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Ecological Engineering

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Changes in soil physico-chemical properties following vegetation restorationmediate bacterial community composition and diversity in Changting, China

Xiaolong Houa,c, Hang Hana, Mulualem Tigabua,d, Liping Caia,c, Fanrui Mengb, Aiqin Liua,c,⁎,Xiangqing Maa,c

a College of Forestry, Fujian Agriculture and Forestry University, Fuzhou 350002, Chinab Faculty of Forestry & Environmental Management, University of New Brunswick, Fredericton E3B5A3, Canadac Key Laboratory of State Forestry Administration on Soil and Water Conservation of Red Soil Region in Southern China, 350002, Chinad Southern Swedish Forest Research Centre, Swedish University of Agricultural Sciences, Box 49, 230 53 Alnarp, Sweden

A R T I C L E I N F O

Keywords:ReforestationSoil propertiesMicrobial communities16S rDNASoil bacteria

A B S T R A C T

Changes in microbial communities and drivers of their composition in different restoration approaches arelargely unexplored. The aim of this study was to evaluate the effects of different ecosystem restoration ap-proaches on bacterial community diversity and whether changes in soil physico-chemical properties are drivingbacterial community dynamics. Soil samples were collected from restored lands covered with grass, coniferousforest, young conifer-broadleaf forest, mature conifer-broadleaf forest, and natural broad-leaved forest and bareland. The bacterial community was determined by 16S rDNA sequencing while soil physico-chemical propertieswere determined using standard methodologies. We found that the physico-chemical properties of degraded redsoil were improved following re-vegetation. Soil bulk density and soil pH decreased while soil moisture contentincreased in restored sites compared to bare land. Soil organic carbon, total P, K, N, and available P and Kcontents were the highest in conifer-broadleaved forest soil. Soil bacterial community diversity significantlyincreased following restoration of degraded landscape, with Chloroflexi, Proteobacteria, Firmicutes,Cyanobacteria, WPS-2, Acidobacteria, Verrucomicrobia, Actinobacteria, and Bacteroidetes being dominant. Themajor bacteria phyla were positively correlated with soil chemical properties, but negatively correlated with soilphysical properties and pH. It can be concluded that favorable changes in soil physico-chemical propertiesfollowing restoration mediate bacterial community diversity, depending on vegetation cover types used to re-store the degraded land.

1. Introduction

Restoration of degraded landscape has gained global recognition torestore the lost ecosystem services and goods as well as climate reg-ulation (Jacobs et al., 2015). As a result, several restoration projectshave been implemented; ranging from passive restoration (e.g. areaexclosure) to active restoration involving planting of different species(Yirdaw et al., 2017). The restoration success is often evaluated basedon recovery of the structural elements of the degraded ecosystem, suchas species composition, diversity, density and cover as well as standstructure, which vary with the time elapsed since restoration began,disturbance type and landscape context (Crouzeilles et al., 2016).However, the functional recovery of degraded ecosystems followingrestoration, particularly soil microbial community dynamics, has justgained increasing attention with the advent of next generation

sequencing technologies, which offers new opportunities for studyingmicrobial composition at the species level (Zhang et al., 2016, 2018).

Soil microbial communities play an important ecological role asthey involve in a wide range of processes, including nutrient cyclingthrough decomposition of litter, soil aggregate formation and promo-tion of plant growth (Feigl et al., 2017; Hiltbrunner et al., 2012).Changes in soil microbial communities are often associated with plantcommunity structure and soil physico-chemical variability (Mahnertet al., 2015). The soil moisture, nutrition, pH, and other factors affectplant growth and vegetation diversity, whilst the plant community canalso modify soil properties (Chen et al., 2008; Li et al., 2015; Klimeket al., 2015; Trivedi et al., 2017; Zhang et al., 2014). As soil physico-chemical properties changes, the composition and diversity of soil mi-crobial communities can shift following forest restoration, dependingon vegetation cover type, soil depth and soil type as well as land use

https://doi.org/10.1016/j.ecoleng.2019.07.031Received 16 May 2019; Received in revised form 12 July 2019; Accepted 26 July 2019

⁎ Corresponding author.E-mail addresses: mulualem.tigabu@slu.se (M. Tigabu), fmeng@unb.ca (F. Meng), fjlaq@126.com (A. Liu).

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history and chemical characteristics (Kennedy et al., 2005; Noll andWellinger, 2008; Deng et al., 2010; Hu et al., 2014; Gunina et al., 2017.Differences in the abundance of bacterial species between forest specieshave been observed with Acidobacteria, for instance, being dominantunder birch while Firmicutes and Proteobacteria were more dominantunder young pine forests (Nazaries et al., 2015). Thus, microbialcommunities might serve as a primary indicator of changes in soilproperties and track trends in soil development following restoration ofdegraded landscape (Klimek et al., 2015; Winding et al., 2005).

