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diversity
Article
Effect of Organic and Conventional Systems Used to
Grow Pecan Trees on Diversity of Soil Microbiota
Alejandra Cabrera-Rodríguez 1, Erika Nava-Reyna 2, Ricardo Trejo-Calzada 1, * ,
Cristina García-De la Peña 3, Jesús G. Arreola-Ávila 1, Mónica M. Collavino 4,
Felipe Vaca-Paniagua 5, Clara Díaz-Velásquez 5and Vicenta Constante-García2
1Unidad Regional Universitaria de Zonas Áridas, Universidad Autónoma Chapingo, carretera Gómez
Palacio-Ciudad Juárez km 40, 35230 Bermejillo, Durango, Mexico;
alejandra.cabrera@chapingo.uruza.edu.mx (A.C.-R.); jgarreola@chapingo.uruza.edu.mx (J.G.A.-Á.)
2Centro Nacional de Investigación Disciplinaria en Relación Agua, Suelo, Planta, Atmósfera, Instituto
Nacional de Investigaciones Forestales, Agrícolas y Pecuarias, Margen Derecho del Canal de
Sacramento km 6.5, 35140 Gómez Palacio, Durango, Mexico; nava.erika@inifap.gob.mx (E.N.-R.);
constante.vicenta@gmail.com (V.C.-G.)
3Facultad de Ciencias Biológicas, Universidad Juárez del Estado de Durango, Av. Universidad s/n,
Fracc. Filadelfia, 35010 Gómez Palacio, Durango, Mexico; cristina.garcia@ujed.mx
4Instituto de Botánica del Nordeste, Facultad de Ciencias Agrarias, Universidad Nacional del
Nordeste-CONICET, calle Sargento Cabral 2131, 34000 Corrientes, Argentina; mmcollavino@yahoo.com.ar
5Laboratorio Nacional en Salud: Diagnóstico Molecular y Efecto Ambiental en Enfermedades
Crónico-Degenerativas, Facultad de Estudios Superiores Iztacala, Universidad Nacional Autónoma de
México, Av. de los Barrios 1, Los Reyes Iztacala, 54090 Tlalnepantla, Estado de México, Mexico;
felipe.vaca@gmail.com (F.V.-P.); cdiazvelasquez@aol.com (C.D.-V.)
*Correspondence: rtrejo@chapingo.uruza.edu.mx
Received: 16 October 2020; Accepted: 16 November 2020; Published: 19 November 2020
Abstract:
Agronomic management modifies the soil bacterial communities and may alter the carbon
fractions. Here, we identify differences in several chemical and biological soil variables, as well as
bacterial composition between organic (Org) and conventional (Conv) agronomic management in
pecan (Carya illinoinensis) orchards located in Coahuila, Mexico. The analyzed variables were pH,
N, P, K, soil organic matter, organic matter quality, soil organic carbon, C/N ratio, carbon fractions,
microbial biomass carbon, easily extractable Glomalin, colony-forming units, CO
2
emissions, and the
enzyme activity. The DNA of soil bacteria was extracted, amplified (V3-V4 16S rRNA), and sequenced
using Illumina. To compare variables between agronomic managements, ttests were used. Sequences
were analyzed in QIIME (Quantitative Insights Into Microbial Ecology). A canonical correspondence
analysis (CCA) was used to observe associations between the ten most abundant phyla and soil
variables in both types of agronomic managements. In Org management, variables related to the
capture of recalcitrant carbon compounds were significant, and there was a greater diversity of
bacterial communities capable of promoting organic carbon sequestration. In Conv management,
variables related to the increase in carbon mineralization, as well as the enzymatic activity related to
the metabolism of labile compounds, were significant. The CCA suggested a separation between
phyla associated with some variables. Agronomic management impacted soil chemical and biological
parameters related to carbon dynamics, including bacterial communities associated with carbon
sequestration. Further research is still necessary to understand the plasticity of some bacterial
communities, as well as the soil–plant dynamics.
Keywords:
organic agriculture; soil organic carbon; 16S rRNA; sequencing; structure of the soil
bacterial community
Diversity 2020,12, 436; doi:10.3390/d12110436 www.mdpi.com/journal/diversity
Diversity 2020,12, 436 2 of 15
1. Introduction
Microorganisms that live in the soil are among the most abundant and diverse organisms on
earth [
1
]. The structure and metabolism of the soil bacterial communities are influenced by elements of
the ecosystem such as climate, type of soil, and plant composition; however, one factor that greatly affects
their composition and functioning is agronomic management [
2
–
5
]. Thus, conventional agronomic
management (CAM) alters the distribution of organic material and affects the rate of mineralization
of micro and macro elements in the soil [
3
], negatively impacting the long-range productivity of the
soil due to the loss of organic matter and erosion [
6
]. In CAM, inorganic supplies, such as synthetic
fertilizers and pesticides, are used [
7
]. These supplies affect the availability of nutrients in the soil,
contaminating the surface and underground water, thus affecting the native biotic community [
8
].
Conversely, in organic management, the traditional cultivation methods (conservationist) are combined
with modern techniques, excluding conventional supplies [
9
]. In these systems, crop rotation is
practiced and residues from animals and organic vegetables are used to increase soil fertility and
productivity [
7
–
10
]. Likewise, it has been reported that these practices also affect the long-term
structure of the microbial community through the accumulation and chemistry changes of soil organic
matter (SOM) [2].
Regarding the above, greater attention should be given to organic agricultural systems in perennial
woody crops with commercial interest, such as pecan trees (Carya illinoinensis). These systems have
the potential to improve soil fertility through microbial activity and carbon accumulation in the
soil [
10
–
13
]. For pecan tree orchards, the essential practices to promote soil fertility involve using
leguminous plants or wild herbs as ground cover, as well as using organic fertilizers [
14
]. The pecan
tree is a perennial woody crop which produces the pecan nut, which is a highly nutritious food [
15
].
The world’s leading producers of pecan nuts are China, United States, Iran, Turkey, and Mexico [
16
].
Furthermore, in Mexico, the states with a greater volume of pecan production are Chihuahua, Sonora,
and Coahuila. These pecan nuts are exported mainly to the United States, China, and Vietnam, at an
annual amount in 2018 worth USD 751 million [
17
]. Considering the cultivation of organic pecan trees
in Mexico, in 2011 there were 1000 hectares certified as organic [14].
Given the importance of preserving and increasing soil fertility in pecan tree cultivation, several
research studies have been developed to determine soil organic carbon (SOC), SOM, carbon–nitrogen
relation, the mineralization of carbon and nitrogen, microbial biomass carbon, enzyme activities
in diverse management systems, age of the crops, and association with leguminous plants and
grasses [
11
,
12
,
18
]. Other research has focused on the qualities of the essential oils in nuts and on the
nutritional deficiencies of the foliage, as well as on pests and diseases [
15
,
19
,
20
]. However, although
the role of microbial communities in carbon sequestration is relevant, there are not enough research
studies related to the structure and functioning of bacterial communities in the soil wherein pecan
trees are grown under different agronomic management. Therefore, the objectives of this study were to
identify the soil variables that respond to agronomic management related to carbon dynamics, and to
determine the structure and composition of the bacterial communities in the soil wherein pecan trees
are grown under organic and conventional management. We hypothesize that the organic management
of pecan tree cultivation will generate greater soil bacterial diversity, capable of promoting greater
efficiency in carbon sequestration than conventional management.
2. Materials and Methods
2.1. Study Area
Soil samples were collected from pecan orchards (Carya illinoinensis (Wangenh.) K. Koch) containing
Cheyenne, Wichita, and Western varieties under organic (Org) and conventional (Conv) managements,
located in the municipality of Allende, Coahuila, Mexico (Org: N 28
◦
20
0
05.72” W
−
100
◦
49
0
24.73”;
Conv: N 28
◦
21
0
57.30” and W
−
100
◦
46
0
06.02”) (Figure 1). Both orchards are located in the same
geographical region, where the type of soil corresponds to haplic xerosol and the texture is clay [
21
].
Diversity 2020,12, 436 3 of 15
The prevalent climate is dry and semi-warm, where annual mean temperature ranges between 20 and
24
◦
C, and the annual mean rainfall is about 461 mm [
22
]. The orchard under organic management
(100 ha) is 20 years old, and the commonly applied practices to the soil are the use of plant covers and
the placing of organic matter (pecan tree residues). On the other hand, the orchard under conventional
management (35 ha) is 30 years old, and chemical fertilizers and pesticides are applied in accordance
with the technical guide for pecan tree management proposed by INIFAP (Instituto Nacional de
Investigaciones Forestales Agrícolas y Pecuarias) [23].
