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Heavy grazing over 64 years reduced soil bacterial diversity in the foothills of the Rocky Mountains, Canada
Applied Soil Ecology xxx (xxxx) xxxx
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Heavy grazing over 64 years reduced soil bacterial diversity in the foothills of the Rocky Mountains, Canada Yuting Zhanga,b, Xinlei Gaoc, Xiying Haob, Trevor W. Alexanderb, Xiaojun Shia, Long Jinb, Ben W. Thomasd,* a
College of Resources and Environment, Southwest University, Chongqing 400716, China Agriculture and Agri-Food Canada, Lethbridge Research and Development Centre, Lethbridge, Alberta, T1J 4B1, Canada c College of Agricultural Sciences, Chifeng University, Hongshan District, Chifeng, Inner Mongolia, 024000, China d Agriculture and Agri-Food Canada, Agassiz Research and Development Centre, Agassiz, British Columbia V0M 1A0, Canada b
ARTICLE INFO
ABSTRACT
Keywords: Bacterial community Foothills grassland Grazing intensity Herbivory
Grazing is one of the most widespread grassland management strategies. However, the effects of over six decades of different grazing intensities on soil bacterial community composition in the foothills of the Rocky Mountains are uncertain. We analyzed the bacterial community composition in soil samples collected in both summer and fall, 64 years after a long-term grazing intensity study was initiated in 1949. Grazing intensity treatments were (i) 0 animal-unit months (AUM) ha−1, (ii) 2.4 AUM ha−1 and (iii) 4.8 AUM ha−1, which represented the control, moderate and heavy grazing intensities, respectively. The evenness and diversity indices decreased with heavy grazing intensity relative to the other treatments in both summer and fall. In summer and fall, heavy grazing significantly shifted the bacterial community composition compared to the other treatments. Heavy grazing intensity significantly decreased the relative abundances of Bacteroidetes, Chlorobi, Nitrospirae and Proteobacteria, but significantly increased the relative abundance of Actinobacteria. Principal Coordinate Analyses revealed that available nitrogen, moisture content, total nitrogen and organic carbon were the primary environmental factors affecting the soil bacterial community composition. This study suggests that the effects of grazing on soil bacterial community composition are largely dependent on changes in soil physicochemical properties induced by the intensity of grazing over periods of six decades.
1. Introduction
However, uncertainty about the responses of the soil bacterial community composition to long-term cattle grazing as well as the underlying mechanisms, including interactions among site-specific edaphic properties and environmental conditions, remains unresolved (Dlamini et al., 2016; Zhao et al., 2017). Microorganisms play an important role in the decomposition of organic matter, transformation of nutrients and maintenance of ecosystem stability (Schulz et al., 2013). Grazing livestock may potentially affect the relative abundance of bacterial taxa and their functional traits through altering plant community composition and biomass, fecal and urine deposition, soil physicochemical properties, grazing period and other factors (Qu et al., 2016; Zhao et al., 2017; Wang et al., 2019). These factors may have positive, neutral or negative effects on soil bacterial community composition. A case study conducted on the subarctic tundra found that ungulate grazing altered substrate availability, which had important consequences on soil microbial community composition (Stark et al., 2015). Qu et al. (2016) reported that heavy
Natural grasslands occupy about 40% of Earth’s land surface (Dlamini et al., 2016). Grazing animals on natural grassland is a longstanding and widespread human-driven grassland management strategy. In western Canada, rough fescue grasslands in the foothills of the Rocky Mountains are primarily managed for cattle grazing (Gao et al., 2018). A growing number of studies show that the health of grassland ecosystems is strongly affected by the intensity of cattle grazing (Zhou et al., 2017; Byrnes et al., 2018). Previous studies in this area reported that long-term excessive cattle grazing may degrade grassland soils, alter plant community composition and increase the release of soil greenhouse gases (Dormaar and Willms, 1998; Li et al., 2012; Gao et al., 2018). Five to six decades of heavy grazing clearly shifted the soil organic matter content, soil mineral nutrition, soil texture and soil base cations of rough fescue grassland in the foothills of the Rocky Mountains (Li et al., 2009, 2012; Zhang et al., 2018a, 2019).
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Corresponding author. E-mail address: [email protected] (B.W. Thomas).
https://doi.org/10.1016/j.apsoil.2019.09.011 Received 17 June 2019; Received in revised form 11 September 2019; Accepted 16 September 2019 0929-1393/ Crown Copyright © 2019 Published by Elsevier B.V. All rights reserved.
Please cite this article as: Yuting Zhang, et al., Applied Soil Ecology, https://doi.org/10.1016/j.apsoil.2019.09.011
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grazing intensity reduced soil bacterial diversity indices in a steppe grassland of Northeast China due to changes in plant community composition, soil total nitrogen/phosphorus (N/P) ratio, electrical conductivity (EC), pH and total N. In a semiarid steppe located in Inner Mongolia, China, researchers also found that heavy grazing intensity decreased soil carbon (C) and N content, which subsequently reduced soil bacterial diversity and community size (Steffens et al., 2008). The energy and nutrients required by soil bacteria are frequently obtained from plant litter or through root exudates from living plants and root decay, which are affected by grazing intensity in grassland ecosystems (Klumpp et al., 2009; Byrnes et al., 2018). Recent data from a metaanalysis demonstrated that the effects of grazing on soil microbial community sizes are largely dependent on grazing intensity (Zhao et al., 2017). Although the effects of grazing intensity on soil microbes have been widely reported across different grassland ecosystems, there is limited information about how long-term cattle grazing impacts bacterial community composition of grassland soils in the foothills of the Rocky Mountains in Canada. To address this knowledge gap, we utilized a 64-year (1949–2013) grazing intensity field trial conducted on rough fescue grassland within the foothills of the Rocky Mountains, Alberta, Canada. The experimental treatments included grazing exclusion (ungrazed control), moderate grazing and heavy grazing.The objectives of this study were to (a) determine the effects of over 60 years of different cattle grazing intensities on soil bacterial α diversity and community composition, and (b) investigate the main soil environmental factors that drive soil bacterial community composition.
KCl ratio (Keeney and Nelson, 1982). The AN concentration was determined with a micro-plate reader (Multiscan GO, Thermo Scientific, Nepean, ON). Available P (AP) was determined by extracting soil with 0.5 mol L-1 NaHCO3 solution (Olsen et al., 1954) at 1:10 soil-to-NaHCO3 ratio. The AP concentrations were determined with an automated colorimeter (Auto-Analyzer III, Bran + Luebbe, Norderstedt, Germany). For soil organic carbon (SOC), total N (TN) and total P (TP) determination, sub-samples were finely ground to pass through a 0.15-mm mesh. The SOC and TN were determined by dry combustion (NA 1500 series 2, Carlo Erba Instruments, Milan, Italy). Soil TP concentration was determined by a Discrete Analyzer (Easy-Chem Pro, Systea Analytical Technologies, Anagni, Italy) after being digested by H2SO4 and H2O2. 2.3. DNA extraction, Amplicon library preparation, and MiSeq sequencing Soil DNA was extracted from 0.25 g fresh soil using the MoBioPowerSoil@ DNA Isolation Kit (MoBio Laboratories, Inc., USA) according to the manufacturer’s instructions. The extracted DNA concentrations were quantified using a NanoDrop 2000 (Thermo Fisher Scientific, USA) and checked using a 1% agarose gel electrophoresis, and then stored at −20 °C. The V4 variable region of 16S rRNA gene was amplified using the primer set 515 F (5′-GTGCCAGCMGCCGCGGTAA-3′)/806R (5′-GGACTACHVGGGTWTCTAAT-3′) (Caporaso et al., 2011), with 8-bp errorcorrecting barcode on the forward primer to characterize each sample. DNA was amplified in triplicate. All PCR amplifications were performed using the HotStar Taq Plus Master Mix Kit (Qiagen, USA) under the following conditions: 94 °C for 3 min, followed by 28 cycles of 94 °C for 30 s, 53 °C for 40 s and 72 °C for 1 min, after which a final elongation step at 72 °C for 5 min was performed. After amplification, PCR products were checked in 2% agarose gel to determine the success of amplification and the relative intensity of bands. Multiple samples were pooled together in equal proportions based on their molecular weight and DNA concentrations. Pooled Samples were purified using calibrated Ampure XP beads (Agencourt, Beckman Coulter, USA). Then, the pooled and purified PCR products were prepared into a DNA library following Illumina TruSeq DNA library protocol. Sequencing was performed at MR DNA (www.mrdnalab.com, Shallowater, TX, USA) on a MiSeq following the manufacturer’s guidelines.
2. Materials and methods 2.1. Experimental design and soil sampling This long-term grazing study site was established in 1949 on a native grassland in the undulating Porcupine Hills, with altitudes varying from 1280 m to 1420 m, at an Agriculture and Agri-Food Canada Research substation (50°12′ N, 113°54′ W), near Stavely, Alberta, Canada in the Foothills of the Rocky Mountains. Rough fescue (Festuca campestris Rydb.) is the the dominant species in the climax community with Parry’s oatgrass (Danthonia parryi Scibn.) and Kentucky bluegrass (Poa pratensis L.) as co-dominant species. The soil is an Orthic Black Chernozem (Typic Haplustolls in US taxonomy) with a loam to clayloam texture. In 1949, two paddocks were constructed, with an area of 32 and 16 ha (Dormaar and Willms, 1998) and were stocked with 13 cattle and their calves for 6-months to produce two distinct moderate and heavy grazing intensities (2.4 and 4.8 animal unit month (AUM) ha−1, respectively). Cattle of the same age and breed (lactating Hereford-continental cross with calves) have been grazed from around midMay to mid-November each year since 1949. A non-grazed 0.8 ha paddock was also constructed in 1949 as a control (0 AUM ha−1). Four, eight and eight 15 m × 30 m subplots were randomly selected as pseudo-replicates in the 0, 2.4 and 4.8 AUM ha−1 paddocks, respectively. Soil samples were collected in both mid-July and midOctober 2013 to represent summer and fall seasons, respectively. The precipitation and mean air temperature in July and October were 89.5 mm/15.3 °C and 31.3 mm/5.4 °C, respectively. Briefly, six randomly selected 0–15 cm depth soil cores from each subplot were collected and thoroughly mixed to form one composite sample. Soil samples were sieved through a 2-mm mesh, and then either air dried for physicochemical property analyses or stored at −20 °C until DNA extraction.
