4 hypervariable region of the bacterial 16S rRNA gene was amplified with primer pairs 338F (5’-ACTCCTACGGGAGGCAGCAG-3’) and 806R (5’-GGACTACHVGGGTWTCTAAT-3’), and the ITS1 region of the fungal ITS gene was amplified with primer pairs ITS1F (5’-CTTGGTCATTTAGAGGAAGTAA-3’) and ITS2R (5’-GCTGCGTTCTTCATCGATGC-3’) by an ABI GeneAmp® 9700 PCR thermocycler (ABI, CA, USA). PCR amplification of the 16S rRNA gene was performed as follows: initial denaturation at 95 °C for 3 min, followed by 27 cycles of denaturing at 95 °C for 30 s, annealing at 55 °C for 30 s and extension at 72 °C for 45 s, a single extension at 72 °C for 10 min, and a final extension at 4 °C. The PCR mixtures contained 5 × TransStart FastPfu buffer 4 μL, 2.5 mM dNTPs 2 μL, forward primer (5 μM) 0.8 μL, reverse primer (5 μM) 0.8 μL, TransStart FastPfu DNA Polymerase 0.4 μL, template DNA 10 ng, and ddH2O up to 20 μL. PCRs were performed in triplicate. The PCR products were extracted from a 2% agarose gel and purified using the AxyPrep DNA Gel Extraction Kit (Axygen Biosciences, Union City, CA, USA) according to the manufacturer’s instructions and quantified using a Quantus™ Fluorometer (Promega, USA). Purified amplicons were pooled in equimolar amounts and paired-end sequenced (2 × 300) on an Illumina MiSeq platform (Illumina, San Diego, USA) according to the standard protocols by Majorbio Bio-Pharm Technology Co. Ltd. (Shanghai, China). The raw reads were deposited into the NCBI Sequence Read Archive (SRA) database (Accession Number: SRP316160).

The Quantitative Insights Into Microbial Ecology (Qiime version 1.9.1) pipeline was used to process the sequences [25]. The raw 16S and ITS rRNA gene sequencing reads were demultiplexed, quality-filtered by Trimmomatic and merged by FLASH with the following criteria: (i) the 300 bp reads were truncated at any site receiving an average quality score of <20 over a 50 bp sliding window, and the truncated reads shorter than 50 bp were discarded, reads containing ambiguous characters were also discarded; (ii) only overlapping sequences longer than 10 bp were assembled according to their overlapped sequence. The maximum mismatch ratio of overlap region is 0.2. Reads that could not be assembled were discarded; (iii) Samples were distinguished according to the barcode and primers, and the sequence direction was adjusted, exact barcode matching, 2 nucleotide mismatch in primer matching. In summary, labelled barcodes, low-quality reads, and ambiguous nucleotides were removed to obtained high-quality sequences. Operational taxonomic units (OTUs) with 97% similarity cutoff were clustered using UPARSE (version 7.1, http://drive5.com/uparse/), and chimeric sequences were identified and removed [26]. The taxonomy of each OTU representative sequence was analyzed by RDP Classifier (http://rdp.cme.msu.edu/) against the SILVA (v132) SSU and the UNITE (v7.2) reference databases using confidence threshold of 0.7.

Statistical analyses

Alpha diversities of bacterial and fungal communities were calculated using Mothur (version v.1.30.2, https://mothur.org/wiki/calculators/). Principal Component Analysis (PCA) was performed, and the R language (version 3.3.1) tool was used for statistics and graphing. For microbial community composition and Venn diagram analysis, OTU tables with a 97% similarity level were selected, and the R language (version 3.3.1) tool was used for statistics and graphing. Linear discriminant analysis (LDA) was performed using LEfSe (http://huttenhower.sph.harvard.edu/galaxy/root?tool_id=lefse_upload) on samples according to different grouping conditions based on taxonomic composition to identify clusters that had a significant differential impact on sample delineation. Functional predictions of the soil fungal communities by Fungi Functional Guild (FUN Guild) tool. The Wilcoxon rank-sum test was used to analyze the significant differences in fungal functions.

All treatments were performed in triplicate with a completely random design. The mean values of soil enzyme activities, microbial biomass, soil bacterial and fungal diversities and richness were compared by Student’s t-test using Statistical Product and Service Solutions (SPSS version 26) software with a significance level of 0.05. The results are shown as the standard deviation of the mean (mean ± SD). The experimental data were analyzed by using Excel 2019 and SPSS Statistics 21, and online data analysis was conducted by using the free online Majorbio Cloud Platform (www.majorbio.com) of Majorbio Bio-Pharm Technology Co. Ltd. (Shanghai, China).

Results

Soil enzyme activities

The changes in soil enzyme activities between the MW and NW treatments in the star anise plantation are shown in Table 1. The activities of phosphatase and aminopeptidase in the MW treatment were significantly different from those in the NW treatment. However, even though the activity of aminopeptidase in the NW soil was significantly higher than that in the MW soil, the activity of phosphatase in the soil of the NW treatment showed the opposite trend as aminopeptidase, i.e., the activity of phosphatase in the soil of the MW treatment was significantly higher than that of the NW soil. This result suggested that the phosphorus cycling process in soil can be promoted by mechanical weeding in star anise plantations (Table 1).

Table 1

Soil enzyme activities between NW and MW treatments in star anise plantations (n mol/g min-1 30°C).

Samples	β-Glucosidase	Aminopeptidase	Phosphatase
No weeding (NW)	0.27±0.02a	16.05±0.50a	0.13±0.02b
Mechanical Weeding (MW)	0.29±0.02a	12.98±0.30b	0.34±0.05a

Note. All data are presented as the means ± SD (standard deviation). The Student’s t-test was performed (P < 0.05). Different letters in the same column indicate significant differences among treatments at P < 0.05.

Soil microbial biomass

As seen in Table 2, the soil microbial biomass carbon (SMC) and nitrogen (SMN) in the MW treatment were all significantly higher than those in the NW treatment, and only the soil microbial biomass phosphorus (SMP) in the MW treatment was significantly lower than that in the NW treatment. This result indicates that soil microbial biomass carbon, nitrogen and phosphorus can all be significantly changed by mechanical weeding in star anise plantations. That is, soil fertility in star anise plantations can be significantly changed by mechanical weeding (Table 2).

Table 2

Soil microbial biomass between the NW and MW treatments in star anise plantations (mg kg-1).

Samples	Microbial biomass C	Microbial biomass N	Microbial biomass P
No weeding (NW)	13.10±1.87b	3.54±0.19b	29.47±1.47a
Mechanical Weeding (MW)	194.01±6.09a	22.52±1.98a	14.92±1.49b

Note. All data are presented as the means ± SD (standard deviation). The Student’s t-test was performed (P < 0.05). Different letters in the same column indicate significant differences among treatments at P < 0.05.

