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The effects of different vegetation restoration patterns on soil bacterial diversity for sandy land in Hulunbeier
Acta Ecologica Sinica 33 (2013) 211–216
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The effects of different vegetation restoration patterns on soil bacterial diversity for sandy land in Hulunbeier Haifang Zhang a,b, Xiaolong Song a, Cailing Wang d, Hongmei Liu a, Jingni Zhang a, Yujie Li c, Gang Li a, Dianlin Yang a,⇑, Shulan Zhao b a
Agro-Environmental Protection Institute, Ministry of Agriculture, Tianjin 300191, China College of Life Sciences, Tianjin Normal University, Tianjin 300387, China College of Horticulture, Shenyang Agricultural University, Shenyang 110866, China d Hailar Agricultural Technology Promotion Center, Inner Mongolia 021008, China b c
a r t i c l e
i n f o
Article history: Received 13 March 2012 Revised 25 October 2012 Accepted 20 January 2013
Keywords: Hulunbeier Sandy land Vegetation restoration Soil microbe Genetic diversity PCR–DGGE
a b s t r a c t Grassland desertification seriously threatens sustainable economic and social development. Much attention has been paid to the control of grassland desertification, and even to the restoration and reconstruction of the grassland. Vegetation restoration is considered to be a very effective solution. Soil sustains an immense diversity of microbes, and the characteristics of soil microbial communities are sensitive indicators of soil. It is important to understand the relationship between vegetation and soil microbial diversity during the restoration process. Soil microbial, which is the main index to evaluate soil quality, plays a significant role in ecosystem and soil microbial diversity is the important one of global diversity. Exploring the effects of different vegetation patterns on soil microbial diversity can provide scientific bases and technical support for systemic and impersonal assessment of the best vegetation restoration patterns, as well as the vegetation restoration and reconstruction of Hulunbeier sandy land. Based on PCR–DGGE technology, a case study was carried out to investigate the effects of five different vegetation restoration patterns on soil microbial functional diversity after 4 years in sandy land in Hulunbeier, China. The five vegetation restoration patterns included mono-cultivar planting of Agropyron cristatum (UA), mono-cultivar planting of Hedysarum fruticosum (UH), mono-cultivar planting of Caragana korshinskii (UC), mixedcultivar planting of Agropyron cristatum and Hedysarum fruticosum (AC) and mixed-cultivar planting of Agropyron cristatum, Hedysarum fruticosum, Caragana korshinskii and Elymus nutans (ACHE). Completely degraded sandy land was used as control. The results indicated that the vegetation restoration increased the genetic diversity of soil bacterial community obviously, and the structure of soil bacterial community was changed. The results of phylogenetic analysis suggested that the bacterial community in Hulunbeier sandy land mainly attributed to Proteobacteria, Bacteroidetes, Firmicutes, Actinobacteria, and Acidobacteria. The dominant groups were Proteobacteria and Bacteroidetes. The effects of different vegetation type on soil bacterial community structures were different. Ó 2013 Ecological Society of China. Published by Elsevier B.V. All rights reserved.
1. Introduction The Hulunbeier Sandy Land, one of four major sandy lands in China with a total area of 1.3051 million hm2, consists of three irregular shaped sandy ribbons running through the hinterland of the Hulunbeier Grassland [1]. The Hulunbeier sandy land, which was a result of long-term vegetation deterioration due to natural and human disturbance, makes a serious threat to the sustainable development of the economy and society in Hulunbeier city [2]. Scientific vegetation restoration and reconstruction is a key ⇑ Corresponding author.
method of sandy land treatment [3]. Sandy lands have low level of soil nutrition and a simple structure of microbial communities. It bears significant theoretical and practical importance to study the vegetation restoration of Hulunbeier sandy land. The soil microbial diversity is essential to keep the soil ecosystem functioning [4–6]. The soil microbes, by being a part of nutrient cycling, decomposition of organic matter and energy flow, are of great significance to ecological functions [7]. To protect the soil microbial diversity contributes greatly to the sustainability of soil properties and reduction of risks of soil and environmental degradation [8,9]. The soil bacteria, an important component of soil ecosystem, plays a key role in biogeochemical cycle such as soil organic matter decomposition, nutrition release, and energy flow
E-mail address: [email protected] (D. Yang). 1872-2032/$ - see front matter Ó 2013 Ecological Society of China. Published by Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.chnaes.2013.05.008