Despite advances in our understanding of soil microbial communitydynamics during secondary succession, the effects of various restorationapproaches on soil microbial communities were largely unexplored,although such studies may provide useful insights to evaluate the ef-fectiveness of the ecological restoration. In the present study, four re-storation approaches applied in the red soil region of Chanting re-storation site, Southern China representing grass cover, coniferousforest, young and mature mixed conifer-broadleaved forests were se-lected to investigate the potential role of vegetation cover type in dif-ferentiating soil bacterial communities and whether changes in soilphysico-chemical properties mediates changes in soil bacterial com-munity in comparison with the nearby natural broad-leaved forest andbare land. The red soil region covers an area of 118 million hectare in10 provinces in Southern China that had suffered degradation to theextent that it’s called “red desert”. The Changting restoration site is oneof the red soil regions that have been most severely affected by soilerosion in China (Zheng et al., 2008; Lin et al., 2012; Chen et al., 2016)as a result of massive deforestation coupled with the acidic soil type,steep slopes, and high rain intensity associated with typhoons. Theseverity of soil erosion in Changting has led to soil loss, degradation ofsoil quality, and increasing sedimentation of rivers and lakes. In thepast 50 years, a series of restoration measures have been implementedin Changting including exclosure from disturbance, grass seeding,planting conifer and broadleaved trees.

The objectives of the study were to: (1) determine changes in soilphysico-chemical properties in relation to vegetation cover types fromChangting restoration site in comparison with bare land soil, (2) toanalyze the soil bacterial diversity and community composition withrespect to vegetation cover types; (3) examine the relationships be-tween the physico-chemical characteristics of soil and the bacterialdiversity within the surface soil (0–20 cm depth). We tested the hy-pothesis that vegetation cover type would select for distinct microbialcommunities beneath them, and such influences are presumablymediated by differences in soil physico-chemical properties, such asbulk density, soil moisture content, acidity, and nutrient status.

2. Materials and methods

2.1. Site description

The study was carried out in Changting model restoration site. The

Changting County is located in the west of Fujian Province, SouthernChina between 25°18′40″–26°02′05″N and 116°00′45″–116°39′20″E. Itis underlain by granite geology and is characterized by complex geo-morphic features, with hills and low mountains accounting for morethan 70% of the total area. The dominant soil type in the area is red soil,rich in iron and aluminum oxides, but with low concentrations of po-tassium, sodium, calcium, and magnesium. The soil generally tends tobe acidic and has high bulk density. The region has a typical subtropicalmonsoon climate. The annual mean temperature is 18.3 °C and annualprecipitation is 1685mm. The majority of precipitation occurs duringthe summer months (June–August) with high-intensity storms asso-ciated with typhoons during.

Forests were re-established in Changting by aerial seeding, mainlyof Pinus massoniana, on six different occasions between 1974 and 1993.After seeding, access to the area has been restricted, except for scientificresearch and inventory purposes. Six sites in the Changting erosionzone with different vegetation cover types, but at similar slope, slopedirection, and altitude, were chosen for this research by a tempor-al–spatial substitution method (Yang et al., 2016). The vegetation covertypes investigated in this study were grass land (GL), coniferous forest(CF), young conifer-broadleaf forest (YCBF), mature conifer-broadleafforest (MCBF), and natural broad-leaved forest (NBF). In addition, bareland (BL) was included to compare the effectiveness of the restorationmeasures.

BL is a severely degraded site with little to no vegetation for morethan 50 years, closely reflecting the historical bare land conditions ofthe area. GL was in a similar condition to that of BL before establish-ment of exclosures in 1990, and the main species were Paspalum wett-steinii, Miscanthus floridulus. CF was established by aerial seeding of P.massoniana in 1990, and today about 11 species can be found in thisvegetation cover type. YCBF was established by enrichment planting ofCF in 2008 by a mixture of different broad-leaved species, includingLiquidambar formosana, Schima superba, and Lespedeza bicolor. TheMCBF was established in 1982 by planting broad-leaved species in CFsite, the main species were Pinus massoniana, Schima superba, etc., about24 species can be found. NBF is considered to be an old-growth naturalforest because there are no historical records of disturbance by humanactivities for more than 100 years, and the main species were Schimasuperba, Adinandra millettii, etc., more than 30 species can be found.More details of each sampling site are provided in Table 1.