Soil bacterial and fungal diversity and richness

As seen in Table 3, the coverage indexes were all 99% and above, it indicates that the analytical data in Table 3 are reliable. The Shannon index, which was used as indicators of bacterial and fungal diversities, no significant differences could be found between NW and MW treatments. In addition, the Ace and Chao1 indexes, which were used as indicators of microbial richness, were also no significant difference between NW and MW treatments. To evaluate the extent of the similarity of the soil bacterial and fungal communities. unweighted UniFrace Principal Component Analysis (PCA) at OUT level was performed. The results suggested that there were quite similarity with the bacterial and fungal compositions between NW and MW (Fig 1). All above results suggested that soil microbial diversity and richness in star anise plantations were not significant changes by mechanical weeding.

Table 3

Alpha diversity index of soil bacteria and fungi in star anise plantations between the NW and MW treatments (OTU level).

	Treatments	Shannon index	Ace index	Chao1 index	Coverage
Bacteria	No weeding (NW)	6.03±0.33a	2414.98±244.60a	2372.22±263.27a	0.99
	Mechanical Weeding (MW)	5.90±0.11a	2468.82±85.85a	2443.81±116.81a	0.99
Fungi	No weeding (NW)	4.03±0.32a	806.88±42.97a	811.17±42.26a	1.00
	Mechanical Weeding (MW)	3.36±0.81a	793.08±133.08a	789.91±132.88a	1.00

Note. All data are presented as the means ± SD (standard deviation). The Student’s t-test was performed (P < 0.05). Different letters in the same column indicate significant differences among treatments at P < 0.05.

Fig 1

PCA of soil bacterial (A) and fungal (B) communities in star anise plantations between the NW and MW treatments (OTU level).

Note. NW: no weeding in the star anise plantation, and MW: mechanical weeding in the star anise plantation. ANOSIM analysis was used to test differences between groups.

Analysis of soil microbial community structure in star anise plantations between the NW and MW treatments

As seen in Fig 2A, 8 and 9 dominant bacteria with relative abundances greater than 1% could be detected in soils of NW and MW at the phylum level, respectively. In soils of star anise plantations under the NW treatment, Proteobacteria (34.72%), Acidobacteria (18.63%), Actinobacteria (16.52%), Chloroflexi (16.85%), Planctomycetes (2.57%), WPS-2 (2.08%), Firmicutes (2.19%), Verrucomicrobia (1.75%) and others (3.72%) were the dominant bacteria at the phylum level. In contrast, Proteobacteria (36.06%), Acidobacteria (17.69%), Actinobacteria (19.72%), Chloroflexi (15.42%), Planctomycetes (2.42%), WPS-2 (2.02%), Firmicutes (1.18%), Verrucomicrobia (1.48%), Bacteroidetes (1.17%) and others (2.85%) were the dominant bacteria at the phylum level in the soil under the MW treatment. The results showed that not only were the proportions of dominant bacteria at the phylum level changed, i.e., the proportions of Acidobacteria, Chloroflexi, Planctomycetes, WPS-2, Firmicutes, and Verrucomicrobia decreased, and those of Proteobacteria and Actinobacteria increased, but Bacteroidetes were also enriched as dominant bacteria in star anise plantations under MW treatment Fig 2A.

Fig 2

Compositions of soil bacterial (A) and fungal (B) communities at the phylum level between the NW and MW treatments.

Note. Only the phyla with relative abundances greater than 1% are presented in Fig 2. NW: no weeding in the star anise plantation, and MW: mechanical weeding in the star anise plantation.

Moreover, all 5 dominant fungal phyla with relative abundances greater than 1% could be found in the soil of star anise plantations under the NW and MW treatments. In soils under the NW treatment, Ascomycota (44.90%), Basidiomycota (26.71%), unclassified_k_Fungi (22.44%), Rozellomycota (4.24%) and Mortierellomycota (1.33%) could be detected. In contrast, Ascomycota (36.73%), Basidiomycota (34.96%), unclassified_k_Fungi (20.80%), Rozellomycota (6.12%) and Mortierellomycota (1.17%) could be found in the soil under the MW treatment. These results suggested that the soil fungal community composition in star anise plantations is not altered by mechanical weeding. However, the proportion of Ascomycota, unclassified_k_fungi and Mortierellomycota decreased, and Basidiomycota and Rozellomycota increased in the MW treatment compared to that in the NW treatment Fig 2B.

As shown in Fig 3, the numbers of dominant bacteria (> 1%) in the star anise plantation soil were 26 and 23 for the NW and MW treatments, respectively. norank_f__norank_o__norank_c__Subgroup_6, 1921–2 and norank_f__norank_o__B12-WMSP1 were the three genera that were undetected in the soil of the MW treatment. Moreover, the proportions of mutually dominant bacteria in soils of the NW and MW treatments, such as norank_f__norank_o__Subgroup_2, norank_f__norank_o__Acidobacteriales, norank_f__norank_o__norank_c__AD3, unclassified_f__Ktedonobacteraceae, norank_f__norank_o__norank_c__norank_p__WPS-2, Burkholderia-Caballeronia-Paraburkholderia, norank_f__Gemmataceae, Conexibacter, and Mycobacterium, were all decreased in soil of the MW treatment compared to those under the NW treatment (S1 Table). This suggests that the bacterial community structure in the soil of star anise plantations can be altered by mechanical weeding management.

Fig 3

Compositions of soil bacterial (A) and fungal (B) communities at the genus level in star anise plantations between the NW and MW treatments.

Note. Only the genera with relative abundances greater than 1% are presented in Fig 3. NW: no weeding in the star anise plantation, and MW: mechanical weeding in the star anise plantation.

In addition, the numbers of dominant fungi in the soil of star anise plantations were 11 and 9 for the NW and MW treatments, respectively. There were 9 mutual fungal genera in the NW and MW treatments, while unclassified_f__Clavicipitaceae and Mortierella were not detected in the soil of the MW treatment. Moreover, the proportions of mutual fungal genera, such as unclassified_k__Fungi, Saitozyma, Archaeorhizomyces, Apiotrichum and Penicillium, were all decreased in the soil of the MW treatment compared to that under the NW treatment (S2 Table). The unique dominant fungi under NW were unclassified_f__Clavicipitaceae and Mortierella. The above results also suggest that the soil fungal community structure in star anise plantations was changed by the MW treatment.

As seen in Fig 4, there were 405 mutually dominant bacteria at the genus level in the soil of the star anise plantation between the NW and MW treatments, but there were 50 and 27 unique dominant bacteria in the soil of the star anise plantation between the NW and MW treatments, respectively Fig 4A. Moreover, there were 164 mutually dominant fungi at the genus level in the soil of star anise plantations between the NW and MW treatments, but there were 98 and 39 unique dominant fungi in the soil of star anise plantations between the NW and MW treatments, respectively Fig 4B.

Fig 4

Venn Diagram of soil bacterial (A) and fungal (B) communities at genus level between the NW and MW treatments in star anise plantations.

Note. NW: no weeding in the star anise plantation, and MW: mechanical weeding in the star anise plantation.