Diversity 2020, 12, x FOR PEER REVIEW 3 of 15
and 24 °C , and the annual mean rainfall is about 461 mm [22]. The orchard under organic management
(100 ha) is 20 years old, and the commonly applied practices to the soil are the use of plant covers and
the placing of organic matter (pecan tree residues). On the other hand, the orchard under conventional
management (35 ha) is 30 years old, and chemical fertilizers and pesticides are applied in accordance
with the technical guide for pecan tree management proposed by INIFAP (Instituto Nacional de
Investigaciones Forestales Agrícolas y Pecuarias) [23].
Figure 1. Geographical location of pecan tree (Carya illinoinensis) orchards in Coahuila, Mexico.
2.2. Soil Sampling and Analysis of Chemical and Biological Variables
Four pecan trees were systematically selected from each orchard. From each tree, four sub-
samples were taken (one from each cardinal point) at a depth of 20 cm. Respective sub-samples were
mixed obtaining composite samples (approximately 1 kg each). The samples were air-dried and
sieved using a 2 mm mesh before analytical determinations. The pH was determined with a
soil/water ratio of 1:2 [24]. The essential nutrients, nitrogen (N) [25], phosphorous (P) [26] and
potassium (K) [27], were quantified. Likewise, the SOM [28] and the organic matter quality (humic
acids (HA), fulvic acids (FA), and humins (HS) [29,30]) were obtained. The SOC was obtained using
a total organic carbon analyzer (TOC), and later the C/N ratio was estimated. Furthermore, the carbon
fractions very labile (F1), labile (F2), less labile (F3) and recalcitrant (F4) were analyzed by digestion
with H2SO4 at concentrations of 12, 18, and 24 N [31]. The microbial biomass carbon (MBC) was
analyzed using the extraction fumigation method [32]. Furthermore, the easily extractable Glomalin
(EEG) was determined [33], as well as the colony-forming units (CFU) by plate count (trypticase soy
agar (total aerobic bacteria) and potato dextrose agar (PDA) (filamentous fungi and yeasts).
Additionally, the CO2 emissions from the soil were measured over 42 days under controlled
conditions of humidity and temperature [34,35]. Furthermore, the enzyme activity of the soil was
evaluated for lacasse (LAC), peroxidase (PER), polyphenol oxidase (PPO) [36,37], B-glucosidase (B-
glu), and B-galactosidase (B-gal) [38].
2.3. DNA Extraction, Amplification and Sequencing
Three trees from each pecan orchard were randomly selected to collect 0.25 g of soil from the
rhizosphere zone, at a depth of 10 cm. Each sample was placed in a BashingBead™ (Zymo Research
Corp., Irvine, CA, USA) cell lysis tube, containing 750 µl of lysing/stabilizing solution. Each tube was
processed in a cellular disruptor (TerraLyzer™) for 30 s; samples were kept at ambient temperature.
Figure 1. Geographical location of pecan tree (Carya illinoinensis) orchards in Coahuila, Mexico.
2.2. Soil Sampling and Analysis of Chemical and Biological Variables
Four pecan trees were systematically selected from each orchard. From each tree, four sub-samples
were taken (one from each cardinal point) at a depth of 20 cm. Respective sub-samples were mixed
obtaining composite samples (approximately 1 kg each). The samples were air-dried and sieved
using a 2 mm mesh before analytical determinations. The pH was determined with a soil/water
ratio of 1:2 [
24
]. The essential nutrients, nitrogen (N) [
25
], phosphorous (P) [
26
] and potassium
(K) [
27
], were quantified. Likewise, the SOM [
28
] and the organic matter quality (humic acids (HA),
fulvic acids (FA), and humins (HS) [
29
,
30
]) were obtained. The SOC was obtained using a total organic
carbon analyzer (TOC), and later the C/N ratio was estimated. Furthermore, the carbon fractions
very labile (F1), labile (F2), less labile (F3) and recalcitrant (F4) were analyzed by digestion with
H
2
SO
4
at concentrations of 12, 18, and 24 N [
31
]. The microbial biomass carbon (MBC) was analyzed
using the extraction fumigation method [
32
]. Furthermore, the easily extractable Glomalin (EEG)
was determined [
33
], as well as the colony-forming units (CFU) by plate count (trypticase soy agar
(total aerobic bacteria) and potato dextrose agar (PDA) (filamentous fungi and yeasts). Additionally,
the CO
2
emissions from the soil were measured over 42 days under controlled conditions of humidity
and temperature [
34
,
35
]. Furthermore, the enzyme activity of the soil was evaluated for lacasse (LAC),
peroxidase (PER), polyphenol oxidase (PPO) [
36
,
37
], B-glucosidase (B-glu), and B-galactosidase (B-gal) [
38
].
2.3. DNA Extraction, Amplification and Sequencing
Three trees from each pecan orchard were randomly selected to collect 0.25 g of soil from the
rhizosphere zone, at a depth of 10 cm. Each sample was placed in a BashingBead
™
(Zymo Research
Diversity 2020,12, 436 4 of 15
Corp., Irvine, CA, USA) cell lysis tube, containing 750
µ
L of lysing/stabilizing solution. Each tube
was processed in a cellular disruptor (TerraLyzer
™
) for 30 s; samples were kept at ambient
temperature. DNA was extracted using a Zymo BIOMICS
™
(Zymo Research Corp., Irvine, CA, USA)
kit. The amount of DNA obtained was measured in a Qubit fluorometer (Invitrogen, Carlsbad, CA, USA).
The V3–V4 region of the 16S rRNA gene was amplified using primers suggested by Klindworth
et al. [
39
] (S-D-Bact-0341-b-S-17, 5
0
-CCTACGGGNGGCWGCAG-3
0
and S-D-Bact-0785-a-A-21,
5
0
-GACTACHVGGGTATCTAATCC-3
0
, (~460 pb amplicon)) using the Illumina protocol [
40
].
The amplicons were purified with Agentcourt
®
AMPure
®
XP 0.8% beads (Beckman Coulter Inc.,
Brea, CA, USA). The Nextera XT Index Kit
™
was used to create the library, following the Illumina
protocol [
41
]. The library quantification, normalization (equimolarity) and next-generation massive
sequencing ((MiSeq; Illumina, San Diego, CA, USA) 2
×
250 paired final readings) were developed
following the 16S metagenomic protocol [
40
]. Sequence data were submitted to The National Center
for Biotechnology Information (GenBank), with the following accession numbers: Org samples
(SAMN15365245, SAMN15365246, SAMN15365247), Conv samples (SAMN15365249, SAMN15365250,
SAMN15365252).
2.4. Statistical Analysis
After verifying normality and homogeneity of variance, Student’s ttest or Welch’s ttest (p<0.05)
were used to compare the chemical and biological variables between pecan orchards. The DNA
sequences were analyzed using Quantitative Insights Into Microbial Ecology (QIIME) [
42
] as suggested
by Garc
í
a-De la Peña et al. [
43
]. The absolute abundance of OTUs at genus level was used to visualize
the number of sequences vs. the number of OTUs to observe depth cover (asymptote curves); this graph
was made in PAST ver 3.15 (44). A simple random rarefaction process was made to standardize all
samples. Using the standardized file, relative abundances for the phylum level were obtained and
represented as bar charts using Excel. Taxa at the genera level with a relative abundance greater than
1% were listed. Finally, a canonical correspondence analysis (CCA) was used to observe associations
between the ten most abundant phyla and soil variables in both types of agronomic managements.
The CCA was made in PAST [44].
3. Results
3.1. Chemical and Biological Variables of the Soil
Some chemical and biological variables of the soil showed significant differences between both
orchards. The significantly higher variables in soil under Org management were N, P, SOC, MBC, and HS.
For Conv management, the soil variables that showed significantly higher values were F2, CO
2
emission,
EEG, HA, FA, LAC, B-glu, and B-gal (Table 1).
3.2. Abundance of Bacterial Taxa
The average number of sequences assembled for Org was 230,680, and for Conv it was 267,539.
After taxonomic designation, averages of 28,062 bacterial sequences for Org, and 48,775 for Conv,
were obtained. The average number of OTUs was 5995 for Org, and 7937 for Conv (Table 2).
Simple random rarefaction was made at 20,000 sequences, since at this point the number of OTUs
reached asymptotes (Figure 2).
Diversity 2020,12, 436 5 of 15
Table 1.
Chemical and biological characteristics of soil in pecan tree (Carya illinoinensis) orchards under
organic and conventional management in Coahuila, Mexico. Mean values and standard deviation (
±
) are
shown. An asterisk indicates when a Welch’s ttest was used; df =degrees of freedom; bold numbers
indicate significant differences between managements (p<0.05).
