Next Article in Journal
Hyperspectral Estimation Model of Forest Soil Organic Matter in Northwest Yunnan Province, China
Next Article in Special Issue
The Effect of Forest Thinning on Soil Microbial Community Structure and Function
Previous Article in Journal
The Impact of the Biomass Crop Assistance Program on the United States Forest Products Market: An Application of the Global Forest Products Model
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Forests
Volume 10
Issue 3
10.3390/f10030216
forests-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Leaf-Associated Shifts in Bacterial and Fungal Communities in Response to Chicken Rearing Under Moso Bamboo Forests in Subtropical China

by
Xiaoping Zhang
1,
Zheke Zhong
1,*,
Xu Gai
1,
Jiafu Ying
2,
Weifen Li
2,
Xuhua Du
1,
Fangyuan Bian
1 and
Chuanbao Yang
1
1
China National Bamboo Research Center, Key Laboratory of Resources and Utilization of Bamboo of State Forestry Administration, Hangzhou 310012, China
2
College of Animal Sciences, Zhejiang University, Hangzhou 310058, China
*
Author to whom correspondence should be addressed.
Forests 2019, 10(3), 216; https://doi.org/10.3390/f10030216
Submission received: 25 January 2019 / Revised: 22 February 2019 / Accepted: 25 February 2019 / Published: 1 March 2019
(This article belongs to the Special Issue Forest Microbial Communities and Processes)
Browse Figures
Versions Notes

Abstract

:
Integrated bamboo-chicken farming (BCF) systems are a traditional agroforestry pattern with large economic benefits in subtropical China. However, little is known regarding the effect of this integration on the bamboo leaf-associated microbiome, which can be very important for disease control and nutrient turnover. In the present study, we compared the leaf-associated bacterial and fungal communities of moso bamboo (Phyllostachys edulis) in a BCF system and an adjacent moso bamboo forest (MBF). The results showed that Cyanobacteria and Ascomycota were the predominant microbial phyla associated with bamboo leaves. Chicken farming under the bamboo forest significantly increased the bacterial and fungal alpha diversity (observed operational taxonomic units (OTUs) and Simpson’s index) associated with bamboo leaves. Principal components analysis (PCoA) further confirmed the shifts in the bacterial and fungal communities caused by chicken farming. Based on the observed relative abundances, the phyla Bacteroidetes, Actinobacteria, TM7, and Basidiomycota were significantly increased on BCF-associated leaves compared with MBF leaves, while Acidobacteria and Ascomycota were significantly decreased. An ecological function prediction analysis based on metabolic processes indicated that BCF could accelerate nutrient (C, N, and S) cycling but may increase the risk of fungal-associated diseases. Our findings suggest that shifts in leaf-associated bacterial and fungal communities can be important indicators for the scientific management of BCF systems.

1. Introduction

Bamboo forests are an important type of forest in tropical and subtropical areas, covering a total area of 31.5 million ha in 2010 and accounting for approximately 0.8% of the world’s total forest area [1]. Moso bamboo (Phyllostachys edulis (Carrière) J. Houzeau, synonym Phyllostachys heterocycla (Carrière) is currently the most important source of woody bamboo [2]. The shoot of moso bamboo can grow from 0–20 m in 45–60 days under suitable spring conditions [3]. Moso bamboo plays an important role in ecological and environmental protection [4,5], as well as in rural economic development in China [6,7]. Bamboo belongs to the subfamily Bambusoideae in the family Gramineae, which includes approximately 1500 species from approximately 90 genera worldwide [1]. China has more than 6 million ha of bamboo forest, 70% of which are moso bamboo forests [8]. However, because of increasing labor operational costs in China that have occurred in the last decade, the traditional management of bamboo forests has lost a great deal of economic attraction. Therefore, how to rationally utilize vast bamboo resources has become an important issue for scientific study.
Agroforestry systems are land-use systems and technologies where woody perennials are deliberately used on the same land management units as agricultural crops and/or animals [9]. Because bamboo forests are characterized by their short rotation and strong regeneration ability, they can typically be used to establish agroforestry systems as a potential strategy for providing food and nutritional security and for contributing to the economic development of developing countries in the tropics [10]. The use of an agroforestry pattern consisting of moso bamboo and chicken farming has been reported in China [11,12]. The results of a previous study showed that chicken farming in a bamboo forest increased soil C, total N, total P, total K, and the soil water-holding capacity [12]. However, because of the continuous input of chicken manure on the soil surface, there was a high risk of surface erosion and manure seepage [12], which may cause water pollution. Therefore, chicken rearing density is the most crucial aspect of this agroforestry practice [11]. There is also increasing concern that the introduction of chickens into a bamboo forest ecosystem may cause niche displacement of native microbiomes [12], which will further influence their functionality.
The surfaces and inner tissues of all land plants are colonized by diverse microorganisms, including bacteria, fungi, oomycetes, viruses, archaea, and protists [13,14]. Lorenz Hiltner defined the term “rhizosphere” in 1904 [15], and plant-associated microorganisms with root systems have received substantial attention in recent years [13,14,16]. Moso bamboo-associated bacteria and fungi have been isolated using culture-dependent methods [17,18] and high-throughput sequencing [19], but the latter study was primarily focused on the bamboo rhizome and pole-bacterial communities. The leaves of plants are ubiquitous global habitats that are inhabited by a diverse community of microorganisms [20,21]. These microbial communities have the potential to influence plant biogeography and ecosystem function through their influence on the fitness and function of their hosts and on soil nutrient turnover [22]. Additionally, the most important fungal and bacterial bamboo diseases are foliar, such as leaf spot disease on Bambusa polymorpha Munro., Dendrocalamus longispathus (Kurz) Kurz, and Dendrocalamus strictus (Roxb.) Nees [23]. However, the shifts in the leaf-associated microbiota (epiphytes and endophytes) in a bamboo-chicken farming (BCF) ecosystem have not been explored.
In this study, we comparatively investigated the leaf-associated bacterial and fungal communities of moso bamboo with and without chicken farming. The aim of this study was to determine how the leaf-associated microbiota of moso bamboo responds to the introduction of chickens into a bamboo forest and the functional profiles associated with these shifts in the microbiota.

