https://creativecommons.org/licenses/by-nc-sa/4.0/La intelligence
eISSN: 1390-8146
http://revistasdigitales.utelvt.edu.ec/revista/index.php/investigacion_y_saberes/index
Impact of anthropogenic activities on soil microbial
biomass in a pre-montane forest in the foothills of the
Andes Mountains.
Impacto de actividades antropogénicas sobre la biomasa
microbiana del suelo en un bosque pre-montano de las
estribaciones de la cordillera de los Andes
Sent (24.09.2020) Accepted (02.03.2021)
ABSTRACT
Soil microbial biomass (BMS),
CO2
emissions, and organic carbon
(
Corganic
) contents were quantified in soils with different anthropogenic
uses in the "Bosque Protector Murocomba" (BPM). Five land use
scenarios (treatments) were established (primary forest, secondary
forest, fallow, plantation of Gmelina arborea, and pasture), within the
Murocomba Protective Forest. Three soil samples were collected per
treatment. Induced substrate respiration technique was employed
using glucose as inducer, streptomycin and chloramphenicol to inhibit
bacterial populations, cycloheximide and captan 80 as fungal
inhibitors. The
CO2
released was trapped in NaOH solution (0.1 M) and
titrated with HCl (0.1 M). Total
Corganic
contents, active microbial
biomass and
CO2
emissions were higher in the primary forest soil: 20.0
mg kg-1, 6.7 mg C-microbial g-1 dry soil (mg C-mic g-1 ss), and 50.4 mg
CO2
100 g-1 s hour-1. Grassland soils generated lower contents: 12.5
mg kg-1, 2.1 mg C-mic g-1 ss, and 15.9 mg
CO2
in 100 g-1 s hour-1,
respectively. In all soils, fungal biomass predominated over bacterial
biomass. These results demonstrate that the soils of the BPM are
important reserves of organic C, however, anthropogenic activities
generate changes in the dynamics of the BMS in these natural forests
of the western foothills of the Andes, causing alterations in nutrient
cycling. This research constitutes a baseline that places the BPM as a
control point for future regional or global biogeochemistry studies.
Keywords: Temperatures, Modeling, Optimization, Tomato.
Carlos Eulogio Belezaca Pinargote
D. in Science with mention in Microbiology,
Universidad Técnica Estatal de Quevedo,
Quevedo-Ecuador. cbelezaca@uteq.edu.ec,
https://orcid.org/0000-0002-3158-7380
Edison Hidalgo Solano Apuntes
Forestry Engineer, Master in Forest
Management, Universidad Técnica Estatal de
Quevedo, Quevedo-Ecuador.
esolano@uteq.edu.ec,
https://orcid.org/0000-0001-8158-0040
Danny Solano-Moncayo
Forestry Engineer, Universidad Técnica
Estatal de Quevedo, Quevedo-Ecuador.
danny.lexander@hotmail.com;
https://orcid.org/0000-0002-5351-2283
Cinthya Katherine Morales Escobar
Forestry Engineer, Universidad Técnica
Estatal de Quevedo, Quevedo, Ecuador,
cinthya.morales2016@uteq.edu.ec,
https://orcid.org/0000-0002-0661-5191
Paola Eunice Diaz Navarrete
D. in Science with mention in Microbiology,
Universidad Católica de Temuco, Chile.