Variable Organic Conventional tdf p
pH 8.1 ±0.09 8.1 ±0.05 1 3 0.391
Nitrogen% 0.050 ±0.004 0.043 ±0.003 3.13 6 0.020
Phosphorous mg kg−116.3 ±5.80 5.6 ±1.00 4.901 6 0.003
Potassium mg L−10.52 ±0.31 0.31 ±0.19 2.06 3.14 0.127 *
Organic Matter% 2.97 ±0.31 3.11 ±0.11 −812 6 0.448
Organic Carbon% 1.91 ±0.04 1.72 ±0.02 7.071 6 0.000
Relation C/N% 38.6 ±3.10 40.5 ±2.00 −1.116 6 0.307
Very labile fraction C g kg−112.30 ±1.35 12.80 ±1.59 −0.522 6 0.620
Labile fraction C g kg−17.57 ±0.70 10.65 ±0.45 −6.392 6 0.001
Less labile fraction C g kg−118.67 ±3.17 18.50 ±0.91 −0.068 6 0.948
Recalcitrant fraction C g kg−14.94 ±3.03 2.43 ±0.49 1.822 3.58 0.151 *
Mineralization of C mg CO2g−1176.0 ±29.30 278.5 ±64.80 −2.781 6 0.032
Easily Extractable Glomalin mg g
−10.5 ±0.00 0.8 ±0.00 −9.076 6 0.000
Microbial biomass carbon µgCg−1751.1 ±73.70 77.0 ±0.00 45.195 3 0.000
Colony forming units g−1516,000 ±323,777 1,200,777 ±701,683 −1.516 6 0.180
Humic acids mg C kg−11657.4 ±91.90 2618 ±181.80 −10.464 6 0.000
Fulvic acids mg C kg−18671.4 ±144.20 9632.2 ±144.10 −8.497 6 0.000
Humins mg C kg−114,316.3 ±221.80 7350 ±166.40 50.229 6 0.000
Peroxidase µmol g−1h−14.34 ±0.71 4.50 ±0.16 −0.472 6 0.653
Polyphenol oxidase µmol g−1h−16.41 ±0.53 7.23 ±0.57 −2.021 6 0.090
Lacasse µmol g−1h−10.02 ±0.01 0.18 ±0.00 −13 6 0.000
B-glucosidase mg PNP g−1145.1 ±7.20 510.6 ±19.5 −42.287 6 0.000
B-galactosidase mg PNP g−124.2 ±9.50 54.4 ±1.00 −4.608 3.03 0.019 *
Table 2.
Soil bacterial sequences of pecan tree (Carya illinoinensis) orchards under organic (Org)
and conventional (Conv) management in Coahuila, Mexico. CD =chimeras discarded, QS =quality
sequences after chimeras were discarded, BS =bacterial sequences, OTUs =operational taxonomic units.
Sample Total Assembled Discarded CD QS BS OTUs
Org 1 278,980 68,366 210,608 568 67,798 27,154 6014
Org 2 225,583 52,984 172,599 486 52,498 22,087 5594
Org 3 187,477 57,859 129,607 610 57,249 34,945 6377
Mean 230,680 59,736 170,938 555 59,182 28,062 5995
Conv 1 212,217 51,586 160,618 523 51,063 33,292 6022
Conv 2 272,201 83,983 188,207 870 83,113 53,264 8653
Conv 3 318,199 94,434 223,744 842 93,592 59,769 9135
Mean 267,539 76,668 190,856 745 75,923 48,775 7937
Diversity 2020, 12, x FOR PEER REVIEW 5 of 15
Easily Extractable Glomalin mg g−1
0.5 ± 0.00
0.8 ± 0.00
−9.076
6
0.000
Microbial biomass carbon µg C g−1
751.1 ± 73.70
77.0 ± 0.00
45.195
3
0.000
Colony forming units g−1
516,000 ± 323,777
1,200,777 ± 701,683
−1.516
6
0.180
Humic acids mg C kg−1
1657.4 ± 91.90
2618 ± 181.80
−10.464
6
0.000
Fulvic acids mg C kg−1
8671.4 ± 144.20
9632.2 ± 144.10
−8.497
6
0.000
Humins mg C kg−1
14,316.3 ± 221.80
7350 ± 166.40
50.229
6
0.000
Peroxidase µmol g−1 h−1
4.34 ± 0.71
4.50 ± 0.16
−0.472
6
0.653
Polyphenol oxidase µmol g−1 h−1
6.41 ± 0.53
7.23 ± 0.57
−2.021
6
0.090
Lacasse µmol g−1 h−1
0.02 ± 0.01
0.18 ± 0.00
−13
6
0.000
B-glucosidase mg PNP g−1
145.1 ± 7.20
510.6 ± 19.5
−42.287
6
0.000
B-galactosidase mg PNP g−1
24.2 ± 9.50
54.4 ± 1.00
−4.608
3.03
0.019 *
3.2. Abundance of Bacterial Taxa
The average number of sequences assembled for Org was 230,680, and for Conv it was 267,539.
After taxonomic designation, averages of 28,062 bacterial sequences for Org, and 48,775 for Conv,
were obtained. The average number of OTUs was 5995 for Org, and 7937 for Conv (Table 2). Simple
random rarefaction was made at 20,000 sequences, since at this point the number of OTUs reached
asymptotes (Figure 2).
Table 2. Soil bacterial sequences of pecan tree (Carya illinoinensis) orchards under organic (Org) and
conventional (Conv) management in Coahuila, Mexico. CD = chimeras discarded, QS = quality
sequences after chimeras were discarded, BS = bacterial sequences, OTUs = operational taxonomic
units.
Sample
Total
Assembled
Discarded
CD
QS
BS
OTUs
Org 1
278,980
68,366
210,608
568
67,798
27,154
6014
Org 2
225,583
52,984
172,599
486
52,498
22,087
5594
Org 3
187,477
57,859
129,607
610
57,249
34,945
6377
Mean
230,680
59,736
170,938
555
59,182
28,062
5995
Conv 1
212,217
51,586
160,618
523
51,063
33,292
6022
Conv 2
272,201
83,983
188,207
870
83,113
53,264
8653
Conv 3
318,199
94,434
223,744
842
93,592
59,769
9135
Mean
267,539
76,668
190,856
745
75,923
48,775
7937
Figure 2.
Rarefaction curves for soil bacteria OTUs identified from pecan tree (Carya illinoinensis)
orchards under organic (Org) and conventional (Conv) management in Coahuila, Mexico.
Diversity 2020,12, 436 6 of 15
For Org management, the most abundant phyla were Proteobacteria (
x
=36%), Actinobacteria
(
x
=24%), Planctomycetes (
x
=18%) and Chloroflexi (
x
=13%), (Figure 3a). A similar phyla
composition was observed for the Conv management: Proteobacteria (
x
=32%), Actinobacteria
(
x
=26%), Planctomycetes (
x
=19%) and Chloroflexi (
x
=15%), (Figure 3b). The remaining phyla were
Acidobacteria, Gemmatimonadetes, Verrumicrobia, Cyanobacteria, Parcubacteria, and Saccharibacteria.
Diversity 2020, 12, x FOR PEER REVIEW 6 of 15
Figure 2. Rarefaction curves for soil bacteria OTUs identified from pecan tree (Carya illinoinensis)
orchards under organic (Org) and conventional (Conv) management in Coahuila, Mexico.
For Org management, the most abundant phyla were Proteobacteria ( = 36%), Actinobacteria
( = 24%), Planctomycetes ( = 18%) and Chloroflexi ( = 13%), (Figure 3a). A similar phyla
composition was observed for the Conv management: Proteobacteria ( = 32%), Actinobacteria ( =
26%), Planctomycetes ( = 19%) and Chloroflexi ( = 15%), (Figure 3b). The remaining phyla were
Acidobacteria, Gemmatimonadetes, Verrumicrobia, Cyanobacteria, Parcubacteria, and
Saccharibacteria.
Figure 3.
Relative abundance (%) per sample and means of the main bacterial phyla in soil samples
of pecan tree (Carya illinoinensis) orchards under organic (
a
) and conventional (
b
) management in
Coahuila, Mexico.
A total of 776 bacterial genera was obtained, of which 29 had a relative abundance greater than 1%
(20 had a taxonomical name, and 9 had a taxonomical key). The three more abundant cultivated genera
were Tepidisphaera (
x
=7.1%), Sphingomonas (
x
=3.2%), and Gemmata (
x
=4.0%). The first two genera
were more representative in the Conv management, while the third one was more representative in
the Org management. The remaining genera were Dongia,Microvirga,Sphingosinicella,Streptomyces,
Rhizomicrobium,Stenotrophobacter,Pseudolabrys,Zavarzinella and Catelliglobosispora; all of these were
present in both managements (Table 3).
Diversity 2020,12, 436 7 of 15
Table 3.
Relative abundance of the bacterial genera found in the soil of pecan tree (Carya illinoinensis)
orchards under organic and conventional management in Coahuila, Mexico. Only those genera whose
relative abundance was
≥
1% are shown. Asterisks indicate greater abundance according to the type
of management.