2.2. Soil sampling

In each vegetation cover type, five 0.5 ha plots were delineatedalong an altitudinal gradient, and five quadrats (20m×20m) were setup along an “S” shape within each plot at each site. Within eachquadrat, five soil samples at a depth of 0–20 cm were collected ran-domly along an “S”-shaped transect in July 2015. A single compositesoil sample from each site was prepared by mixing the five soil samplesfrom quadrats. A total of 30 soil samples were collected from 6

Table 1Geographic and vegetation characteristics of study sites in the Changting.

Vegetation cover types Geographic coordinates Elevation (m) Aspect Dominant species and number

Bare land (BL) 25°37′23.2″N 116°27′22.5″E 305 NW AbsentGrassland (GL) 25°40′01.7″N 116°27′24.9″E 321 SW Paspalum wettsteinii,

Miscanthus floridulusConiferous forest (CFL) 25°40′15.4″N 116°26′05.6″E 306 NW Pinus massoniana, Dicranopteris dichotoma, about 11 speciesYoung conifer-broadleaved forest (FL-Y) 25°39′41.7″N 116°28′56.0″E 300 SW Pinus massoniana, Liquidambar formosana,

Dicranopteris dichotoma, about 12 speciesMature conifer-broadleaved forest (FL-

A)25°40′16.9″N 116°26′07.4″E 297 SW Pinus massoniana,

Schima superba, Liquidambar formosana, Lespedeza bicolor, Dicranopterisdichotoma, about 24 species

Natural broadleaved forest (BFL) 25°40′32.0″N 116°28′56.5″E 308 NW Schima superba, Adinandra millettii,Rhaphiolepis indica, Glochidion puberum, Machilus grijsii, etc., more than 30species

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vegetation cover types (including bare land). Visible roots, plant re-sidues, and stones were removed from the composite samples, and thesamples were divided into two parts for further analysis—one part wassieved through a 2mm mesh, packed in individual sterile plastic bagsand immediately stored in 4 °C cooler, and then transported to the la-boratory and stored at −80 °C for DNA extraction later. The other partof the soil samples was air-dried at room temperature, sieved through anylon net (with 0.25mm aperture), and used for determining thephysico-chemical properties of the soil.

2.3. Analysis of soil physico-chemical properties

The soil bulk density and moisture were determined for each plotand site by the cutting ring method (Zeng et al., 2014) while the che-mical properties were determined using the standard procedures (Bao,1999). The soil samples were sieved through a 0.14mm mesh and totalnitrogen (TN), total phosphorus (TP), total potassium (TK), and organiccarbon (OC) were measured as follows. TN was determined by drycombustion method using CN elemental analyzer (Vario MAX, Ele-mentar, Germany). TP concentrations were measured using inductivelycoupled plasma atomic emission spectrometry (ICP-OES, PerkinElmer,USA) after wet digestion with H2SO4–HClO4 whereas TK was measuredusing a flame spectrophotometer. The available P (AP) was measuredcolorimetrically after extraction with ammonium fluoride–hydrochloricacid. The available K (AK) was measured using a flame spectro-photometer following extraction using a 1mol/L ammonium acetatesolution. Soil pH was determined with a glass electrode Thermo-RusselpH meter in a 1:2.5 (soil/water) suspension.

2.4. DNA extraction from soil and PCR amplification of 16S rDNA

DNA was extracted from 0.25 g of field-moist soil using FastDNA®SPIN Kit for Soil (Bio 101, Vista, CA, USA) according to the manu-facturer’s instructions, and then stored at −70 °C for subsequent ana-lysis. The extracted DNA was subjected to PCR amplification withbacteria-specific primers (336F: 5′-GTACTCCTACGGGAGGCAGCA-3′;806R; 5′-GTGGACTACHVGGGTWTCTAAT-3′) against the V3+V4 re-gion of the bacterial 16S rDNA gene. The PCR premix used was NEBFusion PCR High-Fidelity Master Mix. PCR amplification was performedin a Genius Thermal Cycler in 50 µL reactions, containing approxi-mately 30 ng of purified DNA. The temperature and cycling conditionswere as follows: preheating at 98 °C for 3min, followed by 30 cycles at98 °C for 45 s, 55 °C for 45 s, and 72 °C for 45 s, and a final incubation at72 °C for 7min. The presence of PCR products and their concentrationswas checked using electrophoresis on 1% agarose gel at 150 V for

40min. The amplified products were detected and purified by electro-phoresis and sent to Guangzhou Gene Denovo Biotechnology Co., Ltd.for sequencing by Illumina HiSeq sequencing platform (IlluminaPE250).