These results also suggest that soil bacterial and fungal community structures are all altered by mechanical weeding. In particular, the amounts of dominant bacteria or fungi were all decreased by the mechanical treatment.

Statistical differences of microbial communities at different levels

As analysis of the microbial communities at OTUs level in this study by LEfSe would be too complex. Therefore, microbial community structure at phylum and genus levels only were described in this paper.

As seen at Figs 5 and 6, at phylum level, two phyla of bacteria and one phylum of fungi in NW treatment were significantly enriched, namely Gemmatimonadetes, Elusimicrobia and Glomeromycota, respectively. By contrast, there were no any significantly changed of bacteria and fungi at phylum level in MW treatment. In addition, 5 bacterial genera, such as norank_f__Gemmatimonadaceae, Inquilinus, Actinomadura, Silvimonas, significantly enriched in NW treatment, Meanwhile, 23 fungal genera, i.e., norank_f__P3OB-42, Archaeorhizomyces, unclassified_f__Clavicipitaceae, unclassified_f__Chaetomiaceae, unclassified_f__Myxotrichaceae, unclassified_f__Aspergillaceae, Talaromyces, unclassified_f__Chrysozymaceae, Cladophialophora, unclassified_o__GS33, Purpureocillium, Trechispora, Xylogone, Neopestalotiopsis, Pestalotiopsis, Speiropsis, unclassified_f__Agaricaceae, Pseudeurotium, unclassified_f__Chaetothyriaceae, Scedosporium, unclassified_f__Sarcosomataceae, unclassified_o__Sordariales, Curvularia, Verticillium were also significantly increased in NW treatment, too. On the contrary, 8 bacterial genera, such as Aquisphaera, norank_f__norank_o__WD260, Microbacterium, unclassified_o__Babeliales, Uliginosibacterium, Microbispora, Rudaea, Microvirga and 2 fungal genera, namely unclassified_f__Cuniculitremaceae and Inaequalispora significantly increased in MW treatment only.

Fig 5

Cladogram showing the phylogenetic distribution of the bacterial lineages associated with soil from two treatments (A). Indicator bacteria with LDA scores of 2 or greater in bacterial communities associated with soil from the two treatments (B). Different colour regions represent different constituents (Red: NW; Blue, MW). Circles indicate phylogenetic level from phylum to genus. The diameter of each circle is proportional to the abundance of the group. Different prefixes indicate different levels (p: phylum; c: class, o: Order; f: Family; g: Genus). Note. NW: no weeding in the star anise plantation, and MW: mechanical weeding in the star anise plantation.

Fig 6

Cladogram showing the phylogenetic distribution of the fungal lineages associated with soil from two treatments (A). Indicator fungi with LDA scores of 2 or greater in fungal communities associated with soil from the two treatments (B). Different colour regions represent different constituents (Red, NW; Blue, MW). Circles indicate phylogenetic level from phylum to genus. The diameter of each circle is proportional to the abundance of the group. Different prefixes indicate different levels (p: phylum; c: class; o: Order; f: Family; g: Genus). Note. NW: no weeding in the star anise plantation, and MW: mechanical weeding in the star anise plantation.

Functional predictions of the soil fungal communities by FUNGuild

Fungi Functional Guild (FUN Guild) was employed to predict fungal functions in the two treatments. The Wilcoxon rank-sum test was used to analyze the significant differences in fungal functions between NW and MW. Among them, only the guild which related to unknown of soil fungi in MW treatment could be found higher than those of NW treatment, but there was no significant difference (Fig 7). Moreover, the guilds related to Soil Saprotroph, Fungal Parasite-Undefined Saprotroph, Undefined Saprotroph, Endophyte-Litter Saprotroph-Soil Saprotroph-Undefined Saprotroph, Animal Pathogen-Dung Saprotroph-Endophyte-Epiphyte-Plant Saprotroph-Wood Saprotroph of soil fungi in MW treatment were lower than those of NW treatment, but there were no significant differences.

Fig 7

Functional predictions of the soil fungal communities between the NW and MW treatments.

Note. NW: no weeding in the star anise plantation, and MW: mechanical weeding in the star anise plantation. The Wilcoxon rank-sum test was performed (P < 0.05).

Discussion

The enzymatic activity in soil is mainly derived from microbial origins, such as intracellular, cell-associated or free enzymes, which play an important role in maintaining soil health and the environment [27]. Soil enzymes can play key biochemical functions through the decomposition of organic matter, catalyzing microbial life processes, and stabilizing soil structure and nutrient cycling in the soil system [27-29].

In this experiment, we found that the activity of β-glucosidase was not significantly different between the MW and NW treatments, but the activity of phosphatase in soils of the MW treatment was significantly higher than that of the NW treatment. The activity of aminopeptidase in the soil of the MW treatment showed the opposite trend as the activity of phosphatase. This result suggested that soil fertility and health were not significantly altered by the MW treatment compared to the NW treatment.

Soil microbial biomass is also an important indicator of soil quality and functions in maintaining soil fertility and crop productivity [24]. The greater the microbial biomass in the soil, the greater the capacity of the soil to provide nutrients to plants through mineralization of organic nutrients [30]. Among them, soil microbial biomass carbon can not only promote the formation of new humus with high activity in soil but can also reflect the slight changes in soil before changes in the soil total carbon content [31]. Soil microbial biomass nitrogen can reflect the availability of soil nitrogen and play an important role in the supply and circulation of soil nitrogen [31]. Soil microbial biomass phosphorus can reflect the supply level of soil phosphorus [32]. In addition, although microbial biomass phosphorus cannot be directly absorbed and utilized by plants, the turnover of microbial biomass phosphorus can slowly release inorganic phosphorus, so it has always been considered a source of available phosphorus in the soil, which is very important for plant growth [33]. Some studies have shown that weeding is more effective than nitrogen application for cilantro, especially under poor soil conditions [34]. We also found that biomass C and N in the soil of the MW treatment were significantly higher than those under the NW treatment. However, the microbial biomass P in the MW soil was significantly lower than that in the NW soil. As some types of weeds have good phosphorus uptake capacity, which can accumulate soil surplus phosphorus in biomass and promote phosphorus biocycling [35]. However, without total topsoil inversion, the plant materials cut by a brush cutter and incorporation into the soil which provide fertility is limited. A stratified layer of phosphorus builds up on or near the soil surface, increasing the risk of phosphorus release and subsequent transport of dissolved reactive phosphorus via surface runoff and tile drain water [36]. Therefore, it can be inferred that weed management by mechanical weeding in star anise plantations is not completely harmful to soil fertility and health. Nevertheless, the plant materials need to be smashed and mixed with the soil after weeding to prevent phosphorus loss. In contrast, mechanical weeding promoted soil organic carbon and nitrogen but not soil organic phosphorus in the star anise plantation.