Genera Relative Abundance%
Organic Conventional
Tepidisphaera 3.8 7.1 *
GQ396871 3.9 3.7
Sphingomonas 2.6 3.2 *
Gemmata 4.0 * 3.1
Dongia 3.1 * 2.1
FJ478799 4.2 2.0
Microvirga 0.9 1.9 *
GQ263023 1.4 1.8
Sphingosinicella 0.5 1.7 *
Streptomyces 1.5 1.6 *
Rhizomicrobium 1.1 1.3 *
EU335288 0.9 1.2
AF370880 1.6 1.2
FJ479444 0.7 1.2
Stenotrophobacter
0.9 1.2 *
EF125410 0.3 1.2
EU669599 0.3 1.1
Pseudolabrys 1.2 * 1.1
Zavarzinella 1.7 * 1.1
EU335161 1.1 1.0
Catelliglobosispora
1.2 * 1.0
The CCA suggested that in both managements there is a separation between the phyla, which is
associated with some chemical and biological characteristics of the soil. However, this separation was
visible only in the second axis (Figure 4). Regarding axis 1, the phyla located left of the “y” axis belong
to Gemmatimonadetes, Cyanobacteria, Parcubacteria, Chloroflexi, Actinobacteria, Proteobacteria,
and Saccharibacteria—the same that are favored by PER (
−
0.64) and F3 (
−
0.62). In contrast, on the
right side of the “y” axis, the Verrumicrobia, Planctomycetes and Acidobacteria phyla were located
in association with pH (0.66) and C/N (0.94). Above the “x” axis, the Org management samples
were found, wherein the phyla belonging to Gemmatimonadetes, Parcubacteria, Proteobacteria,
Cyanobacteria, Acidobacteria, and Verrumicrobia were favored by the presence of HS (0.96). On the
other hand, the phyla located below the “x” axis were Chloroflexi, Actinobacteria, Planctomycetes and
Saccharibacteria, which were associated with EEG (−0.98), FA (−0.97) and B-glu (−0.97).
Diversity 2020, 12, x FOR PEER REVIEW 8 of 16
Figure 4. Canonical correspondence analysis of soil from pecan tree (Carya illinoinensis) orchards
under organic and conventional management in Coahuila, Mexico, identifying associations among
the main phyla and the evaluated soil variables.
4. Discussion
4.1. Chemical and Biological Variables of the Soil
The management of the soil in agricultural systems affects its physical, chemical and biological
characteristics [5]. It has been demonstrated that the concentration of N is higher in soils under Org
management, due to the abundance of microorganisms capable of mineralizing N more efficiently
[2,45]. Likewise, the addition of organic amendments generates a greater availability of nutrients such
as P, which is mainly found in humic substances or in the microbial biomass of the soil [46,47]. In this
study, the SOC content was higher than reported by other authors in pecan tree orchards [11,18]. In
addition, HS are considered to be the most recalcitrant fraction of the organic soil and, therefore, are
able to stay in the soil for longer [48]. It is likely that most of the SOC under Org management will be
stabilized in less labile and recalcitrant forms. With respect to MBC, it has been shown that its content
increases with the long-term establishment of plant cover, as in this study [49,50], while nitrogen
fertilization tends to decrease it [51]. Likewise, it is the main agent of SOM decomposition,
transforming nutrients and making them available [52], which may explain the high content of MBC
Figure 4.
Canonical correspondence analysis of soil from pecan tree (Carya illinoinensis) orchards under
organic and conventional management in Coahuila, Mexico, identifying associations among the main
phyla and the evaluated soil variables.
Diversity 2020,12, 436 8 of 15
4. Discussion
4.1. Chemical and Biological Variables of the Soil
The management of the soil in agricultural systems affects its physical, chemical and biological
characteristics [
5
]. It has been demonstrated that the concentration of N is higher in soils under Org
management, due to the abundance of microorganisms capable of mineralizing N more efficiently [
2
,
45
].
Likewise, the addition of organic amendments generates a greater availability of nutrients such as P,
which is mainly found in humic substances or in the microbial biomass of the soil [
46
,
47
]. In this study,
the SOC content was higher than reported by other authors in pecan tree orchards [
11
,
18
]. In addition,
HS are considered to be the most recalcitrant fraction of the organic soil and, therefore, are able to stay
in the soil for longer [
48
]. It is likely that most of the SOC under Org management will be stabilized in
less labile and recalcitrant forms. With respect to MBC, it has been shown that its content increases
with the long-term establishment of plant cover, as in this study [
49
,
50
], while nitrogen fertilization
tends to decrease it [
51
]. Likewise, it is the main agent of SOM decomposition, transforming nutrients
and making them available [
52
], which may explain the high content of MBC and the low percentages
of SOM in pecan orchards under Org management. In contrast, it has been shown that the F2 fraction
has a high rate of decomposition and a shorter residence time in the soil [
53
], thus responding to
Conv management by releasing carbon into the atmosphere in the form of CO
2
, causing losses of
nutrients and soil fertility [
54
]—contrary to what happens in soil Org management [
55
,
56
]. On the
other hand, organic materials with a low degree of humification, i.e., labile, increase the HA and FA
fractions [
57
,
58
]. According to V
á
squez et al. [
59
], there is a positive correlation between CO
2
emissions
and carbon labile fractions. Carbon loss in the form of CO
2
is caused by the decomposition of SOM
by heterotrophic microorganisms, and occurs mainly when there is an increase in the availability of
SOM and when it lacks a biochemical composition enriched with recalcitrant organic compounds,
which makes it more difficult for microorganisms to disintegrate [
60
]. The results herein reported
suggest that in the pecan tree orchard under Conv management, in spite of the fact that the content of
SOM is greater than under Org management, the SOC is less stable and could easily be lost in the form
of CO2, because the SOM lacks recalcitrant organic compounds [60–62].
Agronomic management is influential in the increase of concentrations of glomalin [
63
],
which agrees with the current study since the amount of glomalin was greater in Conv management.
In this regard, the high concentration of CO
2
produces effects in the increase of the glomalin reserves [
64
],
which suggests that glomalin is related to the high respiration rate in soils under Conv management.
Furthermore, the oxidative enzyme LAC (EC 1.10.3.2) participates in the degradation and biosynthesis
of lignin, and its activity may be increased by substrates that degenerate rapidly, such as cellobiose
and glucose, and with an increase in fungi growth [
65
,
66
]. The above may suggest that the increase
in oxidative enzymatic activity in the soil under Conv management may be due to the presence of
substrates that may easily be degraded by fungi, which could also explain the high content of glomalin
under this same management. As for
β
-glu (EC 3.2.1.21), it participates in the hydrolysis of cellobiose
to glucose [
67
], degrading plant cell walls and contributing to the first phases of plant cell tissue
decomposition [
68
]. The increased activity of
β
-gal (EC 3.2.1.23) may suggest that soil microorganisms
are metabolically more active with rapid proliferation, thus increasing the efficiency of enzyme
production [
69
]. Furthermore, as these enzymes degrade labile carbon compounds, their activity shows
how the microorganisms present in the soil under Conv management mineralize this carbon fraction
to obtain nutrients, but not to promote carbon sequestration [70].
4.2. Abundance of Bacterial Taxa
Proteobacteria phyla abound when there is a high availability of nutrients due to an increase in
SOM, and also, they are able to consume labile organic carbon [
71
–
73
], which may suggest that the
disposition of SOC in soil under Org management is subject to microbial decomposition of the SOM,
and the velocity of this decomposition depends on, among other variables, the availability of
Diversity 2020,12, 436 9 of 15
nutrients [
74
]. The Actinobacteria phylum has diverse physiological properties, such as the production
of extracellular enzymes for the decomposition of organic matter [
75
]. It has also been shown that
Actinobacteria abundance is associated with the respiration rates of the soil [
76
,
77
], which agrees with
the current study, since CO
2
emission was greater under Conv management. Regarding bacterial
genera that were more abundant in soil under Org management, Gemmata is capable of using glucose
and galactose as a source of carbon in order to thrive, and therefore it is an important producer
in the carbon and N cycles [
78
,
79
]. Likewise, it has been shown that Dongia and Pseudolabrys
genera were significantly more abundant in the soils under non-tillage and addition of organic
residues [
80
]. Regarding Zavarzinella, in spite of its importance, nowadays its isolation and behavior
have been demonstrated in macroalgae [
81
], while there has been little or no research done in
soils. Lastly, the Catelliglobosispora genera have also been positively correlated with sucrose [
82
] and
have a high potential for the deconstruction of cellulose and chitin [
83
]. It seems probable that the
establishment of vegetation covers and deposits of organic matter in Org management will promote
sources of carbon, which increase the abundance of Gemmata,Dongia, and Pseudolabrys. Regarding
the more representative genera under Conv management, Tepidisphaera hydrolyzes a broad range of
carbohydrates, among which are glucose and galactose, essential components in SOM [
84
]. On the
other hand, in agricultural soils, some species of Sphingomonas have shown the capacity for degrading
chemical compounds of herbicides into CO
2
that is liberated into the atmosphere [
85
], which may
suggest that the abundance of both genera may be related to the SOM content and the mineralization
process of carbon under this management.