paola.diaz@educa.uct.cl,
https://orcid.org/0000-0003-0512-7695
Revista Científica Interdisciplinaria
Investigación y Saberes
Vol. – 11 No. 3
Septiembre - Diciembre 2021
e-ISSN: 1390-8146
1-16
2
Carlos Eulogio Belezaca Pinargote
Edison Hidalgo Solano Apuntes
Danny Solano-Moncayo
Cinthya Katherine Morales Escobar
Paola Eunice Diaz Navarrete
Rev. Cient. Interdisciplinaria Investigación y Saberes 11 (3) 2021
1390-8146
RESUMEN
Se cuantificó la biomasa microbiana del suelo (BMS), emisiones de CO
2
, y contenidos de
carbono orgánico (C
orgánico
), en suelos con diferentes usos antropogénicas en el “Bosque
Protector Murocomba” (BPM). Se establecieron cinco escenarios (tratamientos) de uso del
suelo (bosque primario, bosque secundario, barbecho, plantación de Gmelina arbórea, y
pastizal), dentro del BPM. Se colectaron 3 muestras de suelo por tratamiento. Se empleó
la técnica de respiración inducida de sustrato usando glucosa como inductor,
estreptomicina y cloranfenicol para inhibir poblaciones bacterianas, cicloheximida y captan
80, como inhibidores fúngicos. El CO
2
liberado se atrapó en una solución de NaOH (0.1 M)
y tituló con HCl (0.1 M). Los contenidos de C
orgánico
total, biomasa microbiana activa y
emisiones de CO
2
, fueron superiores en el suelo de bosque primario: 20.0 mg kg
-1
, 6.7 mg
C-microbiano g
-1
de suelo seco (mg C-mic g
-1
ss), y 50.4 mg CO
2
100 g
-1
s hora
-1
. Los suelos
de pastizal generaron menores contenidos: 12.5 mg kg
-1
, 2.1 mg C-mic g
-1
ss, y 15.9 mg CO
2
en 100 g
-1
s hora
-1
,
respectivamente. En todos los suelos predominó la biomasa fúngica, por
sobre la bacteriana. Estos resultados demuestran que los suelos del BPM son importantes
reservas de C orgánico, sin embargo, actividades antropogénicas generan cambios en la
dinámica de la BMS en estos bosques naturales de las estribaciones occidentales de los
Andes, provocando alteraciones en el ciclo de los nutrientes. Esta investigación constituye
una línea base que ubica al BPM como un punto control para futuros estudios de
biogeoquímica regional o global.
Palabras clave: Temperaturas, Modelación, Optimización, Tomate.
1. Introduction
Pre-montane forests, also known as low montane forests in the foothills of the
Andes, have large amounts of stored C, forming part of their biomass, both above
and below ground (Jobbágy & Jackson, 2000, Stockmann et al., 2013). These
mountain forests are characterized by their biodiversity and constitute 26% of the
world's forest area (CDS, 2008).
The soils where these pre-montane forests evolved have their genesis from
volcanic ash, characterized by low nitrogen (N) concentrations (Huygens et al.,
2008), high total phosphorus (P) contents, but with very limited available forms
(Redel et al., 2008, Lambers et al., 2012). Under such a scenario of restrictions,
these ecosystems have developed compensatory functional strategies, where the
transformation and mineralization of SOM and biological nitrogen fixation, among
others (Pérez et al., 2010) are key processes, mediated by soil microbial biomass
(SMB), which is fundamental in nutrient cycling (Valenzuela et al., 2001). BMS
represents only 1-4% of the C and 2-6% of the total N in the soil, its presence is of
vital importance, and plays a fundamental role in nutrient cycling (Van der Heijden
et al., 2008), however, the size of the biomass reservoir and its microbiota are
Rev. Cient. Interdisciplinaria Investigación y Saberes 11 (3) 2021
1390-8146
influenced by the amount of SOM, climatic factors, physicochemical
characteristics, and changes in soil vegetation cover (Dube et al., 2009).
The BMS affects several stages of the biogeochemical cycles (C, N, P and S), and
its determination is useful for studies in natural environments such as pristine or
little altered ecosystems, under different scenarios of spatio-temporal
anthropogenic pressures (Jangid et al. 2011). As land use changes are generated
by land cover modification, some nutrients are released to the atmosphere,
others are stored in the soil, remain on site as dead matter, or are exported by
anthropogenic activities or natural processes.
It is known that the forests located in the western foothills of the Andes
Mountains are privileged control points for baseline studies of global
biogeochemistry, which allow us to answer ecological questions and project
potential effects in the face of future scenarios of human disturbance and global
climate change, where increasingly prolonged periods of drought affect the
productivity and stability of forest ecosystems in the region (Huygens et al., 2011).
Anthropogenic activities imply changes in the natural landscape as a result of
forest clearing for agricultural and silvicultural purposes, fragmenting the
ecosystems and forming a true mosaic of isolated vegetation covers and multiple
land uses, different from the original one.