Bacteria are the most abundant and diverse group of soil microorganisms [37]. They play a crucial role in terrestrial ecosystems, including mineralization of dead organic matter, binding of humic compounds in the soil mineral layer, carbon and nitrogen cycling, and provision of nutrients for plant growth [38-40]. Soil fungi are present in forest ecosystems as decomposers and are involved in material cycling, energy flow and information transfer [41, 42]. Among them, symbiotic fungi are important components of soil microbiomes that form mutually beneficial symbiotic relationships with plant roots, thus facilitating the uptake of nutrients such as nitrogen and phosphorus by plants [43], increasing their resistance to stress, pests and diseases [44, 45], contributing to the formation of soil aggregates and improving soil structure [46]. Soil bacteria and fungi are sensitive to changes in soil quality and are often used to assess environmental changes in ecosystems [47]. Furthermore, soil microbes also play a key role in ecosystem nutrient cycling, affecting vegetation development and succession [48].

In our study, at the phylum level, the proportions of Acidobacteria, Chloroflexi, Planctomycetes, WPS-2, Firmicutes and Verrucomicrobia decreased, but the proportions of Proteobacteria and Actinobacteria increased in soils in the MW treatment compared to those in the NW treatment. Previous studies have confirmed that Proteobacteria are copiotrophic microorganisms that thrive under conditions of high nutrient availability [49]. In addition, Actinomycetes play a key role in terrestrial ecosystem functioning by contributing to the global carbon cycle through the decomposition of soil organic matter, increasing plant productivity, and being producers of bioactive compounds essential for human, animal and environmental health [50]. Moreover, the composition and proportions of the soil fungal community at the phylum level were not significantly altered by the MW treatment compared to the NW treatment. This result suggested that soil microbial community structures at the phylum level were not significantly altered in soils of star anise plantations by mechanical weeding management.

At the genus level, the soil bacterial community structure could be altered by mechanical weeding management, with Acidothermus, norank_f__Xanthobacteraceae, norank_f__norank_o__Elsterales, Bradyrhizobium, Acidibacter, Candidatus_Solibacter, Bryobacter, norank_f__JG30-KF-AS9, FCPS473, norank_f__norank_o__IMCC26256, unclassified_f__Acetobacteraceae, norank_f__norank_o__norank_c__TK10, norank_f__norank_o__norank_c__Actinobacteria, Pajaroellobacter, increasing, norank_f__norank_o__Subgroup_2, norank_f__norank_o__Acidobacteriales, norank_f__norank_o__norank_c__AD3, unclassified_f__Ktedonobacteraceae, norank_f__norank_o__norank_c__norank_p__WPS-2, Burkholderia-Caballeronia-Paraburkholderia, norank_f__Gemmataceae, Conexibacter, Mycobacterium decreasing in soils of the MW treatment. Moreover, norank_f__norank_o__norank_c__Subgroup_6, 1921–2 and norank_f__norank_o__B12-WMSP1 became the unique dominant bacteria in the soil of the NW treatment only. For the fungal community structure, even though the compositions were not significantly changed, the proportions were altered by mechanical weeding management. That is, unclassified_p__Ascomycota, unclassified_c__Agaricomycetes, unclassified_o__GS11 and Trichoderma increased, and unclassified_k__Fungi, Saitozyma, Archaeorhizomyces, Apiotrichum, Penicillium decreased in soils under the MW treatment compared to those under the NW treatment. Moreover, unclassified_f__Clavicipitaceaeand and Mortierella became the unique dominant fungus at the genus level in soils of the NW treatment. As Mortierella was known as a functional microbe in assisting crops and mycorrhizal fungi in phosphorus (P) acquisition. And inorganic P from a range of soils could be dissolved effectively by several members of Mortierella by synthesizing and secreting oxalic acid [51]. Therefore, in association with the microbial biomass P, the ability of soil P supply under NW treatment could be considered higher than that of MW treatment in star anise plantation. However, some plant pathogens, which belongs to the family of Clavicipitaceae [52], enriched as unique dominant fungus in soil of NW treatment. It also suggested that soil-borne diseases maybe easily occurred under NW treatment in star anise plantation.

These results suggested that even though the soil microbial community structure, including bacterial and fungal compositions at the genus level, could be altered by mechanical weeding mainly via changes in the proportions of dominant bacteria and fungi, the compositions of bacteria and fungi in soils of the MW treatment were less changed than those in soils of the NW treatment. It can also be concluded that soil fertility and health in star anise plantations can be improved or maintained by mechanical weeding management.

Conclusions

In this study, a field experiment was carried out to elucidate the effects of mechanical weeding on soil fertility and health in a star anise (Illicium verum Hook.f.) plantation. The conclusions were as follows. The activity of phosphatase in the soil of the MW treatment was significantly higher than that of the NW treatment. However, the activity of aminopeptidase was significantly lower than that of the NW treatment, and there was no significant difference in the activity of β-glucosidase between the MW and NW treatments. Soil microbial biomass C and N in the soil of the MW treatment were significantly higher than those of the NW treatment, but the soil microbial biomass P was significantly lower than that of the NW treatment. Proteobacteria, Acidobacteria, Actinobacteria, Chloroflexi, Planctomycetes, WPS-2, Firmicutes and Verrucomicrobia were the common dominant bacteria at the phylum level in soils of the MW and NW treatments. In particularly, Bacteroidetes was enriched in the soil of the MW treatment as the unique dominant bacteria. Ascomycota, Basidiomycota, unclassified_k_Fungi, Rozellomycota and Mortierellomycota were the common dominant fungi at the phylum level in soils of the MW and NW treatments. The numbers of dominant soil bacteria at the genus level in star anise plantations between the NW and MW treatments were 26 and 23, respectively. norank_f__norank_o__norank_c__Subgroup_6, norank_f__norank_o__B12-WMSP1 and 1921–2 were the three bacterial genera that were undetected in the soils of the MW treatment. The numbers of dominant soil fungi at the genus level in the star anise plantation between the NW and MW treatments were 11 and 9, respectively. Mortierella and unclassified_f__Clavicipitaceae were undetected in soils of the MW treatment. The above results suggest that soil fertility can be improved and that soil heath in star anise plantations can be maintained by the mechanical weeding method. Moreover, soil-borne diseases maybe easily occurred under NW treatment in star anise plantation.

Proportions of soil dominant bacterial communities at genus level between the NW and MW treatments in star anise plantations (%).

(DOCX)

Click here for additional data file.

Proportions of soil dominant fungal communities at genus level between the NW and MW treatments in star anise plantations (%).

(DOCX)

Click here for additional data file.

20 Dec 2021

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There appears to be an overall lack of rigor in the experimental setup and data analysis performed. In particular, the authors must include more detailed statistical analysis and additional analyses performed to support the conclusions made.

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Reviewer #2: Partly

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Reviewer #1: No

Reviewer #2: No

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Reviewer #2: No

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Reviewer #1: The manuscript is well organized and written but there are some major concerns that need to be addressed in the manuscript before publishing:

Line 40: the authors claimed that "soil microbial community structures are not significantly altered by mechanical weeding", this was claimed in the abstract and the discussion (lines 325, 341)? However, after reading the manuscript I didn’t find any statistical analysis that supports this claim “significantly altered”?? It was also mentioned throughout the manuscript (lines 206, 234, 252, 269, 328, 348, 350) that mechanical weeding altered the microbial diversity of the soil, yet the final conclusion claimed that these reported changes in the microbial diversity were not “significant”… authors need to support and explain this conclusion with statistical analysis.