The Streptomyces genera have been described at length for their adaptation to soils, where they are
capable of forming hyphae that branch out to attach to and penetrate into insoluble organic residues
from plants and other organisms, as well as recalcitrant insoluble inorganic polymers such as chitin and
cellulose [
86
,
87
]. In this regard, studies show that the production of oxidative enzymes, such as LAC,
associated with the population growth of Streptomyces, intervene in the degradation of lignocellulosic
compounds [
88
,
89
]. Regarding Rhizomicrobium, a significant abundance has been reported in soils
contaminated with fluoride and chloride [
90
] as well as in soils where organic residues are applied [
80
].
Finally, it has been shown that the Stenotrophobacter genera participate in the carbon and N cycle and
respond to agronomic management [
91
,
92
]. These results suggest that the application of organic and
inorganic compounds to the soil used in the conventional cultivation of pecan trees affects the bacterial
abundance and functional diversity, which impacts the functional properties of the soil, particularly
those related to carbon forms [
6
,
93
,
94
]. The results obtained from the CCA confirm that the bacterial
communities in the soil were influenced by the type of management. Under the Org management,
the Acidobacteria phylum was benefited by HS content. As was mentioned before, HS are the most
recalcitrant fraction of organic soil due to the stabilization of SOC [
31
,
48
,
95
]. Rawat et al. [
96
] showed
that Acidobacteria communities are essential to the cycle of carbon in the soil, and that its activity and
dominion depend on them. Likewise, being classified as oligotrophic organisms, they are related to
C sequestration, since it has been demonstrated that they are autotrophic and have the capacity to
fix atmospheric CO
2
in the soils of arid and semi-arid ecosystems [
97
,
98
], and thus contribute to the
generation of organic carbon reservoirs [
99
,
100
]. Conversely, under Conv management, the bacterial
communities of the Actinobacteria Phylum were influenced by the EEG, FA, and B-glu variables.
Thereon, the change in the microbial community of fungi and Actinobacteria is due to the amounts of
organic residues that result from the availability of resources [
6
,
72
,
101
]. It has been shown that both
microbial communities are fundamental in the degradation process of complex compounds such as
cellulose, lignin, and chitin [
102
], where Actinobacteria, in particular, present diverse physiological
properties, such as the production of extracellular and metabolic enzymes related to the decomposition
of SOM [75].
Diversity 2020,12, 436 10 of 15
5. Conclusions
The use of organic practices in the cultivation of pecan trees seems to influence the concentration of
nutrients and various chemical and biological variables in the soil, mainly in the capture of recalcitrant
C compounds. Furthermore, this type of management could favor bacterial communities capable
of promoting greater efficiency in organic carbon sequestration. On the other hand, conventional
management practices influence the increase in carbon mineralization, as well as the enzymatic activity
of the soil, particularly that of the enzymes related to the metabolism of labile compounds. The use
of genomic technologies has allowed the discovery of the soil microbiome in recent years, however
it is still necessary to understand the adaptation and plasticity of some bacterial communities and
other soil microorganisms, as well as their functional biodiversity and soil–plant dynamics, which are
essential in order to preserve the optimal state of the soil.
Author Contributions:
Conceptualization, A.C.-R., E.N.-R., C.G.-D.l.P. and J.G.A.-
Á
.; data curation, A.C.-R., F.V.-P.
and C.D.-V.; formal analysis, A.C.-R., E.N.-R. and M.M.C.; funding acquisition, E.N.-R. and R.T.-C.; investigation,
A.C.-R.; methodology, A.C.-R., E.N.-R., C.G.-D.l.P., F.V.-P., C.D.-V. and V.C.-G.; project administration, E.N.-R.;
resources, E.N.-R., R.T.-C. and C.G.-D.l.P.; software, A.C.-R., C.G.-D.l.P., F.V.-P. and C.D.-V.; supervision, E.N.-R.,
R.T.-C., C.G.-D.l.P., J.G.A.-
Á
. and M.M.C.; validation, A.C.-R., R.T.-C., C.G.-D.l.P. and J.G.A.-
Á
.; visualization,
R.T.-C. and M.M.C.; writing—original draft, A.C.-R.; writing—review and editing, E.N.-R., R.T.-C., C.G.-D.l.P.,
J.G.A.-
Á
., M.M.C., F.V.-P., C.D.-V. and V.C.-G. All authors have read and agreed to the published version of
the manuscript.
Funding:
This research was funded by Ministry of Agriculture and Rural Development (SADER) of M
é
xico,
grant number 12281434630 and by Consejo Nacional de Ciencia y Tecnologia (CONACYT), by a graduate
scholarship for the first author.
Acknowledgments:
We are grateful to M.C. Jos
é
Heriberto Aguilar P
é
rez and Nueces del Bravo SPR de RL for
their help and facilities provided during the field work.
Conflicts of Interest: The authors declare no conflict of interest.
References
1.
Delgado-Baquerizo, M.; Maestre, F.T.; Reich, P.B.; Trivedi, P.; Osanai, Y.; Liu, Y.R.; Hamonts, K.; Jeffries, T.C.;
Singh, B.K. Carbon Content and Climate Variability Drive Global Soil Bacterial Diversity Patterns. Ecol. Monogr.
2016,86, 373–380. [CrossRef]
2.
Berthrong, S.T.; Buckley, D.H.; Drinkwater, L.E. Agricultural Management and Labile Carbon Additions
Affect Soil Microbial Community Structure and Interact with Carbon and Nitrogen Cycling. Microb. Ecol.
2013,66, 158–170. [CrossRef] [PubMed]
3.
Coleman, D.; Wall, D. Soil Microbiology, Ecology and Biochemistry, 4th ed.; Academic: Boston, MA, USA, 2015;
pp. 11–149.
4.
Creamer, A.; de Menezes, B.; Krull, S.; Sanderman, J.; Newton-Walters, R.; Farrell, M. Corrigendum to
“Microbial Community Structure Mediates Response of soil C Decomposition to Litter Addition and Warming.
Soil Biol. Biochem. 2015,83, 175–188. [CrossRef]
5.
Jim
é
nez-Bueno, N.G.; Valenzuela-Encinas, C.; Marsch, R.; Ortiz-Guti
é
rrez, D.; Verhulst, N.; Govaerts, B.;
Dendooven, L.; Navarro-Noya, Y.E. Bacterial Indicator Taxa in Soils under Different Long-Term Agricultural
Management. J. Appl. Microbiol. 2016,120, 921–933. [CrossRef]
6.
Mathew, R.P.; Feng, Y.; Githinji, L.; Ankumah, R.; Balkcom, K.S. Impact of No-Tillage and Conventional
Tillage Systems on Soil Microbial Communities. Appl. Environ. Soil Sci. 2012,2012, 1–10. [CrossRef]
7.
Van Diepeningen, A.D.; De Vos, O.J.; Korthals, G.W.; Van Bruggen, A.H.C. Effects of Organic versus
Conventional Management on Chemical and Biological Parameters in Agricultural Soils. Appl. Soil Ecol.
2006,31, 120–135. [CrossRef]
8.
Smith, F.P.; Prober, S.M.; House, A.P.N.; McIntyre, S. Maximizing Retention of Native Biodiversity in Australian
Agricultural Landscapes-The 10:20:40:30 Guidelines. Agric. Ecosyst. Environ. 2013,166, 35–45. [CrossRef]
9.
Maffei, D.F.; Batalha, E.Y.; Landgraf, M.; Schaffner, D.W.; Franco, B.D.G.M. Microbiology of Organic and
Conventionally Grown Fresh Produce. Braz. J. Microbiol. 2016,47, 99–105. [CrossRef]
Diversity 2020,12, 436 11 of 15
10.
Mishra, D.; Rajvir, S.; Mishra, U.; Kumar, S. Role of Bio-Fertilizer in Organic Agriculture: A Review.
Res. J. Recent 2013,2, 39–41.
11.
Lee, K.H.; Jose, S. Soil Respiration and Microbial Biomass in a Pecan—Cotton Alley Cropping System in
Southern USA. Agrofor. Syst. 2003,58, 45–54. [CrossRef]
12.
Kremer, R.J.; Kussman, R.D. Soil Quality in a Pecan-Kura Clover Alley Cropping System in the Midwestern
USA. Agrofor. Syst. 2011,83, 213–223. [CrossRef]
13.
Duchene, O.; Vian, J.F.; Celette, F. Intercropping with Legume for Agroecological Cropping Systems:
Complementarity and Facilitation Processes and the Importance of Soil Microorganisms. A Review.
Agric. Ecosyst. Environ. 2017,240, 148–161. [CrossRef]
14. Pérez, H. Manual Para El Manejo Orgánico Del Nogal Pecanero; Palibrio: Bloomington, IN, USA, 2014; p. 274.
15.