2.4. Bioinformatics analyses The raw data were quality-filtered by QIIME (Version 1.9.1). Briefly, sequences were joined and depleted of barcodes and primers. The reads were then scanned with a 4-base wide sliding window and cut when the average quality per base dropped below 20. Sequences shorter than 150 bp and homo-polymers and ambiguous base calls longer than six nucleotides were removed. The Operational Taxonomic Units (OTUs) were clustered with 97% similarity using UPARSE (Edgar, 2013) and the chimeric sequences were then identified and removed using UCHIME (Edgar et al., 2011). The OTUs with 3 or fewer reads were removed as they potentially originated from sequencing artifacts (Kunin et al., 2010). The representative sequence for each OTU was picked and the taxonomic affiliation of each representative sequence was assigned by the Ribosomal Database Project classifier against the Silva (SSU123) 16S rRNA database (Quast et al., 2013). Soil bacterial αdiversities (observed OTUs, Chao1, Heip_e, Simpson_e, Shannon and Simpson index) were generated after randomly subsampling the sequences to an equal number. Bacterial-weighted UniFrac distances were calculated based on the phylogenetic information.
2.2. Determination of soil basic chemical properties
2.5. Statistical analyses
Soil pH was measured (1:2 soil-to-water ratio) using an Accumet AB pH meter (Fisher Scientific, Hampton, NH). Available N (AN) was determined by extracting soil with a 2 mol L−1 KCl solution at 1:5 soil-to-
One replication of 0 AUM ha−1 in July was excluded from statistical analyses due to bad sequence coverage. Directed network analysis was 2
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performed to visualize the OTU distribution across a taxonomic tree with Cytoscape (Version 3.3.0) software (National Institute of General Medical Sciences (NIGMS), Bethesda, MD, USA). Individual nodes in the dendrogram correspond to OTUs and the size of the pink nodes indicates mean relative abundance of the OTU. Line edges connecting the nodes represent the taxonomic path from the domain to OTU level. The OTUs were placed at the level of the lowest possible assignment. All the analyses were performed by R version 3.2.3 (R Core Team, 2013). Univariate permutational analysis of variances (PERMANOVA) with 999 permutations test was performed to analyze the effect of grazing intensity and season factors on on soil bacterial α-diversity and soil physicochemical properties. The effect of grazing intensity on soil bacterial α-diversity index and soil physicochemical properties were determined by univariate Analysis of Variance (ANOVA) and when significant grazing effects were detected the differences among them were detemined by Tukey’s honestly significant difference (HSD) test. The P values in the Tukey’s HSD test were adjusted by the BenjaminiHochberg false discovery rate correction. Multivariate PERMANOVA with 999 permutations test were performed to analyze the effect of grazing intensity and season factors on soil bacterial community composition based on weighted Unifrac distance. Principal Coordinate Analyses (PCoA) based on the weighted Unifrac distance was used to visualize the patterns of bacterial community distribution in relation to grazing intensity. Dissimilarity in the bacterial community composition between pairwise grazing intensities were investigated by multivariate PERMANOVA, in which the option “strata” in the R package “vegan” was performed to constrain permutation of the grazing intensity treatment within the same season. The significant differences of bacterial abundance between the different grazing intensities were performed by the STAMP software. Statistical significance was estimated with the Post-hoc test for p ≤ 0.05, using Benjamini-Hochberg FDR correction method for the adjustment of pvalues.
Table 2 Effect of grazing intensity on soil bacterial community composition after more than six decades of cattle grazing in the foothills of the Rocky Mountains, Alberta, Canada. Main testa
F
P
Grazing intensity (F2,33) Season (F1,33) Grazing intensity × Season (F2,33) Pairwise comparisonsb 0 vs. 2.4AUM ha−1 0 vs. 4.8 AUM ha−1 2.4 vs. 4.8 AUM ha−1
6.2 17.1 2.1
0.001 0.001 0.03
1.73 4.94 4.96
0.01 0.001 0.001
Abbreviation: AUM, Animal unit month. a The effects of grazing intensity, season, and their interactions were determined by multivariate permutational analysis of variance (PERMANOVA; (PERMANOVA; degrees of freedom for each factor and residuals are given in brackets). Grazing intensities were 0 (ungrazed control), 2.4 (moderate grazing intensity) and 4.8 AUM ha−1 (heavy grazing intensity), and season factors were summer (July sampling) and fall (October sampling). b Pairwise comparisons were performed by multivariate permutational analysis of variance (PERMANOVA) and constrained the permutation of samples within each season group.
(Table 1). Grazing intensity significantly affected the soil bacterial evenness (Heip_e and Simpson_e) and diversity (Shannon and Simpson) indices, which were all significantly lower with heavy grazing (4.8 AUM ha−1) than the other two treatments (Table 1). No significant differences were found between the ungrazed control (0 AUM ha−1) and moderate (2.4 AUM ha−1) grazing treatments for soil bacterial evenness and diversity indices. 3.2. The effect of long-term (64 years) grazing on soil bacterial community composition
3. Results
Grazing intensity, sampling season and the grazing intensity × sampling season interaction all significantly affected soil bacterial community composition (Table 2). The PCoA ordination mainly separated July and October soil samples on the first axis (Fig. 1), explaining 53.51% of the total variation. The influence of grazing intensity on soil bacterial community composition became evident on the second axis (Fig. 1), which explained 19.71% of the total variation. The heavy grazing treatment resulted in significantly distinct clusters from
3.1. The effect of long-term (64 years) grazing on soil bacterial α-diversity Sampling season significantly affected the soil bacterial OTUs (Table 1). However, there were no significant differences in bacterial OTUs among grazing intensity treatments (Table 1). The Chao1 richness index showed a similar result, also not affected by grazing intensity
Table 1 Effect of grazing intensity on soil bacterial α-diversity after more than six decades of cattle grazing in the foothills of the Rocky Mountains, Alberta, Canada. Main testa
Richness
−1
Diversity
Observed OTUs F(P)
Chao1 F(P)
Heip_e F(P)
Simpson_e F(P)
Shannon F(P)
Simpson F(P)
1.6 (0.23) 63.4 (< 0.001) 0.4 (0.71)
1.8 (0.18) 27.8 (< 0.001) 0.5 (0.63)
12.8 (< 0.001) 22.4 (< 0.001) 0.2 (0.81)
6.2 (0.005) 0.0 (0.92) 0.6 (0.56)
12.5 (< 0.001) 33.3 (< 0.001) 1.5 (0.25)
6.4 (0.004) 3.0 (0.09) 0.0 (0.98)
b
Mean ± s.d.
Mean ± s.d.
Mean ± s.d.
Mean ± s.d.
Mean ± s.d.
Mean ± s.d.
c
4892 ± 271 a 4705 ± 345 a 4445 ± 532 a
19088 ± 865 a 17985 ± 1574 a 17860 ± 2628 a
0.278 ± 0.025 a 0.261 ± 0.032 a 0.226 ± 0.035 b
0.054 ± 0.005 a 0.050 ± 0.011 a 0.041 ± 0.007 b
10.40 ± 0.21 a 10.25 ± 0.28 a 9.94 ± 0.39 b
0.997 ± 0.001 a 0.996 ± 0.001 a 0.994 ± 0.001 b
Grazing intensity (F2,33) Season (F1,33) Grazing intensity × Season (F2,33) Multiple comparison
Evenness
0 AUM ha (n = 7) 2.4 AUM ha−1 (n = 16) −1 (n = 16) 4.8 AUM ha
Abbreviation: AUM, Animal unit month. a The effects of grazing intensity, season, and their interactions were determined by univariate permutational analysis of variance (PERMANOVA; degrees of freedom for each factor and residuals are given in brackets). Values represent the pseudo-F ratio (F) and the level of significance (P). Grazing intensities were 0 (ungrazed control), 2.4 (moderate grazing intensity) and 4.8 AUM ha−1 (heavy grazing intensity), and season factors were summer (July sampling) and fall (October sampling). b Mean value of each grazing intensity. Means within a column that do not share a letter are significantly different at P < 0.05 assessed by Tukey’s HSD test. Pvalues < 0.05 are shown in bold. c One out of four replications for 0 AUM ha−1 in July was excluded from statistical analysis due to bad sequence coverage, which resulted in seven replications for 0 AUM ha−1 in both July and October. 3
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the other two grazing intensity treatments (PERMANOVA: F > 4.9, p = 0.001) (Fig. 1 and Table 2), and the ungrazed control and moderate grazing treatments also showed significantly different bacterial community composition (PERMANOVA: F = 1.73, p = 0.01) (Fig. 1 and Table 2). 3.3. The effect of long-term (64 years) grazing on relative abundance of major bacterial taxa Overall, 16S rRNA sequences were assigned to 19 major bacterial phyla (Fig. 2). The dominant phyla were Actinobacteria (mean relative abundance: 29.7%), Acidobacteria (19.8%), Proteobacteria (16.0%), Chloroflexi (13.7%), Planctomycete (5.2%), Gemmatimonadetes (3.3%), Verrucomicrobia (2.0%) and Bacteroidetes (1.1%), which accounted for more than 90% of the total bacterial relative abundance (Fig. 2). Most abundances of the bacterial taxa were similar between the ungrazed control and the moderate grazing treatment, except WS3 (Fig. 3) and Anaerolineae (Chloroflexi) (Fig. 4), which showed greater abundance with the ungrazed control than the moderate grazing treatment. Compared to the control and moderate grazing treatments, the heavy grazing treatment significantly decreased the relative abundances of Bacteroidetes, Chlorobi, Nitrospirae and Proteobacteria at the phylum level (Fig. 3), as well as Acidobacteria-6 and iii1-8 (Acidobacteria), Alphaproteobacteria, Betaproteobacteria, Deltaproteobacteria and Gammaproteobacteria (Proteobacteria), Chloroflexi and TK17 (Chloroflexi), Nitrospira (Nitrospirae), OPB56 and SJA-28 (Chlorobi), Pedosphaerae and Verrucomicrobiae (Verrucomicrobia), Saprospirae (Bacteroidetes), 028H05-P-BN-P5, C6 and OM190
Fig. 1. Principal coordination analysis (PCoA) of soil bacterial community composition as affected by sampling season and grazing intensity after more than six decades of cattle grazing in the foothills of the Rocky Mountains, Alberta, Canada. Abbreviation: AUM, Animal unit month.
