qPCR conditions and quality assessment
Each 20 μl reaction contained 10 μl of master mix, 20 pmol of the appropriate forward and reverse primers, 0.2 mg ml-1 BSA, 5 μl nuclease free
water, and 20 ng of template DNA. Thermal cycling conditions were 1 cycle of 2 min at 50C and 15 min at 95C; 30 cycles of 95C for 15 s,
60C for 30 s, 72C for 30 s, 80C for 15 s; and 1 cycle of 95°C for 15 s, 60 to 95°C. Copy number per gram of dry soil was calculated on the
basis of dilution factor and soil water content. A standard curve was prepared using purified PCR products obtained from a Pseudomonas sp.
control strain. Only the standard curves linear over six orders of magnitude and r2 value of 0.99 or higher were selected. Standards were run on
each individual qPCR plate for consistency. The efficiency of the reaction was between 95% and 100% (based on the slopes of the standard
curves). All samples and standards were run in triplicate. Consistency of Y-intercept values was checked between different qPCR runs and the
specificity of the amplified products was assessed by melting curve analysis. Amplification inhibition effects were assessed by assessing gene
abundance on three different dilutions of representative samples and selecting the dilution that minimized inhibition (Dumonceaux et al., 2006).
Table S1. Soil and microbial properties measured at 0-10 cm depth in 54 samples obtained from three types of agroforestry systems across three
soil-climate zones (north, central and south) in Alberta, Canada. Each agroforestry system consisted of a forested plot (shelterbelts or hedgerow
or woodland) and an adjacent herbland plot (Agricultural land or grassland). One-way ANOVA with Duncan’s post hoc test was performed
across three soil-climate zones within each land use (n = 3).
Soil
properties
Bact 16S
rRNA
pH
WHC
Moisture
NH4
NO3
TN
TOC
DOC
DON
TC
Shelterbelts
S_Agricultural
Hedgerow
H_Agricultural
Woodland
Grassland
North
Central
South
North
Central
South
North
Central
South
North
Central
South
North
Central
South
North
Central
South
6.78 a
6.51 a
59.59 a
12.72 a
1.11 a
4.04 a
0.32 a
4.11 a
3.03 a
0.54 a
151.64a
6.93 a
5.69 a
84.67 a
21.79 a
1.85 a
3.89 a
0.53 a
6.48 a
6.90 a
1.15 a
345.04a
7.01 a
5.79 a
73.50 a
20.89 a
2.03 a
3.52 a
0.54 a
7.02 a
6.00 a
0.88 a
299.93a
6.45 a
6.12 a
66.66 a
19.91 a
0.91 a
7.42 a
0.30 a
3.50 a
2.09 a
0.84 a
104.60a
6.74 a
5.55 a
81.14 a
33.83 b
1.40 a
6.05 a
0.47 b
5.35 b
1.89 a
0.82 a
94.53 a
6.65 a
5.54 a
75.23 a
25.71ab
1.23 a
7.19 a
0.41 ab
5.05 ab
2.18 a
0.87 a
108.82a
7.29 a
5.89 a
119.98a
43.71 a
4.81 a
5.83 a
0.79 a
11.42 a
5.00 a
0.72 a
250.10a
7.19 a
5.57 a
89.41 a
29.20 a
2.18 a
1.52 a
0.54 a
6.71 a
4.15 a
0.72 a
207.52a
7.02 a
5.56 a
104.48a
22.34 a
2.86 a
2.27 a
0.53 a
7.71 a
3.70 a
0.46 a
184.89a
6.37 a
5.18 a
48.72a
15.88a
0.69 a
4.50 a
0.23 a
2.64 a
1.48 a
0.55 a
73.78a
6.91 a
5.56 a
74.62a
31.51 b
1.06 a
6.32 a
0.44 a
4.94 a
1.98 a
0.92 a
99.08 a
6.73 a
5.58 a
64.07a
19.50a
1.39 a
6.38 a
0.47 a
6.06 a
1.65 a
0.72 a
82.57a
7.51 a
5.60 a
156.77a
59.38 a
5.95 a