Malik, N.S.A.; Perez, J.L.; Lombardini, L.; Cornacchia, R.; Cisneros-Zevallosb, L.; Braforda, J. Phenolic
Compounds and Fatty Acid Composition of Organic and Conventional Grown Pecan Kernels. J. Sci.
Food Agric. 2009,89, 2207–2213. [CrossRef]
16.
FAO. FAOSTAT, Produccion de Nuez Con C
á
scara. 2018. Available online: http://www.fao.org/faostat/es/
#data/QC (accessed on 21 April 2020).
17.
SADER. Panorama Agroalimentario 2019. Available online: https://federacion-anech.org/2019/11/14/atlas-
agroalimentario-2019/(accessed on 21 April 2020).
18.
Mungai, N.W.; Motavalli, P.P.; Kremer, R.J. Soil Organic Carbon and Nitrogen Fractions in Temperate Alley
Cropping Systems. Commun. Soil Sci. Plant Anal. 2006,37, 977–992. [CrossRef]
19.
Bai, C.; Reilly, C.C.; Wood, B.W. Nickel Deficiency Disrupts Metabolism of Ureides, Amino Acids, and Organic
Acids of Young Pecan Foliage. Plant Physiol. 2006,140, 433–443. [CrossRef]
20.
Brown, V.; Braun de Torrez, E.; McCracken, G. Crop Pests Eaten by Bats in Organic Pecan Orchards. Crop Prot.
2015,67, 66–71. [CrossRef]
21.
INIFAP; CONABIO. Instituto Nacional de Investigaciones Forestales y Agropecuarias (INIFAP)—Comisi
ó
n
Nacional para el Conocimiento y Uso de la Biodiversidad (CONABIO), (1995). “Edafolog
í
a”. Escalas
1:250000 y 1:1000000. M
é
xico. Available online: http://www.conabio.gob.mx/informacion/gis/(accessed on 2
November 2020).
22.
INEGI. Prontuario de Informaci
ó
n Geogr
á
fica Municipal, Allende, Coahuila de Zaragoza. Available online:
http://www3.inegi.org.mx/contenidos/app/mexicocifras/datos_geograficos/05/05030.pdf (accessed on 2 April 2020).
23.
INIFAP. Tecnolog
í
a de Producci
ó
n En Nogal Pecanero, Prmera; Salinas, H., Quiroga, H., Tijerina, A., Figueroa, U.,
Eds.; INIFAP-SAGARPA: Matamoros, Mexico, 2002; p. 221.
24. Jackson, L. Análisis Químico de Suelos, 4th ed.; Beltrán, M., Ed.; Omega: Barcelona, Spain, 1982; p. 662.
25.
Bremner, J.M. Inorganic Forms of Nitrogen in Soil. In Methods of Soil Analysis; Black, C.A., Ed.; Crop Science
Society of America: Ames, IA, USA, 1965; pp. 1179–1237. [CrossRef]
26.
Olsen, S.; Sommers, L. Phosphurus. In Methods of Soil Analysis; American Society of Agronomy:
Madison, WI, USA, 1982; pp. 404–430.
27.
Thomas, G. Exchangeable Cations. In Methods of Soil Analysis; Black, C.A., Ed.; American Society of
Agronomy: Madison, WI, USA, 1982; pp. 159–165.
28.
Walkley, A.; Black, I. An Examination of DegtjareffMethod for Determining Soil Organic Matter and a
Proposed Modification of the Chromic Acid Titration Method. Soil Sci. 1934,37, 29–37. [CrossRef]
29.
Anderson, D.; Schoenau, J. Soli Humus Fractions. In Soli Sampling Methods of Analysis; Carter, M., Ed.;
CRC Press: Boca Ratón, FL, USA, 1993; pp. 391–395.
30.
D˛ebska, B.; Długosz, J.; Piotrowska-Długosz, A.; Banach-Szott, M. The Impact of a Bio-Fertilizer on the Soil
Organic Matter Status and Carbon Sequestration—Results from a Field-Scale Study. J. Soils Sediments
2016
,
16, 2335–2343. [CrossRef]
31.
Chan, K.Y.; Bowman, A.; Oates, A. Oxidizible Organic Carbon Fractions and Soil Quality Changes in an Oxic
Paleustalf under Different Pasture Leys. Soil Sci. 2001,166, 61–67. [CrossRef]
32.
Brookes, P.; Landman, A.; Pruden, G.; Jenkinson, D. Chloroform Fumigation and the Release of Soil Nitrogen;
a Rapid Direct Extraction Method to Measure Microbial Biomasa Nitrogen in Soil. Soil Biol. Biochem.
1985
,
17, 837–842. [CrossRef]
33.
Rillig, M.C.; Ramsey, P.W.; Morris, S.; Paul, E.A. Glomalin, an Arbuscular-Mycorrhizal Fungal Soil Protein,
Responds to Land-Use Change. Plant Soil 2003,253, 293–299. [CrossRef]
Diversity 2020,12, 436 12 of 15
34.
Guerrero, P.; Quintero, R.; Espinoza, V.; Benedicto, G.; Sanchez, M. Respiration of CO
2
as an Indicator of
Microbial Activity in Organic Fertilizers of Lupinus. Terra Latinoam. 2012,30, 355–362.
35.
Garc
í
a, A.; Rivero, C. Evaluaci
ó
n Del Carbono Microbiano y La Respiraci
ó
n Basal En Respuesta a La
Aplicaci
ó
n de Lodo Papelero En Los Suelos de La Cuenca Del Lago de Valencia. Rev. Fac. Agron.
2008
,34, 215–229.
36.
Saiya-Cork, K.R.; Sinsabaugh, R.L.; Zak, D.R. The Effects of Long Term Nitrogen Deposition on Extracellular
Enzyme Activity in an Acer saccharum Forest Soil. Soil Biol. Biochem. 2002,34, 1309–1315. [CrossRef]
37.
Bourbonnais, R.; Paice, M.G. Oxidation of Non-Phenolic Substrates. FEBS Lett.
1990
,267, 99–102. [CrossRef]
38.
Tabatabai, M. Soil Enzymes. In Methods of Soil Analysis; Weavwe, R., Ed.; American Society of Agronomy:
Madison, WI, USA, 1994; pp. 775–833.
39.
Klindworth, A.; Pruesse, E.; Schweer, T.; Peplies, J.; Quast, C.; Horn, M.; Glöckner, F.O. Evaluation of General
16S Ribosomal RNA Gene PCR Primers for Classical and Next-Generation Sequencing-Based Diversity
Studies. Nucleic Acids Res. 2013,41, 1–11. [CrossRef] [PubMed]
40.
Illumina. 16S Metagenomic Sequencing Library Preparation, Preparing 16S Ribosomal RNA Gene
Amplicons for the Illumina MiSeq System. Available online: https://emea.illumina.com/content/dam/
illuminasupport/documents/documentation/chemistry_documentation/16s/16s-metagenomic-library-
prep-guide-15044223-b.pdf (accessed on 20 February 2019).
41.
Illumina. Nextera XT DNA Library Prep Kit Reference Guide. Available online:
https://support.illumina.com/content/dam/illumina-support/documents/documentation/chemistry_
documentation/samplepreps_nextera/nextera-xt/nextera-xt-library-prep-reference-guide-15031942-05.pdf
(accessed on 20 February 2019).
42.
Caporaso, J.G.; Fierer, N.; Peña, A.G.; Goodrich, J.K.; Gordon, J.I.; Huttley, G.A.; Kelley, S.T.; Knights, D.;
McDonald, D.; Muegge, B.D.; et al. QIIME Allows Analysis of High-Throughput Community Sequencing
Data. Nat. Methods 2010,7, 335–336. [CrossRef] [PubMed]
43.
Garc
í
a-De la Peña, C.; Garduño-Niño, E.; Vaca-Paniagua, F.; D
í
az-Vel
á
squez, C.; Barrows, C.; Gomez-Gil, B.;
Valenzuela-N
ú
ñez, L. Comparison of the Fecal Bacterial Microbiota Composition between Wild and Captive
Bolson Tortoises (Gopherus flavomarginatus). Herpetol. Conserv. Biol. 2019,14, 587–600.
44.
Hammer, Ø.; Harper, D.A.T.; Ryan, P.D. Past: Paleontological Statistics Software Package for Education and
Data Analysis. Palaeontol. Electron. 2001,4, 1–9.
45.
Compton, J.E.; Watrud, L.S.; Porteous, L.A.; DeGrood, S. Response of Soil Microbial Biomass and Community
Composition to Chronic Nitrogen Additions at Harvard Forest. For. Ecol. Manag. 2004,196, 143–158. [CrossRef]
46.