Fig. 2. The distribution of soil bacterial operational taxonomic units (OTUs) across taxonomic branches after more than six decades of cattle grazing in the foothills of the Rocky Mountains, Alberta, Canada. Individual nodes in the dendrogram correspond to OTUs and size of the pink nodes indicates mean relative abundance of the OTU. Lines that connect the nodes represent the taxonomic path from the domain to OTU level. The OTUs were placed at the level of the lowest possible assignment. Numbers in the brackets are the average relative abundance of each phylum. 4
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Fig. 3. Significant differences of phyla level bacterial abundances among the different grazing intensities [0 (ungrazed control), 2.4 (moderate grazing intensity) and 4.8 AUM ha−1 (heavy grazing intensity)] after more than six decades of cattle grazing in the foothills of the Rocky Mountains, Alberta, Canada. Bars on the left represent the proportion of each bacterial phylum abundance in the grazing treatments. Bacterial abundance differences with a q-value of < 0.05 were considered to be significant. Q-values are from the adjustment of p-values by the Benjamini-Hochberg method. Abbreviation: AUM, Animal unit month.
(Planctomycetes) at the class level (Fig. 4). However, the relative abundances of the Actinobacteria phylum (Fig. 3) and Rubrobacteria class (Actinobacteria) (Fig. 4) were greater with heavy grazing than the other two grazing intensity treatments.
previous research also found distinct soil bacterial α-diversity and community composition was affected by sampling season near the study site (Zhang et al., 2018b). Such differences were mainly attributed to changes in temperature, precipitation, and/or plant biomass. Warmer seasons were always associated with greater soil temperature, precipitation and plant biomass, which drives greater soil microbial activity and bacterial diversity (Yao et al., 2011; Zhou et al., 2017; Zhang et al., 2018b). Nevertheless, the long-term (64 years) effects of cattle grazing on soil bacterial community composition were similar in the two sampling seasons (Fig. 1 and Table 2), which provides robust evidence to evaluate the effect of different grazing intensities on soil bacterial α-diversity and community composition. In the current study, cattle grazing at moderate and heavy grazing intensities for 64 years (1949–2013) provided a unique opportunity to evaluate the effect of long-term grazing intensity on soil bacterial diversity. This study shows that the effects of long-term grazing on soil bacterial α-diversity and community composition were largely dependent on grazing intensity and varied significantly between the nongrazed control and heavy grazing intensity, with no observed differences between moderate grazing and the ungrazed control. Compared to the control, heavy grazing intensity significantly decreased soil bacterial evenness and diversity, while there were no significant differences between moderate grazing and the control (Table 1). These results are consistent with previous studies that found heavy grazing significantly reduced all soil bacterial diversity indices in the grasslands of northeast China and southern New Zealand (Qi et al., 2011; Qu et al.,
3.4. Relationships between soil physicochemical properties and bacterial community composition Grazing intensity significantly affected soil moisture, TN, AN, TP, AP and SOC, while soil moisture, AN and AP were also significantly affected by sampling season (Table 3). Overall, heavy grazing led to significantly lower soil moisture, TN, AN, and SOC (Table 3) than moderate grazing and the ungrazed control. Moderate grazing had lower soil moisture than the control treatment (Table 3). Distance-based RDA model analysis shows that individual soil physicochemical properties explained the changes in soil bacterial community composition (Table 4). Soil AN, moisture, SOC and TN had significant influence on the soil bacterial community composition, explaining 8.01%, 7.03%, 5.25% and 4.39% of the total variance, respectively (Table 4). 4. Discussion Sampling season appeared to significantly affect soil bacterial richness, Heip_e evenness index and Shannon diversity index (Table 1), as well as bacterial community composition (Table 2 and Fig. 1). Our 5
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Fig. 4. Significant differences in Class level bacterial abundance among the different cattle grazing intensities [0 (ungrazed control), 2.4 (moderate grazing intensity) and 4.8 AUM ha−1 (heavy grazing intensity)] after more than six decades of cattle grazing in the foothills of the Rocky Mountains, Alberta, Canada. Bars on the left represent the proportion of each bacterial phylum abundance in the treatments. Bacterial abundance differences with a q-value of < 0.05 were considered to be significant. Q-values are from the adjustment of p-values by the Benjamini-Hochberg method. Abbreviation: AUM, Animal unit month.
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Table 3 Effect of grazing intensity on soil physico-chemical properties after more than six decades of cattle grazing in the foothills of the Rocky Mountains, Alberta, Canada. Main test
a
Moisture F(P)
pH F(P)
TN F(P)
AN F(P)
TP F(P)
AP F(P)
SOC F(P)
C:N F(P)
Grazing intensity (F2,33) Season (F1,33) Grazing intensity × Season (F2,33)
17.0 (< 0.001) 5.5 (0.03) 0.8 (0.45)
2.4 (0.11) 0.0 (0.98) 0.0 (1.00)
7.6 (0.002) 0.4 (0.53) 0.32 (0.73)
14.9 (< 0.001) 33.8 (< 0.001) 7.5 (0.002)
8.4 (0.001) 0.0 (0.85) 0.0 (0.97)
3.1 (0.02) 8.3 (0.007) 0.2 (0.85)
14.4 (< 0.001) 0.4 (0.54) 0.3 (0.74)
2.5 (0.10) 0.0 (0.99) 0.0 (1.00)
Multiple comparisonb
Mean ± s.d. %
Mean ± s.d.
Mean ± s.d. g kg−1
Mean ± s.d. mg kg−1
Mean ± s.d. g kg−1
Mean ± s.d. mg kg−1
Mean ± s.d. g kg−1
Mean ± s.d. mg kg−1
0 AUM ha−1 (n = 7)c 2.4 AUM ha−1 (n = 16) 4.8 AUM ha−1 (n = 16)
42.1 ± 5.3 a 33.1 ± 6.8 b 27.5 ± 3.9 c
6.3 ± 0.2 a 6.5 ± 0.3 a 6.3 ± 0.2 a
6.9 ± 1.3 a 6.9 ± 0.6 a 5.9 ± 0.6 b
16.0 ± 5.4 a 15.9 ± 6.5 a 10.1 ± 2.9 b
0.87 ± 0.09 ab 0.91 ± 0.13 a 0.76 ± 0.08 b
1.9 ± 0.6 ab 2.5 ± 1.1 a 1.7 ± 0.9 b
80.6 ± 9.0 a 85.7 ± 8.1 a 69.1 ± 7.7 b
11.6 ± 0.4 a 12.5 ± 1.8 a 11.7 ± 0.4 a
Abbreviation: AUM, Animal unit month. a The effects of grazing intensity, season, and their interactions were determined by univariate permutational analysis of variance (PERMANOVA; degrees of freedom for each factor and residuals are given in brackets). Values represent the pseudo-F ratio (F) and the level of significance (P). Grazing intensities were 0 (ungrazed control), 2.4 (moderate grazing intensity) and 4.8 AUM ha−1 (heavy grazing intensity), and season factors were summer (July sampling) and fall (October sampling). b Mean value of each grazing intensity. Means within a column that do not share a letter are significantly different at P < 0.05 as assessed by Tukey’s HSD test. Pvalues < 0.05 are shown in bold. Abbreviations: AN, available nitrogen; AP, available phosphorus; C:N, soil organic carbon to total nitrogen ratio; SOC, soil organic carbon; TN, total nitrogen; TP, total phosphorus. c One out of four replications for 0 AUM ha−1 in July was excluded from statistical analysis due to bad sequence coverage, which resulted in seven replications for 0 AUM ha−1 in both July and October. Table 4 Relationship between soil physicochemical properties and bacterial community composition after more than six decades of cattle grazing in the foothills of the Rocky Mountains, Alberta, Canada. dbRDA analysis
Moisture
pH
TN
AN
TP
AP
SOC
C:N
VC P-value
7.03% 0.01
2.20% 0.33
4.39% 0.04
8.01% 0.002
2.29% 0.30
3.03% 0.17
5.25% 0.02
4.27% 0.06
The variance component (VC) for each physicochemical soil property explaining soil bacterial community composition was performed by distance-based redundancy analysis (dbRDA). Significant P-values were performed by marginal tests and are shown in parentheses. P-values < 0.05 are shown in bold. Abbreviations: AN, available nitrogen; AUM, animal unit month; AP, available phosphorus; C:N, soil organic carbon to total nitrogen ratio; SOC, soil organic carbon; TN, total nitrogen; TP, total phosphorus.