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[10]. Now, the academic arena mainly adopts the PCR–DGGE technique in researches of genetic diversity of soil bacteria for analyzing soil bacterial community structure in cultivated lands, grasslands, and highlands. The 16S rDNA-based PCR–DGGE technique, advocated by Muyzer and others in 1993 [11], is widely used in analyzing bacterial communities in various environmental conditions, for example, soil and sediment [12], marine plankton [13,14] and limnoplankton [15,16], lithophytic biomembrane [17–19]. DGGE can directly analyze the soil microbial community structure without cultivating them; hence it is more and more used in researches of microbial community structure and functions. Analyzing how different vegetation restoration models will influence soil microbial community in Hulunbeier sandy land, and unveiling how the soil microbes will react to the vegetation restoration, will significantly contribute to the choice of appropriate vegetation to restore and rebuild the sandy land ecosystem [20]. At present, most researches relevant to the Hulunbeier Grassland using the DGGE technique are mainly about the variances of soil bacterial community with different grazing intensity and different level of soil deterioration. There are many researches on vegetation restoration of sandy lands, however, most of them are about designing vegetation restoration model, variance pattern of aboveground vegetation community structure and soil physical and chemical properties after vegetation restoration [21,22]. Researches about Hulunbeier sandy land mostly concentrate on finding the root causes and control measures [23,24]. There are few research subjects about the microbial community variance under vegetation restoration. This paper analyzed the variances of genetic diversity of soil microbial community under different models of vegetation restoration by adopting the PCR–DGGE technique, verified the community restoration mechanism and decided the best vegetation restoration pattern, so as to provide theoretical and technical support for the vegetation restoration and reconstruction in Hulunbeier sandy lands. 2. Materials and methods 2.1. Study area
2.2.2. Vegetation survey method The field survey of the plots was conducted. The longitude and latitude were assessed via the GPS device, the vegetation coverage via eye inspection, and the natural height of grass via tape measure. The vegetation quadrats survey method: in each plot under different vegetation restoration models, 10 quadrats (1 1 m) were set, in order to count the coverage, height, number, and variety of plants. 2.2.3. Soil sampling On July 30, 2010, soil samples were collected according to an Sshaped curve at the depth from 0 to 20 cm. Twenty spots were chosen in each plot. Soil samples taken from such spots were mixed together, and removed of all rocks and debris. Using the quartering method, 1 kg of soil sample was taken and placed in aseptic bags, and brought back to the lab in ice box. The sample was divided into two halves, one half air-dried as a backup, and the other half kept in 20 °C ice boxes. 2.3. Total soil DNA extraction The total DNA extraction of soil sample was conducted by using the EZ-10 Spin Soil DNA Extraction kit, which is produced by BBI. Referenced the instruction for specific operation details. 2.4. PCR-amplification of soil 16S rDNA 341f-GC (50 -CCTACGGGAGGCAGCAG-30 ) and 534r (50 -ATTACCGCGGCTGCTGG-30 ), universal primers of bacterium 16S rDNA, were used to conduct PCR-amplification of the soil genomic DNA. The GC clamp in 50 end was CGCCCGCCGCGCGCGGCGGGCGGGGCG GGGGCACGGGGGG [25,26]. The 50 ll PCR reaction system contains: 25 ll of Premix Ex Taq, 1.0 ll of both primers, 2.0 ll of 10-times diluted soil DNA template, and filled to 50 ll with 1-class sterile water. The PCR reaction conditions are: 95 °C 7 min, 94 °C 1 min, 61 °C 1 min (each cycle the temperature reduced by 0.5 °C), 72 °C 1 min, all together 10 cycles; 94 °C 1 min, 56 °C 1 min, 72 °C 1 min, all together 25 cycles, and 72 °C 7 min at the end. PCR product is examined in 1.5% AGE.
The study area, 49°120 N, 118°540 E, is located at the heart of the Hulunbeier sandy area in the Chen Barag Banner, Hulunbeier City, Inner Mongolia. It is a typical representative of the Hulunbeier sandy land, with a temperate semi-arid continental climate. The chosen area has a height above sea-level of 618.0 m, an annual temperature of 2.6 °C, annual rainfall of 307.7 mm (70% concentrates in summer and fall), annual evaporation of 1371.1 mm, annual average wind speed of 3.5 m/s, and 24.8 days with gale force wind or above a year. The soil is sandy chestnut soil, and the natural vegetation types surrounding the sandy area are Stipa grandis typical steppe and Leymus chinensis typical steppe.
DGGE is an improvement on the basis of Muzyer’s method [27]. Bio-Rad’s D-Code Universal Mutation Detection System is used to analyze PCR product. 8% Polyacrylamide gel and 40–60% denaturing gradient (100% denaturant concentration being 7 mol-1 urea, and 40% deionized formamide). 30 ll of PCR products was added to each hole. After 16 h of electrophoresis at 60 °C and 100 V, dyed the gel for 30 min with SYBR Green (1:10,000), then observed and snapshoot them under the D-Code system.
2.2. Experimental design, vegetation survey and soil sampling
2.6. Sequence determination and phylogenetic analysis
2.2.1. Experimental design The plots are completely degraded before the vegetation restoration. The experiment started in July, 2006. There were five vegetation restoration patterns, namely Unicast Agropyron cristatum, Unicast Hedysarum fruticosum, Unicast Caragana korshinskii, Caragana korshinskii + Agropyron cristatum, Caragana korshinskii + Agropyron cristatum + Hedysarum fruticosum + Elymus nutans, take the completely degraded soil as control. The plot each covered 1 hm2, and was repeated three times. There were 18 plots in total and all distributed randomly. Table 1 shows the five vegetation restoration patterns.
Cut off the main DGGE bands. Placed the bands in 1.5 ml centrifuge tubes, add 500 ll sterile water to each tube, and keep them overnight in 4 °C fridge. Take 5 ll as a template to be amplified with primers 341f (without GC clamps) and 534r. The products were connected by using pMD19-T Vector by TaKaRa. Sequence determination was conducted by Sangon Bitotech (Shanghai). The DNA sequence was compared with the existing sequences in the database of NCBI (http://www.ncbi.nlm.nih.gov/) by using BLAST. The DGGE fingerprint was analyzed in Quality One. The phylogenetic tree was processed by ClustalX1.83 and Mega4.1.