Idowu, O.J.; Sanogo, S.; Brewer, C.E. Short-Term Impacts of Pecan Waste By-Products on Soil Quality in
Texturally Different Arid Soils. Commun. Soil Sci. Plant Anal. 2017,48, 1781–1791. [CrossRef]
47.
Kruse, J.; Abraham, M.; Amelung, W.; Baum, C.; Bol, R.; Kühn, O.; Lewandowski, H.; Niederberger, J.;
Oelmann, Y.; Rüger, C.; et al. Innovative Methods in Soil Phosphorus Research: A Review. J. Plant Nutr. Soil Sci.
2015,178, 43–88. [CrossRef] [PubMed]
48.
Benbi, D.K.; Brar, K.; Toor, A.S.; Singh, P.; Singh, H. Soil Carbon Pools under Poplar-Based Agroforestry,
Rice-Wheat, and Maize-Wheat Cropping Systems in Semi-Arid India. Nutr. Cycl. Agroecosyst.
2012
,92,
107–118. [CrossRef]
49.
Mäder, P.; Fließbach, A.; Dubois, D.; Gunst, L.; Fried, P.; Niggli, U. Soil Fertility and Biodiversity in Organic
Farming. Science 2002,296, 1694–1697. [CrossRef]
50.
Culman, S.W.; DuPont, S.T.; Glover, J.D.; Buckley, D.H.; Fick, G.W.; Ferris, H.; Crews, T.E. Long-Term
Impacts of High-Input Annual Cropping and Unfertilized Perennial Grass Production on Soil Properties and
Belowground Food Webs in Kansas, USA. Agric. Ecosyst. Environ. 2010,137, 13–24. [CrossRef]
51.
Liu, E.; Yan, C.; Mei, X.; Zhang, Y.; Fan, T. Long-Term Effect of Manure and Fertilizer on Soil Organic Carbon
Pools in Dryland Farming in Northwest China. PLoS ONE 2013,8, 1–9. [CrossRef]
52.
Brookes, P.; Cayuela, M.L.; Contin, M.; De Nobili, M.; Kemmitt, S.J.; Mondini, C. The Mineralisation of Fresh
and Humified Soil Organic Matter by the Soil Microbial Biomass. Waste Manag.
2008
,28, 716–722. [CrossRef]
53.
de Souza, G.P.; de Figueiredo, C.C.; de Sousa, D.M.G. Relationships between Labile Soil Organic Carbon
Fractions under Different Soil Management Systems. Sci. Agric. 2016,73, 535–542. [CrossRef]
54.
Mart
í
nez, E.; Fuentes, J.P.; Acevedo, E. Carbono Org
á
nico y Propiedades Del Suelo. Revista de la Ciencia del
Suelo y Nutrición Vegetal 2008,8, 68–96. [CrossRef]
55.
Ginebra, M.; Rodr
í
guez, M.; Calero, B.; Ponce de Le
ó
n, D.; Font, L. The Labile Carbon as Indicator of Changes
in Two Soils under Different Uses. Cultiv. Trop. 2015,36, 64–70.
Diversity 2020,12, 436 13 of 15
56.
Dignac, M.F.; Derrien, D.; Barr
é
, P.; Barot, S.; C
é
cillon, L.; Chenu, C.; Chevallier, T.; Freschet, G.T.; Garnier, P.;
Guenet, B.; et al. Increasing Soil Carbon Storage: Mechanisms, Effects of Agricultural Practices and Proxies.
A Review. Agron. Sustain. Dev. 2017,37, 1–27. [CrossRef]
57.
Lejon, D.; Sebastia, J.; Lamy, I.; Chaussod, R.; Ranjard, L. Relationships between Soil Organic Status and
Microbial Community Density and Genetic Structure in Two Agricultural Soils Submitted to Various Types
of Organic Management. Microb. Ecol. 2007,53, 650–663. [CrossRef]
58.
Abril, A.; Noe, L.; Filippini, M.F. Manejo de Enmiendas Para Restaurar La Materia Org
á
nica Del Suelo En
Oasis de Regadío de Mendoza, Argentina. Rev. Investig. Agropecu. 2014,40, 83–91.
59.
V
á
squez, J.R.; Mac
í
as, F.; Menjivar, J.C. Respiraci
ó
n Del Suelo Seg
ú
n Su Uso y Su Relaci
ó
n Con Algunas
Formas de Carbono En El Departamento Del Magdalena, Colombia. Bioagro 2013,25, 175–180.
60. Á
lvaro-Fuentes, J.; Cantero-Mart
í
nez, C.; L
ó
pez, M.; Arr
ú
e, J. Fijaci
ó
n de Carbono y Reducci
ó
n de Emisiones
de CO
2
. In Aspectos Agron
ó
micos y Medioambientales de la Agricultura de Conservaci
ó
n; Gonz
á
lez, E.K.,
Ord
ó
ñez, R., Gil, J.A., Eds.; Ministerio de Medio Ambiente y Medio Rural y Marino: Zaragoza, Spain, 2010;
pp. 89–96.
61.
Jinbo, Z.; Changchun, S.; Wenyan, Y. Land Use Effects on the Distribution of Labile Organic Carbon Fractions
through Soil Profiles. Soil Sci. Soc. Am. J. 2006,70, 660–667. [CrossRef]
62.
Stockmann, U.; Adams, M.A.; Crawford, J.W.; Field, D.J.; Henakaarchchi, N.; Jenkins, M.; Minasny, B.;
McBratney, A.B.; De Courcelles, V.D.R.; Singh, K.; et al. The Knowns, Known Unknowns and Unknowns of
Sequestration of Soil Organic Carbon. Agric. Ecosyst. Environ. 2013,164, 80–99. [CrossRef]
63.
B
á
ez-P
é
rez, A.; Gonz
á
lez-Ch
á
vez, M.C.
Á
.; Etchevers-Barra, J.D.; Prat, C.; Hidalgo-Moreno, C. Glomalina y
Secuestro de Carbono En Tepetates Cultivados. Agrociencia 2010,44, 517–529.
64. Treseder, K.K.; Turner, K.M. Glomalin in Ecosystems. Soil Sci. Soc. Am. J. 2007,71, 1257–1266. [CrossRef]
65.
Otto, B.; Schlosser, D.; Reisser, W. First Description of a Laccase-like Enzyme in Soil Algae. Arch. Microbiol.
2010,192, 759–768. [CrossRef]
66.
Rivera-Hoyos, C.M.; Morales-
Á
lvarez, E.D.; Poutou-Piñales, R.A.; Pedroza-Rodr
í
guez, A.M.;
Rodr
Í
guez-V
á
zquez, R.; Delgado-Boada, J.M. Fungal Laccases. Fungal Biol. Rev.
2013
,27, 67–82. [CrossRef]
67.
Sardans, J.; Peñuelas, J.; Estiarte, M. Changes in Soil Enzymes Related to C and N Cycle and in Soil C and N
Content under Prolonged Warming and Drought in a Mediterranean Shrubland. Appl. Soil Ecol.
2008
,39,
223–235. [CrossRef]
68.
Arag
ó
n, R.; Sardans, J.; Peñuelas, J. Soil Enzymes Associated with Carbon and Nitrogen Cycling in Invaded
and Native Secondary Forests of Northwestern Argentina. Plant Soil 2014,384, 169–183. [CrossRef]
69.
Zhang, X.; Dong, W.; Dai, X.; Schaeffer, S.; Yang, F.; Radosevich, M.; Xu, L.; Liu, X.; Sun, X. Responses of
Absolute and Specific Soil Enzyme Activities to Long Term Additions of Organic and Mineral Fertilizer.
Sci. Total Environ. 2015,536, 59–67. [CrossRef]
70.
Kotrocz
ó
, Z.; Veres, Z.; Fekete, I.; Krakomperger, Z.; T
ó
th, J.A.; Lajtha, K.; T
ó
thm
é
r
é
sz, B. Soil Enzyme
Activity in Response to Long-Term Organic Matter Manipulation. Soil Biol. Biochem.
2014
,70, 237–243. [CrossRef]
71.
Vigdis, T.; Øvreås, L. Microbial Diversity, Life Strategies, and Adaptation to Life in Extreme Soils.
In Microbiology of Extreme Soils; Dion, P., Shekhar, C., Eds.; Springer: Berlin/Heidelberg, Germany, 2008;
Volume 16, pp. 15–43. [CrossRef]
72.
Carbonetto, B.; Rascovan, N.;
Á
lvarez, R.; Mentaberry, A.; V
á
zquez, M.P. Structure, Composition and
Metagenomic Profile of Soil Microbiomes Associated to Agricultural Land Use and Tillage Systems in
Argentine Pampas. PLoS ONE 2014,9, 1–11. [CrossRef]
73.