heterotrophic and utilize soil C sources or decomposing plant material for their growth (Dwivedi et al., 2017; Morriën et al., 2017). Although soil moisture and SOC content were important drivers of soil bacterial community composition, this study showed that the soil available N level was the most pronounced factor shaping the soil bacterial community (Table 4). Similar to previous studies (Ingram et al., 2008; Qu et al., 2016), the current study also provides evidence of greater soil N losses with heavy grazing intensity than moderate grazing or the ungrazed control (Table 3). Ingram et al. (2008) reported that heavy grazing intensity resulted in a loss of approximately 50% of aboveground plant N, while only 10% of this N was lost with light grazing intensity. About 80–95% of consumed plant N is estimated to be returned via excreta but a large proportion of N in livestock excreta is in organic form and is unable to be taken up by plants, while a large proportion of ammonium and nitrate ends up being either volatilized, leached or denitrified (Ingram et al., 2008). The changes in soil C and N levels due to heavy grazing intensity will inevitably influence the soil bacterial composition by decreasing substrate availability for soil microbes. An oligotroph-copiotroph strategy shift of soil bacteria with changes in soil nutrient availability has been observed, i.e., high nutrient availability promotes the growth of copiotrophic organisms while low nutrient levels lead to an increase of slow-growing oligotrophic microorganisms (Fierer et al., 2012). In the present study, high intensity grazing had lower Bacteroidetes, Nitrospirae and Proteobacteria abundances (Fig. 3), which was mainly due to reduced soil nutrients. These bacterial groups are considered copiotrophic microorganisms (Fierer et al., 2007, 2012) and were found to be positively correlated with soil C and N levels (Fierer et al., 2012; Ling et al., 2017; Dai et al., 2018). The Actinobacteria are one of the few groups of saprotrophic
2016; Zhong et al., 2016). A meta-analysis also reported that heavy grazing intensity significantly decreased soil bacterial community size, while light and moderate grazing intensity had no effect on soil bacterial community size (Zhao et al., 2017). Previous studies all clearly indicate that the changes in soil bacterial α-diversity largely depend on changes in soil bacterial community composition (Qu et al., 2016; Zhang et al., 2018b). In the present study, both PCoA ordination (Fig. 1) and PERMANOVA analyses (Table 2) primarily showed that the heavy grazing intensity had the greatest differences compared to the other two treatments. These results appear mainly attributable to the changes in soil physicochemical properties induced by more than six decades of cattle grazing. Heavy grazing intensity tended to reduce soil C and N concentrations, as well as soil moisture content, relative to other two grazing treatments (Table 3). Soil AN, moisture, SOC and TN were found to be the most important drivers of bacterial community composition, explaining 17.7% of total soil bacterial community variance (Table 4). This study provides more evidence that soil moisture is one of the strongest factors in shaping soil bacterial richness and composition in this semi-arid region of Canada (Zhang et al., 2018b). Heavy grazing intensity has been found to reduce soil moisture by decreasing the canopy cover, which enhances solar radiation reaching the soil surface compared to light grazing or the ungrazed control (Odriozola et al., 2014; Rong et al., 2015), which impacts soil bacterial community composition (Manzoni et al., 2012; Hartmann et al., 2017). Furthermore, heavy grazing may increase the loss of photosynthetic tissue and reduce below-ground C inputs through lower plant productivity, thus leading to declining plant material and C content in soil (Kawasaki et al., 2012; Aldezabal et al., 2015; Byrnes et al., 2018). Subsequently, soil bacterial numbers may decrease as bacteria are mostly 7
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microorganisms and are key mediators of plant litter decay. Previous studies have reported that the abundance of Actinobacteria is regulated by soil N levels, and that higher soil N concentration always enhanced the growth of Actinobacteria (Dai et al., 2018; Zhang et al., 2018b). In contrast, this study found that heavy grazing intensity with the lowest N level had the greatest Actinobacteria abundance (Fig. 3). The underlying mechanism might be that heavy grazing intensity caused a greater proportion of stem-leaf material to enter the soil, which would stimulate the growth of the Actinobacteria group to decompose the plant litter with higher lignin content (Eisenlord and Zak, 2010). It may also be possible that greater fecal matter deposition high in partially digested plant residues with heavier grazing intensity provided recalcitrant substrate for Actinobacteria to decompose.
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A decade of irrigation transforms the soil microbiome of a semi‐arid pine forest. Mol. Ecol. 26, 1190–1206. Ingram, L., Stahl, P., Schuman, G., Buyer, J., Vance, G., Ganjegunte, G., Welker, J., Derner, J., 2008. Grazing impacts on soil carbon and microbial communities in a mixed-grass ecosystem. Soil Sci. Soc. Am. J. 72, 939–948. Kawasaki, A., Watson, E.R., Kertesz, M.A., 2012. Indirect effects of polycyclic aromatic hydrocarbon contamination on microbial communities in legume and grass rhizospheres. Plant Soil 358, 169–182. Keeney, D.R., Nelson, D.W., 1982. Nitrogen–Inorganic forms. In: Page, A.L. (Ed.), Methods of Soil Analysis. Part 2, 2nd ed. ASA and SSSA, Madison, WI, pp. 643–698 Agron. Monogr. 9. Klumpp, K., Fontaine, S., Attard, E., Le Roux, X., Gleixner, G., Soussana, J.F., 2009. Grazing triggers soil carbon loss by altering plant roots and their control on soil microbial community. J. Ecol. 97, 876–885. Kunin, V., Engelbrektson, A., Ochman, H., Hugenholtz, P., 2010. 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The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 41 (Database issue), 590–596. Qu, T.B., Du, W.-C., Yuan, X., Yang, Z.-M., Liu, D.-B., Wang, D.-L., Yu, L.J., 2016. Impacts of grazing intensity and plant community composition on soil bacterial community diversity in a steppe grassland. PLoS One 11, e0159680. R Core Team, 2013. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna. Rong, Y., Ma, L., Johnson, D.A., Yuan, F., 2015. Soil respiration patterns for four major land-use types of the agro-pastoral region of northern China. Agric. Ecosyst. Environ. 213, 142–150. Schulz, S., Brankatschk, R., Dümig, A., Kögel-Knabner, I., Schloter, M., Zeyer, J., 2013. The role of microorganisms at different stages of ecosystem development for soil formation. Biogeosciences 10, 3983–3996. Stark, S., Männistö, M.K., Ganzert, L., Tiirola, M., Häggblom, M.M., 2015. Grazing intensity in subarctic tundra affects the temperature adaptation of soil microbial communities. Soil Biol. Biochem. 84, 147–157. Steffens, M., Kölbl, A., Totsche, K.U., Kögel-Knabner, I., 2008. Grazing effects on soil chemical and physical properties in a semiarid steppe of Inner Mongolia (PR China). Geoderma 143, 63–72. Wang, Z., Zhang, Q., Staley, C., Gao, H., Ishii, S., Wei, X., Liu, J., Cheng, J., Hao, M., Sadowsky, M.J., 2019. Impact of long-term grazing exclusion on soil microbial community composition and nutrient availability. Biol. Fertil. Soils 55, 121–134. Yao, H., Bowman, D., Shi, W., 2011. Seasonal variations of soil microbial biomass and activity in warm- and cool-season turfgrass systems. Soil Biol. Biochem. 43, 1536–1543. Zhang, B., Beck, R., Pan, Q., Zhao, M., Hao, X., 2019. Soil physical and chemical properties in response to long-term cattle grazing on sloped rough fescue grassland in the foothills of the Rocky Mountains, Alberta. Geoderma 346, 75–83. Zhang, B., Thomas, B.W., Beck, R., Liu, K., Zhao, M., Hao, X., 2018a. Labile soil organic matter in response to long-term cattle grazing on sloped rough fescue grassland in the foothills of the Rocky Mountains, Alberta. Geoderma 318, 9–15. Zhang, Y., Hao, X., Alexander, T.W., Thomas, B.W., Shi, X., Lupwayi, N.Z., 2018b. Long-
5. Conclusions The soil bacterial community composition shifted between summer and fall seasons, but the grazing intensity effect was similar each season. Soil bacterial evenness and diversity indices significantly decreased after 64 years of heavy grazing, compared to moderate grazing intensity and the ungrazed control. Long-term heavy grazing significantly decreased the relative abundances of Bacteroidetes, Chlorobi, Nitrospirae and Proteobacteria, while significantly increasing the relative abundance of Actinobacteria. Heavy grazing decreased soil moisture, C and N levels, and shifted the relative abundances of major bacterial taxa leading to a distinct soil bacterial community composition. Moderate grazing intensity did not alter the soil bacterial community composition compared to the ungrazed control. This suggests that multi-decadal grazing at moderate cattle stocking rates does not impact the soil bacterial community composition in the foothills of the Rocky Mountains, Canada. The impacts of grazing on the soil bacterial community composition are largely driven by how the intensity of grazing affects soil physicochemical properties. Declaration of Competing Interest The Authors declare there are no conflicts of interest to report. Acknowledgements Funding for this project was provided by Agriculture and Agri-Food Growing Forward 2 (J-000251 and J-001360). Support was also provided by China Agriculture Research System-Green Manure (CARS-22G-13) and the National Natural Science Foundation of China (31902116). References Aldezabal, A., Moragues, L., Odriozola, I., Mijangos, I., 2015. Impact of grazing abandonment on plant and soil microbial communities in an Atlantic mountain grassland. Appl. Soil Ecol. 96, 251–260. Byrnes, R.C., Eastburn, D.J., Tate, K.W., Roche, L.M., 2018. A global meta-analysis of grazing impacts on soil health indicators. J. Environ. Qual. 47, 758–765. Caporaso, J.G., Lauber, C.L., Walters, W.A., Berg-Lyons, D., Lozupone, C.A., Turnbaugh, P.J., Fierer, N., Knight, R., 2011. Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. Proc. Natl. Acad. Sci. U. S. A. 108, 4516–4522. Dai, Z., Su, W., Chen, H., Barberán, A., Zhao, H., Yu, M., Yu, L., Brookes, P.C., Schadt, C.W., Chang, S.X., 2018. Long‐term nitrogen fertilization decreases bacterial diversity and favors the growth of Actinobacteria and Proteobacteria in agro‐ecosystems across the globe. Glob. Change Biol. 24, 3452–3461. Dlamini, P., Chivenge, P., Chaplot, V., 2016. Overgrazing decreases soil organic carbon stocks the most under dry climates and low soil pH: a meta-analysis shows. Agric. Ecosyst. Environ. 221, 258–269. Dormaar, J.F., Willms, W.D., 1998. Effect of forty-four years of grazing on fescue grassland soils. J. Range Manage. 51, 122–126. Dwivedi, D., Riley, W., Torn, M., Spycher, N., Maggi, F., Tang, J., 2017. Mineral properties, microbes, transport, and plant-input profiles control vertical distribution and age of soil carbon stocks. Soil Biol. Biochem. 107, 244–259. Edgar, R., 2013. UPARSE: highly accurate OTU sequences from microbial amplicon reads. Nat. Methods 10, 996–998. Edgar, R., Haas, B., Clemente, J., Quince, C., Knight, R., 2011. UCHIME improves
8
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Y. Zhang, et al. term and legacy effects of manure application on soil microbial community composition. Biol. Fertil. Soils 54, 269–283. Zhao, F., Ren, C., Shelton, S., Wang, Z., Pang, G., Chen, J., Wang, J., 2017. Grazing intensity influence soil microbial communities and their implications for soil respiration. Agric. Ecosyst. Environ. 249, 50–56. Zhong, L., Hoogendoorn, C.J., Bowatte, S., Li, F.Y., Wang, Y., Luo, D., 2016. Slope class
and grazing intensity effects on microorganisms and nitrogen transformation processes responsible for nitrous oxide emissions from hill pastures. Agric. Ecosyst. Environ. 217, 70–78. Zhou, G., Zhou, X., He, Y., Shao, J., Hu, Z., Liu, R., Zhou, H., Hosseinibai, S., 2017. Grazing intensity significantly affects belowground carbon and nitrogen cycling in grassland ecosystems: a meta‐analysis. Glob. Change Biol. 23, 1167–1179.