In this sense, the present research sought to quantify the impact of
anthropogenic pressures/activities on soil microbial biomass content, organic C
content and
CO2
emissions in soils of the Murocomba Protected Forest, located in
the western foothills of the Andes Mountains.
2. Materials and Methods
The field research was conducted in and around the Murocomba Protected Forest
(BPM). The BPM is located in a remote area, at an altitude between 350 - 1500
m.a.s.l., with two distinct climatic seasons. According to Holdridge, it comprises
the life zones "Pre-montane very humid forest" and "Pre-montane rainforest".
The rainy season contributes 85% - 90%, and the dry season between 10% - 15%
of the rainfall. Rainfall varies according to altitude, with an increasing third order
polynomial distribution. At 350 meters above sea level, rainfall averages 2000
mm, but when the elevation reaches 900 - 1300 meters above sea level, rainfall
can exceed 4500 mm. The average annual temperature is modal, with 23°C
(March - April) and 18°C (July - August). The average annual relative humidity
depends on the climatic season and ranges between 85 - 87% (rainy season) and
79 - 84% (dry season) (Cuásquer et al., 2008).
4
Carlos Eulogio Belezaca Pinargote
Edison Hidalgo Solano Apuntes
Danny Solano-Moncayo
Cinthya Katherine Morales Escobar
Paola Eunice Diaz Navarrete
Rev. Cient. Interdisciplinaria Investigación y Saberes 11 (3) 2021
1390-8146
The processing and analysis of samples was carried out at the Environmental and
Plant Microbiology Laboratory of the State Technical University of Quevedo,
located at the Manuel Haz Álvarez Campus, Km 1.5 of the Quevedo-Quito
highway.
Treatments and study plots. Five treatments based on vegetation cover (land use)
with different levels of anthropogenic intervention (scenarios) were established
in remote areas of the BPM. For this purpose, three plots (replicates) of 100
m2
(10
m x 10 m) each, representative of each treatment, were delimited for each
treatment. Table 1 details the treatments according to current land use:
Table 1. Treatments based on vegetation cover (land use) in Murocomba
Protected Forest.
Codes
Treatments
T1
Primary forest (control)
T2
Secondary forest
T3
Regenerating forest
(fallow)
T4
Pasture
T5
Planting of Gmelina
arborea
Soil sample collection . In the rainy climatic season of 2018, three soil sub-samples
were collected from all plots at a depth between 0 - 20 cm, from which a
composite sample was constituted for each plot, which was equivalent to three
samples/replicates (n=3) per treatment. The soil samples were transferred to the
Environmental and Plant Microbiology laboratory of the UTEQ in insulated boxes,
where rocks, plant debris, and macro-invertebrates were removed. The fresh soil
(without previous drying) was sieved through a 2 mm mesh and stored at 5° C for
later analysis. At the same time, the soil samples were subjected to chemical
analysis: pH, total organic carbon (
Corganic
), total nitrogen (Nt), C/N ratio,
phosphorus (P), potassium (K), and magnesium (Mg) according to the
methodology used by (Sadzawka et al. , 2006).
Field capacity. Sieved soil samples were oven-dried for 72 h at 60 °C to constant
weight. Then, 100 g-1 of dry soil per sample was placed in a 100 mL-1 test tube,
the volume occupied by the soil mass was recorded, added 5 mL-1 of water
(dropwise) in the center and capped the test tube. After 24 hours, the volume of
soil that was not hydrated (dry soil) was recorded (Sadzawka et al., 2006). The
calculation of field capacity (%) was performed employing the equation used by
Silva et al. (2015):
Rev. Cient. Interdisciplinaria Investigación y Saberes 11 (3) 2021
1390-8146
Where:
V1= Initial volume (volume occupied by g-1 of soil)
V2= Final volume (volume that has not been wetted)
CC= Field Capacity
Moisture content. Wet soil samples of known weight were placed in an oven at
60 °C for 72 hours, until a constant weight was obtained. Subsequently, the dry
soil was again weighed and the moisture content was calculated using the
following equation (Silva et al., 2015):
Where:
Ph=Wet soil weight
Ps= Dry soil weight
%H =Percentage of humidity
Amount of water to add to the samples. Once the field capacity and moisture
content were determined, the amount of water needed to add to the soil was
estimated according to the equation described below (Silva et al., 2015):
&
)
Where:
CC
?% =FIELD CAPACITY TO BE DETERMINED
=Field capacity to be determined
%H =Percentage of soil moisture
Soil active microbial biomass (AMB). It was determined by the substrate-induced
respiration technique (RIS), described by (Chiu et al., 2006; Ananyeva et al., 2006).