4.19 a
0.89 a
13.73 a
6.96 a
1.02 a
347.94a
6.74 a
5.23 a
58.26 a
16.99 a
1.40 a
1.87 a
0.26 a
3.56 a
1.99 a
0.47 a
99.65 a
7.24 a
6.57 a
111.26a
32.33 a
5.32 a
12.53 a
0.81 a
10.70 a
5.28 a
1.41 a
263.97a
6.86 ab
6.19 a
64.71a
24.97a
0.86 a
6.05 ab
0.42 a
6.04 a
2.27 a
0.68 a
113.27a
6.33 a
5.88 a
47.31 a
12.12 a
0.61 a
0.81 a
0.14 a
1.54 a
0.93 a
0.17 a
46.42 a
7.10 b
5.58 a
124.07a
38.83 a
3.50 b
8.62 b
1.02 a
11.49 a
5.16 a
1.20 a
258.24a
* unit of bacterial 16S rRNA is copies g–1 dry soil and all other soil properties are mg kg–1 soil
# each value is the mean of three replicates with standard errors in parentheses
$ different letters represent statistical significance among all systems at P<0.05
Significant differences are shown in bold letters
S_Agricultural and H_ Agricultural indicate agricultural lands adjacent to shelterbelt and hedgerow, respectively
Table S2: Results of SIMPER analyses indicating the contribution of specific operational taxonomic units (OTUs) to observed similarities between land use
types
Group A vs. B
Average
similarity
Five most influential OTUs
Percent
contribution to
similarity
Average abundance
in group A
Average abundance
in group B
S_Agricultural
vs. Shelterbelt
70.76
1 (Uncl. Bradyrhizobeaceae)
5 (Pseudomonas)
57 (Uncl. Propionibacteriaceae)
3 (Uncl. Propionibacteriaceae)
129 (Uncl. Propionibacteriaceae)
2.03
1.43
0.76
0.74
0.67
170.22
7.78
52
59.22
56.67
315.22
178.56
67.67
69
42.56
H_Agricultural
vs. Hedgerow
73.97
1 (Uncl. Bradyrhizobeaceae)
2 (Pseudomonas)
3319 (Uncl. Bradyrhizobeaceae)
22 (Acidobacteria_Gp4)
72 (Acidobacteria_Gp4)
3.96
2.12
1.11
1.01
0.73
202.89
384.56
39.67
114.56
49.22
524
7.11
133
5.22
74.22
S_Agricultural
vs.
H_Agricultural
69.40
2 (Pseudomonas)
1 (Uncl. Bradyrhizobeacaeae)
22 (Acidobacteria_Gp4)
14 (Uncl. Propionibacteriaceae)
35 (Uncl. Proteobacteria)
2.21
1.35
0.87
0.65
0.64
4.89
170.22
55.56
49.11
69.44
384.56
202.89
114.56
46.22
50.78
Shelterbelt vs.
Hedgerow
64.00
1 (Uncl. Bradyrhizobeaceae)
5 (Pseudomonas)
3319 (Uncl. Bradyrhizobeaceae)
57 (Uncl. Propionibacteriaceae)
26 (Acidobacteria_Gp16)
3.81
1.58
1.14
0.83
0.72
315.22
178.56
80.89
67.67
55.56
524
13.44
133
19.44
76.11
Grassland vs.
Woodland
74.35
1 (Uncl. Bradyrhizobeaceae)
3319 (Uncl. Bradyrhizobeaceae)
3.7
1.29
179.5
50.17
514
159.33
26 (Acidobacteria_Gp16)
8 (Acidobacteria_Gp16)
12 (Arthrobacter)
0.68
0.67
0.67
34
29
63
102.11
91.89
45.78
Shelterbelt vs
Woodland
68.25
1 (Uncl. Bradyrhizobeaceae)
5 (Pseudomonas)
3319 (Uncl. Bradyrhizobeaceae)
8 (Acidobacteria_Gp16)
57 (Uncl. Propionibacteriaceae)
2.82
1.4
1.21
0.69
0.69
315.22
178.56
80.89
72.33
67.67
514
10.78
159.33
91.89
18.67
Hedgerow vs.
Woodland
66.51
1 (Uncl. Bradyrhizobeaceae)
3319 (Uncl. Bradyrhizobeaceae)
26 (Acidobacteria_Gp16)
72 (Acidobacteria_Gp4)
10 (Gemmatimonas)
3.89
1.19
0.94
0.78
0.64
524
133
76.11
74.22
51.44
514
159.33
102.11
90.89
67.11
# SIMPER was conducted on Bray-Curtis resemblance matrix of untransformed OTU abundance data to retain the contribution (importance) of
the dominant OTUs.