2. Materials and Methods

2.1. Experimental Site and Design

The study area (30°38′14.92″ N, 119°21′1.05″ E) was located in the town of Hanggai, western Anji County, Zhejiang Province. The area has a mid-latitudinal subtropical monsoon climate, with an average annual precipitation of approximately 1854 mm, a mean annual temperature of approximately 17 °C, and an altitude of 400–450 m above sea level. The average annual sunshine duration in this region is 1946 h, and the frost-free period is 230 days. In addition, the soils in the region are classified as Ferric Luvisols, derived from silty sand and fine sand-mixed rock [24]. The investigated BCF system was established in 2006. To maintain a rational bamboo density, a selective harvest practice was adopted into this system. The stand density was approximately 2100 stems ha−1, with an average plant height and diameter at breast of 9.0 m and 8.9 cm, respectively. A previous study showed that chicken farming resulted in significant increases in soil organic C and the total N, P, and K contents [12]. Therefore, the chicken rearing density was maintained within 2500–3000 ha−1 to avoid the risk of over-application of manure. The adjacent bamboo forest was selected as a control, because it had very similar site conditions with respect to soil type, position of slope, slope gradient, and other aspects that were the same as in the BCF system. The adjacent moso bamboo forest (MBF) without chicken farming was the control group. The MBF was selectively harvested to maintain a specific density. The growth status of the MBF forest was very close to that of the BCF system, namely, the stand density was approximately 2300 stems ha−1 and the average plant height and diameter at breast were 8.6 m and 8.5 cm, respectively.

2.2. Sampling

Leaf samples were collected in late September 2018. The paired-site sampling method [25] was adopted for sampling, namely, three sites along the border between BCF and MBF forests were chosen. The distance between each site was greater than 100 m. Each site included two sampling subplots (10 m × 10 m) belonging to BCF and MBF, respectively. Originally, both forests (BCF and MBF) in each site had very similar soil conditions, slope positions, and management systems. One bamboo plant with an average size was chosen in each subplot for sampling. The healthy leaves were randomly collected from the fifth to the seventh branches (from the bottom up) from both the shaded and unshaded parts of the plant. Approximately 10 g of leaves were pooled as a composite sample, these were immediately frozen in liquid nitrogen and stored at −80 °C for further analysis.

2.3. Illumina High-Throughput Sequencing

DNA was extracted from the leaf samples using a Magnetic Soil and Stool DNA kit (Tiangen, Beijing, China) according to the manufacturer’s instructions. The bacterial 16S rRNA and fungal ITS2 genes were amplified using the primer pairs 338F (5′-ACTCCTACGGGAGGCAGCAG-3′)/806R (5′-GGACTACHVGGGTWTCTAAT-3′) and ITS1F (5′-CTTGGTCATTTAGAGGAAGTAA-3′)/ITS2R (5′-GCTGCGTTCTTCATCGATGC-3′), respectively. PCR amplification and MiSeq sequencing were performed by Majorbio Bio-pharm Technology Co., Ltd. (Shanghai, China). Raw sequences have been deposited in NCBI under Bioproject PRJNA514420 and PRJNA514422.

2.4. Data Analyses

Paired reads were assembled using FLASH [26], and the assembled sequences from each sample were combined into one file using the add_qiime_labels.py script in QIIME [27]. The chimeric 16S and ITS sequences were removed with Vsearch v2.8.0 [28] using the RDP “Gold” database (https://drive5.com/uchime/gold.fa) and the UNITE/INSD ITS2-only UCHIME reference dataset v. 7.2 [29] as references, respectively. Next, the nonchimeric sequences with 97% similarity were clustered into operational taxonomic units (OTUs) using the open-reference OTU picking workflow pipelines in QIIME [27]. The representative OTU sequences were assigned using the RDP classifier to identify bacterial taxa against the Greengenes reference database released in August 2013 [30], while the representative sequences of fungi were identified using the UNITE database [31].
The bacterial and fungal OTU tables were rarefied to the lowest number of sequences using QIIME [27]. Alpha diversity indices (observed OTUs, Shannon, and Simpson’s index) were calculated using the alpha_rarefaction.py workflow in QIIME. Principal coordinates analysis (PCoA) based on the Bray–Curtis distance was conducted and visualized in R using the phyloseq package [32] and ggplot2 [33]. The Sorenson Similarity Index (Cs) was used to measure the similarity between MBF and BCF based on the presence and absence of OTUs. The index was calculated as: Cs=2C/(A + B), where A and B are the number of OTUs in MBF and BCF, respectively, and C is the number of OTUs shared by the two groups. METAGENassist [34] and FUNGuild [35] were used to assess putative functional profiles based on the bacterial and fungal community composition of the leaf samples from moso bamboo. The differences in microbial composition and alpha diversity were analysed using an independent samples t-test using IBM-SPSS (version 22.0; Chicago IL, USA).

3. Results

3.1. Compositions of Bacterial and Fungal Communities

After filtering out the low-quality reads and chimeric sequences, 328,471 and 377,590 bacterial and fungal sequences were obtained from the moso bamboo leaf samples of both MBF and BCF, which clustered into 2056 and 798 OTUs, respectively, at the 97% similarity cut-off level.
The most abundant bacterial phylum in the moso bamboo leaves was Cyanobacteria, accounting for an average of 63.38% of the total sequences, followed by Proteobacteria, Bacteroidetes, Actinobacteria, Firmicutes, Thermi, Acidobacteria, TM7, Planctomycetes, and Armatimonadetes, which accounted for 23.65, 5.53, 4.13, 0.93, 0.51, 0.45, 0.40, 0.25, and 0.19% of the total sequences, respectively (Figure 1a). In contrast, only two fungal phyla with an average relative abundance of >0.1% were detected in the bamboo leaves, with the dominant phylum being Ascomycota, accounting for an average of 97.72% of the total sequences (Figure 1b), followed by Basidiomycota, which accounted for 0.72% of the total sequences. At the genus level, fifteen bacterial genera with an average relative abundance >0.1% were detected (Table 1), i.e., Methylobacterium (7.73%), Hymenobacter (4.74%), Sphingomonas (4.70%), Deinococcus (0.51%), Kineococcus (0.48%), Spirosoma (0.41%), Beijerinckia (0.35%), Curtobacterium (0.19%), Friedmanniella (0.17%), Microbacterium (0.16%) and Ralstonia (0.16%). Based on the classifiable sequences, the fungal reads were primarily assigned to fourteen genera with an average relative abundance of >0.1%, and these genera were ranked in order of relative abundance as follows (Table 1): Alatosessilispora (12.66%), Strelitziana (12.10%), Shiraia (1.75%), Cladosporium (1.01%), Camptophora (0.75%), Geastrumia (0.39%), Mycosphaerella (0.36%), Ramularia (0.35%), Bacidina (0.35%), Trichomerium (0.27%), Hortaea (0.20%), Hygrocybe (0.14%), and Arthrinium (0.14%).
At the phylum level, the abundances of the bacterial phyla Bacteroidetes, Actinobacteria, and TM7 were significantly increased (p < 0.05) and that of Acidobacteria was significantly decreased (p < 0.05) in the BCF samples compared with those of the MBF (Figure 2a). The bacterial genera Methylobacterium, Hymenobacter, Kineococcus, Spirosoma, Friedmanniella, Bdellovibrio, and Arthrobacter were significantly increased in the BCF samples (p < 0.05), while that of Terriglobus was significantly decreased (p < 0.05) relative to the MBF samples (Table 1). For the fungal communities (Figure 2b, Table 1), the relative abundances of the taxa Ascomycota, Shiraia, Geastrumia, Mycosphaerella, Bacidina, and Hortaea were significantly lower (p < 0.05) in the BCF samples than in the MBF samples, while the relative abundances of the taxa Basidiomycota, Alatosessilispora, Strelitziana, Cladosporium, Camptophora, Ramularia, Trichomerium, and Arthrinium in the BCF samples were significantly increased (p < 0.05) compared to those observed in the MBF samples.