2.5. DGGE examination
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H. Zhang et al. / Acta Ecologica Sinica 33 (2013) 211–216 Table 1 Five vegetation restoration patterns. Planting patterns
Sowing rate 3
UA UH UC AC ACHE
3.75 10 4.5 103 5.25 103 5.25 103 5.25 103
Sowing depth
Sowing patterns
Plot settings
3–4 3–4 3–4 3–4 3–4
in in in in in
50 200 50 200 50 200 50 200 50 200
drill drill drill drill drill
Note: UA: Unicast Agropyron cristatum; UH: Unicast Hedysarum fruticosum; UC: Unicast Caragana korshinskii; AC: Agropyron cristatum + Caragana korshinskii; ACHE: Agropyron cristatum + Caragana korshinskii + Hedysarum fruticosum + Elymus nutans.
3. Results and analysis
CK
UA
UH
AC ACHE
UC
3.1. Vegetation community features under different vegetation restoration models For information concerning basic conditions of all plots, please see Table 2. According to the survey of plant quadrats, vegetation restoration using different types of plants had significant effects. In the sample plots, besides Agropyron cristatum, Caragana korshinskii, Hedysarum fruticosum and Elymus nutans, plants that were sown, other species existed too, for example, Artemisia scoparia, Stipa grandis, Cleistogenes squarrosa, Serratula centauroides, Artemisia halodendron, Melissitus ruthenicus, Artemisia frigida, Artemisia sieversiana, Stizolobium capitatum, Leymus chinensis, Achnatherum sibiricum, Artemisia oxycephala, Carex tristachya, Setaria viridis, Corispermum hyssopifolium, Poa pratensis, Astragalus adsurgens, Torilis scabra, Carex duriuscula, Astragalus galactites, Cynanchum thesioides, Astragalus melilotoides, Astragalus adsurgens and Bupleurum densiflorum. The survey showed that after implementing different models of vegetation restoration, new plant species come into being besides the sown ones. Number of plant species increased and the vegetation coverage went as high as 69% at its peak. The unicast Agropyron cristatum had the highest level of total coverage, natural height and average above-ground biomass, which were respectively 69%, 98 cm and 260 g. The mixed-sowing of Agropyron cristatum and Caragana korshinskii had the most plant species reached 15. These proved the effective restoration of vegetation and that the vegetation restoration was benefit to the ecologic recovering of Hulunbeier sandy land. 3.2. DGGE profile analysis of soil 16S rDNA By comparing DGGE profiles under different vegetation restoration models (Fig. 1, 3-time repeat, the other two not shown in the same gel), it can be inferred that the electrophoretic bands of restored areas outnumbers the complete degraded sandy lands significantly, the bands were also brighter. It indicated that the soil microbial amount and species both increased after vegetation restoration. Different soil samples shared the same band, which showed that the sampled soil may share some bacteria in common. However, the difference of brightness of shared bands indicated
B7
B1 B2 B3
B8 B5 B4
B11 B12 B13
B14
B6 B9 B10
Fig. 1. PCR–DGGE profiles of soil Bacteria under different vegetation restoration.
significant change of soil bacterial community structure. The unicast Agropyron cristatum has the brightest bands, which meant the largest number of soil bacteria. These proved that vegetation restoration improved the soil bacteria genetic diversity, and unicast Agropyron cristatum can more conducive to improve the soil bacterial community structure. By using the clustering analysis for the DGGE profiles (Fig. 2), the soil bacterial communities shared the same pattern in the models of unicast Agropyron cristatum, unicast Caragana korshinskii, Agropyron cristatum + Caragana korshinskii, and mixed-cast of four kinds of plants. The similarity factor is 0.74 between unicast
Table 2 The basic situation of the plots. Planting patterns
Total coverage (%)
Natural height (cm)
Plant species
Average aboveground biomass (g)
UA UH UC AC ACHE
43 69 41 45 60
65 98 49 64 78
9 11 11 15 12
90 260 116 86 151
Note: UA: Unicast Agropyron cristatum; UC: Unicast Caragana korshinskii, AC: Agropyron cristatum + Caragana korshinskii; ACHE: Agropyron cristatum + Caragana korshinskii + Hedysarum fruticosum + Elymus nutans.
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3.3. Phylogenetic analysis of soil bacterial communities
Fig. 2. Clustering analysis of DGGE profiles for soil bacterial community. (Note: 1: CK; 2: Unicast Agropyron cristatum; 3: unicast Hedysarum fruticosum; 4: unicast Caragana korshinskii; 5: Agropyron cristatum + Caragana korshinskii; 6: Caragana korshinskii + Agropyron cristatum + Hedysarum fruticosum + Elymus nutans).
Agropyron cristatum and unicast Caragana korshinskii, and 0.77 between Agropyron cristatum + Caragana korshinskii and Caragana korshinskii + Agropyron cristatum + Hedysarum fruticosum + Elymus nutans. The bacterial community structure of the unicast Agropyron cristatum had a low similarity to the others.