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Applied Soil Ecology journal homepage: www.elsevier.com/locate/apsoil
Heavy grazing over 64 years reduced soil bacterial diversity in the foothills of the Rocky Mountains, Canada Yuting Zhanga,b, Xinlei Gaoc, Xiying Haob, Trevor W. Alexanderb, Xiaojun Shia, Long Jinb, Ben W. Thomasd,* a
College of Resources and Environment, Southwest University, Chongqing 400716, China Agriculture and Agri-Food Canada, Lethbridge Research and Development Centre, Lethbridge, Alberta, T1J 4B1, Canada c College of Agricultural Sciences, Chifeng University, Hongshan District, Chifeng, Inner Mongolia, 024000, China d Agriculture and Agri-Food Canada, Agassiz Research and Development Centre, Agassiz, British Columbia V0M 1A0, Canada b
ARTICLE INFO
ABSTRACT
Keywords: Bacterial community Foothills grassland Grazing intensity Herbivory
Grazing is one of the most widespread grassland management strategies. However, the effects of over six decades of different grazing intensities on soil bacterial community composition in the foothills of the Rocky Mountains are uncertain. We analyzed the bacterial community composition in soil samples collected in both summer and fall, 64 years after a long-term grazing intensity study was initiated in 1949. Grazing intensity treatments were (i) 0 animal-unit months (AUM) ha−1, (ii) 2.4 AUM ha−1 and (iii) 4.8 AUM ha−1, which represented the control, moderate and heavy grazing intensities, respectively. The evenness and diversity indices decreased with heavy grazing intensity relative to the other treatments in both summer and fall. In summer and fall, heavy grazing significantly shifted the bacterial community composition compared to the other treatments. Heavy grazing intensity significantly decreased the relative abundances of Bacteroidetes, Chlorobi, Nitrospirae and Proteobacteria, but significantly increased the relative abundance of Actinobacteria. Principal Coordinate Analyses revealed that available nitrogen, moisture content, total nitrogen and organic carbon were the primary environmental factors affecting the soil bacterial community composition. This study suggests that the effects of grazing on soil bacterial community composition are largely dependent on changes in soil physicochemical properties induced by the intensity of grazing over periods of six decades.
1. Introduction
However, uncertainty about the responses of the soil bacterial community composition to long-term cattle grazing as well as the underlying mechanisms, including interactions among site-specific edaphic properties and environmental conditions, remains unresolved (Dlamini et al., 2016; Zhao et al., 2017). Microorganisms play an important role in the decomposition of organic matter, transformation of nutrients and maintenance of ecosystem stability (Schulz et al., 2013). Grazing livestock may potentially affect the relative abundance of bacterial taxa and their functional traits through altering plant community composition and biomass, fecal and urine deposition, soil physicochemical properties, grazing period and other factors (Qu et al., 2016; Zhao et al., 2017; Wang et al., 2019). These factors may have positive, neutral or negative effects on soil bacterial community composition. A case study conducted on the subarctic tundra found that ungulate grazing altered substrate availability, which had important consequences on soil microbial community composition (Stark et al., 2015). Qu et al. (2016) reported that heavy
Natural grasslands occupy about 40% of Earth’s land surface (Dlamini et al., 2016). Grazing animals on natural grassland is a longstanding and widespread human-driven grassland management strategy. In western Canada, rough fescue grasslands in the foothills of the Rocky Mountains are primarily managed for cattle grazing (Gao et al., 2018). A growing number of studies show that the health of grassland ecosystems is strongly affected by the intensity of cattle grazing (Zhou et al., 2017; Byrnes et al., 2018). Previous studies in this area reported that long-term excessive cattle grazing may degrade grassland soils, alter plant community composition and increase the release of soil greenhouse gases (Dormaar and Willms, 1998; Li et al., 2012; Gao et al., 2018). Five to six decades of heavy grazing clearly shifted the soil organic matter content, soil mineral nutrition, soil texture and soil base cations of rough fescue grassland in the foothills of the Rocky Mountains (Li et al., 2009, 2012; Zhang et al., 2018a, 2019).
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Corresponding author. E-mail address: [email protected] (B.W. Thomas).
https://doi.org/10.1016/j.apsoil.2019.09.011 Received 17 June 2019; Received in revised form 11 September 2019; Accepted 16 September 2019 0929-1393/ Crown Copyright © 2019 Published by Elsevier B.V. All rights reserved.
Please cite this article as: Yuting Zhang, et al., Applied Soil Ecology, https://doi.org/10.1016/j.apsoil.2019.09.011
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grazing intensity reduced soil bacterial diversity indices in a steppe grassland of Northeast China due to changes in plant community composition, soil total nitrogen/phosphorus (N/P) ratio, electrical conductivity (EC), pH and total N. In a semiarid steppe located in Inner Mongolia, China, researchers also found that heavy grazing intensity decreased soil carbon (C) and N content, which subsequently reduced soil bacterial diversity and community size (Steffens et al., 2008). The energy and nutrients required by soil bacteria are frequently obtained from plant litter or through root exudates from living plants and root decay, which are affected by grazing intensity in grassland ecosystems (Klumpp et al., 2009; Byrnes et al., 2018). Recent data from a metaanalysis demonstrated that the effects of grazing on soil microbial community sizes are largely dependent on grazing intensity (Zhao et al., 2017). Although the effects of grazing intensity on soil microbes have been widely reported across different grassland ecosystems, there is limited information about how long-term cattle grazing impacts bacterial community composition of grassland soils in the foothills of the Rocky Mountains in Canada. To address this knowledge gap, we utilized a 64-year (1949–2013) grazing intensity field trial conducted on rough fescue grassland within the foothills of the Rocky Mountains, Alberta, Canada. The experimental treatments included grazing exclusion (ungrazed control), moderate grazing and heavy grazing.The objectives of this study were to (a) determine the effects of over 60 years of different cattle grazing intensities on soil bacterial α diversity and community composition, and (b) investigate the main soil environmental factors that drive soil bacterial community composition.
KCl ratio (Keeney and Nelson, 1982). The AN concentration was determined with a micro-plate reader (Multiscan GO, Thermo Scientific, Nepean, ON). Available P (AP) was determined by extracting soil with 0.5 mol L-1 NaHCO3 solution (Olsen et al., 1954) at 1:10 soil-to-NaHCO3 ratio. The AP concentrations were determined with an automated colorimeter (Auto-Analyzer III, Bran + Luebbe, Norderstedt, Germany). For soil organic carbon (SOC), total N (TN) and total P (TP) determination, sub-samples were finely ground to pass through a 0.15-mm mesh. The SOC and TN were determined by dry combustion (NA 1500 series 2, Carlo Erba Instruments, Milan, Italy). Soil TP concentration was determined by a Discrete Analyzer (Easy-Chem Pro, Systea Analytical Technologies, Anagni, Italy) after being digested by H2SO4 and H2O2. 2.3. DNA extraction, Amplicon library preparation, and MiSeq sequencing Soil DNA was extracted from 0.25 g fresh soil using the MoBioPowerSoil@ DNA Isolation Kit (MoBio Laboratories, Inc., USA) according to the manufacturer’s instructions. The extracted DNA concentrations were quantified using a NanoDrop 2000 (Thermo Fisher Scientific, USA) and checked using a 1% agarose gel electrophoresis, and then stored at −20 °C. The V4 variable region of 16S rRNA gene was amplified using the primer set 515 F (5′-GTGCCAGCMGCCGCGGTAA-3′)/806R (5′-GGACTACHVGGGTWTCTAAT-3′) (Caporaso et al., 2011), with 8-bp errorcorrecting barcode on the forward primer to characterize each sample. DNA was amplified in triplicate. All PCR amplifications were performed using the HotStar Taq Plus Master Mix Kit (Qiagen, USA) under the following conditions: 94 °C for 3 min, followed by 28 cycles of 94 °C for 30 s, 53 °C for 40 s and 72 °C for 1 min, after which a final elongation step at 72 °C for 5 min was performed. After amplification, PCR products were checked in 2% agarose gel to determine the success of amplification and the relative intensity of bands. Multiple samples were pooled together in equal proportions based on their molecular weight and DNA concentrations. Pooled Samples were purified using calibrated Ampure XP beads (Agencourt, Beckman Coulter, USA). Then, the pooled and purified PCR products were prepared into a DNA library following Illumina TruSeq DNA library protocol. Sequencing was performed at MR DNA (www.mrdnalab.com, Shallowater, TX, USA) on a MiSeq following the manufacturer’s guidelines.