3.2. Bacterial and Fungal Community Diversities

The observed OTUs and Simpson’s indices were calculated to estimate the alpha-diversity characteristics of each sample. As shown in Figure 3, compared with the MBF, the BCF treatment significantly increased the number of observed OTUs and the Simpson’s indices of the bacterial and fungal communities associated with bamboo leaves. For the fungal communities, the Shannon index was significantly higher in BCF than that in MBF (p < 0.05), while no difference (p > 0.05) was observed between MBF and BCF within the bacterial communities.
The PCoA based on Bray–Curtis distances revealed that the first principal component (PCoA 1) explained 79.50% and 99.10% of the variability in the bacterial and fungal community, respectively (Figure 4a,b). Two different clusters were formed for the MBF and BCF samples with respect to the bacterial (Sorenson index = 0.51) and fungal (Sorenson index = 0.55) community compositions, indicating that chicken farming in the bamboo forest caused bacterial and fungal community shifts associated with the bamboo leaves.

3.3. Ecological Function Evaluation of the Niche Shift of Leaf-Associated Microbiome

The functional potential of the bacterial and fungal communities associated with moso leaves was evaluated based on their metabolic processes using METAGENassist [33] and FUNGuild [34], respectively. The results (Figure 5) showed that the shift in the bacterial niche in the BCF treatment significantly increased the nutrient cycling pathways, including nitrogen (nitrogen fixation), carbon (carbon fixation), sulfur (sulfur and sulfide oxidation), and other metabolic processes (propionate metabolism, aromatic hydrocarbon degradation, naphthalene degradation, and atrazine metabolism). In contrast, the results showed that the shift in the fungal niche in the BCF treatment significantly increased the proportion of trophic types of fungi (pathotrophic, pathotrophic–saprotrophic, saprotrophic–symbiotrophic, pathotrophic–symbiotrophic and saprotrophic taxa), but significantly decreased the proportion of symbiotrophic fungi in comparison to the MBF treatment (Figure 6).

4. Discussion

The worldwide biomass of moso bamboo leaves is 2.89–3.65 Mg ha−1, which accounts for 3–5% of the total aboveground bamboo biomass and changes every two years [36]. Bamboo leaves play an important role in bamboo forest carbon sequestration, soil nutrient development, and adaptation to environmental change [37,38]. To the best of our knowledge, the moso bamboo leaf-associated bacterial and fungal communities have not been well investigated. In this study, the use of high-throughput sequencing revealed that Cyanobacteria was the dominant bacterial phylum in the leaves of moso bamboo. A previous study showed that the bamboo species Merostachys neesii had a large number of cyanobacterial 16S rRNA genes per cm2 of leaf [39]. Cyanobacteria have been suggested to be capable of both nitrogen and carbon fixation [40,41]. We also observed that Ascomycota was the most abundant fungal phylum associated with moso bamboo leaves, followed by Basidiomycota. This finding is in line with that of a previous study in which the endophytic fungi isolated from moso bamboo seeds belonged to the phyla Ascomycota and Basidiomycota [18], the members of which are important decomposers that break down dead leaves in forest ecosystems [42,43]. As mentioned above, the dominant leaf-associated bacterial and fungal phyla may contribute to C and N cycling in moso bamboo plantation ecosystems. The results of this study also identified fifteen bacterial genera with a relative abundance greater than 0.1% in the moso bamboo leaves (Table 1), which differs from the findings obtained using traditional bacterial isolation and culture methods. Yuan et al. [17] isolated five genera (Pseudomonas, Micrococcus, Dermacoccus, Pantoea, and Streptomyces) from the leaves of moso bamboo stands in the Wuyi Mountain, Jiangle, and Changting regions of China. However, traditional culture-based bacterial isolation methods cannot sufficiently identify the bacteria associated with leaves, especially for the cyanobacteria.
The results of the current study indicated that the introduction of chicken farming into a moso bamboo forest markedly influenced the moso bamboo leaf-associated microbiome, by increasing the relative abundance of the taxa Bacteroidetes, Actinobacteria, TM7, Arthrobacter, Kineococcus, Friedmanniella, Hymenobacter, Methylobacterium, Bdellovibrio, and Spirosoma compared with that observed in the MBF. Members of the bacterial phylum Bacteroidetes are important contributors to nutrient turnover because they harbour genes for denitrification, indicating a possible role in nitrogen cycling [44]. Members of the genus Hymenobacter can be used as plant growth-promoting bacteria to enhance plant nutritive properties [45]. Methylobacterium and Spirosoma belong to the class Alphaproteobacteria within the phylum Proteobacteria. Alphaproteobacteria participate in a variety of metabolic strategies including photosynthesis, nitrogen fixation, ammonia oxidation, and methylotrophy [46]. The results of previous studies showed that moderate chicken farming in bamboo forests can significantly improve the soil properties, increasing soil N, organic matter, total P, available P, total K, and available K [12]. As mentioned above, the shifts in bacterial abundances in moso bamboo leaves caused by chicken farming may contribute to nutrient cycling. Actinobacteria species may contribute to their host plants by promoting growth and enhancing their ability to withstand environmental stresses [47]. Arthrobacter species can promote legume growth by solubilizing iron, which is then taken up by the plants [48]. Members of the genus Kineococcus are reported to play roles in the immediate response to stress and/or the recovery from stress [49]. Species of the genus Methylobacterium are able to interact symbiotically with different plant species, and these interactions can promote plant growth or induce systemic resistance, increasing plant fitness [50]. Zhu et al. [12] also observed that chicken farming in bamboo forests may increase the risk of excess phosphorus input. Thus, the presence of different bacteria may help bamboo trees respond to the excessive nutrient stress caused by chicken farming. Fries et al. [51] isolated a Spirosoma strain from Zn- and Cd-accumulating Salix caprea, and Lee et al. [52] reported a novel Spirosoma strain with high gamma and UVC radiation resistance. In addition, some studies have reported that moso bamboo has a high metal tolerance [53,54]. Thus, the genus Spirosoma may be associated with moso bamboo with a high metal tolerance.
Fungal endophytes have been reported to promote plant growth [55], affect plant resistance to abiotic and biotic stresses [55,56,57], and decompose plant litter [58]. Rodriguez and Redman [59] noted that fungal symbiosis represents significant ecological plasticity, e.g. Colletotrichum species can express either parasitic or mutualistic lifestyles depending on the host genotype colonized. Similar to endophytic fungi, epiphytic fungal colonization on the surfaces of plant tissues can protect host plants from disease [60,61], and can participate in the decomposition of plant litter [62]. In the current study, BCF was observed to increase the relative abundance of Basidiomycota and decrease that of Ascomycota associated with moso bamboo leaves compared to that observed in MBF. Previous studies have shown that species of the phyla Ascomycota and Basidiomycota are important soil fungal decomposers [63,64]. Members of the phylum Basidiomycota are able to degrade lignocellulose organic matter [65,66], while members of the phylum Ascomycota have a limited ability to degrade recalcitrant lignin-containing litter material [67]. The results also indicated that all of the different genera belong to the phylum Ascomycota, such as Alatosessilispora, Strelitziana, Cladosporium, Camptophora, Ramularia, Trichomerium, and Arthrinium. Thus, these fungal phyla and genera may contribute to the carbon cycle in bamboo plantations.
Previous studies observed that animal manure in forest-livestock systems can improve the soil nutrient status by accelerating N cycling [68,69], although excess manure may result in soil nutrient erosion and imbalance [70,71]. Zhu et al. [12] observed that chicken trampling can significantly increase soil bulk density, which causes further environmental stress that impacts plant growth. The niche shift of leaf-associated bacterial communities in BCF also showed higher potential for nutrient cycling, which may be related to change in environmental stress. Chicken guts are colonized by diverse microbial classes including archaea, bacteria, and fungi [72]. Those microbial communities also contain pathogens [73], and the gastrointestinal pathogens can enter the food chain through defecation in the farm environment or by fertilization of crops with manure [74]. In this study, we also found that moso bamboo leaves from the BCF treatment exhibited an increased proportion of pathotrophic, pathotrophic–saprotrophic and saprotrophic fungi, indicating that chicken farming in bamboo plantations may lead to a higher risk of fungal-associated diseases. Thus, BCF systems should include certain management practices such as controlling chicken density, and good sterilization practices should be undertaken during chicken farming.