Choose the 14 main bands from the DGGE profile for rubber tapping, cloning and sequencing. Took the BLAST analysis in the database of NCBI, and formulated the phylogenetic tree in MEGA 4.0 by using the neighbor-joining method (Fig. 3). The result showed that under different models of vegetation restoration the major bacterial communities of Hulunbeier sandy land conclude Proteobacteria, Bacteroidetes, Bacilli of Firmicutes, Actinobacteria and Acidobacteria. The Proteobacteria and Bacteroidetes were the dominant groups, with the Proteobacteria accounting for about 43%.
4. Discussions The soil microbial communities are subject to the influences of multiple factors, soil texture, properties, temperature and moisture, pH, minerals, organic matter, root secretions, root casts, the quality of plant residues and litter time [28,29]. Vegetation has a great impact on the composition and functions of soil microbes [30].
Fig. 3. The phylogenetic tree of soil 16S rDNA (Neighbor-joining).
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Long-term coevolution leads to the choice of decomposers that quicken the decomposition of litters by plants, hence the synergy exists between plants and decomposers [31], as well as the positive and negative feedback effects which one drives the other [32]. Researchers showed that plant species and community structure can significantly change the soil microbe community structure and diversity in the rhizosphere of plants [33]. Vegetation and season exert obvious influence over the genetic diversity of soil bacteria and fungi [34,35]. There were researches showed that the lower the vegetation diversity, the lower the soil microbes diversity. But Hedlund found that vegetation diversity did not affect soil decomposer community which includes bacteria and saprophytic fungi [36]. By analyzing soil bacterial community structure in different vegetation patterns, it is showed that vegetation restoration significantly increased the genetic diversity of soil bacterial communities, and changed the community structure, in comparison to the complete degraded sandy land. The unicast Hedysarum fruticosum had the largest number of bacterial communities. The cause was that the rhizosphere released large amount of carbon after the vegetation restoration, meantime the litters increased. Along with the decomposition of litters which drove up organic matter content in soil, the soil microhabitats changed with more nutrition, thereby affecting the distribution and diversity of soil microbial communities. The plant coverage, natural height and above-ground biomass were the highest when the Hedysarum fruticosum were sown alone, therefore more litters fell from plants, and more nutrition were added to the soil, hence the most significant change of soil bacterial community structure. However the sandy land, in comparison, had low accumulation of nutrition in soil due to lack of plants, so both the microbe amount and diversity were low. Clustering analysis of DGGE profiles indicated that soil bacterial community structures under different vegetation restoration patterns were different. The unicast Hedysarum fruticosum and unicast Caragana korshinskii resemble each other, and the Agropyron cristatum + Caragana korshinskii resembles Caragana korshinskii + Agropyron cristatum + Hedysarum fruticosum + Elymus nutans. It was mainly because that plant species had influences on the selection of rhizosphere microbes [37,38]. And different plants had different influences on soil microbe communities [39]. Diversified aboveground parts could lead to larger amount and more kinds of litters; and the heterogeneity of resources could lead to diversity of decomposers [40]. Soil organic matter was a key factor to the composition and diversity of microbe community [41]. The differences of soil microbial community structure and activity among different types of steppe were mainly related to the changes of the amount and quality of soil carbon resources [42]. Vegetation changed the soil microbial communities by influencing the soil environment. Different plants provided different carbon resources for soil, resulting in the different soil microenvironment for microbes, and thus lead to different soil microbial community structure. The soil bacterial communities under different vegetation patterns mainly concluded a, band c groups of Proteobacteria, Bacteroidetes, Bacilli of Firmicutes, Actinobacteria and Acidobacteria. The Proteobacteria and Bacteroidetes were the dominant groups. This was consistent with previous researches. In the researches by Wu Yongsheng and others on desert steppe soil bacterial community structure, the result was that with the degradation of steppe soil, the soil bacterial community structure significantly changed. The main bacterial groups in desert steppe soil in Inner Mongolia are Bacteroidetes, Acidobacteria, canddgroups of Proteobacteria, and Firmicutes. The Bacteroidetes, accounting for about 47%, was the dominant group. Zhou Xiaoqi and others’ researches showed that there were five sub-branches of soil bacteria in the typical grassland of Inner Mongolia: Actinobacteria, a, band c groups of Proteobacteria, Bacteroidetes, Gemmatimonadetes and Acidobacteria.
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5. Conclusions The following conclusions were reached after analyzing the soil bacterial community structure under different vegetation restoration patterns: (1) Vegetation restoration significantly increased the amount of soil bacterial communities, and improved the genetic diversity of the soil bacterial communities, in comparison to the completely degraded sandy lands. (2) Soil bacterial groups under different vegetation restoration patterns in Hulunbeier sandy land include Proteobacteria, Bacteroidetes, Bacilli of Firmicutes, Actinobacteria and Acidobacteria, among which the Proteobacteria and Bacteroidetes are the dominant groups. (3) The soil bacterial community structures were different under different vegetation restoration patterns. The unicast Hedysarum fruticosum could best improve the soil bacterial community structures.
Acknowledgement This study was supported by National Natural Science Foundation of China (31170435 and 31000242).