For this purpose, 10 g of soil at field moisture, previously sieved, were placed in
glass chambers (100 mL capacity) and stabilized for 24 hours at room
6
Carlos Eulogio Belezaca Pinargote
Edison Hidalgo Solano Apuntes
Danny Solano-Moncayo
Cinthya Katherine Morales Escobar
Paola Eunice Diaz Navarrete
Rev. Cient. Interdisciplinaria Investigación y Saberes 11 (3) 2021
1390-8146
temperature. Subsequently, the soil was mixed with 10 mg of glucose (1 mg g-1
of soil), dissolved in the amount of water (sterile distilled) necessary to adjust the
samples to 80% of their water retention capacity.
CO2
released during the
incubation period (6 h at 22
oC
) was trapped in NaOH solution (0.1 M) and titrated
with HCl (0.1 M). The BMA was calculated on the basis that 1 mL of HCl (0.1 M) is
equivalent to 2.2 mg
CO2
and that for a respiration coefficient equal to 1: 1 mg
CO2/100
g h = 20.6 mg C-biomass/100 g.
Selective fungal and bacterial inhibition. Streptomycin and chloramphenicol
were used as bacterial inhibitors, while cycloheximide and captan 80 were used
as fungal inhibitors. The selection and concentration of the antimicrobials applied
to the soil were carried out according to the reports of (West, 1986; Bailey et al. ,
2002; Nakamoto & Wakahara, 2004). As with glucose, the antimicrobials were
mixed with the soil, and sufficient water was applied to moisten the soil, without
saturating it. The
CO2
detected represented the response to the inhibition of
respiration caused by the microbial inhibitors and was expressed in mg C-mic g-1
of soil. To determine the fungal (BF), bacterial (BB), and residual (BR) biomass in
each of the soil use treatments, the triplicate samples received the following
combination of antimicrobials (Table 2):
Table 2. Combination of soil, glucose, and antimicrobialsto determine BF, BB, and
BR.
1.
Soil + glucose (1 mg g-1soil).
2.
Soil + glucose (1 mg g-1) + streptomycin (32 mg
g-1) + chloramphenicol (32 mg g-1).
3.
Soil + glucose (1 mg g-1) + cycloheximide (20 mg
g-1) + captan (20 mg g-1).
4.
Soil + glucose (1 mg g-1) + streptomycin (32 mg
g-1) + chloramphenicol (32 mg g-1) +
cycloheximide (20 mg g-1) + captan (20 mg g-1).
BF, BB, and BR were calculated according to West (1986): A = active microbial
biomass; (A-B) = fungal biomass; (A-C) = bacterial biomass; D = residual biomass;
(A-B)/(A-C) = fungi/bacteria ratio. The percentage inhibition of microbial biomass
caused by the use of antibiotics individually and in combination was determined
according to the following equations:
Rev. Cient. Interdisciplinaria Investigación y Saberes 11 (3) 2021
1390-8146
IBB = [(A - C)/A]
*100
IBF = [(A - B)/A]
*100
IBR = [(A - D)/A]
*100
Where:
IBB=Percentage of inhibition by combination of antibiotics.
IBF =Percentage of inhibition by combination of antifungals.
IBR =Percentage of inhibition by combination of antibiotics and
antifungals.
The following equations were used to estimate the proportion of fungal and
bacterial biomass:
100[{(A - B) + (A - D)} / 2]/(A - D)
100[{(A - C) + (B - D)} / 2]/(A - D)
Inhibitor additivity ratio (IAR). It was calculated according to Beare et al. (1990),
using RIS. It was expressed as the microbial biomass of soils treated with
antibiotics (streptomycin + chloramphenicol) to inhibit bacteria, antifungals
(cycloheximide + captan) to inhibit fungi, and the simultaneous use of inhibitors
of both microbial groups. Intact soil (without antimicrobials) was also used. It has
been established that when RAI is equal to 1.0, antimicrobials do not exert
inhibitory effect on other organisms for which they were not designed. Whereas
an additivity ratio >1.0 indicates that antimicrobials have an inhibitory effect on
other organisms for which they were not designed. An additivity ratio <1.0 shows
that they exert a stimulatory effect on microorganisms (Beare et al., 1990;
Nakamoto & Wakahara, 2004). RAI was determined by the following equation.