The experiment included three replicate blocks (lines 108-112) and that was good for proper statistical analysis for the soil biological properties, yet in the soil microbial diversity analysis the replicates were pooled (line 152) and thus no statistical analysis was done to compare the two groups (no weeding and mechanical weeding) throughout the manuscript.

Line 163: The authors mentioned that they used “the free online Majorbio Cloud Platform”? The authors should mention in details which tools in the mentioned platform were used for the microbiome analysis… was it QIIME or Mothur or what??? They should also mention which database was used for taxonomy picking and alignment…. was it Greengages or SILVA or what?? they should also mention the version used in the analysis.

Figures 1, 2 and 3: the tool/software used to generate these figures should be mentioned in the legend.

Tables 3 and 4: These tables represent the same data in figure 2, they may move to supplementary materials to avoid redundancy in the manuscript.

Line 251: The results showed that two fungal genera were unique in the NW (no weeding ) soil, these two genera didn’t appear in the MW (mechanical weeding) soil, yet throughout the manuscript the authors didn’t rationalize this finding or discussed the functionality of these two genera (are they plant growth-promoting fungi or toxic fungi?? )…. this need to be addressed

For better contrasting the two soil groups (NW and MW) the authors might check the core microbial community in each group and see whether it is different or not… many free tools are available for this analysis (LEfSe, QIIME,..)

Reviewer #2: In the manuscript by Xiao et al., the authors measure several properties of soil fertility (the activities of three extracellular enzymes and microbial biomass C, N and P) and examine bacterial and fungal taxa in agricultural fields of star anise that were subjected to mechanical weeding. These same soil properties were measured in control plots that were not weeded and compared between the two treatments. The authors conclude that the soil microbial community structure is not altered by mechanical weeding; however, the lack of statistical analysis on the bacterial and fungal community data make such a conclusion impossible, in my opinion. Further, the authors conclude that mechanical weeding improve soil health, but I don’t think the phosphatase and microbial biomass P data support this conclusion. My comments are detailed below. But, overall, I suggest a more rigorous investigation of the data, especially the microbial community data.

Overall concerns:

The conclusions made about bacterial and fungal community changes are based on proportional representation of different phyla or genera. But, there are no statistics conducted on these numbers, despite the authors concluding that no significant differences were found at the phylum level (lines 40 and 326). The authors also make conclusions about genera that change between their treatments (line 347), again without statistics being done on the data. There are programs available that can run t-tests between treatments with corrections for multiple comparisons to test for differences between specific taxa (see STAMP for example https://doi.org/10.1007/978-1-4614-6418-1_780-1). But, what I suggest for this data set is that the authors explore the metagenomic data further before making conclusions, such as by calculating alpha diversity (richness, Shannon diversity, etc.) and beta diversity (i.e., turnover). These will help with whether or not you can conclude that the MW treatment led to “less changed” communities than the NW treatment (lines 349-350). Community data like what are presented here are also typically analyzed with multivariate statistics, such as ordination (principle coordinates analysis, nonmetric multidimensional scaling, etc.) and permutational multivariate analysis of variance (PERMANOVA). Fungal taxa can be assigned to different guilds using FUNGuild (Nguyen et al. 2016, doi: 10.1016/j.funeco.2015.06.006) or the newly available FungalTraits (Polme et al. 2020, doi: 10.1007/s13225-020-00466-2). Exploring how the different fungal guilds changed between treatments could be useful, especially because the Discussion mentions beneficial plant symbionts (i.e., mycorrhizal fungi) (lines 308-311).

The phosphatase activity and microbial biomass P data presented here suggest an increase in P demand in the MW plots. The increase in phosphatase activity and decrease in microbial biomass P with weeding, to me, suggests that the organisms were actively acquiring P from organic sources to a greater extent, potentially because inorganic P availability was lower with weeding. Overall, it was difficult for me to follow the conclusions the authors make based on the extracellular enzyme activity and microbial biomass C, N and P data because they don’t compare their numbers with other experiments. What have other studies found with mechanical weeding and how it affects extracellular enzyme activity and assimilated nutrients into microbial biomass? In particular, the difference in microbial biomass C between NW and MW plots reported here (Table 2) is quite large. Is this typical for mechanical weeding? Placing the numbers reported here into context by relating them to other published studies is needed.

Minor comments:

Line 67: Do weeds really compete with agricultural plants for oxygen? I skimmed reference 12 and don’t see anything about weeds competing with crops for oxygen.

Line 110: Was each plot divided in half - one side weeded one side not weeded? A methods figure could help here with a diagram of the set up.

Line 115: Each species of what? Aren't all plant species star anise? Please clarify in the methods.

Lines 162-164: It seems to me that Majorbio is just a cloud for processing data. What pipeline or process was used for the sequence reads? More details are needed on how chimeras were removed, how low-quality reads were filtered out, at what percent OTUs were clustered, etc. If chimeras and low-quality reads were not removed, the conclusions for microbial taxa could be based on sequence errors. The process for analyzing sequence reads needs to be explained in the methods.

Lines 300-301: I don't follow the conclusion that weeding is not completely harmful to soil fertility. The phosphatase activity and microbial biomass P data suggest increased P demand (i.e., lower P availability) with mechanical weeding. Wouldn’t this be a harmful effect of weeding? P is an essential nutrient to plants. More context is needed on how the enzyme and microbial biomass data compare to other agricultural studies.

Line 307: Fungi are decomposers in more ecosystems than just forests. Please rephrase.

**********

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Reviewer #1: Yes: Mariam Hassan

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4 Jan 2022

Dear Editors and Reviewers:

Thank you for your letter and the reviewers’ comments concerning our manuscript entitled “Effects of mechanical weeding on soil fertility and microbial community structure in star anise (Illicium verum Hook.f.) plantations” (PONE-D-21-29819). Those comments are all valuable and very helpful for revising and improving our paper, as well as the important guiding significance tour researches. We have read comments carefully and have made correction which we hope meet with approval. Revised portion are marked in Green in the paper. The main corrections in the paper and the responds to the reviewer’s comments are as flowing:

Responds to the Editors’ and Reviewers’ comments:

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Reply: The authors have revised the manuscript style according to the PLOS ONE style templates.

2. In your Methods section, please provide additional information regarding the permits you obtained for the work. Please ensure you have included the full name of the authority that approved the field site access and, if no permits were required, a brief statement explaining why.

Reply: No permits were required. Because the experimental site belongs to the national forest farm, and it is one of the experimental sites of Guangxi Forestry Research Institute.