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Acta Ecologica Sinica journal homepage: www.elsevier.com/locate/chnaes
The effects of different vegetation restoration patterns on soil bacterial diversity for sandy land in Hulunbeier Haifang Zhang a,b, Xiaolong Song a, Cailing Wang d, Hongmei Liu a, Jingni Zhang a, Yujie Li c, Gang Li a, Dianlin Yang a,⇑, Shulan Zhao b a
Agro-Environmental Protection Institute, Ministry of Agriculture, Tianjin 300191, China College of Life Sciences, Tianjin Normal University, Tianjin 300387, China College of Horticulture, Shenyang Agricultural University, Shenyang 110866, China d Hailar Agricultural Technology Promotion Center, Inner Mongolia 021008, China b c
a r t i c l e
i n f o
Article history: Received 13 March 2012 Revised 25 October 2012 Accepted 20 January 2013
Keywords: Hulunbeier Sandy land Vegetation restoration Soil microbe Genetic diversity PCR–DGGE
a b s t r a c t Grassland desertification seriously threatens sustainable economic and social development. Much attention has been paid to the control of grassland desertification, and even to the restoration and reconstruction of the grassland. Vegetation restoration is considered to be a very effective solution. Soil sustains an immense diversity of microbes, and the characteristics of soil microbial communities are sensitive indicators of soil. It is important to understand the relationship between vegetation and soil microbial diversity during the restoration process. Soil microbial, which is the main index to evaluate soil quality, plays a significant role in ecosystem and soil microbial diversity is the important one of global diversity. Exploring the effects of different vegetation patterns on soil microbial diversity can provide scientific bases and technical support for systemic and impersonal assessment of the best vegetation restoration patterns, as well as the vegetation restoration and reconstruction of Hulunbeier sandy land. Based on PCR–DGGE technology, a case study was carried out to investigate the effects of five different vegetation restoration patterns on soil microbial functional diversity after 4 years in sandy land in Hulunbeier, China. The five vegetation restoration patterns included mono-cultivar planting of Agropyron cristatum (UA), mono-cultivar planting of Hedysarum fruticosum (UH), mono-cultivar planting of Caragana korshinskii (UC), mixedcultivar planting of Agropyron cristatum and Hedysarum fruticosum (AC) and mixed-cultivar planting of Agropyron cristatum, Hedysarum fruticosum, Caragana korshinskii and Elymus nutans (ACHE). Completely degraded sandy land was used as control. The results indicated that the vegetation restoration increased the genetic diversity of soil bacterial community obviously, and the structure of soil bacterial community was changed. The results of phylogenetic analysis suggested that the bacterial community in Hulunbeier sandy land mainly attributed to Proteobacteria, Bacteroidetes, Firmicutes, Actinobacteria, and Acidobacteria. The dominant groups were Proteobacteria and Bacteroidetes. The effects of different vegetation type on soil bacterial community structures were different. Ó 2013 Ecological Society of China. Published by Elsevier B.V. All rights reserved.
1. Introduction The Hulunbeier Sandy Land, one of four major sandy lands in China with a total area of 1.3051 million hm2, consists of three irregular shaped sandy ribbons running through the hinterland of the Hulunbeier Grassland [1]. The Hulunbeier sandy land, which was a result of long-term vegetation deterioration due to natural and human disturbance, makes a serious threat to the sustainable development of the economy and society in Hulunbeier city [2]. Scientific vegetation restoration and reconstruction is a key ⇑ Corresponding author.
method of sandy land treatment [3]. Sandy lands have low level of soil nutrition and a simple structure of microbial communities. It bears significant theoretical and practical importance to study the vegetation restoration of Hulunbeier sandy land. The soil microbial diversity is essential to keep the soil ecosystem functioning [4–6]. The soil microbes, by being a part of nutrient cycling, decomposition of organic matter and energy flow, are of great significance to ecological functions [7]. To protect the soil microbial diversity contributes greatly to the sustainability of soil properties and reduction of risks of soil and environmental degradation [8,9]. The soil bacteria, an important component of soil ecosystem, plays a key role in biogeochemical cycle such as soil organic matter decomposition, nutrition release, and energy flow
E-mail address: [email protected] (D. Yang). 1872-2032/$ - see front matter Ó 2013 Ecological Society of China. Published by Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.chnaes.2013.05.008
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[10]. Now, the academic arena mainly adopts the PCR–DGGE technique in researches of genetic diversity of soil bacteria for analyzing soil bacterial community structure in cultivated lands, grasslands, and highlands. The 16S rDNA-based PCR–DGGE technique, advocated by Muyzer and others in 1993 [11], is widely used in analyzing bacterial communities in various environmental conditions, for example, soil and sediment [12], marine plankton [13,14] and limnoplankton [15,16], lithophytic biomembrane [17–19]. DGGE can directly analyze the soil microbial community structure without cultivating them; hence it is more and more used in researches of microbial community structure and functions. Analyzing how different vegetation restoration models will influence soil microbial community in Hulunbeier sandy land, and unveiling how the soil microbes will react