RAI = [(A - B) + (A - C)]/(A - D)
Total inhibition by combined effect of inhibitors (ITC). This variable expresses the
percentage of microbial biomass inhibited by the combination of antimicrobials:
antibiotics (streptomycin + chloramphenicol) and antifungals (cycloheximide +
captan), (Chiu et al., 2006; Susyan et al., 2011). It was calculated based on the
equation described below.
8
Carlos Eulogio Belezaca Pinargote
Edison Hidalgo Solano Apuntes
Danny Solano-Moncayo
Cinthya Katherine Morales Escobar
Paola Eunice Diaz Navarrete
Rev. Cient. Interdisciplinaria Investigación y Saberes 11 (3) 2021
1390-8146
ITC = {(A - D) / (A)}*100
Potential
CO2
emissions from soil at laboratory level. For this purpose, 10 g of soil
at field humidity, previously sieved in a 2 mm mesh opening, were placed in glass
chambers (100 mL capacity) and stabilized for 24 hours at room temperature.
Subsequently, the soil was mixed with 10 mg of glucose (1 mg g-1 of soil),
dissolved in the amount of sterile distilled water necessary to adjust the samples
to 80% of their water retention capacity.
CO2
released during the incubation period
(6 h at 22
oC
) was trapped in a NaOH solution (0.1 M) and titrated with HCl (0.1
M).
Statistical analysis. In order to determine the effects of vegetation cover and
anthropogenic interventions (treatments) on soil microbial biomass, the data
obtained were subjected to an analysis of variance (ANOVA) with a significance
level of 95% (P < 0.05). Subsequently, the LSD (least significant difference) test
was applied, with a significance level of 95% (P < 0.05). The statistical package
SYTAT 11 version for Windows was used for the effect.
3. Results
Soil chemical analysis. Significant statistical differences (P ≤ 0.05) were detected
in the soil chemical analyses (pH, NH4, P, K, MO and
Corganic
) among the treatments
under study (soil uses). For pH (F=16.35; P=0.000) soils subjected to livestock
activities (pasture) presented the highest acidity levels with 5.30, placing them in
the "strongly acid" category, while soils of the other treatments were in the range
of 5.50 to 6.0, which places them in the "moderately acid" category. Regarding
cations, it was detected that the highest available NH4 concentrations (F=8.53;
P=0.002) were in the treatments: primary forest soil, secondary forest soil, and G.
arborea plantation soil, with 19.0, 16.5, and 19.5 ppm, being higher and different
from the other treatments. For P (F=11.90; P=0.000), K (F=22.56; P=0.000),
primary forest, secondary forest and regenerating forest soils presented the
highest concentrations, with values of 13.0, 10.5 and 9.5 ppm (P); 0.42, 0.51 and
0.29 (meq/100 mL) (K), respectively, being significantly higher than pasture and
G. arborea plantation soils.
The MO contents (F=14.62; P=0.000) were statistically higher in the primary forest
soils, with 3.4%, being different from the secondary forest, regenerating forest,
G. arborea plantation and pasture soils, which showed ranges from 2.7% to 2.15%.
Regarding soil
Corganic (
F=14.65; P=0.000), the treatments that presented the
highest concentrations were the primary forest, regenerating forest and G.
Rev. Cient. Interdisciplinaria Investigación y Saberes 11 (3) 2021
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arborea plantation soils with 20.0, 15.4 and 15.7 (mg/kg), in contrast to the
secondary forest and pasture soils that presented values of 14.0 and 12.5 mg/kg
(Table 3).
Table 3. Chemical variables analyzed in soils with different vegetation cover
(anthropogenic uses). Murocomba Protected Forest, Valencia, Ecuador.