5. Conclusions

In summary, introducing chicken farming to a moso bamboo forest markedly changed the leaf-associated bacterial and fungal communities. The observed bacterial and fungal shifts may have dual effects. On the one hand, BCF systems may contribute to increased nutrient cycling in moso bamboo forests and enhance the adaption ability of trees to environmental stresses caused by shifts in bacterial communities. On the other hand, BCF may increase the risk of fungal-associated diseases. Therefore, increased attention is required in terms of soil nutrient management and leaf disease control in BCF systems.

Author Contributions

Z.Z. and X.Z. designed the experiment. X.Z., X.G., J.Y., W.L., and X.D. performed the study data collection. X.Z., C.Y., F.B., and X.G. analyzed the results. Z.Z. contributed to discussing content and reviewing the article. X.Z. wrote the final article. All authors approved the final version of the manuscript.

Funding

This project was financially supported by the National Key R&D Program of China (2018YFD0600105).

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. FAO. Global Forest Resources Assessment; FAO Forestry Paper: Rome, Italy, 2010. [Google Scholar]
  2. Xie, L.; Li, X.; Hou, D.; Cheng, Z.; Liu, J.; Li, J.; Mu, S.; Gao, J. Genome-Wide Analysis and Expression Profiling of the Heat Shock Factor Gene Family in Phyllostachys edulis during Development and in Response to Abiotic Stresses. Forests 2019, 10, 100. [Google Scholar] [CrossRef]
  3. Li, L.; Cheng, Z.; Ma, Y.; Bai, Q.; Li, X.; Cao, Z.; Wu, Z.; Gao, J. The association of hormone signaling genes, transcription, and changes in shoot anatomy during moso bamboo growth. Plant Biotechnol. J. 2017, 16, 72–85. [Google Scholar] [CrossRef] [PubMed]
  4. Xu, L.; Shi, Y.; Zhou, G.; Xu, X.; Liu, E.; Zhou, Y.; Li, C.; Fang, H.; Deng, X. Temporal Change in Aboveground Culms Carbon Stocks in the Moso Bamboo Forests and Its Driving Factors in Zhejiang Province, China. Forests 2017, 8, 371. [Google Scholar] [CrossRef]
  5. Gu, L.; Zhou, Y.; Mei, T.; Zhou, G.; Xu, L. Carbon Footprint Analysis of Bamboo Scrimber Flooring—Implications for Carbon Sequestration of Bamboo Forests and Its Products. Forests 2019, 10, 51. [Google Scholar] [CrossRef]
  6. Flynn, A.; Chan, K.W.; Zhu, Z.H.; Yu, L. Sustainability, space and supply chains: The role of bamboo in Anji County, China. J. Rural. Stud. 2017, 49, 128–139. [Google Scholar] [CrossRef] [Green Version]
  7. Chen, S.; Jiang, H.; Cai, Z.; Zhou, X.; Peng, C. The response of the net primary production of Moso bamboo forest to the On and Off-year management: A case study in Anji County, Zhejiang, China. For. Ecol. Manag. 2018, 409, 1–7. [Google Scholar] [CrossRef]
  8. Song, X.; Peng, C.; Zhou, G.; Gu, H.; Li, Q.; Zhang, C. Dynamic allocation and transfer of non-structural carbohydrates, a possible mechanism for the explosive growth of Moso bamboo (Phyllostachys heterocycla). Sci. Rep. 2016, 6, 25908. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  9. FAO. FAO Projects. 2015. Available online: http://www.fao.org/forestry/agroforestry/90030/en/ (accessed on 27 March 2017).
  10. Kittur, B.; Sudhakara, K.; Kumar, B.M.; Kunhamu, T.; Sureshkumar, P. Bamboo based agroforestry systems in Kerala, India: Performance of turmeric (Curcuma longa L.) in the subcanopy of differentially spaced seven year-old bamboo stand. Agroforest. Syst. 2016, 90, 237–250. [Google Scholar] [CrossRef]
  11. Zhang, X.; Wen, T.; Zhang, Z.; Huang, S.; Huo, D.; Jiang, X.; Yuan, K.; Shen, X.; Huang, X. A Study of Vegetation on Biomass Changes and Black-Bone Chicken Breeding Technologies under Phyllostachys Pubesebs Forest in Chishui River Basin. World Bamboo Rattan 2015, 13, 1–7. [Google Scholar]
  12. Zhu, C.; Yang, C.; Shen, X.; Wang, B. Effects of Raising Chicken on Soil Quality and Bamboo Growth in Phyllostachys edulis Forest. J. Bamboo Res. 2018, 37, 49–53. [Google Scholar]
  13. Levy, A.; Conway, J.M.; Dangl, J.L.; Woyke, T. Elucidating Bacterial Gene Functions in the Plant Microbiome. Cell Host Microbe 2018, 24, 475–485. [Google Scholar] [CrossRef] [PubMed]
  14. Müller, D.B.; Vogel, C.; Bai, Y.; Vorholt, J.A. The plant microbiota: Systems-level insights and perspectives. Annu. Rev. Genet. 2016, 50, 211–234. [Google Scholar] [CrossRef] [PubMed]
  15. Hartmann, A.; Rothballer, M.; Schmid, M. Lorenz Hiltner, a pioneer in rhizosphere microbial ecology and soil bacteriology research. Plant Soil 2008, 312, 7–14. [Google Scholar] [CrossRef]
  16. Schlaeppi, K.; Bulgarelli, D. The plant microbiome at work. Mol. Plant-Microbe Interact. 2015, 28, 212–217. [Google Scholar] [CrossRef] [PubMed]
  17. Yuan, Z.; Liu, F.; Zhang, G. Isolation of culturable endophytic bacteria from Moso bamboo (Phyllostachys edulis) and 16S rDNA diversity analysis. Arch. Biol. Sci. 2015, 67, 1001–1008. [Google Scholar] [CrossRef]
  18. Shen, X.-Y.; Cheng, Y.-L.; Cai, C.-J.; Fan, L.; Gao, J.; Hou, C.-L. Diversity and antimicrobial activity of culturable endophytic fungi isolated from moso bamboo seeds. PLoS ONE 2014, 9, e95838. [Google Scholar] [CrossRef] [PubMed]
  19. Liu, F.; Yuan, Z.; Zhang, X.; Zhang, G.; Xie, B. Characteristics and diversity of endophytic bacteria in moso bamboo (Phyllostachys edulis) based on 16S rDNA sequencing. Arch. Microbiol. 2017, 199, 1259–1266. [Google Scholar] [CrossRef] [PubMed]
  20. Kembel, S.W.; O’Connor, T.K.; Arnold, H.K.; Hubbell, S.P.; Wright, S.J.; Green, J.L. Relationships between phyllosphere bacterial communities and plant functional traits in a neotropical forest. Proc. Natl. Acad. Sci. USA 2014, 111, 13715–13720. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  21. Vorholt, J.A. Microbial life in the phyllosphere. Nat. Rev. Microbiol. 2012, 10, 828–840. [Google Scholar] [CrossRef] [PubMed]