to the vegetation restoration, will significantly contribute to the choice of appropriate vegetation to restore and rebuild the sandy land ecosystem [20]. At present, most researches relevant to the Hulunbeier Grassland using the DGGE technique are mainly about the variances of soil bacterial community with different grazing intensity and different level of soil deterioration. There are many researches on vegetation restoration of sandy lands, however, most of them are about designing vegetation restoration model, variance pattern of aboveground vegetation community structure and soil physical and chemical properties after vegetation restoration [21,22]. Researches about Hulunbeier sandy land mostly concentrate on finding the root causes and control measures [23,24]. There are few research subjects about the microbial community variance under vegetation restoration. This paper analyzed the variances of genetic diversity of soil microbial community under different models of vegetation restoration by adopting the PCR–DGGE technique, verified the community restoration mechanism and decided the best vegetation restoration pattern, so as to provide theoretical and technical support for the vegetation restoration and reconstruction in Hulunbeier sandy lands. 2. Materials and methods 2.1. Study area
2.2.2. Vegetation survey method The field survey of the plots was conducted. The longitude and latitude were assessed via the GPS device, the vegetation coverage via eye inspection, and the natural height of grass via tape measure. The vegetation quadrats survey method: in each plot under different vegetation restoration models, 10 quadrats (1 1 m) were set, in order to count the coverage, height, number, and variety of plants. 2.2.3. Soil sampling On July 30, 2010, soil samples were collected according to an Sshaped curve at the depth from 0 to 20 cm. Twenty spots were chosen in each plot. Soil samples taken from such spots were mixed together, and removed of all rocks and debris. Using the quartering method, 1 kg of soil sample was taken and placed in aseptic bags, and brought back to the lab in ice box. The sample was divided into two halves, one half air-dried as a backup, and the other half kept in 20 °C ice boxes. 2.3. Total soil DNA extraction The total DNA extraction of soil sample was conducted by using the EZ-10 Spin Soil DNA Extraction kit, which is produced by BBI. Referenced the instruction for specific operation details. 2.4. PCR-amplification of soil 16S rDNA 341f-GC (50 -CCTACGGGAGGCAGCAG-30 ) and 534r (50 -ATTACCGCGGCTGCTGG-30 ), universal primers of bacterium 16S rDNA, were used to conduct PCR-amplification of the soil genomic DNA. The GC clamp in 50 end was CGCCCGCCGCGCGCGGCGGGCGGGGCG GGGGCACGGGGGG [25,26]. The 50 ll PCR reaction system contains: 25 ll of Premix Ex Taq, 1.0 ll of both primers, 2.0 ll of 10-times diluted soil DNA template, and filled to 50 ll with 1-class sterile water. The PCR reaction conditions are: 95 °C 7 min, 94 °C 1 min, 61 °C 1 min (each cycle the temperature reduced by 0.5 °C), 72 °C 1 min, all together 10 cycles; 94 °C 1 min, 56 °C 1 min, 72 °C 1 min, all together 25 cycles, and 72 °C 7 min at the end. PCR product is examined in 1.5% AGE.
The study area, 49°120 N, 118°540 E, is located at the heart of the Hulunbeier sandy area in the Chen Barag Banner, Hulunbeier City, Inner Mongolia. It is a typical representative of the Hulunbeier sandy land, with a temperate semi-arid continental climate. The chosen area has a height above sea-level of 618.0 m, an annual temperature of 2.6 °C, annual rainfall of 307.7 mm (70% concentrates in summer and fall), annual evaporation of 1371.1 mm, annual average wind speed of 3.5 m/s, and 24.8 days with gale force wind or above a year. The soil is sandy chestnut soil, and the natural vegetation types surrounding the sandy area are Stipa grandis typical steppe and Leymus chinensis typical steppe.
DGGE is an improvement on the basis of Muzyer’s method [27]. Bio-Rad’s D-Code Universal Mutation Detection System is used to analyze PCR product. 8% Polyacrylamide gel and 40–60% denaturing gradient (100% denaturant concentration being 7 mol-1 urea, and 40% deionized formamide). 30 ll of PCR products was added to each hole. After 16 h of electrophoresis at 60 °C and 100 V, dyed the gel for 30 min with SYBR Green (1:10,000), then observed and snapshoot them under the D-Code system.
2.2. Experimental design, vegetation survey and soil sampling
2.6. Sequence determination and phylogenetic analysis
2.2.1. Experimental design The plots are completely degraded before the vegetation restoration. The experiment started in July, 2006. There were five vegetation restoration patterns, namely Unicast Agropyron cristatum, Unicast Hedysarum fruticosum, Unicast Caragana korshinskii, Caragana korshinskii + Agropyron cristatum, Caragana korshinskii + Agropyron cristatum + Hedysarum fruticosum + Elymus nutans, take the completely degraded soil as control. The plot each covered 1 hm2, and was repeated three times. There were 18 plots in total and all distributed randomly. Table 1 shows the five vegetation restoration patterns.
Cut off the main DGGE bands. Placed the bands in 1.5 ml centrifuge tubes, add 500 ll sterile water to each tube, and keep them overnight in 4 °C fridge. Take 5 ll as a template to be amplified with primers 341f (without GC clamps) and 534r. The products were connected by using pMD19-T Vector by TaKaRa. Sequence determination was conducted by Sangon Bitotech (Shanghai). The DNA sequence was compared with the existing sequences in the database of NCBI (http://www.ncbi.nlm.nih.gov/) by using BLAST. The DGGE fingerprint was analyzed in Quality One. The phylogenetic tree was processed by ClustalX1.83 and Mega4.1.