3. Thank you for stating the following financial disclosure:

“This work was supported by Open Research Fund of Guangxi Key Laboratory of Special Non-wood Forest Cultivation & Utilization (19-B-02-01), Project of key R & D of Guangxi (No. AB1850014) and the eighth batch of special funds for specially invited experts in Guangxi Province, China.”

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Reply: This work was mainly supported by Open Research Fund of Guangxi Key Laboratory of Special Non-wood Forest Cultivation & Utilization (19-B-02-01). However, the money in this fund was not wholly enough to carry out the whole experiment. Therefore, the authors used part of the money in project 2 and 3 for conducting the experiment continuously. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Additional Editor Comments:

There appears to be an overall lack of rigor in the experimental setup and data analysis performed. In particular, the authors must include more detailed statistical analysis and additional analyses performed to support the conclusions made.

There appears to be an overall lack of rigor in the experimental setup and data analysis performed. In particular, the authors must include more detailed statistical analysis and additional analyses performed to support the conclusions made.

Reply: The authors have revised the content in manuscript according to the Editor comments.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

Reviewer #2: Partly

Reply: The authors have revised this part in manuscript according to the Reviewers’ comments.

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: No

Reviewer #2: No

Reply: The authors have revised this part in manuscript according to the Reviewers’ comments.

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: No

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1:

The manuscript is well organized and written but there are some major concerns that need to be addressed in the manuscript before publishing:

Line 40: the authors claimed that "soil microbial community structures are not significantly altered by mechanical weeding", this was claimed in the abstract and the discussion (lines 325, 341)? However, after reading the manuscript I didn’t find any statistical analysis that supports this claim “significantly altered”?? It was also mentioned throughout the manuscript (lines 206, 234, 252, 269, 328, 348, 350) that mechanical weeding altered the microbial diversity of the soil, yet the final conclusion claimed that these reported changes in the microbial diversity were not “significant”… authors need to support and explain this conclusion with statistical analysis.

Reply: The authors have revised this part in manuscript according to the Reviewers’ comments.

The experiment included three replicate blocks (lines 108-112) and that was good for proper statistical analysis for the soil biological properties, yet in the soil microbial diversity analysis the replicates were pooled (line 152) and thus no statistical analysis was done to compare the two groups (no weeding and mechanical weeding) throughout the manuscript.

Reply: The authors have revised this part in manuscript according to the Reviewers’ comments.

Line 163: The authors mentioned that they used “the free online Majorbio Cloud Platform”? The authors should mention in details which tools in the mentioned platform were used for the microbiome analysis… was it QIIME or Mothur or what??? They should also mention which database was used for taxonomy picking and alignment…. was it Greengages or SILVA or what?? they should also mention the version used in the analysis.

Reply: The authors have revised this part in manuscript according to the Reviewers comments.

Figures 1, 2 and 3: the tool/software used to generate these figures should be mentioned in the legend.

Reply: The authors had revised the points where Reviewers suggested in the manuscript. And, the tool/software were also used to generate the figures mentioned in manuscript.

Tables 3 and 4: These tables represent the same data in figure 2, they may move to supplementary materials to avoid redundancy in the manuscript.

Reply: The authors had revised the points where Reviewers suggested in the manuscript.

Line 251: The results showed that two fungal genera were unique in the NW (no weeding ) soil, these two genera didn’t appear in the MW (mechanical weeding) soil, yet throughout the manuscript the authors didn’t rationalize this finding or discussed the functionality of these two genera (are they plant growth-promoting fungi or toxic fungi?? )…. this need to be addressed

Reply: The authors have revised this content in manuscript according to the Reviewers’ comments.

For better contrasting the two soil groups (NW and MW) the authors might check the core microbial community in each group and see whether it is different or not… many free tools are available for this analysis (LEfSe, QIIME.)

Reply: The authors have revised this content according to the Reviewers suggestions. Also, the authors analyzed the microbial communities of the two soil treatments by the LEfSe tool.

Special thanks to you for your good comments.

Reviewer #2:

In the manuscript by Xiao et al., the authors measure several properties of soil fertility (the activities of three extracellular enzymes and microbial biomass C, N and P) and examine bacterial and fungal taxa in agricultural fields of star anise that were subjected to mechanical weeding. These same soil properties were measured in control plots that were not weeded and compared between the two treatments. The authors conclude that the soil microbial community structure is not altered by mechanical weeding; however, the lack of statistical analysis on the bacterial and fungal community data make such a conclusion impossible, in my opinion. Further, the authors conclude that mechanical weeding improve soil health, but I don’t think the phosphatase and microbial biomass P data support this conclusion. My comments are detailed below. But, overall, I suggest a more rigorous investigation of the data, especially the microbial community data.

Reply: The authors have revised this content in manuscript according to the Reviewers’ comments.

Overall concerns:

The conclusions made about bacterial and fungal community changes are based on proportional representation of different phyla or genera. But there are no statistics conducted on these numbers, despite the authors concluding that no significant differences were found at the phylum level (lines 40 and 326). The authors also make conclusions about genera that change between their treatments (line 347), again without statistics being done on the data. There are programs available that can run t-tests between treatments with corrections for multiple comparisons to test for differences between specific taxa (see STAMP for example https://doi.org/10.1007/978-1-4614-6418-1_780-1). But, what I suggest for this data set is that the authors explore the metagenomic data further before making conclusions, such as by calculating alpha diversity (richness, Shannon diversity, etc.) and beta diversity (i.e., turnover). These will help with whether or not you can conclude that the MW treatment led to “less changed” communities than the NW treatment (lines 349-350). Community data like what are presented here are also typically analyzed with multivariate statistics, such as ordination (principle coordinates analysis, nonmetric multidimensional scaling, etc.) and permutational multivariate analysis of variance (PERMANOVA). Fungal taxa can be assigned to different guilds using FUNGuild (Nguyen et al. 2016, doi: 10.1016/j.funeco.2015.06.006) or the newly available FungalTraits (Polme et al. 2020, doi: 10.1007/s13225-020-00466-2). Exploring how the different fungal guilds changed between treatments could be useful, especially because the Discussion mentions beneficial plant symbionts (i.e., mycorrhizal fungi) (lines 308-311).

Reply: The authors have revised these points according to Reviewers’ suggestion in manuscript. That is, using the FUNGuild and the LEfSe tools in manuscript analyzed the functional predictions of the microbial community.

The phosphatase activity and microbial biomass P data presented here suggest an increase in P demand in the MW plots. The increase in phosphatase activity and decrease in microbial biomass P with weeding, to me, suggests that the organisms were actively acquiring P from organic sources to a greater extent, potentially because inorganic P availability was lower with weeding. Overall, it was difficult for me to follow the conclusions the authors make based on the extracellular enzyme activity and microbial biomass C, N and P data because they don’t compare their numbers with other experiments. What have other studies found with mechanical weeding and how it affects extracellular enzyme activity and assimilated nutrients into microbial biomass? In particular, the difference in microbial biomass C between NW and MW plots reported here (Table 2) is quite large. Is this typical for mechanical weeding? Placing the numbers reported here into context by relating them to other published studies is needed.