TREATMENTS
Ph
NH4
(ppm)
P (ppm)
K (meq/100
mL)
MO (%)
C
organic
(mg/kg)
Primary
forest
(control)
5.6 ± 0.1
b
19.0 ±
2.0 a
13.0 ± 2.0
a
0.42 ± 0.06 a
3.4 ± 0.20
a
20.0 a
Secondary
forest
6.0 ± 0.2
a
16.5 ±
6.5 a
10.5 ± 0.5
ab
0.51 ± 0.10 a
2.4 ± 0.10
bc
14.0 bc
Regenerating
forest
(fallow)
6.0 ± 0.1
a
8.0 ± 2.0
b
9.5 ± 2.5 b
0.29 ± 0.03 b
2.65 ± 0.15
b
15.4 b
Pasture
5.3 ± 0.0
c
9.0 ± 1.0
b
6.0 ± 0.0 c
0.18 ± 0.02 c
2.15 ± 0.25
c
12.5 c
Gmelina
arborea
plantation
5.5 ± 0.2
bc
19.5 ±
1.5 a
6.0 ± 1.0 c
0.17 ± 0.01 c
2.7 ± 0.30
b
15.7 b
Values correspond to averages of three replications with their respective standard
deviation. Equal letters indicate statistically similar means (P < 0.05).
Active microbial biomass and fungal biomass/bacterial biomass ratio. Significant
statistical differences (P < 0.05) were detected between soils with different
vegetation cover (anthropogenic uses), for the variables: active microbial biomass
(AMB) (F=7.60, P=0.030), fungal biomass (BF) (F=5.30, P=0.000), bacterial biomass
(BB) (F=4.35, P=0.000), fungal biomass/bacterial biomass (BF/BB) ratio (F=1.15,
P=0.000), while for the residual microbial biomass (BMR) variable no differences
were found (F=.6.10, P=0.03). The highest BMA contents were detected in the
soils of primary forest (control) and secondary forest, with 6.65 mg C-mic g-1 dry
soil (mg C-mic g-1 ss), and 5.75 mg C-mic g-1 ss, respectively, being statistically
similar but higher than the contents found in the soils of regenerating forest, and
G. arborea plantation, with 6.65 mg C-mic g-1 dry soil (mg C-mic g-1 ss), and 5.75
mg C-mic g-1 ss, respectively, being statistically similar but higher than the
contents found in the soils of regenerating forest, and plantation of G. arborea,
10
Carlos Eulogio Belezaca Pinargote
Edison Hidalgo Solano Apuntes
Danny Solano-Moncayo
Cinthya Katherine Morales Escobar
Paola Eunice Diaz Navarrete
Rev. Cient. Interdisciplinaria Investigación y Saberes 11 (3) 2021
1390-8146
with 5.40 mg C-mic g-1 ss, and 5.10 mg C-mic g-1 ss. However, the lowest BMA
contents were detected in the pasture soil, with 2.10 mg C-mic g-1 ss.
In all treatments, BF predominated over BB, which is reflected in the BF/BB ratio
higher than 1.11 for all treatments. The soil from primary forest showed the
highest values of BF, BB, and BF/BB with 3.75, 2.27, and 1.65 mg C-mic g-1 g-1 ,
respectively. While in the soil from the pasture, lower contents were detected.
The BMR values found in all soils were statistically similar (Table 4).
Table 4. Active (AMB), fungal (FB), bacterial (BB), residual (BR) microbial biomass
contents in mg g-1 of dry soil, and fungal biomass/bacterial biomass ratio (BF/BB)
in soils with different vegetation cover (uses). Murocomba Protected Forest,
Valencia, Ecuador.
TREATMENTS.
BMA (mg g-
1)*
BF (mg g-
1)*
BB (mg g-
1)*
BF/BB *
BF/BB
BMR (mg
g-1)*
Primary Forest
6.65
(±0.15) a
3.75
(±0.20) a
2.27
(±0.38) a
1.65
(±0.80) a
0.63 ns
Secondary
forest
5.75
(±0.27) a
3.26
(±0.09) a
2.15
(±0.55) a
1.51
(±0.92) a
0.34 ns
Regenerating
forest
5.40
(±0.35) b
2.95
(±0.41) b
1.72
(±0.18) b
1.71
(±0.36) a
0.73 ns
Pasture
2.10
(±0.25) c
0,80
(±0.33) c
0.72
(±0.20) c
1.11
(±0.22) b
0.58 ns
Plantation of
Gmelina
arborea
5.10
(±0.35) b
2.90
(±0.65) b
1.80
(±0.41) b
1.61
(±0.75) a
0.35 ns
Values correspond to averages of three replications with their respective standard
deviation. Equal letters indicate statistically similar means (P < 0.05).