2.5. DGGE examination
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H. Zhang et al. / Acta Ecologica Sinica 33 (2013) 211–216 Table 1 Five vegetation restoration patterns. Planting patterns
Sowing rate 3
UA UH UC AC ACHE
3.75 10 4.5 103 5.25 103 5.25 103 5.25 103
Sowing depth
Sowing patterns
Plot settings
3–4 3–4 3–4 3–4 3–4
in in in in in
50 200 50 200 50 200 50 200 50 200
drill drill drill drill drill
Note: UA: Unicast Agropyron cristatum; UH: Unicast Hedysarum fruticosum; UC: Unicast Caragana korshinskii; AC: Agropyron cristatum + Caragana korshinskii; ACHE: Agropyron cristatum + Caragana korshinskii + Hedysarum fruticosum + Elymus nutans.
3. Results and analysis
CK
UA
UH
AC ACHE
UC
3.1. Vegetation community features under different vegetation restoration models For information concerning basic conditions of all plots, please see Table 2. According to the survey of plant quadrats, vegetation restoration using different types of plants had significant effects. In the sample plots, besides Agropyron cristatum, Caragana korshinskii, Hedysarum fruticosum and Elymus nutans, plants that were sown, other species existed too, for example, Artemisia scoparia, Stipa grandis, Cleistogenes squarrosa, Serratula centauroides, Artemisia halodendron, Melissitus ruthenicus, Artemisia frigida, Artemisia sieversiana, Stizolobium capitatum, Leymus chinensis, Achnatherum sibiricum, Artemisia oxycephala, Carex tristachya, Setaria viridis, Corispermum hyssopifolium, Poa pratensis, Astragalus adsurgens, Torilis scabra, Carex duriuscula, Astragalus galactites, Cynanchum thesioides, Astragalus melilotoides, Astragalus adsurgens and Bupleurum densiflorum. The survey showed that after implementing different models of vegetation restoration, new plant species come into being besides the sown ones. Number of plant species increased and the vegetation coverage went as high as 69% at its peak. The unicast Agropyron cristatum had the highest level of total coverage, natural height and average above-ground biomass, which were respectively 69%, 98 cm and 260 g. The mixed-sowing of Agropyron cristatum and Caragana korshinskii had the most plant species reached 15. These proved the effective restoration of vegetation and that the vegetation restoration was benefit to the ecologic recovering of Hulunbeier sandy land. 3.2. DGGE profile analysis of soil 16S rDNA By comparing DGGE profiles under different vegetation restoration models (Fig. 1, 3-time repeat, the other two not shown in the same gel), it can be inferred that the electrophoretic bands of restored areas outnumbers the complete degraded sandy lands significantly, the bands were also brighter. It indicated that the soil microbial amount and species both increased after vegetation restoration. Different soil samples shared the same band, which showed that the sampled soil may share some bacteria in common. However, the difference of brightness of shared bands indicated
B7
B1 B2 B3
B8 B5 B4
B11 B12 B13
B14
B6 B9 B10
Fig. 1. PCR–DGGE profiles of soil Bacteria under different vegetation restoration.
significant change of soil bacterial community structure. The unicast Agropyron cristatum has the brightest bands, which meant the largest number of soil bacteria. These proved that vegetation restoration improved the soil bacteria genetic diversity, and unicast Agropyron cristatum can more conducive to improve the soil bacterial community structure. By using the clustering analysis for the DGGE profiles (Fig. 2), the soil bacterial communities shared the same pattern in the models of unicast Agropyron cristatum, unicast Caragana korshinskii, Agropyron cristatum + Caragana korshinskii, and mixed-cast of four kinds of plants. The similarity factor is 0.74 between unicast
Table 2 The basic situation of the plots. Planting patterns
Total coverage (%)
Natural height (cm)
Plant species
Average aboveground biomass (g)
UA UH UC AC ACHE
43 69 41 45 60
65 98 49 64 78
9 11 11 15 12
90 260 116 86 151
Note: UA: Unicast Agropyron cristatum; UC: Unicast Caragana korshinskii, AC: Agropyron cristatum + Caragana korshinskii; ACHE: Agropyron cristatum + Caragana korshinskii + Hedysarum fruticosum + Elymus nutans.
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3.3. Phylogenetic analysis of soil bacterial communities
Fig. 2. Clustering analysis of DGGE profiles for soil bacterial community. (Note: 1: CK; 2: Unicast Agropyron cristatum; 3: unicast Hedysarum fruticosum; 4: unicast Caragana korshinskii; 5: Agropyron cristatum + Caragana korshinskii; 6: Caragana korshinskii + Agropyron cristatum + Hedysarum fruticosum + Elymus nutans).
Agropyron cristatum and unicast Caragana korshinskii, and 0.77 between Agropyron cristatum + Caragana korshinskii and Caragana korshinskii + Agropyron cristatum + Hedysarum fruticosum + Elymus nutans. The bacterial community structure of the unicast Agropyron cristatum had a low similarity to the others.