Pan, Y.; Cassman, N.; de Hollander, M.; Mendes, L.W.; Korevaar, H.; Geerts, R.H.E.M.; van Veen, J.A.;
Kuramae, E.E. Impact of Long-Term N, P, K, and NPK Fertilization on the Composition and Potential
Functions of the Bacterial Community in Grassland Soil. FEMS Microbiol. Ecol.
2014
,90, 195–205. [CrossRef]
74.
Rabbi, S.M.F.; Daniel, H.; Lockwood, P.V.; Macdonald, C.; Pereg, L.; Tighe, M.; Wilson, B.R.; Young, I.M.
Physical Soil Architectural Traits Are Functionally Linked to Carbon Decomposition and Bacterial Diversity.
Sci. Rep. 2016,6, 1–9. [CrossRef]
75.
Goodfellow, M.; Williams, S.T. Ecology of Actinomycetes. Annu. Rev. Microbiol.
1983
,37, 189–216. [CrossRef]
76.
Ozdemir-Kocak, F.; Isik, K.; Saricaoglu, S.; Saygin, H.; Inan-Bektas, K.; Cetin, D.; Guven, K.; Sahin, N. Kribbella
sindirgiensis sp. Nov. Isolated from Soil. Arch. Microbiol. 2017,199, 1399–1407. [CrossRef]
Diversity 2020,12, 436 14 of 15
77.
Liu, Y.R.; Delgado-Baquerizo, M.; Yang, Z.; Feng, J.; Zhu, J.; Huang, Q. Microbial Taxonomic and Functional
Attributes Consistently Predict Soil CO
2
Emissions across Contrasting Croplands. Sci. Total Environ.
2020
,
702, 1–8. [CrossRef]
78. Devos, D.P. Gemmata obscuriglobus.Curr. Biol. 2013,23, 705–707. [CrossRef] [PubMed]
79. Fuerst, J.A.; Lee, K.-C.; Butler, M.K. Gemmata. Bergey’s Man. Syst. Archaea Bact. 2015, 1–5. [CrossRef]
80.
Wang, H.; Li, X.; Li, X.; Wang, J.; Li, X.; Guo, Q.; Yu, Z.; Yang, T.; Zhang, H. Long-Term No-Tillage and
Different Residue Amounts Alter Soil Microbial Community Composition and Increase the Risk of Maize
Root Rot in Northeast China. Soil Tillage Res. 2020,196, 104452. [CrossRef]
81.
Faria, M.; Bordin, N.; Kizina, J.; Harder, J.; Devos, D.; Lage, O.M. Planctomycetes Attached to Algal Surfaces:
Insight into Their Genomes. Genomics 2018,110, 231–238. [CrossRef]
82.
Sun, J.; Zhang, Q.; Zhou, J.; Wei, Q. Pyrosequencing Technology Reveals the Impact of Different Manure
Doses on the Bacterial Community in Apple Rhizosphere Soil. Appl. Soil Ecol. 2014,78, 28–36. [CrossRef]
83.
Talamantes, D.; Biabini, N.; Dang, H.; Abdoun, K.; Berlemont, R. Natural Diversity of Cellulases, Xylanases,
and Chitinases in Bacteria. Biotechnol. Biofuels 2016,9, 1–11. [CrossRef]
84.
Kovaleva, O.L.; Elcheninov, A.G.; Kublanov, I.V.; Bonch-Osmolovskaya, E. Tepidisphaera. Bergey’s Man. Syst.
Archaea Bact. 2019,1, 1–5. [CrossRef]
85.
Sørensen, S.; Ronen, Z.; Aamand, J. Isolation from Agricultural Soil and Characterization of a Sphingomonas
sp. Able to Mineralize the Phenylurea Herbicide Isoproturon. Society 2001,67, 5403–5409. [CrossRef]
86.
Chater, K.F.; Bir
ó
, S.; Lee, K.J.; Palmer, T.; Schrempf, H. The Complex Extracellular Biology of Streptomyces.
FEMS Microbiol. Rev. 2010,34, 171–198. [CrossRef]
87.
Seipke, R.F.; Kaltenpoth, M.; Hutchings, M.I. Streptomyces as Symbionts: An Emerging and Widespread
Theme? FEMS Microbiol. Rev. 2012,36, 862–876. [CrossRef]
88.
de Oru
é
Lucana, D.O.; Schaa, T.; Schrempf, H. The Novel Extracellular Streptomyces reticuli Haem-Binding
Protein HbpS Influences the Production of the Catalase-Peroxidase CpeB. Microbiology
2004
,150, 2575–2585.
[CrossRef]
89.
Tuncer, M.; Kuru, A.; Isikli, M.; Sahin, N.; Çelenk, F.G. Optimization of Extracellular Endoxylanase,
Endoglucanase and Peroxidase Production by Streptomyces sp. F2621 Isolated in Turkey. J. Appl. Microbiol.
2004,97, 783–791. [CrossRef]
90.
Wu, S.; Li, Y.; Wang, P.; Zhong, L.; Qiu, L.; Chen, J. Shifts of Microbial Community Structure in Soils of a
Photovoltaic Plant Observed Using Tag-Encoded Pyrosequencing of 16S RRNA. Appl. Microbiol. Biotechnol.
2016,100, 3735–3745. [CrossRef]
91.
Pascual, J.; Huber, K.J.; Foesel, B.U.; Overmann, J. Stenotrophobacter. Bergey’s Man. Syst. Archaea Bact.
2017
,
1, 1–8. [CrossRef]
92.
Li, W.H.; Liu, Q.Z.; Chen, P. Effect of Long-Term Continuous Cropping of Strawberry on Soil Bacterial
Community Structure and Diversity. J. Integr. Agric. 2018,17, 2570–2582. [CrossRef]
93.
Marschner, P.; Kandeler, E.; Marschner, B. Structure and Function of the Soil Microbial Community in a
Long-Term Fertilizer Experiment. Soil Biol. Biochem. 2003,35, 453–461. [CrossRef]
94.
Yu, C.; Hu, X.M.; Deng, W.; Li, Y.; Xiong, C.; Ye, C.H.; Han, G.M.; Li, X. Changes in Soil Microbial Community
Structure and Functional Diversity in the Rhizosphere Surrounding Mulberry Subjected to Long-Term
Fertilization. Appl. Soil Ecol. 2015,86, 30–40. [CrossRef]
95.
Simpson, A.J.; Song, G.; Smith, E.; Lam, B.; Novotny, E.H.; Hayes, M.H.B. Unraveling the Structural
Components of Soil Humin by Use of Solution-State Nuclear Magnetic Resonance Spectroscopy.
Environ. Sci. Technol. 2007,41, 876–883. [CrossRef] [PubMed]
96.
Rawat, S.R.; Männistö, M.K.; Bromberg, Y.; Häggblom, M.M. Comparative Genomic and Physiological
Analysis Provides Insights into the Role of Acidobacteria in Organic Carbon Utilization in Arctic Tundra
Soils. FEMS Microbiol. Ecol. 2012,82, 341–355. [CrossRef]
97.
Eichorst, S.A.; Trojan, D.; Roux, S.; Herbold, C.; Rattei, T.; Woebken, D. Genomic Insights into the Acidobacteria
Reveal Strategies for Their Success in Terrestrial Environments. Environ. Microbiol.
2018
,20, 1041–1063. [CrossRef]
98.
Zhao, K.; Kong, W.; Wang, F.; Long, X.E.; Guo, C.; Yue, L.; Yao, H.; Dong, X. Desert and Steppe Soils Exhibit
Lower Autotrophic Microbial Abundance but Higher Atmospheric CO
2
Fixation Capacity than Meadow
Soils. Soil Biol. Biochem. 2018,127, 230–238. [CrossRef]
99.
Miltner, A.; Richnow, H.H.; Kopinke, F.D.; Kästner, M. Assimilation of CO
2
by Soil Microorganisms and
Transformation into Soil Organic Matter. Org. Geochem. 2004,35, 1015–1024. [CrossRef]
Diversity 2020,12, 436 15 of 15
100.
Videmšek, U.; Hagn, A.; Suhadolc, M.; Radl, V.; Knicker, H.; Schloter, M.; Vodnik, D. Abundance and
Diversity of CO2-Fixing Bacteria in Grassland Soils Close to Natural Carbon Dioxide Springs. Microb. Ecol.
2009,58, 1–9. [CrossRef] [PubMed]
101.
Arcand, M.M.; Helgason, B.L.; Lemke, R.L. Microbial Crop Residue Decomposition Dynamics in Organic
and Conventionally Managed Soils. Appl. Soil Ecol. 2016,107, 347–359. [CrossRef]
102.
Singh, G.; Bhattacharyya, R.; Das, T.K.; Sharma, A.R.; Ghosh, A.; Das, S.; Jha, P. Crop Rotation and Residue
Management Effects on Soil Enzyme Activities, Glomalin and Aggregate Stability under Zero Tillage in the
Indo-Gangetic Plains. Soil Tillage Res. 2018,184, 291–300. [CrossRef]
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