  22. Rastogi, G.; Coaker, G.L.; Leveau, J.H. New insights into the structure and function of phyllosphere microbiota through high-throughput molecular approaches. FEMS Microbiol. Lett. 2013, 348, 1–10. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  23. Mohanan, C.; Liese, W. Diseases of bamboos. Int. J. Trop. Plant Dis. 1990, 8, 1–20. [Google Scholar]
  24. Yang, C.; Zhong, Z.; Zhang, X.; Bian, F.; Du, X. Responses of Soil Organic Carbon Sequestration Potential and Bacterial Community Structure in Moso Bamboo Plantations to Different Management Strategies in Subtropical China. Forests 2018, 9, 657. [Google Scholar] [CrossRef]
  25. Chen, C.R.; Xu, Z.H.; Mathers, N.J. Soil Carbon Pools in Adjacent Natural and Plantation Forests of Subtropical Australia. Soil Sci. Soc. Am. J. 2004, 68, 282–291. [Google Scholar] [CrossRef]
  26. Magoč, T.; Salzberg, S.L. FLASH: Fast length adjustment of short reads to improve genome assemblies. Bioinformatics 2011, 27, 2957–2963. [Google Scholar] [CrossRef] [PubMed]
  27. Caporaso, J.G.; Kuczynski, J.; Stombaugh, J.; Bittinger, K.; Bushman, F.D.; Costello, E.K.; Fierer, N.; Pena, A.G.; Goodrich, J.K.; Gordon, J.I. QIIME allows analysis of high-throughput community sequencing data. Nat. Methods 2010, 7, 335–336. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  28. Rognes, T.; Flouri, T.; Nichols, B.; Quince, C.; Mahé, F. VSEARCH: A versatile open source tool for metagenomics. PeerJ 2016, 4, e2584. [Google Scholar] [CrossRef] [PubMed]
  29. McDonald, D.; Price, M.N.; Goodrich, J.; Nawrocki, E.P.; DeSantis, T.Z.; Probst, A.; Andersen, G.L.; Knight, R.; Hugenholtz, P. An improved Greengenes taxonomy with explicit ranks for ecological and evolutionary analyses of bacteria and archaea. ISME J. 2012, 6, 610–618. [Google Scholar] [CrossRef] [PubMed]
  30. Nilsson, R.H.; Tedersoo, L.; Ryberg, M.; Kristiansson, E.; Hartmann, M.; Unterseher, M.; Porter, T.M.; Bengtsson-Palme, J.; Walker, D.M.; De Sousa, F. A comprehensive, automatically updated fungal ITS sequence dataset for reference-based chimera control in environmental sequencing efforts. Microbes Environ. 2015, 30, 145–150. [Google Scholar] [CrossRef] [PubMed]
  31. Abarenkov, K.; Henrik Nilsson, R.; Larsson, K.H.; Alexander, I.J.; Eberhardt, U.; Erland, S.; Høiland, K.; Kjøller, R.; Larsson, E.; Pennanen, T. The UNITE database for molecular identification of fungi–recent updates and future perspectives. New Phytol. 2010, 186, 281–285. [Google Scholar] [CrossRef] [PubMed]
  32. McMurdie, P.J.; Holmes, S. phyloseq: An R package for reproducible interactive analysis and graphics of microbiome census data. PLoS ONE 2013, 8, e61217. [Google Scholar] [CrossRef] [PubMed]
  33. Wickham, H. ggplot2: Elegant Graphics for Data Analysis; Springer: New York, NY, USA, 2016. [Google Scholar]
  34. Arndt, D.; Xia, J.; Liu, Y.; Zhou, Y.; Guo, A.C.; Cruz, J.A.; Sinelnikov, I.; Budwill, K.; Nesbø, C.L.; Wishart, D.S. METAGENassist: A comprehensive web server for comparative metagenomics. Nucleic Acids Res. 2012, 40, W88–W95. [Google Scholar] [CrossRef] [PubMed]
  35. Nguyen, N.H.; Song, Z.; Bates, S.T.; Branco, S.; Tedersoo, L.; Menke, J.; Schilling, J.S.; Kennedy, P.G. FUNGuild: An open annotation tool for parsing fungal community datasets by ecological guild. Fungal Ecol. 2016, 20, 241–248. [Google Scholar] [CrossRef]
  36. Yen, T.-M.; Lee, J.-S. Comparing aboveground carbon sequestration between moso bamboo (Phyllostachys heterocycla) and China fir (Cunninghamia lanceolata) forests based on the allometric model. For. Ecol. Manag. 2011, 261, 995–1002. [Google Scholar] [CrossRef]
  37. Christanty, L.; Mailly, D.; Kimmins, J. “Without bamboo, the land dies”: Biomass, litterfall, and soil organic matter dynamics of a Javanese bamboo talun-kebun system. For. Ecol. Manag. 1996, 87, 75–88. [Google Scholar] [CrossRef]
  38. Lobovikov, M.; Schoene, D.; Yping, L. Bamboo in climate change and rural livelihoods. Mitig. Adapt. Strateg. Glob. Chang. 2012, 17, 261–276. [Google Scholar] [CrossRef]
  39. Rigonato, J.; Gonçalves, N.; Andreote, A.P.D.; Lambais, M.R.; Fiore, M.F. Estimating genetic structure and diversity of cyanobacterial communities in Atlantic forest phyllosphere. Can. J. Microbiol. 2016, 62, 953–960. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  40. Klawonn, I.; Nahar, N.; Walve, J.; Andersson, B.; Olofsson, M.; Svedén, J.; Littmann, S.; Whitehouse, M.J.; Kuypers, M.; Ploug, H. Cell-specific nitrogen-and carbon-fixation of cyanobacteria in a temperate marine system (Baltic Sea). Environ. Microbiol. 2016, 18, 4596–4609. [Google Scholar] [CrossRef] [PubMed]
  41. Olofsson, M.; Egardt, J.; Singh, A.; Ploug, H. Inorganic phosphorus enrichments in Baltic Sea water have large effects on growth, carbon fixation, and N2 fixation by Nodularia spumigena. Aquat. Microb. Ecol. 2016, 77, 111–123. [Google Scholar] [CrossRef]
  42. Chaverri, P.; Vilchez, B. Hypocrealean (Hypocreales, Ascomycota) Fungal Diversity in Different Stages of Tropical Forest Succession in Costa Rica. Biotropica 2006, 38, 531–543. [Google Scholar] [CrossRef]
  43. Trappe, J.M.; Castellano, M.A. New sequestrate Ascomycota and Basidiomycota covered by the northwest forest plan. Mycotaxon 2000, 75, 153–180. [Google Scholar]
  44. Chaparro, J.M.; Badri, D.V.; Vivanco, J.M. Rhizosphere microbiome assemblage is affected by plant development. ISME J. 2014, 8, 790–803. [Google Scholar] [CrossRef] [PubMed]
  45. Dimitrijević, S.; Pavlović, M.; Maksimović, S.; Ristić, M.; Filipović, V.; Antonović, D.; Dimitrijević-Branković, S. Plant growth-promoting bacteria elevate the nutritional and functional properties of black cumin and flaxseed fixed oil. J. Sci. Food Agric. 2018, 98, 1584–1590. [Google Scholar] [CrossRef] [PubMed]