Choose the 14 main bands from the DGGE profile for rubber tapping, cloning and sequencing. Took the BLAST analysis in the database of NCBI, and formulated the phylogenetic tree in MEGA 4.0 by using the neighbor-joining method (Fig. 3). The result showed that under different models of vegetation restoration the major bacterial communities of Hulunbeier sandy land conclude Proteobacteria, Bacteroidetes, Bacilli of Firmicutes, Actinobacteria and Acidobacteria. The Proteobacteria and Bacteroidetes were the dominant groups, with the Proteobacteria accounting for about 43%.
4. Discussions The soil microbial communities are subject to the influences of multiple factors, soil texture, properties, temperature and moisture, pH, minerals, organic matter, root secretions, root casts, the quality of plant residues and litter time [28,29]. Vegetation has a great impact on the composition and functions of soil microbes [30].
Fig. 3. The phylogenetic tree of soil 16S rDNA (Neighbor-joining).
H. Zhang et al. / Acta Ecologica Sinica 33 (2013) 211–216
Long-term coevolution leads to the choice of decomposers that quicken the decomposition of litters by plants, hence the synergy exists between plants and decomposers [31], as well as the positive and negative feedback effects which one drives the other [32]. Researchers showed that plant species and community structure can significantly change the soil microbe community structure and diversity in the rhizosphere of plants [33]. Vegetation and season exert obvious influence over the genetic diversity of soil bacteria and fungi [34,35]. There were researches showed that the lower the vegetation diversity, the lower the soil microbes diversity. But Hedlund found that vegetation diversity did not affect soil decomposer community which includes bacteria and saprophytic fungi [36]. By analyzing soil bacterial community structure in different vegetation patterns, it is showed that vegetation restoration significantly increased the genetic diversity of soil bacterial communities, and changed the community structure, in comparison to the complete degraded sandy land. The unicast Hedysarum fruticosum had the largest number of bacterial communities. The cause was that the rhizosphere released large amount of carbon after the vegetation restoration, meantime the litters increased. Along with the decomposition of litters which drove up organic matter content in soil, the soil microhabitats changed with more nutrition, thereby affecting the distribution and diversity of soil microbial communities. The plant coverage, natural height and above-ground biomass were the highest when the Hedysarum fruticosum were sown alone, therefore more litters fell from plants, and more nutrition were added to the soil, hence the most significant change of soil bacterial community structure. However the sandy land, in comparison, had low accumulation of nutrition in soil due to lack of plants, so both the microbe amount and diversity were low. Clustering analysis of DGGE profiles indicated that soil bacterial community structures under different vegetation restoration patterns were different. The unicast Hedysarum fruticosum and unicast Caragana korshinskii resemble each other, and the Agropyron cristatum + Caragana korshinskii resembles Caragana korshinskii + Agropyron cristatum + Hedysarum fruticosum + Elymus nutans. It was mainly because that plant species had influences on the selection of rhizosphere microbes [37,38]. And different plants had different influences on soil microbe communities [39]. Diversified aboveground parts could lead to larger amount and more kinds of litters; and the heterogeneity of resources could lead to diversity of decomposers [40]. Soil organic matter was a key factor to the composition and diversity of microbe community [41]. The differences of soil microbial community structure and activity among different types of steppe were mainly related to the changes of the amount and quality of soil carbon resources [42]. Vegetation changed the soil microbial communities by influencing the soil environment. Different plants provided different carbon resources for soil, resulting in the different soil microenvironment for microbes, and thus lead to different soil microbial community structure. The soil bacterial communities under different vegetation patterns mainly concluded a, band c groups of Proteobacteria, Bacteroidetes, Bacilli of Firmicutes, Actinobacteria and Acidobacteria. The Proteobacteria and Bacteroidetes were the dominant groups. This was consistent with previous researches. In the researches by Wu Yongsheng and others on desert steppe soil bacterial community structure, the result was that with the degradation of steppe soil, the soil bacterial community structure significantly changed. The main bacterial groups in desert steppe soil in Inner Mongolia are Bacteroidetes, Acidobacteria, canddgroups of Proteobacteria, and Firmicutes. The Bacteroidetes, accounting for about 47%, was the dominant group. Zhou Xiaoqi and others’ researches showed that there were five sub-branches of soil bacteria in the typical grassland of Inner Mongolia: Actinobacteria, a, band c groups of Proteobacteria, Bacteroidetes, Gemmatimonadetes and Acidobacteria.
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5. Conclusions The following conclusions were reached after analyzing the soil bacterial community structure under different vegetation restoration patterns: (1) Vegetation restoration significantly increased the amount of soil bacterial communities, and improved the genetic diversity of the soil bacterial communities, in comparison to the completely degraded sandy lands. (2) Soil bacterial groups under different vegetation restoration patterns in Hulunbeier sandy land include Proteobacteria, Bacteroidetes, Bacilli of Firmicutes, Actinobacteria and Acidobacteria, among which the Proteobacteria and Bacteroidetes are the dominant groups. (3) The soil bacterial community structures were different under different vegetation restoration patterns. The unicast Hedysarum fruticosum could best improve the soil bacterial community structures.
Acknowledgement This study was supported by National Natural Science Foundation of China (31170435 and 31000242).
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