PCR products without primer dimer and contamination bands wereselected for sequencing. Sequences with an average phred score lessthan 30, fuzzy bases, homopolymers running more than 15 bp, andmore than two mismatches or sequence lengths less than 100 bp werediscarded. Only sequences that were perfectly matched and overlappedby more than 10 bp were assembled. The sequences were further fil-tered and processed to remove chimaeras. The 16S rDNA gene se-quences were aligned using PICRUSt against a template alignment ofthe Greengenes core set filtered at 97% similarity level, and a phylo-genic tree was generated from the filtered alignment using FastTree.Each OTU sequence was used for subsequent classification and statis-tical analysis. Sequences were entered into the NCBI databases andcompared using Mothur to calculate the abundance of each OTU.

2.5. Statistical analysis

The OTU richness index was calculated for each of the soil samplesusing the alpha diversity indices: Chao1, ACE, Shannon, and Simpson(Magurran, 2004). The data for soil physico-chemical properties andthe bacterial alpha community diversity were subjected to One-wayANOVA to examine differences among vegetation cover types. Meansthat exhibited significant differences were compared by Tukey’s post-hoc test (p < 0.05). All statistical analyses were performed using SPSSv.17.0 (SPSS Inc., Chicago, IL, USA). Redundancy analysis (RDA) wasconducted to examine the relationship between the dominant bacteriaphyla and soil physico-chemical properties using Canoco (4.5) software.To check the applicability of RDA analysis, we carried out a DCA, andthe lengths of gradient was 1.291 which is shorter than 3.0. Thus, RDAis a better choice.

3. Results

3.1. Soil physico-chemical properties

The soil bulk density and soil moisture content varied significantly(p < 0.05) among the different vegetation cover types. Compared tothe bare land, bulk density was low in soils of coniferous forest, matureconifer-broadleaf forest and the natural broad-leaved forest (Fig. 1a).However, the young conifer-broadleaved forest and the grassland hadsimilar bulk density as the bare land. The soil moisture content gra-dually increased with complexity of the vegetation cover type (Fig. 1b)

BL GL CF YCBF MCBF NBF

1.15

1.20

1.25

1.30

1.35

1.40

1.45

1.50

1.55

1.60(a)

d

bcab

cd

abBu

lk d

ensi

ty (g

m3 )

Different vegetation cover stages

a

BL GL CF YCBF MCBF NBF

150

175

200

225

(b)a

bc

ab

cd

de

Moi

stur

e co

nten

t (g

kg-1

)

Different vegetation cover types

e

Fig. 1. Mean bulk density (a) and moisture content (b) of soils of different vegetation cover types (BL: bare land; GL: grass land; CF: coniferous forest; YCBF: youngconifer-broadleaf forest; MCBF: mature conifer-broadleaf forest; NBF: natural broad-leaved forest). Values are means ± standard error (n= 5), and means followedby different letter (s) are significantly difference at 0.05 level.

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and was significantly higher for all vegetation cover types, except forthe grassland, than for bare land.

The mean soil chemical properties also varied significantly(p < 0.05) across the different vegetation cover types (Table 2).Compared to the bare land, the pH was low for most of the vegetationcover types except the natural broadleaved forest soil that had a similarpH as the bare land. Soils of the mature confer-broadleaved forests andthe natural broadleaved forests had higher organic carbon content, totalN and Total P than both the bare land and the coniferous forest soilsalthough the later had significantly more organic carbon than theformer. The total K content was higher in soils of the conifer and thenatural broadleaved forests than the other vegetation cover types,which in turn had higher total K content than soils of the bare land.Available P was the highest in the natural broadleaved forest soil whileavailable K was the highest in mature conifer-broadleaved and thenatural broadleaved forest soils compared to other vegetation covertypes and the bare land soils.

3.2. Diversity of bacterial community

A total of 2,487,353 sequences were obtained from 30 soil samplesby analysing the V3-V4 region of bacterial 16S rRNA genes. The totalnumber of effective sequences per sample ranged from 38 936 to85,675 sequences. The unique tag sequences, selected through re-dundant processing by Mothur v1.34.0 software, resulted in a total of867,624 OTUs (range: 14,282–35,187) with 97% similarity clusteringlevel at a genetic distance of 3%. Shannon rarefaction analyses showedthat the curve tended to plateau after 20,000 sequences at 97% simi-larity (Fig. 2). Thus, additional sequencing had little effect on speciesdiversity.