2. Materials and methods 2.1. Experimental design and soil sampling This long-term grazing study site was established in 1949 on a native grassland in the undulating Porcupine Hills, with altitudes varying from 1280 m to 1420 m, at an Agriculture and Agri-Food Canada Research substation (50°12′ N, 113°54′ W), near Stavely, Alberta, Canada in the Foothills of the Rocky Mountains. Rough fescue (Festuca campestris Rydb.) is the the dominant species in the climax community with Parry’s oatgrass (Danthonia parryi Scibn.) and Kentucky bluegrass (Poa pratensis L.) as co-dominant species. The soil is an Orthic Black Chernozem (Typic Haplustolls in US taxonomy) with a loam to clayloam texture. In 1949, two paddocks were constructed, with an area of 32 and 16 ha (Dormaar and Willms, 1998) and were stocked with 13 cattle and their calves for 6-months to produce two distinct moderate and heavy grazing intensities (2.4 and 4.8 animal unit month (AUM) ha−1, respectively). Cattle of the same age and breed (lactating Hereford-continental cross with calves) have been grazed from around midMay to mid-November each year since 1949. A non-grazed 0.8 ha paddock was also constructed in 1949 as a control (0 AUM ha−1). Four, eight and eight 15 m × 30 m subplots were randomly selected as pseudo-replicates in the 0, 2.4 and 4.8 AUM ha−1 paddocks, respectively. Soil samples were collected in both mid-July and midOctober 2013 to represent summer and fall seasons, respectively. The precipitation and mean air temperature in July and October were 89.5 mm/15.3 °C and 31.3 mm/5.4 °C, respectively. Briefly, six randomly selected 0–15 cm depth soil cores from each subplot were collected and thoroughly mixed to form one composite sample. Soil samples were sieved through a 2-mm mesh, and then either air dried for physicochemical property analyses or stored at −20 °C until DNA extraction.
2.4. Bioinformatics analyses The raw data were quality-filtered by QIIME (Version 1.9.1). Briefly, sequences were joined and depleted of barcodes and primers. The reads were then scanned with a 4-base wide sliding window and cut when the average quality per base dropped below 20. Sequences shorter than 150 bp and homo-polymers and ambiguous base calls longer than six nucleotides were removed. The Operational Taxonomic Units (OTUs) were clustered with 97% similarity using UPARSE (Edgar, 2013) and the chimeric sequences were then identified and removed using UCHIME (Edgar et al., 2011). The OTUs with 3 or fewer reads were removed as they potentially originated from sequencing artifacts (Kunin et al., 2010). The representative sequence for each OTU was picked and the taxonomic affiliation of each representative sequence was assigned by the Ribosomal Database Project classifier against the Silva (SSU123) 16S rRNA database (Quast et al., 2013). Soil bacterial αdiversities (observed OTUs, Chao1, Heip_e, Simpson_e, Shannon and Simpson index) were generated after randomly subsampling the sequences to an equal number. Bacterial-weighted UniFrac distances were calculated based on the phylogenetic information.
2.2. Determination of soil basic chemical properties
2.5. Statistical analyses
Soil pH was measured (1:2 soil-to-water ratio) using an Accumet AB pH meter (Fisher Scientific, Hampton, NH). Available N (AN) was determined by extracting soil with a 2 mol L−1 KCl solution at 1:5 soil-to-
One replication of 0 AUM ha−1 in July was excluded from statistical analyses due to bad sequence coverage. Directed network analysis was 2
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performed to visualize the OTU distribution across a taxonomic tree with Cytoscape (Version 3.3.0) software (National Institute of General Medical Sciences (NIGMS), Bethesda, MD, USA). Individual nodes in the dendrogram correspond to OTUs and the size of the pink nodes indicates mean relative abundance of the OTU. Line edges connecting the nodes represent the taxonomic path from the domain to OTU level. The OTUs were placed at the level of the lowest possible assignment. All the analyses were performed by R version 3.2.3 (R Core Team, 2013). Univariate permutational analysis of variances (PERMANOVA) with 999 permutations test was performed to analyze the effect of grazing intensity and season factors on on soil bacterial α-diversity and soil physicochemical properties. The effect of grazing intensity on soil bacterial α-diversity index and soil physicochemical properties were determined by univariate Analysis of Variance (ANOVA) and when significant grazing effects were detected the differences among them were detemined by Tukey’s honestly significant difference (HSD) test. The P values in the Tukey’s HSD test were adjusted by the BenjaminiHochberg false discovery rate correction. Multivariate PERMANOVA with 999 permutations test were performed to analyze the effect of grazing intensity and season factors on soil bacterial community composition based on weighted Unifrac distance. Principal Coordinate Analyses (PCoA) based on the weighted Unifrac distance was used to visualize the patterns of bacterial community distribution in relation to grazing intensity. Dissimilarity in the bacterial community composition between pairwise grazing intensities were investigated by multivariate PERMANOVA, in which the option “strata” in the R package “vegan” was performed to constrain permutation of the grazing intensity treatment within the same season. The significant differences of bacterial abundance between the different grazing intensities were performed by the STAMP software. Statistical significance was estimated with the Post-hoc test for p ≤ 0.05, using Benjamini-Hochberg FDR correction method for the adjustment of pvalues.
Table 2 Effect of grazing intensity on soil bacterial community composition after more than six decades of cattle grazing in the foothills of the Rocky Mountains, Alberta, Canada. Main testa
F
P
Grazing intensity (F2,33) Season (F1,33) Grazing intensity × Season (F2,33) Pairwise comparisonsb 0 vs. 2.4AUM ha−1 0 vs. 4.8 AUM ha−1 2.4 vs. 4.8 AUM ha−1
6.2 17.1 2.1
0.001 0.001 0.03
1.73 4.94 4.96
0.01 0.001 0.001
Abbreviation: AUM, Animal unit month. a The effects of grazing intensity, season, and their interactions were determined by multivariate permutational analysis of variance (PERMANOVA; (PERMANOVA; degrees of freedom for each factor and residuals are given in brackets). Grazing intensities were 0 (ungrazed control), 2.4 (moderate grazing intensity) and 4.8 AUM ha−1 (heavy grazing intensity), and season factors were summer (July sampling) and fall (October sampling). b Pairwise comparisons were performed by multivariate permutational analysis of variance (PERMANOVA) and constrained the permutation of samples within each season group.
(Table 1). Grazing intensity significantly affected the soil bacterial evenness (Heip_e and Simpson_e) and diversity (Shannon and Simpson) indices, which were all significantly lower with heavy grazing (4.8 AUM ha−1) than the other two treatments (Table 1). No significant differences were found between the ungrazed control (0 AUM ha−1) and moderate (2.4 AUM ha−1) grazing treatments for soil bacterial evenness and diversity indices. 3.2. The effect of long-term (64 years) grazing on soil bacterial community composition
3. Results
Grazing intensity, sampling season and the grazing intensity × sampling season interaction all significantly affected soil bacterial community composition (Table 2). The PCoA ordination mainly separated July and October soil samples on the first axis (Fig. 1), explaining 53.51% of the total variation. The influence of grazing intensity on soil bacterial community composition became evident on the second axis (Fig. 1), which explained 19.71% of the total variation. The heavy grazing treatment resulted in significantly distinct clusters from
3.1. The effect of long-term (64 years) grazing on soil bacterial α-diversity Sampling season significantly affected the soil bacterial OTUs (Table 1). However, there were no significant differences in bacterial OTUs among grazing intensity treatments (Table 1). The Chao1 richness index showed a similar result, also not affected by grazing intensity
Table 1 Effect of grazing intensity on soil bacterial α-diversity after more than six decades of cattle grazing in the foothills of the Rocky Mountains, Alberta, Canada. Main testa
Richness
−1
Diversity
Observed OTUs F(P)
Chao1 F(P)
Heip_e F(P)
Simpson_e F(P)
Shannon F(P)
Simpson F(P)
1.6 (0.23) 63.4 (< 0.001) 0.4 (0.71)
1.8 (0.18) 27.8 (< 0.001) 0.5 (0.63)
12.8 (< 0.001) 22.4 (< 0.001) 0.2 (0.81)
6.2 (0.005) 0.0 (0.92) 0.6 (0.56)
12.5 (< 0.001) 33.3 (< 0.001) 1.5 (0.25)
6.4 (0.004) 3.0 (0.09) 0.0 (0.98)
b
Mean ± s.d.
Mean ± s.d.
Mean ± s.d.
Mean ± s.d.
Mean ± s.d.