Reply: The authors have revised this content in manuscript according to the Reviewers’ comments.

Minor comments:

Line 67: Do weeds really compete with agricultural plants for oxygen? I skimmed reference 12 and don’t see anything about weeds competing with crops for oxygen.

Reply: The authors have revised this content in manuscript according to the Reviewers’ comments.

Line 110: Was each plot divided in half - one side weeded one side not weeded? A methods figure could help here with a diagram of the set up.

Reply: The authors have revised this content in manuscript according to the Reviewers’ comments.

Line 115: Each species of what? Aren't all plant species star anise? Please clarify in the methods.

Reply: The authors re-checked this part and revised part of the content in manuscript according to the Reviewers’ comments.

Lines 162-164: It seems to me that Majorbio is just a cloud for processing data. What pipeline or process was used for the sequence reads? More details are needed on how chimeras were removed, how low-quality reads were filtered out, at what percent OTUs were clustered, etc. If chimeras and low-quality reads were not removed, the conclusions for microbial taxa could be based on sequence errors. The process for analyzing sequence reads needs to be explained in the methods.

Reply: The authors re-checked this part and revised the content in manuscript according to the Reviewers’ comments.

Lines 300-301: I don't follow the conclusion that weeding is not completely harmful to soil fertility. The phosphatase activity and microbial biomass P data suggest increased P demand (i.e., lower P availability) with mechanical weeding. Wouldn’t this be a harmful effect of weeding? P is an essential nutrient to plants. More context is needed on how the enzyme and microbial biomass data compare to other agricultural studies.

Reply: The authors re-checked this part and revised part of the content in manuscript according to the Reviewers’ comments.

Line 307: Fungi are decomposers in more ecosystems than just forests. Please rephrase.

Reply: The authors re-checked this part and revised part of the content in manuscript according to the Reviewers’ comments.

Special thanks to you for your good comments.

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Mariam Hassan

Reviewer #2: No

Special thanks to you for your good comments.

We tried our best to improve the manuscript and made some changes will not influence the content and framework of the paper. We appreciate for Editors/Reviewers’ warm work earnestly, and hope that the correction will meet with approval.

Once again, thank you very much for your comments and suggestions.

Correspondence should be addressed to Prof.& Dr. Shang-dong Yang at the following address, phone number, and email address.

Corresponding author: 1) Name: Wenhui Liang; E-mail address: 723746615@qq.com; Tel: 86-771-2319966; 2) Name: Shangdong Yang; E-mail address: 924433816@qq.com; Tel: 86-771-3270813.

Thanks very much for your attention and consideration. We are looking forward to hearing from you soon.

With kind personal regards,

Sincerely yours,

Jian Xiao (E-mail: 1318513279@qq.com)

Submitted filename: Response to Reviewers.doc

Click here for additional data file.

10 Mar 2022

Effects of mechanical weeding on soil fertility and microbial community structure in star anise (Illicium verum Hook.f.) plantations

PLOS ONE

Dear Dr. Yang,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. In particular, you all have not adequately responded to the reviewers' concerns regarding performing appropriate statistical analyses on the data, such that the conclusions are adequately supported statistically. I will remind the authors that it is important to solid statistical support to ensure scientific rigor. I will allow one more round of revision for the authors to address these issues raised by the reviewers.

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Kind regards,

Brenda A Wilson, Ph.D.

Academic Editor

PLOS ONE

Additional Editor Comments:

At this point, the authors have still not included appropriate statistics to support their conclusions despite several suggestions by the reviewers, and so the majority of their conclusions are not supported with appropriate statistics.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: (No Response)

Reviewer #2: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: No

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: No

Reviewer #2: No

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Regarding the statistical analysis, throughout the manuscript the authors didn’t mention the used tests to analyse the data. As a reader and reviewer we need to know the used statistical test and wether it was appropriate or not. Wherever you mention any significance with P value you need to mention the used statistical test.

Reviewer #2: While I think the data collected by the authors for this manuscript are valuable, the study still lacks proper statistical analysis for the conclusions that are being made. I do see that both FUNGuild and LEfSe were used to analyze the data, but a large portion of the Results and Conclusions are still based on changes in the abundances of different taxa and no statistics are conducted on these numbers.

Lines 235-302: These results and the conclusions that follow are all just observations on how the abundance of different taxa change. Statistics need to be conducted to make conclusions about how the taxa changed. As I suggested previously, I recommend using the free software STAMP (https://doi.org/10.1007/978-1-4614-6418-1_780-1). The website is here: https://beikolab.cs.dal.ca/software/STAMP. This program will allow you to conduct t-tests between the MW and NW treatments. Both taxonomic identities and functional groups from FUNGuild can be compared (lines 341-348).

Lines 305-307: There are plenty of statistics that do analyze community data at the OTU level. As I suggested previously, community data like what are presented here are also typically analyzed with multivariate statistics, such as ordination (principle coordinates analysis, nonmetric multidimensional scaling, etc.) and permutational multivariate analysis of variance (PERMANOVA). These statistics can all be run in the vegan package of the program R. You can download R for free here: https://www.r-project.org/.

Discussion: I previously commented "The phosphatase activity and microbial biomass P data suggest increased

P demand (i.e., lower P availability) with mechanical weeding. Wouldn’t this be a harmful effect of weeding? P is an essential nutrient to plants. More context is needed on how the enzyme and microbial biomass data compare to other agricultural studies." In the revised manuscript, I don't see any inclusion of extracellular enzyme production or microbial biomass nutrient content from other agricultural studies. This will help put the data presented in the current study into context. in addition, I do not see any discussion of changes to P availability with mechanical weeding. Given the increase in phosphatase production and decrease in microbial biomass P with mechanical weeding, I think that there is lower P availability with mechanical weeding. The way I interpret the data presented, the mechanical weeding increases assimilation of nutrients by the soil microbes (thus the increase in organic C and organic N content). But, organic P content does not show this same pattern. Instead, phosphatase activity increases with mechanical weeding. This means that there is not enough inorganic P available, so the microbes need to put their energy into releasing phosphatase to free up P that is bound in organic matter. In other words, the data suggest that there is a higher P demand or lower P availability with mechanical weeding. I understand that the authors may disagree with me here, but the Discussion overall lacks these kinds of conclusions and mostly just re-states the results.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Mariam Hassan

Reviewer #2: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

13 Mar 2022

Dear Editors and Reviewers:

Thank you for your letter and the reviewers’ comments concerning our manuscript entitled “Effects of mechanical weeding on soil fertility and microbial community structure in star anise (Illicium verum Hook.f.) plantations” (PONE-D-21-29819). Those comments are all valuable and very helpful for revising and improving our paper, as well as the important guiding significance tour researches. We have read comments carefully and have made correction which we hope meet with approval. Revised portion are marked in Green in the paper. The main corrections in the paper and the responds to the reviewer’s comments are as flowing:

Responds to the Editors’ and Reviewers’ comments:

Additional Editor Comments:

At this point, the authors have still not included appropriate statistics to support their conclusions despite several suggestions by the reviewers, and so the majority of their conclusions are not supported with appropriate statistics.