The alpha diversity indices of soil bacteria across different vegeta-tion cover types are given in Table 3. The number of reads was sig-nificantly higher for conifer forest, mature conifer-broadleaved forestand natural broadleaved forest than the bare land. The number of OTUswas significantly greater for all vegetation cover types than the bareland except the grass land that had similar OTU number. The Chao andACE richness indices showed that the diversity was highest for theconiferous forest, natural broadleaved forest young conifer-broadleavedforest mature conifer-broadleaved forest compared with grassland andbare land. The Shannon index indicated a gradual increase in diversityfrom the bare land to the natural broadleaved forest and significantlyhigher diversity in all vegetation cover types compared to bare land,whereas the Simpson index showed the opposite trend. As a whole, thebacterial community diversity increased with the progression of therevegetation stages.

3.3. Composition of bacterial community

All valid sequences from the soil sample libraries were classifiedinto phylum and order, and a total of 32 phyla were found in allsamples (see supplementary materials). The dominant bacterial phyla

(relative abundance>5%) across the soil samples were Chloroflexi,Proteobacteria, Firmicutes, Cyanobacteria, WPS-2, Acidobacteria,Verrucomicrobia, Actinobacteria, and Bacteroidetes, accounting formore than 86% of the total sequences (Fig. 3). The bacterial phylumwith the maximum relative abundance in the bare land soil wasChloroflexi (25.3%); its abundance gradually decreased from thegrassland to the natural broadleaved forest soil. The relative abundanceof Proteobacteria exceeded 20% for all vegetation cover types andshowed a trend of increasing abundance from bare land to naturalbroadleaved forest soil. It accounted for more than 38% of the relativeabundance in the mature conifer-broadleaved and natural broadleavedforest soils. The relative abundance of Firmicutes gradually decreasedfrom bare land (17.4%) to young conifer-broadleaved soil (5.6%), and itwas< 5% for mature conifer-broadleaved forest soil. Cyanobacteriawere only present at> 5% relative abundance in the bare land (8.9%)and young conifer-broadleaved forest (6.9%) soils. The relative abun-dance of Acidobacteria increased significantly from the bare land(5.9%) to the grassland (21.8%) soils and other forest types exceptconifer-broadleaf young forest.

At the order level, we observed at least one sample with relativeabundance greater than 2%; the remaining species were classified intoother categories, and those for which we were unable to comment tothe level of sequences are classified as “unclassified category” (Fig. 4).Although Rhodospirillales, Rhizobiales, Acidobacteriales, and Soli-bacterales were present in all the sites, there were differences in relativeabundance of bacterial order across the sites. iii1-15, Bacteroidales,Enterobacteriales, and Xanthomonadales were only present in naturalbroadleaved forest soil. Thermogemmatisporales (20%) and Bacillales(15%) were the main orders found in bare land soil. Acidobacteriales(9%), Ellin6513 (7%), Rhizobiales (6%), Rhodospirillales (6%), andActinomycetales (5%) were the main orders found in grassland soils.Rhizobiales (9%), Acidobacteriales (8%), Rhodospirillales (7%), Bur-kholderiales (6%), Bacillales (5%), and Solibacterales (5%) were themain orders in coniferous forest soil. Bacillales (14%), Rhizobiales(7%), Acidobacteriales (5%), and Rhodospirillales (5%) were the mainorders in young conifer-broadleaved mixed forest soil while Acid-obacteriales (11%), Ellin6513 (9%), Rhizobiales (8%), Rhodospirillales(7%), and Xanthomonadales (6%) were the main orders found in soilsof mature conifer-broadleaved forest soil. Rhizobiales (7%), Soli-bacterales (6%), Acidobacteriales (6%), and Rhodospirillales (5%) werethe main orders found in soils of natural broadleaved forest.

3.4. Relationship between bacterial communities and soil physico-chemicalproperties

Redundancy analysis was conducted to investigate the relationshipsbetween the eight main bacterial phyla and eight physico-chemical soilproperties (Fig. 5). The composition of soil bacteria community variedconsiderably among vegetation cover types. All the bacterial phyla,except Firmicutes and Chloroflexi, were positively correlated with totalK, total P, available K, available P, organic carbon, and total N, and

Table 2Soil chemical properties across different vegetation cover types used to restore degraded land in Changting. Values are means ± standard error (n= 5) and meansfollowed by different letter in the same column are significant difference at 0.05 level.