Table S3. Overall Pearson correlations among soil properties and bacterial species richness estimators in 54 samples obtained from 27
agroforestry systems across a 270 km soil-climate gradient in Alberta, Canada.
Soil properties
SOBS
ACE
Chao1
WHC
0.374**
0.308*
0.353*
TN
0.303*
0.289*
TOC
0.273*
0.269*
DOC
0.358*
0.290*
TC
0.301*
Bacterial diversity indices did not any significant correlations
* and ** significant at P<0.05 and P<0.01 respectively
#pH, gravimetric moisture, NH4, NO3 and DON did not show any significant correlation
$ No noticeable trend appeared when agroforestry systems and controls were considered separately and the correlations were fairly weak.
Table S4. Overall Pearson correlations among the major phyla and soil properties in 54 samples obtained from 27 agroforestry systems across a
270 km soil-climate gradient in Alberta, Canada.
Genera
pH
WHC
Acidobacteria
0.251*
0.284*
Moisture
NH4
NO3
TN
TOC
0.283*
0.314*
DOC
TC
Actinobacteria
-0.256*
-0.265*
-0.335*
-0.323*
-0.323*
Bacteroidetes
-0.261*
-0.282*
-0.357*
-0.329*
-0.329*
-0.487**
-0.273*
-0.369**
-0.398**
-0.398**
-0.331*
-0.345*
0.460**
0.460**
Firmicutes
0.371**
Gemmatimonadetes
-0.502**
Nitrospirae
-0.330*
-0.346*
Alphaproteobacteria
Betaproteobacteria
Deltaproteobacteria
0.339*
0.382**
0.412**
0.252*
-0.265*
0.308*
0.280*
0.272*
0.242*
0.305*
0.247*
* and ** significant at P<0.05 and P<0.01 respectively
# DON and phyla Gammaproteobacteria, Unclassified Proteobacteria, Verrucomicrobia did not show significant relationship
$ No noticeable trend appeared when agroforestry systems and controls were considered separately and the correlations were fairly weak.
Table S5. Overall Pearson correlations among the most abundant genera and soil properties in 54 samples obtained from 27 agroforestry
systems across a 270 km soil-climate gradient in Alberta, Canada.
Genera
pH
Arthrobacter
0.659**
Bradyrhizobium
-0.509*
Burkholderia
WHC
Moisture
NH4
0.578**
0.610**
0.557*
Dokdonella
NO3
TN
TOC
DOC
0.485*
.465*
0.465*
-0.510*
-0.510*
0.460*
Microvirga
-0.543*
-0.461*
-0.491*
Nitrospira
-0.475*
0.711**
Pasteuria
0.554*
TC
-0.499*
0.783**
Nocardioides
DON
0.489*
0.581**
Rhodanobacter
Rhodoplanes
0.554*
Solirubrobacter
0.495*
0.462*
0.590**
0.590**
0.522*
0.522*
* and ** significant at P<0.05 and P<0.01 respectively
# Gemmatimonas, Nitrosospira, Flavobacterium, Pseudomonas, Rhizobium, Rhizobacter, Streptomyces, Terrimonas and TM7_genus did not
show significant relationship with any soil attributes
$ No noticeable trend appeared when agroforestry systems and controls were considered separately and the correlations were fairly weak.
Figure S1. Study area across 270 km north-south and 226 east-west geographical gradient in Alberta, Canada. The 270 km north-south gradient
comprised three soil zones (north, central and south).
Figure S2. Interactive diagram showing split-plot design of sampling and number of different agroforestry systems in three soil-climate zones in
Alberta, Canada
Figure S3. Canonical analysis of principal coordinates (CAP) of Bray-Curtis similarity matrix with 105 permutations showing clustering of
bacterial communities in (A) six land use types and (B) three soil zones. Three agroforestry systems consisting of plots with trees (shelterbelt or
hedgerow or woodland) and adjacent herbland plots (agricultural land and grassland). S_Agricultural land and H_Agricultural land represent
agricultural lands adjacent to shelterbelts and hedgerows respectively. Each value is the average of three replicates.
Figure S4. Results of MCODE analysis showing eight sub-networks with highest node scores. Networks and connectedness were visualised in
Phytoscape 3.2.0 software. MCODE app was used to analyse networks with maximum scores.