Mean ± s.d.
c
4892 ± 271 a 4705 ± 345 a 4445 ± 532 a
19088 ± 865 a 17985 ± 1574 a 17860 ± 2628 a
0.278 ± 0.025 a 0.261 ± 0.032 a 0.226 ± 0.035 b
0.054 ± 0.005 a 0.050 ± 0.011 a 0.041 ± 0.007 b
10.40 ± 0.21 a 10.25 ± 0.28 a 9.94 ± 0.39 b
0.997 ± 0.001 a 0.996 ± 0.001 a 0.994 ± 0.001 b
Grazing intensity (F2,33) Season (F1,33) Grazing intensity × Season (F2,33) Multiple comparison
Evenness
0 AUM ha (n = 7) 2.4 AUM ha−1 (n = 16) −1 (n = 16) 4.8 AUM ha
Abbreviation: AUM, Animal unit month. a The effects of grazing intensity, season, and their interactions were determined by univariate permutational analysis of variance (PERMANOVA; degrees of freedom for each factor and residuals are given in brackets). Values represent the pseudo-F ratio (F) and the level of significance (P). Grazing intensities were 0 (ungrazed control), 2.4 (moderate grazing intensity) and 4.8 AUM ha−1 (heavy grazing intensity), and season factors were summer (July sampling) and fall (October sampling). b Mean value of each grazing intensity. Means within a column that do not share a letter are significantly different at P < 0.05 assessed by Tukey’s HSD test. Pvalues < 0.05 are shown in bold. c One out of four replications for 0 AUM ha−1 in July was excluded from statistical analysis due to bad sequence coverage, which resulted in seven replications for 0 AUM ha−1 in both July and October. 3
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the other two grazing intensity treatments (PERMANOVA: F > 4.9, p = 0.001) (Fig. 1 and Table 2), and the ungrazed control and moderate grazing treatments also showed significantly different bacterial community composition (PERMANOVA: F = 1.73, p = 0.01) (Fig. 1 and Table 2). 3.3. The effect of long-term (64 years) grazing on relative abundance of major bacterial taxa Overall, 16S rRNA sequences were assigned to 19 major bacterial phyla (Fig. 2). The dominant phyla were Actinobacteria (mean relative abundance: 29.7%), Acidobacteria (19.8%), Proteobacteria (16.0%), Chloroflexi (13.7%), Planctomycete (5.2%), Gemmatimonadetes (3.3%), Verrucomicrobia (2.0%) and Bacteroidetes (1.1%), which accounted for more than 90% of the total bacterial relative abundance (Fig. 2). Most abundances of the bacterial taxa were similar between the ungrazed control and the moderate grazing treatment, except WS3 (Fig. 3) and Anaerolineae (Chloroflexi) (Fig. 4), which showed greater abundance with the ungrazed control than the moderate grazing treatment. Compared to the control and moderate grazing treatments, the heavy grazing treatment significantly decreased the relative abundances of Bacteroidetes, Chlorobi, Nitrospirae and Proteobacteria at the phylum level (Fig. 3), as well as Acidobacteria-6 and iii1-8 (Acidobacteria), Alphaproteobacteria, Betaproteobacteria, Deltaproteobacteria and Gammaproteobacteria (Proteobacteria), Chloroflexi and TK17 (Chloroflexi), Nitrospira (Nitrospirae), OPB56 and SJA-28 (Chlorobi), Pedosphaerae and Verrucomicrobiae (Verrucomicrobia), Saprospirae (Bacteroidetes), 028H05-P-BN-P5, C6 and OM190
Fig. 1. Principal coordination analysis (PCoA) of soil bacterial community composition as affected by sampling season and grazing intensity after more than six decades of cattle grazing in the foothills of the Rocky Mountains, Alberta, Canada. Abbreviation: AUM, Animal unit month.
Fig. 2. The distribution of soil bacterial operational taxonomic units (OTUs) across taxonomic branches after more than six decades of cattle grazing in the foothills of the Rocky Mountains, Alberta, Canada. Individual nodes in the dendrogram correspond to OTUs and size of the pink nodes indicates mean relative abundance of the OTU. Lines that connect the nodes represent the taxonomic path from the domain to OTU level. The OTUs were placed at the level of the lowest possible assignment. Numbers in the brackets are the average relative abundance of each phylum. 4
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Fig. 3. Significant differences of phyla level bacterial abundances among the different grazing intensities [0 (ungrazed control), 2.4 (moderate grazing intensity) and 4.8 AUM ha−1 (heavy grazing intensity)] after more than six decades of cattle grazing in the foothills of the Rocky Mountains, Alberta, Canada. Bars on the left represent the proportion of each bacterial phylum abundance in the grazing treatments. Bacterial abundance differences with a q-value of < 0.05 were considered to be significant. Q-values are from the adjustment of p-values by the Benjamini-Hochberg method. Abbreviation: AUM, Animal unit month.
(Planctomycetes) at the class level (Fig. 4). However, the relative abundances of the Actinobacteria phylum (Fig. 3) and Rubrobacteria class (Actinobacteria) (Fig. 4) were greater with heavy grazing than the other two grazing intensity treatments.
previous research also found distinct soil bacterial α-diversity and community composition was affected by sampling season near the study site (Zhang et al., 2018b). Such differences were mainly attributed to changes in temperature, precipitation, and/or plant biomass. Warmer seasons were always associated with greater soil temperature, precipitation and plant biomass, which drives greater soil microbial activity and bacterial diversity (Yao et al., 2011; Zhou et al., 2017; Zhang et al., 2018b). Nevertheless, the long-term (64 years) effects of cattle grazing on soil bacterial community composition were similar in the two sampling seasons (Fig. 1 and Table 2), which provides robust evidence to evaluate the effect of different grazing intensities on soil bacterial α-diversity and community composition. In the current study, cattle grazing at moderate and heavy grazing intensities for 64 years (1949–2013) provided a unique opportunity to evaluate the effect of long-term grazing intensity on soil bacterial diversity. This study shows that the effects of long-term grazing on soil bacterial α-diversity and community composition were largely dependent on grazing intensity and varied significantly between the nongrazed control and heavy grazing intensity, with no observed differences between moderate grazing and the ungrazed control. Compared to the control, heavy grazing intensity significantly decreased soil bacterial evenness and diversity, while there were no significant differences between moderate grazing and the control (Table 1). These results are consistent with previous studies that found heavy grazing significantly reduced all soil bacterial diversity indices in the grasslands of northeast China and southern New Zealand (Qi et al., 2011; Qu et al.,
3.4. Relationships between soil physicochemical properties and bacterial community composition Grazing intensity significantly affected soil moisture, TN, AN, TP, AP and SOC, while soil moisture, AN and AP were also significantly affected by sampling season (Table 3). Overall, heavy grazing led to significantly lower soil moisture, TN, AN, and SOC (Table 3) than moderate grazing and the ungrazed control. Moderate grazing had lower soil moisture than the control treatment (Table 3). Distance-based RDA model analysis shows that individual soil physicochemical properties explained the changes in soil bacterial community composition (Table 4). Soil AN, moisture, SOC and TN had significant influence on the soil bacterial community composition, explaining 8.01%, 7.03%, 5.25% and 4.39% of the total variance, respectively (Table 4). 4. Discussion Sampling season appeared to significantly affect soil bacterial richness, Heip_e evenness index and Shannon diversity index (Table 1), as well as bacterial community composition (Table 2 and Fig. 1). Our 5
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Fig. 4. Significant differences in Class level bacterial abundance among the different cattle grazing intensities [0 (ungrazed control), 2.4 (moderate grazing intensity) and 4.8 AUM ha−1 (heavy grazing intensity)] after more than six decades of cattle grazing in the foothills of the Rocky Mountains, Alberta, Canada. Bars on the left represent the proportion of each bacterial phylum abundance in the treatments. Bacterial abundance differences with a q-value of < 0.05 were considered to be significant. Q-values are from the adjustment of p-values by the Benjamini-Hochberg method. Abbreviation: AUM, Animal unit month.
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Table 3 Effect of grazing intensity on soil physico-chemical properties after more than six decades of cattle grazing in the foothills of the Rocky Mountains, Alberta, Canada. Main test
a
Moisture F(P)
pH F(P)
TN F(P)
AN F(P)
TP F(P)
AP F(P)
SOC F(P)
C:N F(P)
Grazing intensity (F2,33) Season (F1,33) Grazing intensity × Season (F2,33)
17.0 (< 0.001) 5.5 (0.03) 0.8 (0.45)
2.4 (0.11) 0.0 (0.98) 0.0 (1.00)
7.6 (0.002) 0.4 (0.53) 0.32 (0.73)
14.9 (< 0.001) 33.8 (< 0.001) 7.5 (0.002)
8.4 (0.001) 0.0 (0.85) 0.0 (0.97)
3.1 (0.02) 8.3 (0.007) 0.2 (0.85)
14.4 (< 0.001) 0.4 (0.54) 0.3 (0.74)
2.5 (0.10) 0.0 (0.99) 0.0 (1.00)
Multiple comparisonb
Mean ± s.d. %
Mean ± s.d.