Cover* pH Organic C(g kg−1)

Total N(g kg−1)

Total P(g kg−1)

Total K(g kg−1)

Available P(mg kg−1)

Available K(mg kg−1)

BL 5.15 ± 0.16a 2.57 ± 0.12f 1.07 ± 0.15c 0.12 ± 0.02d 2.79 ± 0.12c 2.30 ± 0.41c 24.34 ± 1.75d

GL 4.82 ± 0.06b 12.27 ± 0.40c 1.17 ± 0.12c 0.21 ± 0.03b 8.61 ± 0.28b 7.96 ± 0.21b 42.35 ± 1.60c

CF 4.57 ± 0.08c 7.11 ± 0.92d 1.26 ± 0.06c 0.14 ± 0.01d 14.57 ± 3.72a 3.07 ± 0.16c 68.42 ± 5.79b

YCBF 4.66 ± 0.10c 4.57 ± 0.12e 1.03 ± 0.12c 0.18 ± 0.02c 11.06 ± 0.67b 2.98 ± 0.31c 49.14 ± 2.01c

MCBF 4.34 ± 0.11d 25.00 ± 0.20a 2.47 ± 0.12a 0.27 ± 0.02a 10.52 ± 1.00b 6.70 ± 0.67b 79.29 ± 5.45a

NBF 5.30 ± 0.04a 16.07 ± 0.65b 1.57 ± 0.23b 0.26 ± 0.02a 14.68 ± 1.30a 13.20 ± 1.80a 81.62 ± 6.60a

* The vegetation cover BL: bare land; GL: grass land; CF: coniferous forest; YCBF: young conifer-broadleaf forest; MCBF: mature conifer-broadleaf forest; NBF: naturalbroad-leaved forest.

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negatively correlated with pH, bulk density and moisture content.Proteobacteria was most strongly associated with available P, Acid-obacteria, Planctomycetes, and Verrucomicrobia were most stronglyassociated with organic carbon, and Bacteroidetes and Actinobacteriawere most strongly associated with total K and total N. respectively.Whilst Firmicutes and Chloroflexi were strongly associated with pH andbulk density, Chloroflexi was negatively correlated with soil moisturecontent.

4. Discussion

Generally reforestation results in an improvement in soil physico-chemical properties (Gunina et al., 2017; Zeng et al., 2014). Soil bulkdensity plays an important role in soil nutrient storage, water-holdingcapacity and gas penetration (Wang et al., 2010), which is linked withsoil development, parent material and land use pattern. For the studiedsites, soil bulk density decreased by 6.5% in grassland, 18.6% in coniferforest, 8.7% in young conifer-broadleaved forest and 14.5% in matureconifer-broadleaved forest compared with the bare land soil. Thissuggests that reforestation loosens up the top-soil and increased soilporosity and water retention capacity as the vegetation established.This is further evidenced from increased soil moisture content withvegetation cover type (Fig. 1). The difference in soil bulk density amongthe different vegetation cover types could be attributed to amounts ofeasily-decomposable litter, resulting in thicker humus layers, and suc-cessional stages of the forest (Zeng et al., 2014).

We also found that the bulk density of the YCBF were not onlyhigher than the CF, but close to that of grass land. This result is con-tradicting to our expectation because the broad leaf planting into theconifer forest was designed to improve the ecological functions. Wespeculated the increase in bulk density in YCBF forest could be attrib-uted to the compaction during the planting process. This hypothesis issupported by the fact that the bulk density of MCBF was also higherthan that of CF, and lower than YCBF. The bulk density simply takestime to recover. In summary, forest cover will increase soil bulk densityand increase soil moisture content. However, reducing compaction re-lated to human activities, including silviculture operations is important

Fig. 2. Comparison of soil bacterial diversity across different vegetation cover types using multi samples Shannon–Wiener curves. BL: bare land; GL: grass land; CF:coniferous forest; YCBF: young conifer-broadleaf forest; MCBF: mature conifer-broadleaf forest; NBF: natural broad-leaved forest.

Table 3Number of reads, operational taxonomic units (OTUs) and diversity indices ofsoil bacterial communities based on 16S sequencing data of samples collectedfrom different vegetation cover types. Values are mean ± standard error(n=5), and means followed by different letter (s) in across column are sig-nificantly difference at 0.05 level.

Cover* Reads OTU Chao ACE Shannon Simpson

BL 64623b 21301c 102793c 241606c 6.99c 0.022aGL 75611ab 26206bc 134181bc 330884bc 8.11b 0.005bCF 81014a 33948a 179166a 452860a 8.61ab 0.003bYCBF 70483ab 28569ab 154492ab 389533ab 8.14b 0.007bMCBF 79704a 30399ab 145832ab 357472ab 8.49b 0.002bNBF 83616a 33102a 154894ab 356714ab 9.13a 0.001b

* The vegetation cover BL: bare land; GL: grass land; CF: coniferous forest;YCBF: young conifer-broadleaf forest; MCBF: mature conifer-broadleaf forest;NBF: natural broad-leaved forest.

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to ensure the restoration of soil physical properties in degraded red soil.In the present study, the soil pH values decreased in the grass land,

coniferous forest and conifer-broadleaved forest soils compared withthe bare land and the natural broadleaved forest soils (Table 2). Ourresult concurs with those of previous studies, which showed that con-ifers can cause soil acidification (Kong et al., 2000; Kuang et al., 2008).The decrease in soil pH may also be attributed to the release of organicacids from tree roots, removal of exchangeable cations by plant uptakeand/or soil microbial processes that transform organic matter and therelease of organic acids (Wei et al., 2006). Microbial decomposition oflitters of P. massoniana forest which contain less base ions, and moreresin and tannin may also contribute to soil acidification.

Reforestation improved soil fertility with marked variation amongvegetation cover types used to restore the degraded land (Table 2). Theorganic carbon and total nitrogen contents were 873% and 130% morein the mature conifer-broadleaved forest soil than the bare land soil,respectively. Such huge changes could be related to accumulation oftree litter inputs over time which decomposes relatively quickly as theintrinsic microbial community is gradually adapted to this new sub-strate. It could also be related to lack of or minimal decomposition ofthe intrinsic soil organic carbon by microorganisms, thus resulting inlower C mineralization long after reforestation. Furthermore, the lower

organic carbon and total N contents in the coniferous forest soil couldbe due to the lower litter input and the higher resistance to degradation(Chiti et al., 2012). While the total P content was 127.8% higher inmature conifer-broadleaved forest soil compared to the bare land soil,available P were 245.9% higher in grassland soil and 191.4% higher inmature conifer-broadleaved forest soils than the bare land soil. Total Kwas 422% higher in coniferous forest soil whereas available K was225% higher in mature conifer-broadleaved forest soil than the bareland soil. Such big differences can be explained by the quality andquantity of litter accumulated on the soil surface and the increasedactivity and content of microbial biomass.

As a whole, the results are consistent with previous studies thatdemonstrated improvements in soil nutrient condition with revegeta-tion (Fan et al., 2014; Zhuet al., 2012). We noticed that organic Ccontent in YCBF (4.6 g kg−1) was less than CF (7.1 g kg−1). Total N,Available P and Available K also showed the similar trend. The Avail-able K in YCBF was significantly lower than CF without addingbroadleaf species. This is again, contradicting to our expectations that arestoration effort resulted in poor performance. In compaction and in-creased exposure associated with planting broadleaf species in coniferforests did result in temporary degradation of soil physical and che-mical properties. The soil physical and chemical properties will recover

Fig. 3. Phylogenetic relationships of bacterial communities and the relative abundance of bacterial phyla (> 5%) in the soils of different vegetation cover types. BL:bare land; GL: grass land; CF: coniferous forest; YCBF: young conifer-broadleaf forest; MCBF: mature conifer-broadleaf forest; NBF: natural broad-leaved forest.

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over time; however, the degradation will take more than 8 years or evenlonger to recover in our study sites.

Soil microorganisms play an important role in the formation and

development of soil, in the transformation of organic matter, and inmaintaining a balanced ecosystem in the soil environment (Fierer andJackson, 2006). Many studies have also demonstrated a direct re-lationship between soil bacteria and vegetation diversity (Faoro et al.,2010; Chen et al., 2015). For the studied sites, the number of OTUs wassignificantly greater for restored sites than the bare land, and those inthe coniferous forest and natural broad leaved forest soils were greaterthan those in the grassland soil. This might be related to the time sincerestoration (25 years since the coniferous forest was established). Thediversity of soil microorganisms was not always at the same pace as thatof vegetation restoration, and varied with composition of the vegetation(Dan et al., 2011). Our study showed that the Chao and Ace indicestended to be highest for coniferous forest soil than the conifer-broad-leaved forests (Table 3) probably because the soil microbial diversitylagged behind the vegetation change and, therefore, it took time torespond. As a whole, the alpha community diversity indices, such as theShannon index, increased with the restoration of the vegetation(Table 3). Therefore, changes in the microbial diversity can reflect theprocess of change in the soil quality following restoration of degradedecosystems.