  46. Williams, K.P.; Sobral, B.W.; Dickerman, A.W. A robust species tree for the alphaproteobacteria. J. Bacteriol. 2007, 189, 4578–4586. [Google Scholar] [CrossRef] [PubMed]
  47. Qin, S.; Xing, K.; Jiang, J.-H.; Xu, L.-H.; Li, W.-J. Biodiversity, bioactive natural products and biotechnological potential of plant-associated endophytic actinobacteria. Appl. Microbiol. Biotechnol. 2011, 89, 457–473. [Google Scholar] [CrossRef] [PubMed]
  48. Aviles-Garcia, M.; Flores-Cortez, I.; Hernández-Soberano, C.; Santoyo, G.; Valencia-Cantero, E. The plant growth-promoting rhizobacterium Arthrobacter agilis UMCV2 endophytically colonizes Medicago truncatula. Rev. Argent. Microbiol. 2016, 48, 342–346. [Google Scholar] [PubMed]
  49. Chen, Z.; Li, L.; Shan, Z.; Huang, H.; Chen, H.; Ding, X.; Guo, J.; Liu, L. Transcriptome sequencing analysis of novel sRNAs of Kineococcus radiotolerans in response to ionizing radiation. Microbiol. Res. 2016, 192, 122–129. [Google Scholar] [CrossRef] [PubMed]
  50. Dourado, M.N.; Bogas, A.C.; Pomini, A.M.; Andreote, F.D.; Quecine, M.C.; Marsaioli, A.J.; Araújo, W.L. Methylobacterium-plant interaction genes regulated by plant exudate and quorum sensing molecules. Braz. J. Microbiol. 2013, 44, 1331–1339. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  51. Fries, J.; Pfeiffer, S.; Kuffner, M.; Sessitsch, A. Spirosomaendophyticum sp. nov.; isolated from Zn-and Cd-accumulating Salix caprea. Int. J. Syst. Evol. Microbiol. 2013, 63, 4586–4590. [Google Scholar] [CrossRef] [PubMed]
  52. Lee, J.-J.; Srinivasan, S.; Lim, S.; Joe, M.; Im, S.; Bae, S.I.; Park, K.R.; Han, J.-H.; Park, S.-H.; Joo, B.-m. Spirosoma radiotolerans sp. nov.; a gamma-radiation-resistant bacterium isolated from gamma ray-irradiated soil. Curr. Microbiol. 2014, 69, 286–291. [Google Scholar] [CrossRef] [PubMed]
  53. Liu, D.; Li, S.; Islam, E.; Chen, J.-r.; Wu, J.-s.; Ye, Z.-q.; Peng, D.-l.; Yan, W.-b.; Lu, K.-p. Lead accumulation and tolerance of Moso bamboo (Phyllostachys pubescens) seedlings: Applications of phytoremediation. J. Zhejiang Univ. Sci. B 2015, 16, 123–130. [Google Scholar] [CrossRef] [PubMed]
  54. Bian, F.; Zhong, Z.; Zhang, X.; Yang, C. Phytoremediation potential of moso bamboo (Phyllostachys pubescens) intercropped with Sedum plumbizincicola in metal-contaminated soil. Environ. Sci. Pollut. 2017, 24, 27244–27253. [Google Scholar] [CrossRef] [PubMed]
  55. Xia, Y.; Amna, A.; Opiyo, S.O. The culturable endophytic fungal communities of switchgrass grown on a coal-mining site and their effects on plant growth. PLoS ONE 2018, 13, e0198994. [Google Scholar] [CrossRef] [PubMed]
  56. Verma, S.K.; Gond, S.K.; Mishra, A.; Sharma, V.K.; Kumar, J.; Singh, D.K.; Kumar, A.; Kharwar, R.N. Fungal Endophytes Representing Diverse Habitats and Their Role in Plant Protection. In Developments in Fungal Biology and Applied Mycology; Springer: Singapore, 2017; pp. 135–157. [Google Scholar]
  57. Rodriguez, R.J.; Henson, J.; Van Volkenburgh, E.; Hoy, M.; Wright, L.; Beckwith, F.; Kim, Y.-O.; Redman, R.S. Stress tolerance in plants via habitat-adapted symbiosis. ISME J. 2008, 2, 404–416. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  58. Gundel, P.; Helander, M.; Garibaldi, L.; Vázquez-de-Aldana, B.; Zabalgogeazcoa, I.; Saikkonen, K. Direct and indirect effects of the fungal endophyte Epichloë uncinatum on litter decomposition of the host grass, Schedonorus pratensis. Plant Ecol. 2017, 218, 1107–1115. [Google Scholar] [CrossRef]
  59. Rodriguez, R.; Redman, R. More than 400 million years of evolution and some plants still can’t make it on their own: Plant stress tolerance via fungal symbiosis. J. Exp. Bot. 2008, 59, 1109–1114. [Google Scholar] [CrossRef] [PubMed]
  60. Gafni, A.; Calderon, C.E.; Harris, R.; Buxdorf, K.; Dafa-Berger, A.; Zeilinger-Reichert, E.; Levy, M. Biological control of the cucurbit powdery mildew pathogen Podosphaera xanthii by means of the epiphytic fungus Pseudozyma aphidis and parasitism as a mode of action. Front. Plant. Sci. 2015, 6, 132. [Google Scholar] [CrossRef] [PubMed]
  61. Barda, O.; Shalev, O.; Alster, S.; Buxdorf, K.; Gafni, A.; Levy, M. Pseudozyma aphidis induces salicylic-acid-independent resistance to Clavibacter michiganensis in tomato plants. Plant Dis. 2015, 99, 621–626. [Google Scholar] [CrossRef] [PubMed]
  62. Osono, T.; Bhatta, B.K.; Takeda, H. Phyllosphere fungi on living and decomposing leaves of giant dogwood. Mycoscience 2004, 45, 35–41. [Google Scholar] [CrossRef]
  63. Vandenkoornhuyse, P.; Baldauf, S.L.; Leyval, C.; Straczek, J.; Young, J.P.W. Extensive fungal diversity in plant roots. Science 2002, 295, 2051. [Google Scholar] [CrossRef] [PubMed]
  64. Bastian, F.; Bouziri, L.; Nicolardot, B.; Ranjard, L. Impact of wheat straw decomposition on successional patterns of soil microbial community structure. Soil Biol. Biochem. 2009, 41, 262–275. [Google Scholar] [CrossRef]
  65. Osono, T.; Takeda, H. Fungal decomposition of Abies needle and Betula leaf litter. Mycologia 2006, 98, 172–179. [Google Scholar] [CrossRef] [PubMed]
  66. Yelle, D.J.; Ralph, J.; Lu, F.; Hammel, K.E. Evidence for cleavage of lignin by a brown rot basidiomycete. Environ. Microbiol. 2008, 10, 1844–1849. [Google Scholar] [CrossRef] [PubMed]
  67. Lundell, T.K.; Mäkelä, M.R.; Hildén, K. Lignin-modifying enzymes in filamentous basidiomycetes–ecological, functional and phylogenetic review. J. Basic Microbiol. 2010, 50, 5–20. [Google Scholar] [CrossRef] [PubMed]
  68. Bardgett, R.; Leemans, D.; Cook, R.; Hobbs, P. Seasonality of the soil biota of grazed and ungrazed hill grasslands. Soil Biol. Biochem. 1997, 29, 1285–1294. [Google Scholar] [CrossRef]