Mean ± s.d. g kg−1
Mean ± s.d. mg kg−1
Mean ± s.d. g kg−1
Mean ± s.d. mg kg−1
Mean ± s.d. g kg−1
Mean ± s.d. mg kg−1
0 AUM ha−1 (n = 7)c 2.4 AUM ha−1 (n = 16) 4.8 AUM ha−1 (n = 16)
42.1 ± 5.3 a 33.1 ± 6.8 b 27.5 ± 3.9 c
6.3 ± 0.2 a 6.5 ± 0.3 a 6.3 ± 0.2 a
6.9 ± 1.3 a 6.9 ± 0.6 a 5.9 ± 0.6 b
16.0 ± 5.4 a 15.9 ± 6.5 a 10.1 ± 2.9 b
0.87 ± 0.09 ab 0.91 ± 0.13 a 0.76 ± 0.08 b
1.9 ± 0.6 ab 2.5 ± 1.1 a 1.7 ± 0.9 b
80.6 ± 9.0 a 85.7 ± 8.1 a 69.1 ± 7.7 b
11.6 ± 0.4 a 12.5 ± 1.8 a 11.7 ± 0.4 a
Abbreviation: AUM, Animal unit month. a The effects of grazing intensity, season, and their interactions were determined by univariate permutational analysis of variance (PERMANOVA; degrees of freedom for each factor and residuals are given in brackets). Values represent the pseudo-F ratio (F) and the level of significance (P). Grazing intensities were 0 (ungrazed control), 2.4 (moderate grazing intensity) and 4.8 AUM ha−1 (heavy grazing intensity), and season factors were summer (July sampling) and fall (October sampling). b Mean value of each grazing intensity. Means within a column that do not share a letter are significantly different at P < 0.05 as assessed by Tukey’s HSD test. Pvalues < 0.05 are shown in bold. Abbreviations: AN, available nitrogen; AP, available phosphorus; C:N, soil organic carbon to total nitrogen ratio; SOC, soil organic carbon; TN, total nitrogen; TP, total phosphorus. c One out of four replications for 0 AUM ha−1 in July was excluded from statistical analysis due to bad sequence coverage, which resulted in seven replications for 0 AUM ha−1 in both July and October. Table 4 Relationship between soil physicochemical properties and bacterial community composition after more than six decades of cattle grazing in the foothills of the Rocky Mountains, Alberta, Canada. dbRDA analysis
Moisture
pH
TN
AN
TP
AP
SOC
C:N
VC P-value
7.03% 0.01
2.20% 0.33
4.39% 0.04
8.01% 0.002
2.29% 0.30
3.03% 0.17
5.25% 0.02
4.27% 0.06
The variance component (VC) for each physicochemical soil property explaining soil bacterial community composition was performed by distance-based redundancy analysis (dbRDA). Significant P-values were performed by marginal tests and are shown in parentheses. P-values < 0.05 are shown in bold. Abbreviations: AN, available nitrogen; AUM, animal unit month; AP, available phosphorus; C:N, soil organic carbon to total nitrogen ratio; SOC, soil organic carbon; TN, total nitrogen; TP, total phosphorus.
heterotrophic and utilize soil C sources or decomposing plant material for their growth (Dwivedi et al., 2017; Morriën et al., 2017). Although soil moisture and SOC content were important drivers of soil bacterial community composition, this study showed that the soil available N level was the most pronounced factor shaping the soil bacterial community (Table 4). Similar to previous studies (Ingram et al., 2008; Qu et al., 2016), the current study also provides evidence of greater soil N losses with heavy grazing intensity than moderate grazing or the ungrazed control (Table 3). Ingram et al. (2008) reported that heavy grazing intensity resulted in a loss of approximately 50% of aboveground plant N, while only 10% of this N was lost with light grazing intensity. About 80–95% of consumed plant N is estimated to be returned via excreta but a large proportion of N in livestock excreta is in organic form and is unable to be taken up by plants, while a large proportion of ammonium and nitrate ends up being either volatilized, leached or denitrified (Ingram et al., 2008). The changes in soil C and N levels due to heavy grazing intensity will inevitably influence the soil bacterial composition by decreasing substrate availability for soil microbes. An oligotroph-copiotroph strategy shift of soil bacteria with changes in soil nutrient availability has been observed, i.e., high nutrient availability promotes the growth of copiotrophic organisms while low nutrient levels lead to an increase of slow-growing oligotrophic microorganisms (Fierer et al., 2012). In the present study, high intensity grazing had lower Bacteroidetes, Nitrospirae and Proteobacteria abundances (Fig. 3), which was mainly due to reduced soil nutrients. These bacterial groups are considered copiotrophic microorganisms (Fierer et al., 2007, 2012) and were found to be positively correlated with soil C and N levels (Fierer et al., 2012; Ling et al., 2017; Dai et al., 2018). The Actinobacteria are one of the few groups of saprotrophic
2016; Zhong et al., 2016). A meta-analysis also reported that heavy grazing intensity significantly decreased soil bacterial community size, while light and moderate grazing intensity had no effect on soil bacterial community size (Zhao et al., 2017). Previous studies all clearly indicate that the changes in soil bacterial α-diversity largely depend on changes in soil bacterial community composition (Qu et al., 2016; Zhang et al., 2018b). In the present study, both PCoA ordination (Fig. 1) and PERMANOVA analyses (Table 2) primarily showed that the heavy grazing intensity had the greatest differences compared to the other two treatments. These results appear mainly attributable to the changes in soil physicochemical properties induced by more than six decades of cattle grazing. Heavy grazing intensity tended to reduce soil C and N concentrations, as well as soil moisture content, relative to other two grazing treatments (Table 3). Soil AN, moisture, SOC and TN were found to be the most important drivers of bacterial community composition, explaining 17.7% of total soil bacterial community variance (Table 4). This study provides more evidence that soil moisture is one of the strongest factors in shaping soil bacterial richness and composition in this semi-arid region of Canada (Zhang et al., 2018b). Heavy grazing intensity has been found to reduce soil moisture by decreasing the canopy cover, which enhances solar radiation reaching the soil surface compared to light grazing or the ungrazed control (Odriozola et al., 2014; Rong et al., 2015), which impacts soil bacterial community composition (Manzoni et al., 2012; Hartmann et al., 2017). Furthermore, heavy grazing may increase the loss of photosynthetic tissue and reduce below-ground C inputs through lower plant productivity, thus leading to declining plant material and C content in soil (Kawasaki et al., 2012; Aldezabal et al., 2015; Byrnes et al., 2018). Subsequently, soil bacterial numbers may decrease as bacteria are mostly 7
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microorganisms and are key mediators of plant litter decay. Previous studies have reported that the abundance of Actinobacteria is regulated by soil N levels, and that higher soil N concentration always enhanced the growth of Actinobacteria (Dai et al., 2018; Zhang et al., 2018b). In contrast, this study found that heavy grazing intensity with the lowest N level had the greatest Actinobacteria abundance (Fig. 3). The underlying mechanism might be that heavy grazing intensity caused a greater proportion of stem-leaf material to enter the soil, which would stimulate the growth of the Actinobacteria group to decompose the plant litter with higher lignin content (Eisenlord and Zak, 2010). It may also be possible that greater fecal matter deposition high in partially digested plant residues with heavier grazing intensity provided recalcitrant substrate for Actinobacteria to decompose.
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5. Conclusions The soil bacterial community composition shifted between summer and fall seasons, but the grazing intensity effect was similar each season. Soil bacterial evenness and diversity indices significantly decreased after 64 years of heavy grazing, compared to moderate grazing intensity and the ungrazed control. Long-term heavy grazing significantly decreased the relative abundances of Bacteroidetes, Chlorobi, Nitrospirae and Proteobacteria, while significantly increasing the relative abundance of Actinobacteria. Heavy grazing decreased soil moisture, C and N levels, and shifted the relative abundances of major bacterial taxa leading to a distinct soil bacterial community composition. Moderate grazing intensity did not alter the soil bacterial community composition compared to the ungrazed control. This suggests that multi-decadal grazing at moderate cattle stocking rates does not impact the soil bacterial community composition in the foothills of the Rocky Mountains, Canada. The impacts of grazing on the soil bacterial community composition are largely driven by how the intensity of grazing affects soil physicochemical properties. Declaration of Competing Interest The Authors declare there are no conflicts of interest to report. Acknowledgements Funding for this project was provided by Agriculture and Agri-Food Growing Forward 2 (J-000251 and J-001360). Support was also provided by China Agriculture Research System-Green Manure (CARS-22G-13) and the National Natural Science Foundation of China (31902116). References Aldezabal, A., Moragues, L., Odriozola, I., Mijangos, I., 2015. Impact of grazing abandonment on plant and soil microbial communities in an Atlantic mountain grassland. Appl. Soil Ecol. 96, 251–260. Byrnes, R.C., Eastburn, D.J., Tate, K.W., Roche, L.M., 2018. A global meta-analysis of grazing impacts on soil health indicators. J. Environ. Qual. 47, 758–765. Caporaso, J.G., Lauber, C.L., Walters, W.A., Berg-Lyons, D., Lozupone, C.A., Turnbaugh, P.J., Fierer, N., Knight, R., 2011. Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. Proc. Natl. Acad. Sci. U. S. A. 108, 4516–4522. Dai, Z., Su, W., Chen, H., Barberán, A., Zhao, H., Yu, M., Yu, L., Brookes, P.C., Schadt, C.W., Chang, S.X., 2018. Long‐term nitrogen fertilization decreases bacterial diversity and favors the growth of Actinobacteria and Proteobacteria in agro‐ecosystems across the globe. Glob. Change Biol. 24, 3452–3461. Dlamini, P., Chivenge, P., Chaplot, V., 2016. Overgrazing decreases soil organic carbon stocks the most under dry climates and low soil pH: a meta-analysis shows. Agric. Ecosyst. Environ. 221, 258–269. Dormaar, J.F., Willms, W.D., 1998. Effect of forty-four years of grazing on fescue grassland soils. J. Range Manage. 51, 122–126. Dwivedi, D., Riley, W., Torn, M., Spycher, N., Maggi, F., Tang, J., 2017. Mineral properties, microbes, transport, and plant-input profiles control vertical distribution and age of soil carbon stocks. Soil Biol. Biochem. 107, 244–259. Edgar, R., 2013. UPARSE: highly accurate OTU sequences from microbial amplicon reads. Nat. Methods 10, 996–998. Edgar, R., Haas, B., Clemente, J., Quince, C., Knight, R., 2011. UCHIME improves
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and grazing intensity effects on microorganisms and nitrogen transformation processes responsible for nitrous oxide emissions from hill pastures. Agric. Ecosyst. Environ. 217, 70–78. Zhou, G., Zhou, X., He, Y., Shao, J., Hu, Z., Liu, R., Zhou, H., Hosseinibai, S., 2017. Grazing intensity significantly affects belowground carbon and nitrogen cycling in grassland ecosystems: a meta‐analysis. Glob. Change Biol. 23, 1167–1179.
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