Inhibitory effect of antimicrobials . No significant statistical differences (P < 0.05)
were detected for the variables inhibition of fungal biomass (% IBF), inhibition of
bacterial biomass (% IBB), and inhibition by combined effect of antifungals and
antibiotics (% ITC), as well as in the additivity ratio of inhibitors (RAI), (Table 5).
Rev. Cient. Interdisciplinaria Investigación y Saberes 11 (3) 2021
1390-8146
Table 5. Inhibition percentages of fungal biomass (% IBF), bacterial biomass (%
IBB), inhibition by combined effect of antimicrobials (% ITC), and inhibitor
additivity ratio (RAI), in soils with different vegetation cover (uses). Murocomba
Protected Forest, Valencia, Ecuador.
TREATMENTS.
% IBF (C + C)
*
% IBB (E +
C) *
% ITC (F +
A) *
RAI * RAI
Primary Forest
44.35
(±8.40) ns
29.44
(±11.50)
ns
83.79
(±7.08) ns
1.07
(±0.06) ns
Secondary forest
50.27
(±6.46) ns
27.33
(±18.47)
ns
87.60
(±5.82) ns
1.14
(±0.24) ns
Regenerating forest
47.85
(±7.10) ns
26.99
(±3.81) ns
84.84
(±6.43) ns
1.08
(±0.09) ns
Pasture
46.81
(±12.49) ns
20.86
(±7.80) ns
87.67
(±2.03) ns
1.35
(±0.21) ns
Planting of Gmelina
arborea
45.98
(±5.60) ns
28.61
(±6.04) ns
84.59
(±3.80) ns
1.18
(±0.12) ns
Values correspond to averages of three replications with their respective standard
deviation. Equal letters indicate statistically similar means (P < 0.05).
CO2
emissions from the soil. Significant statistical differences were detected
among treatments (F=4.2, P=0.03). Soils from primary forest released 50.38 mg
CO2
in 100 g-1 soil hour-1 (mg
CO2
100 g-1 s hour-1), which emissions were
statistically higher than those from secondary forest, regenerating forest and G.
arborea plantation soils, with 43.56, 40.91 and 38.64 mg
CO2
100 g-1 s hour-1,
respectively. While Grassland soils released 15.91 mg
CO2
100 g-1 s hour-1,
emissions statistically lower than those released from soils with other vegetation
covers (Figure 1).
Figure 1. CO2 emissions (mg
CO2
100 g-1 s hour-1) at laboratory level, from soils
with different vegetation cover (uses). Murocomba Protected Forest, Valencia,
Ecuador.
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Carlos Eulogio Belezaca Pinargote
Edison Hidalgo Solano Apuntes
Danny Solano-Moncayo
Cinthya Katherine Morales Escobar
Paola Eunice Diaz Navarrete
Rev. Cient. Interdisciplinaria Investigación y Saberes 11 (3) 2021
1390-8146
Values correspond to averages of three replications with their respective standard
deviation. Equal letters indicate statistically similar means (P < 0.05).
The higher soil
corganic
contents detected in the treatments with forest cover:
primary forest, secondary forest, regenerating forest and G. arborea plantation
(20.0, 14.0, 15.4 and 15.7 mg/kg, respectively), would probably be associated with
the presence of available SOM in the soils, given by constant contributions of fine
and coarse litter, and the progressive decomposition of the same, unlike the
Pasture soils where lower contents of
Corganic
were obtained, This is attributable to
the decrease in the availability of C and N in the SOM, as a consequence of its
accelerated mineralization, changes in the microclimate, volatilization into the
atmosphere and nutrient leaching mechanisms, factors associated with intensive
livestock activity (Galicia et al., 2016; Céspedes-Flores et al., 2018). This
phenomenon has been detected in other studies of forest-covered soils, where
internal recycling, conservation mechanisms and nutrient retention are efficient
in ecosystems similar to the forest-covered soils analyzed in the present study
(Zanabria & Cuellar, 2015; Suárez-Duque et al., 2016), with higher edaphic
microbial biomass concentrations than those ecosystems intensely
anthropogenically intervened, such as pasture soils.