  69. Kohler, F.; Hamelin, J.; Gillet, F.; Gobat, J.-M.; Buttler, A. Soil microbial community changes in wooded mountain pastures due to simulated effects of cattle grazing. Plant Soil 2005, 278, 327–340. [Google Scholar] [CrossRef]
  70. Kauffman, J.B.; Thorpe, A.S.; Brookshire, E.J. Livestock exclusion and belowground ecosystem responses in riparian meadows of eastern Oregon. Ecol. Appl. 2004, 14, 1671–1679. [Google Scholar] [CrossRef]
  71. Kobayashi, T.; Hori, Y.; Nomoto, N. Effects of trampling and vegetation removal on species diversity and micro-environment under different shade conditions. J. Veg. Sci. 1997, 8, 873–880. [Google Scholar] [CrossRef]
  72. Skraban, J.; Dzeroski, S.; Zenko, B.; Tusar, L.; Rupnik, M. Changes of poultry faecal microbiota associated with Clostridium difficile colonisation. Vet. Microbiol. 2013, 165, 416–424. [Google Scholar] [CrossRef] [PubMed]
  73. Stanley, D.; Hughes, R.J.; Moore, R.J. Microbiota of the chicken gastrointestinal tract: Influence on health, productivity and disease. Appl. Microbiol. Biotechnol. 2014, 98, 4301–4310. [Google Scholar] [CrossRef] [PubMed]
  74. Maciorowski, K.G.; Herrera, P.; Jones, F.T.; Pillai, S.D.; Ricke, S.C. Effects on poultry and livestock of feed contamination with bacteria and fungi. Anim. Feed Sci. Technol. 2007, 133, 109–136. [Google Scholar] [CrossRef]
Forests 10 00216 g001 550
Figure 1. Bacterial and fungal compositions at the phylum level in the moso bamboo leaves. (a) Bacterial phyla with an average relative abundance of greater than 0.1%; (b) Fungal phyla relative abundance. MBF, adjacent moso bamboo forest; BCF, moso bamboo-chicken farming agroforestry.
Figure 1. Bacterial and fungal compositions at the phylum level in the moso bamboo leaves. (a) Bacterial phyla with an average relative abundance of greater than 0.1%; (b) Fungal phyla relative abundance. MBF, adjacent moso bamboo forest; BCF, moso bamboo-chicken farming agroforestry.
Forests 10 00216 g001
Forests 10 00216 g002 550
Figure 2. Differences in the dominant phyla of the moso bamboo leaf-associated microbiome in the BCF and MBF samples. (a) Bacteria; (b) fungi.
Figure 2. Differences in the dominant phyla of the moso bamboo leaf-associated microbiome in the BCF and MBF samples. (a) Bacteria; (b) fungi.
Forests 10 00216 g002
Forests 10 00216 g003 550
Figure 3. Alpha diversity indices of bacterial and fungal taxa for the BCF and MBF samples from moso bamboo.
Figure 3. Alpha diversity indices of bacterial and fungal taxa for the BCF and MBF samples from moso bamboo.
Forests 10 00216 g003
Forests 10 00216 g004 550
Figure 4. Principal coordinates analysis based on the Bray–Curtis distance for the moso bamboo leaf-associated bacterial (a) and fungal (b) community structures in the MBF and moso bamboo-chicken farming agroforestry system samples.
Figure 4. Principal coordinates analysis based on the Bray–Curtis distance for the moso bamboo leaf-associated bacterial (a) and fungal (b) community structures in the MBF and moso bamboo-chicken farming agroforestry system samples.
Forests 10 00216 g004
Forests 10 00216 g005 550
Figure 5. Taxonomic to phenotypic mapping based on the metabolism of bacterial communities associated with the leaves of moso bamboo.
Figure 5. Taxonomic to phenotypic mapping based on the metabolism of bacterial communities associated with the leaves of moso bamboo.
Forests 10 00216 g005
Forests 10 00216 g006 550
Figure 6. Taxonomy-based functional profiling of fungal communities from the MBF and BCF samples. *↑, significantly increased in the BCF samples relative to the MBF samples; *↓, significantly decreased in the BCF samples relative to the MBF samples.
Figure 6. Taxonomy-based functional profiling of fungal communities from the MBF and BCF samples. *↑, significantly increased in the BCF samples relative to the MBF samples; *↓, significantly decreased in the BCF samples relative to the MBF samples.
Forests 10 00216 g006
Table
Table 1. Relative abundances of the dominant bacterial and fungal genera in moso bamboo leaves.
Table 1. Relative abundances of the dominant bacterial and fungal genera in moso bamboo leaves.
PhylumGenusMBFBCFp Value
BacteriaProteobacteriaMethylobacterium2.05% ± 1.46%13.40% ± 3.96%0.010
BacteroidetesHymenobacter1.84% ± 0.88%7.64% ± 2.14%0.012
ProteobacteriaSphingomonas3.57% ± 2.41%5.84% ± 2.20%0.297
[Thermi]Deinococcus0.00% ± 0.01%1.02% ± 0.42%0.052
ActinobacteriaKineococcus0.08% ± 0.05%0.88% ± 0.12%0.003
BacteroidetesSpirosoma0.02% ± 0.01%0.79% ± 0.23%0.027
ProteobacteriaBeijerinckia0.58% ± 0.46%0.11% ± 0.07%0.158
ActinobacteriaCurtobacterium0.11% ± 0.09%0.26% ± 0.15%0.203
ActinobacteriaFriedmanniella0.00% ± 0.00%0.33% ± 0.06%0.001
ActinobacteriaMicrobacterium0.22% ± 0.22%0.10% ± 0.04%0.446
ProteobacteriaRalstonia0.18% ± 0.20%0.14% ± 0.11%0.790
ProteobacteriaBurkholderia0.25% ± 0.20%0.03% ± 0.01%0.197
ProteobacteriaBdellovibrio0.08% ± 0.05%0.17% ± 0.03%0.039
AcidobacteriaTerriglobus0.20% ± 0.07%0.04% ± 0.02%0.019
ActinobacteriaArthrobacter0.01% ± 0.01%0.22% ± 0.08%0.012
FungiAscomycotaAlatosessilispora0.02% ± 0.02%25.30% ± 2.14%0.002
AscomycotaStrelitziana0.03% ± 0.02%24.17% ± 0.84%0.000
AscomycotaShiraia3.11% ± 0.69%0.40% ± 0.10%0.003
AscomycotaCladosporium0.11% ± 0.05%1.91% ± 0.35%0.001
AscomycotaCamptophora0.05% ± 0.01%1.46% ± 0.13%0.000
AscomycotaGeastrumia0.76% ± 0.30%0.02% ± 0.02%0.013
AscomycotaMycosphaerella0.54% ± 0.04%0.18% ± 0.03%0.000
AscomycotaRamularia0.01% ± 0.01%0.70% ± 0.15%0.001
AscomycotaBacidina0.69% ± 0.18%0.01% ± 0.01%0.003
AscomycotaTrichomerium0.00% ± 0.00%0.53% ± 0.05%0.003
AscomycotaHortaea0.40% ± 0.09%0.00% ± 0.00%0.015
BasidiomycotaHygrocybe0.00% ± 0.00%0.29% ± 0.19%0.118
AscomycotaArthrinium0.07% ± 0.03%0.20% ± 0.07%0.043
AscomycotaDidymella0.06% ± 0.01%0.14% ± 0.02%0.006