Reply: The authors have revised the content in manuscript according to the Editor comments.

Reviewers' comments:

Reviewer #1:

Regarding the statistical analysis, throughout the manuscript the authors didn’t mention the used tests to analyse the data. As a reader and reviewer we need to know the used statistical test and wether it was appropriate or not. Wherever you mention any significance with P value you need to mention the used statistical test.

Reply: The authors have revised the content in manuscript according to the Reviewer comments.

Special thanks to you for your good comments.

Reviewer #2:

While I think the data collected by the authors for this manuscript are valuable, the study still lacks proper statistical analysis for the conclusions that are being made. I do see that both FUNGuild and LEfSe were used to analyze the data, but a large portion of the Results and Conclusions are still based on changes in the abundances of different taxa and no statistics are conducted on these numbers.

Reply: LEfSe is a software for discovering high-dimensional biomarkers and revealing genomic features to distinguish between two or more biological conditions (or taxa). The software first uses the non-parametric factorial Kruskal-Wallis (KW) sum-rank test (non-parametric factorial Kruskal-Wallis rank sum test) to detect features with significant abundance differences and to find taxa that differ significantly from the abundance. Finally, LEfSe used linear discriminant analysis (LDA) to estimate the magnitude of the effect of each component (species) abundance on the difference effect. Therefore, we can directly identify bacteria and fungi with significant differences in NW and MW by LEfSe directly, without the need to do a separate test for differences between groups.

In addition, we had used R language (version 3.3.1) to perform Wilcoxon rank-sum test and graphs, compared taxonomic identities and functional groups from FUNGuild of NW and MW.

Lines 235-302: These results and the conclusions that follow are all just observations on how the abundance of different taxa change. Statistics need to be conducted to make conclusions about how the taxa changed. As I suggested previously, I recommend using the free software STAMP (https://doi.org/10.1007/978-1-4614-6418-1_780-1). The website is here: https://beikolab.cs.dal.ca/software/STAMP. This program will allow you to conduct t-tests between the MW and NW treatments. Both taxonomic identities and functional groups from FUNGuild can be compared (lines 341-348).

Reply: We have used R language (version 3.3.1) to perform Wilcoxon rank-sum test and graphs, compared taxonomic identities and functional groups from FUNGuild of NW and MW.

Lines 305-307: There are plenty of statistics that do analyze community data at the OTU level. As I suggested previously, community data like what are presented here are also typically analyzed with multivariate statistics, such as ordination (principle coordinates analysis, nonmetric multidimensional scaling, etc.) and permutational multivariate analysis of variance (PERMANOVA). These statistics can all be run in the vegan package of the program R. You can download R for free here: https://www.r-project.org/.

Reply: We have added Principal Component Analysis (PCA) to analyze community data at the OTU level. And R language (version 3.3.1) for PCA statistical analysis and graphing also was used.

Discussion: I previously commented "The phosphatase activity and microbial biomass P data suggest increased P demand (i.e., lower P availability) with mechanical weeding. Wouldn’t this be a harmful effect of weeding? P is an essential nutrient to plants. More context is needed on how the enzyme and microbial biomass data compare to other agricultural studies." In the revised manuscript, I don't see any inclusion of extracellular enzyme production or microbial biomass nutrient content from other agricultural studies. This will help put the data presented in the current study into context. in addition, I do not see any discussion of changes to P availability with mechanical weeding. Given the increase in phosphatase production and decrease in microbial biomass P with mechanical weeding, I think that there is lower P availability with mechanical weeding. The way I interpret the data presented, the mechanical weeding increases assimilation of nutrients by the soil microbes (thus the increase in organic C and organic N content). But, organic P content does not show this same pattern. Instead, phosphatase activity increases with mechanical weeding. This means that there is not enough inorganic P available, so the microbes need to put their energy into releasing phosphatase to free up P that is bound in organic matter. In other words, the data suggest that there is a higher P demand or lower P availability with mechanical weeding. I understand that the authors may disagree with me here, but the Discussion overall lacks these kinds of conclusions and mostly just re-states the results.

Reply: Some types of weeds have good phosphorus uptake capacity, which can accumulate soil surplus phosphorus in biomass and promote phosphorus biocycling (Roy 2017). However, without total topsoil inversion, the plant materials cut by a brush cutter and incorporation into the soil which provide fertility is limited. A stratified layer of phosphorus builds up on or near the soil surface, increasing the risk of phosphorus release and subsequent transport of dissolved reactive phosphorus via surface runoff and tile drain water (Ulén et al, 2010). We speculate that this may be the reason why microbial biomass phosphorus was significantly lower in the MW treatment than in the NW treatment.

Roy ED. Phosphorus recovery and recycling with ecological engineering: A review. Ecol Eng. 2017;98: 213-227.

Ulén B, Aronsson H, Bechmann M, Krogstad T, ØYgarden L, Stenberg M. Soil tillage methods to control phosphorus loss and potential side-effects: a Scandinavian review. Soil Use Manage. 2010; 26(2): 94-107.

Special thanks to you for your good comments.

We tried our best to improve the manuscript and made some changes will not influence the content and framework of the paper. We appreciate for Editors/Reviewers’ warm work earnestly, and hope that the correction will meet with approval.

Once again, thank you very much for your comments and suggestions.

Correspondence should be addressed to Prof.& Dr. Shang-dong Yang at the following address, phone number, and email address.

Corresponding author: 1) Name: Wenhui Liang; E-mail address: 723746615@qq.com; Tel: 86-771-2319966; 2) Name: Shangdong Yang; E-mail address: 924433816@qq.com; Tel: 86-771-3270813.

Thanks very much for your attention and consideration. We are looking forward to hearing from you soon.

With kind personal regards,

Sincerely yours,

Jian Xiao (E-mail: 1318513279@qq.com)

Submitted filename: Response to Reviewers.doc

Click here for additional data file.

31 Mar 2022

Effects of mechanical weeding on soil fertility and microbial community structure in star anise (Illicium verum Hook.f.) plantations

PONE-D-21-29819R2

Dear Dr. Yang,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Brenda A Wilson, Ph.D.

Academic Editor

PLOS ONE

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #3: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #3: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #3: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #3: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #3: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: (No Response)

Reviewer #3: I think the current version of the paper includes enough statistics (principal component analysis, linear discriminant analysis, and Wilcoxon rank-sum test) to support the conclusions of the authors. As a minor comment, I have only the following typo:

Line 185: substitute “tool, The” with “tool. The”.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Mariam Hassan

Reviewer #3: No

4 Apr 2022

PONE-D-21-29819R2

Effects of mechanical weeding on soil fertility and microbial community structure in star anise (Illicium verum Hook.f.) plantations

Dear Dr. Yang:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Brenda A Wilson

Academic Editor

PLOS ONE