The dominant bacterial phyla in the bare land soil were Chloroflexiand Proteobacteria, which accounted for 46% of the bacterial sequences(Fig. 3), but the grassland soil was dominated by Acidobacteria withProteobacteria, accounting for more than 40% of the bacterial se-quences in all the soil samples. Proteobacteria was detected as one ofthe most abundant phyla in soil bacterial communities, which is relatedwith Rhizobiales (a nitrogen-fixing organism), suggesting nitrogenfixation may play an important role in differentiating communitystructure. Similar result was obtained by He et al. (2008) who reportedthat 74% of the clones in the upland red soil of Yingtan, Jiangxi Pro-vince, China, were classified as Proteobacteria. The fact that

Fig. 4. Relative abundance of bacterial orders (> 2%) in soils of different vegetation cover types. BL: bare land; GL: grass land; CF: coniferous forest; YCBF: youngconifer-broadleaf forest; MCBF: mature conifer-broadleaf forest; NBF: natural broad-leaved forest.

Fig. 5. Redundancy analysis of the relationships among the main bacterialphyla, OTU, and soil physico-chemical properties. BL: bare land (No. 1–5); GL:grass land (No. 6–10); CF: coniferous forest (No. 11–15); YCBF: young conifer-broadleaf forest (No. 16–20); MCBF: mature conifer-broadleaf forest (No.21–25); NBF: natural broad-leaved forest (No. 26–30); BD: bulk density; MC:moisture content; TP: total phosphorus; AP: available phosphorus; TK: totalpotassium, AK: available K; OC: organic carbon; TN: total nitrogen.

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Acidobacteria was one of the dominant phyla in our study is due to theacid nature of the soils in the studied sites as Acidobacteria are usuallyfound in soils and known to grow under oligotrophic conditions at lowpH (Dion, 2008; Jones et al., 2009). Soil bacterial orders significantlyincreased from bare land soil to grassland soil, and there was somedifference for other vegetation cover types. We found that iii1-15,Bacteroidales, Enterobacteriales, and Xanthomonadales were relativelymore abundant in the natural broadleaved forest soil (Fig. 4). Theseresults indicated that the vegetation cover type drives the compositionof soil bacterial community, thus the main bacteria may differ betweenvegetation cover types. The structure of the soil microbial communityhas been shown to be a holistic indicator of the stage of revegetationand the degree of degradation (Hu et al., 2014).

Soil organic C, total N, available N, and available P concentrationswere significantly positively correlated with the abundance of most ofthe bacterial groups and the Shannon index, indicating the dependenceof bacterial community diversity on nutrient supply in the soil.Moreover, the diverse soil bacterial community promotes nutrient cy-cling and availability in the soil (Zhang et al., 2016). In our study, therelationships between the soil bacteria and soil physico-chemicalproperties varied between phyla. Most of the bacterial phyla, such asProteobacteria, Planctomycetes, Acidobacteria, and Bacteroidetes, werepositively correlated with the soil total K, total P, available K, OC, andtotal N concentrations (Fig. 5), which is in agreement with the results ofprevious studies (Mahnert et al., 2015; Koranda et al., 2011). However,most of the bacterial phyla negatively correlated with soil pH, and bulkdensity, which may be related to the acidic nature of the red soil andlarge rainfall in Southern China. A shift in soil microbial communitieshas been observed with agricultural management practices and season(Gałązka et al., 2017a, b), which was attributed to lower disturbance ofsoil structure, good aeration, and the accumulation of crop residues onthe surface. This finding is in line with the negative correlation betweenabundance of bacterial community and soil bulk density (an indicatorof soil structure) in our study. Firmicutes was positively correlated withsoil pH, moisture content, and bulk density as this phylum is dominantin the bare land soil and hence adapted to this environment.

5. Conclusions

Based on the findings, the following conclusions can be drawn: (1)the physical and chemical properties of soil were improved with re-vegetation of degraded land; particularly conifer-broadleaved mixedforest yield substantial improvement in soil quality; (2) the diversityand composition of soil bacterial community vary with the vegetationcover type used to restore the degraded land, suggesting selecting fordistinct microbial communities beneath them; (3) diversity and struc-ture of bacterial community are driven by changes in soil physico-chemical properties, which in turn are dependent on the vegetationcover types. Thus, composition and diversity of bacterial communitymay serve as indicator of functional recovery of restored ecosystem.

Declaration of Competing Interest

The authors declare that they have no known competing financialinterests or personal relationships that could have appeared to influ-ence the work reported in this paper.

Acknowledgments

This work was supported by the Key Project of Fujian ProvinceScience and Technology Department (2017Y0001), and the NationalKey Technology R&D Program (2014BAD15B02).

We also thank Dr Kate Heal from School of GeoSciences, TheUniversity of Edinburgh, for offering comments which have sub-stantially improved the manuscript.

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