In all treatments, BF predominated over BB, which is reflected in the BF/BB ratio
higher than (1.11). The primary forest treatment showed the highest values of
BF, BB, and BF/BB with 3.75 mg C-mic g-1 ss, 2.27 mg C-mic g-1 ss, and 1.65,
respectively, due to the fact that the abundance of bacteria per unit of organic
matter was less variable than fungal biomass, which correlates with the findings
a
b
b
c
b
0
10
20
30
40
50
60
Bosque Primario Bosque
secundario
Bosque en
regeneración
Pastizal Plantación de G.
arborea
mg
CO2
100 g-1 s hour-1
Treatments (land use)
Rev. Cient. Interdisciplinaria Investigación y Saberes 11 (3) 2021
1390-8146
reported by Findlay et al. (2002), who indicate that bacteria are a very predictable
component within the BMS; however, bacterial populations, despite having more
individuals (cells) per unit weight than fungal populations, are smaller, but no less
important for the biogeochemistry of ecosystems. The low BF contents in
grassland soil would be due to the very low organic matter input and availability
for BMS, compared to forest-covered soils.
The highest
CO2
emissions from the primary forest floor (50.38 mg
CO2
in 100 g-1 ss
hour-1), are surely associated with the intense activity of the BMS during the
process of biodegradation and mineralization of supplies of fine litter (leaf litter,
fine branches, flowers, fruits, bark) and coarse litter (trunks, thick branches, roots,
fallen tree stumps) abundant in this type of ecosystems, compared to a lower
contribution of biomass to the soil by other vegetation covers such as Grasslands
(15.91 mg
CO2
in 100 g-1 ss hour-1), which are associated a lower BMS activity due
to a lack of carbonaceous resources, as pointed out by Céspedes-Flores et al.
(2018).
CO2
emissions from secondary forest, regenerating forest and G. arborea
plantation soils (43.56, 40.91, 38.64 mg
CO2
in 100 g-1 ss hour-1, respectively) show
that their organic matter inputs and BMS size are similar, which would indicate
that
CO2
release from these types of ecosystems is sustained and conserves soil C
stocks. On the other hand, the fact that the forest-covered soils analyzed in this
research release more
CO2
than grasslands does not mean that transforming these
ecosystems into grasslands would prevent the release of C from the soil; on the
contrary, most of the conserved C would be released. While carbon cycling in
forested ecosystems is very dynamic, with higher C inputs that are immobilized
for long periods of time (residence time) in the plant biomass, with a gradual and
lower release of
CO2
compared to that fixed by the ecosystem. In this sense, the
scientific literature shows that the BMS pool and its metabolic activity is closely
related to the contributions of carbonaceous materials, results of the net primary
production within terrestrial ecosystems (Pardo-Plaza et al., 2019; Rosero et al.,
2019), a situation that correlates with the results obtained in this research.
5. Conclusions
The soils of the "Bosque Protector Murocomba" are subject to anthropogenic
pressures, whose changes in use imply modifications in the soil microbial biomass,
nutrient balance, and
Corganic
. Forest cover contributes to the conservation of
Corganic
stored in the soils of this protective forest, being the conversion of these
soils to pasture the main cause of C loss from the soil pool. Soil microbial biomass
can be used as a sensitive and robust bioindicator of disturbance or early
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Danny Solano-Moncayo
Cinthya Katherine Morales Escobar
Paola Eunice Diaz Navarrete
Rev. Cient. Interdisciplinaria Investigación y Saberes 11 (3) 2021
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anthropogenic changes in the soils of the BPM. This research is the first report of
the use of soil microbial biomass as a biological indicator of anthropogenic
changes in soils of this type of ecosystems, already scarce and very sensitive,
located in the western foothills of the Ecuadorian Andes, and constitute a baseline
for future studies of local, regional and global biogeochemistry.
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