Share and Cite

MDPI and ACS Style

Zhang, X.; Zhong, Z.; Gai, X.; Ying, J.; Li, W.; Du, X.; Bian, F.; Yang, C. Leaf-Associated Shifts in Bacterial and Fungal Communities in Response to Chicken Rearing Under Moso Bamboo Forests in Subtropical China. Forests 2019, 10, 216. https://doi.org/10.3390/f10030216

AMA Style

Zhang X, Zhong Z, Gai X, Ying J, Li W, Du X, Bian F, Yang C. Leaf-Associated Shifts in Bacterial and Fungal Communities in Response to Chicken Rearing Under Moso Bamboo Forests in Subtropical China. Forests. 2019; 10(3):216. https://doi.org/10.3390/f10030216

Chicago/Turabian Style

Zhang, Xiaoping, Zheke Zhong, Xu Gai, Jiafu Ying, Weifen Li, Xuhua Du, Fangyuan Bian, and Chuanbao Yang. 2019. "Leaf-Associated Shifts in Bacterial and Fungal Communities in Response to Chicken Rearing Under Moso Bamboo Forests in Subtropical China" Forests 10, no. 3: 216. https://doi.org/10.3390/f10030216

APA Style

Zhang, X., Zhong, Z., Gai, X., Ying, J., Li, W., Du, X., Bian, F., & Yang, C. (2019). Leaf-Associated Shifts in Bacterial and Fungal Communities in Response to Chicken Rearing Under Moso Bamboo Forests in Subtropical China. Forests, 10(3), 216. https://doi.org/10.3390/f10030216

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop