2356-1424SAINS TANAH - Journal of Soil Science and AgroclimatologySains Tanah J. Soil Sci. Agroclimatology2356-14241412-3606Universitas Sebelas MaretIndonesia10.20961/stjssa.v23i1.92633Soil ScienceSoil physicochemical properties and microbial biomass in agriculture and abandoned lands of Shivapuri-Nagarjun National Park, Kathmandu, Nepalhttps://orcid.org/0000-0002-4764-4554DhakalTil MayaNepalTilmaya.765702@cdb.tu.edu.nphttps://orcid.org/0000-0003-3513-2276ThapaLal BahadurNepallal.thapa@cdb.tu.edu.npMonokrousosNikolaosGreecechandra.pokhrel@cdb.tu.edu.nphttps://orcid.org/0000-0001-5787-3134YadavRam Kailash PrasadNepalramkailash.yadav@cdb.tu.edu.nphttps://orcid.org/0000-0003-2573-8370PokhrelChandra PrasadNepalchandra.pokhrel@cdb.tu.edu.nphttps://orcid.org/0000-0001-7704-0754KomariahDr. KomariahIndonesiasainstanah@mail.uns.ac.idCentral Department of Botany, Institute of Science and TechnologyTribhuvan Universityhttps://ror.org/02rg1r889NepalDepartment of Botany, Siddhanath Science Campus, Institute of Science and TechnologyTribhuvan Universityhttps://ror.org/02rg1r889NepalUniversity Center of International Programmes of StudiesInternational Hellenic Universityhttps://ror.org/00708jp83GreeceInstitut za zemljištehttps://ror.org/03gef1f50Faculty of AgricultureSerbiaCorresponding author: Chandra Prasad Pokhrel. Email: chandra.pokhrel@cdb.tu.edu.np0201202602012026231June111250820240207202504092025Copyright (c) 2025 Chandra Prasad Pokhrel, Til Maya Dhakal, Lal Bahadur Thapa, Ram Kailash Prasad Yadav2025Chandra Prasad Pokhrel, Til Maya Dhakal, Lal Bahadur Thapa, Ram Kailash Prasad Yadavhttps://creativecommons.org/licenses/by-nc/4.0/Copyright (c) 2025 Chandra Prasad Pokhrel, Til Maya Dhakal, Lal Bahadur Thapa, Ram Kailash Prasad YadavAuthors who publish with this journal agree to the following terms:Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-NonCommercial License that allows others to Share (copy and redistribute the material in any medium or format) and Adapt (remix, transform, and build upon the material) the work non-commercially with an acknowledgement of the work's authorship and initial publication in this journal.Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
Abstract
Evaluating soil physicochemical and biological properties helps to understand ecosystem functions and nutrient dynamics. This study assessed the physicochemical and microbial properties of soil in agricultural and abandoned lands within Shivpuri-Nagarjun National Park, Nepal. Soil samples were collected from both agricultural and abandoned lands at soil depths of 0-10, 10-20, and 20-30 cm during the pre-monsoon, monsoon, and post-monsoon seasons. The physicochemical parameters of the soil were analyzed using standard protocols. The chloroform fumigation extraction method was used for determining microbial biomass carbon and nitrogen. Soil temperature decreased with increasing depth during both the pre-monsoon and monsoon seasons, but increased with depth during the post-monsoon season. Agricultural land exhibited higher proportions of silt and clay, whereas abandoned land was characterized by a higher sand content. In agricultural soils, soil organic carbon was 2.63%, total nitrogen and available phosphorus were 0.21% and 72.16 kg ha-1, respectively, while available potassium was 636.55 kg ha-1. These nutrient levels peaked during the monsoon season and declined with increasing soil depth. Similarly, microbial biomass carbon (465.82 μg g-1) and nitrogen (48.58 μg g-1) were also higher in agricultural land, showing a decreasing trend with depth. The microbial biomass carbon-to-nitrogen ratio ranged from 9.61 to 19.41. The first (PC1) and second (PC2) components of Principal Component Analysis (PCA) accounted for 35.5% and 12.4% of the total variance, respectively. Overall, agricultural land, upper soil layers, and the monsoon season were identified as the most influential factors contributing to improved soil characteristics.
Buffer zoneLand typesSoil nutrientsSoil healthEcosystem managementFile created by JATS Editorhttps://jatseditor.comissue-created-year20261. INTRODUCTION
The pedosphere is the most active and vital layer of the Earth's surface (Herreño et al., 2023). Soil is an important natural resource, which provides numerous ecosystem services, supports plant growth and development, retains water, and nutrient cycling (Anikwe & Ife, 2023). The physicochemical properties of soil determine soil quality and provide information about the capacity of soil to supply mineral nutrients (Amgain et al., 2020; Nepal & Mandal, 2018). Similarly, soil microorganisms play a crucial role in maintaining soil biochemical properties and ecosystem functions (Dobrovol’skaya et al., 2015), soil organic matter processes (Nguyen-Sy et al., 2022) and formation of soil structure (Chandra et al., 2016). Soil microbial biomass, hence, is a dynamic labile pool of plant-available nutrients (Yokoyama et al., 2017). However, changes in practices on land use and management can affect soil physicochemical or biological properties (Abera & Belachew, 2011; Novara et al., 2017). Therefore, the results of soil mapping illustrate the distribution of soil fertility, which can help maintain soil fertility and improve land management (Suntoro et al., 2024).
Abandonment of agricultural lands is a significant phenomenon of land-use change with profound ecological and environmental consequences. It was estimated that the global area of farmland abandonment accounts for around 8-10% of the world’s total cultivated area (Campbell et al., 2008). Urbanization and industrialization have created a significant gap in income between the agricultural and non-agricultural sectors, leading to widespread abandonment of farmlands (Zhou et al., 2019). Agricultural activities in rural areas have declined significantly due to the outmigration of people to urban areas for employment, better education, and other amenities. Several studies have indicated that, on average, 37% of arable land in Nepal is abandoned (Dahal et al., 2020; Ojha et al., 2017).
Agricultural land abandonment is particularly pronounced in the buffer zones surrounding national parks, largely due to human–wildlife conflicts and restrictive park policies that limit resource use and traditional land management practices (Silwal et al., 2022). Soil infertility and degradation of soil quality may also contribute to land abandonment within park premises. Shivapuri-Nagarjun National Park (SNNP), situated near the capital city, Kathmandu, is a forested area, which comprises the majority of land cover (74.45%), followed by shrubland (20.45%), abandoned land (3.22%), and agricultural land (1.8%) (SNNP, 2017). This indicates that a significant area of land within the park has been abandoned, which was previously cultivated. However, studies regarding the causes and consequences of abandonment remain limited.
Previous studies in the national park have focused on vegetation (Dhakal et al., 2023), insects (Budhathoki et al., 2021), birds and wild mammals (Poudyal et al., 2023), and soil organic carbon (Shapkota & Kafle, 2021). These studies provide critical insights into vegetation, biodiversity, and ecosystem functioning, which could be helpful for sustainable forest management practices. In addition, analyzing the soil characteristics of abandoned and agricultural land is important for soil fertility assessment, understanding soil degradation processes, land restoration planning, and environmental impact assessment (Paudel et al., 2014). This study aims to assess the physicochemical properties and microbial biomass in the soils of agricultural and abandoned lands within the SNNP, taking into account seasonal variations and soil depth gradients.
2. MATERIALS AND METHODS2.1. Study site
This study was carried out in Shivapuri-Nagarjun National Park (SNNP). The National Park is located in the mid-hill region towards the northern side of the Kathmandu Valley, Nepal (Fig. 1). There are two villages, where the study was confined within the National Park (i) Okhreni (27°79'53''N, 85°42'14''E; elevation 1950 m) and (ii) Chilauni (27°79'36''N, 85°42'18''E; elevation 1976 m). The area experiences a subtropical monsoon climate, with temperature range of 2°C to 17°C during the winter season and 19°C to 30°C during the summer, and the mean annual rainfall is 2,727 mm (SNNP, 2017).
The villages contain abundant agricultural lands, including both actively farmed areas and abandoned traces of past cultivation. Common crops like maize, wheat, millet, mustard, beans, etc. were grown in the agricultural fields. Seasonal vegetables are also grown alongside these staple crops. In contrast, the abandoned lands lack significant vegetation and are primarily used for grazing and forage collection.
Map of the study site (a) Nepal showing Kathmandu district, (b) Kathmandu district showing SNNP, and (c) SNNP showing the study site.
Figure 1.2.2. Soil sampling and soil analyses
Soil samples were collected from both agricultural and abandoned land sites during 2020 and 2021. Three transects were established in each land-use type. In each transect, three square plots of 10 × 10 m² were established for soil sampling, with approximately 100 m spacing between plots. From each plot, soil cores were extracted from three different depths: (i) 0-10 cm, (ii) 10-20 cm, and (iv) 20-30 cm. The collected samples were thoroughly mixed from each plot to create a composite sample of approximately 1 kg. Soil samples were collected during pre-monsoon, monsoon, and post-monsoon seasons. Altogether 162 composite samples (2 land-use types × 3 transects × 3 plots × 3 depths × 3 seasons) were collected. The samples were dried, gently crushed, and sieved using a mesh with a pore size of ≤ 2 mm. Soil samples were transported in iceboxes and stored in the refrigerator (<4°C) until use.
A soil thermometer was used to measure the temperature on-site. The dry weight method was used for moisture content (MC), following Piper (2019). Bulk density (BD) was measured using the core method (Blake & Hartge, 1986) and soil texture was estimated by using the Bouyoucos hydrometer (Bouyoucos, 1962). Soil and water ratio (1:2.5) was prepared, and soil pH was measured using a digital pH meter (Jackson, 1969). Soil organic carbon (SOC) was estimated by the Walkley-Black method followed by Gelman et al. (2012). Total Nitrogen (TN), available phosphorus, and potassium were estimated following the Kjeldahl method (Jackson, 1969), Olsen’s sodium bicarbonate extraction method (Olsen et al., 1954), and the ammonium acetate extraction method (Jackson, 1969), respectively. Soil microbial biomass carbon and nitrogen were determined by using the chloroform fumigation extraction method (Brookes et al., 1985). After determining microbial biomass carbon and nitrogen in the soil, the microbial C: N ratio was calculated.
2.3. Statistical analysis
The effects of land-use types, seasons, soil depths and their interactions on soil physicochemical and microbial parameters were analyzed using Three-way analysis of variance (ANOVA). The differences in the soil parameters among each land use type, seasons, and depth were compared using One-way ANOVA. An independent sample t-test was used for the comparison of the parameters between agriculture and abandoned lands. The software Statistical Package for the Social Sciences (SPSS, version 25) was used for the analyses (IBM Corp., 2017). Principal Component Analysis (PCA) was performed to visualize the overall impact of seasons and land use type on soil parameters along the soil depth gradient. This analysis was carried out using the software R (R Core Team, 2023).
3 RESULTS3.1. Physical properties of soil
Soil temperature varied with land-use type (p = 0.004), seasons (p = 0.001), and depths (p = 0.001) (Table 1). Temperature was recorded as high during the pre-monsoon season (29.77 ± 0.14°C) in the abandoned land. Soil temperature decreased with increasing soil depth from pre-monsoon to monsoon seasons. However, it increased with increasing depth in the post-monsoon season. The interaction of land-use type, seasons, and depths showed a significant effect, but the interaction between land-use type and depths was not significant (Table 1).
Average soil moisture (SM) ranged from 12.29% to 41.15%, and the bulk density (BD) ranged from 0.95 g cm-³ to 1.68 g cm-³. Agricultural land showed the highest SM, while the abandoned land exhibited the highest bulk density (BD) during the monsoon season (Table 1). The SM and BD increased with depth in all seasons and land types. The SM varies with season and soil depth (p = 0.001). In contrast, BD varied with land use, season, and depth (p = 0.001); however, the interaction of land-use type and depth, as well as the effects of land use types, seasons, and depths, did not show significant effects (p > 0.05) (Table 1).
Soil of the agricultural land showed the highest silt (25.66±0.85%) and clay content (15.85±0.94%), while the abandoned land had a higher sand content (66.10±0.84%) (Table 1). Generally, the sand and silt contents decreased, while the clay content increased with increasing soil depth. Sand content varied with the season and soil depth (p = 0.001), except for the interaction of these factors. The silt content varied according to land use and season (p = 0.001), but not with depth. Similarly, clay content also differed with depth (p = 0.001), but not between agricultural and abandoned lands, or among seasons (Table 1).
Soil physical properties in different land use types across seasons and soil depths.
Land use type
Seasons
Depths (cm)
Temperature (oC)
Moisture (%)
BD (gcm-3)
Sand (%)
Silt (%)
Clay (%)
Agricultural land
Pre-monsoon
0-10
28.81± 0.89αaA
14.18±4.64αbC
1.23±0.18βaA
63.32±0.76βaA
22.88±1.05αaB
13.78±0.89αaA
10-20
27.07±0.82αbA
17.14±4.36αaC
1.23±0.17βaA
62.89±0.82βaA
23.68±2.00αaA
13.63±1.12αaA
20-30
22.77±1.39αcA
18.71±3.25αaB
1.36±0.08αaA
62.42±1.23αaA
24.08±1.90αaA
13.71±1.14αaA
Monsoon
0-10
27.61 ±0.99αaB
40.13±5.16αaA
0.95±0.77αbB
63.09±0.66βaA
24.90±0.79αaA
12.22±0.93αcB
10-20
23.14±0.50αbB
41.15±6.16αaA
1.07±0.18αabA
63.57±0.49βaA
22.09±1.25αbA
14.55±1.07αbA
20-30
22.03±1.21αbA
40.68±8.17αaA
1.16±0.18βaB
63.02±1.01αaA
20.83±.128αcB
15.85±0.94αaB
Post-monsoon
0-10
13.77±0.97αbC
22.99±12.49αbA
1.03±0.08αbB
63.60±0.80βaA
25.66±0.85αaA
10.73±0.73βbC
10-20
16.77±0.66αaC
23.93±6.31αabB
1.12±0.15bA
63.01±0.66αaA
23.42±1.46αbA
13.33±1.29αaA
20-30
17.66±1.00βaB
24.64±11.14αaB
1.32±0.12αaAB
62.90±0.69αaA
23.16±1.58αbA
14.04±1.50αaA
Abandoned land
Pre-monsoon
0-10
29.77±0.14αaA
12.29±2.19αbC
1.50±0.15αcA
66.01±1.24αaA
21.37±1.13βaA
12.05±0.93αbA
10-20
26.50±0.86αaA
13.55±7.96αaB
1.57±0.12αbA
64.66±1.0αbA
21.74±1.38βaB
13.59±0.86αaA
20-30
23.11±1.16αbA
16.23±4.28αaB
1.68±0.08βaA
63.69±0.88βbA
22.50±1.59αaAB
13.69±1.19αaA
Monsoon
0-10
27.77±1.39αaB
32.44±6.21βaA
0.99±0.06αcB
66.10±0.84αaA
22.11±0.62βaA
11.87±0.62αbA
10-20
22.17±1.39αbB
37.34±6.20αaA
1.19±0.12αbB
64.56±0.84αbA
22.09±0.80αaB
13.44±1.31αaA
20-30
19.22±0.83βcB
38.95±12.96αaA
1.44±0.19αaB
64.10±1.19αbA
21.69±1.28αaB
13.87±0.87βaA
Post-monsoon
0-10
10.33±1.22βcC
18.66±5.59αaB
1.02±0.14αcB
65.18±0.68αaA
22.48±1.60βcA
12.77±0.73αbA
10-20
16.36±2.60αbC
18.80±7.67αaB
1.25±0.12αbB
62.31±1.12αbB
24.11±1.19aA
13.57±0.98αabA
20-30
19.38±0.88αaB
18.11±4.93αaB
1.34±0.23αaB
61.90±1.24αbB
23.63±1.77αbA
14.46±1.21αaA
Three-way ANOVA
F value
p value
F value
p value
F value
p value
F value
p value
F value
p value
F value
p value
Land use (LU)
8.57
0.004
2.19
0.141
62.78
0.001
66.07
0.001
21.64
0.001
3.01
0.085
Season (S)
1119.6
0.001
106.58
0.001
65.62
0.001
14.02
0.001
16.24
0.001
2.93
0.056
Depth (D)
49.415
0.001
12.23
0.001
51.05
0.001
38.79
0.001
2.54
0.082
54.82
0.001
LU×S
4.947
0.008
3.27
0.041
10.64
0.001
17.89
0.001
2.51
0.085
14.05
0.001
LU×D
0.671
0.513
2.79
0. 064
2.90
0.058
18.24
0.001
12.34
0.001
0.84
0.434
S×D
186.04
0.001
4.96
0.001
2.55
0.042
2.45
0.048
7.11
0.001
5.09
0.001
LU×S×D
14.33
0.001
1.98
0.100
0.82
0.509
0.68
0.602
3.95
0.004
5.04
0.001
Values are mean ± SE. Different alphabets ‘a, b, c’ represent the significant differences across depths within the season; ‘A, B, C’ represent the significant differences across seasons within the same depth (One-way ANOVA); and ‘α, β’ represent significant differences between land use types within the same season and depth (independent sample t-test); BD: Bulk density, LU: Land use, S: Seasons, D: depth.
3.2. Chemical properties of soil
The mean soil pH ranged from 4.97±0.33 to 6.48±0.03. A high value of pH was found in the abandoned land at 20-30 cm in the monsoon, while the value was low in the agricultural land at 0-10 cm in the pre-monsoon (Table 2). Soil pH was high in the deeper soil layer across the seasons in both agriculture and abandoned lands. Variation in soil pH was found between types of land-use (p = 0.01), among the seasons (p = 0.001), and across the depths (p = 0.009). Interaction between land-use type and seasons was also found to be significant (p = 0.005) (Table 2). The soil was slightly acidic in both land use types.
Amount of SOC varied from 0.92 ± 0.51 to 2.63 ± 0.23 %. Agricultural land contained a higher concentration of SOC than abandoned land, particularly during the monsoon, compared to the pre- and post-monsoon periods (Table 2). The carbon content decreased in the deeper soil layer. Overall, carbon concentration was significantly higher in agricultural land compared to the abandoned land across all seasons and depths (p < 0.005). Land use, season, and depths showed significant effects on SOC (p = 0.001) (Table 2). The content of total nitrogen (TN) ranged from 0.08 ± 0.07 to 0.21 ± 0.05 %, available phosphorus (AP) from 29.29 ± 5.67 to 72.16 ± 15.91 kg ha-1, and available potassium (AK) ranged from 186.13 ± 49.81 to 636.55 ± 44.25 kg ha-1. These nutrients were high in the upper layer of soil (0-10 cm) during the monsoon season in agricultural land, while concentrations decreased at 20-30 cm during the post-monsoon season in abandoned land, except for TN during the pre-monsoon season. Nutrient values followed the order monsoon > pre-monsoon > post-monsoon (Table 2).
Influence of land-use type (p = 0.001), season (p = 0.03), and soil depth (p = 0.005) on TN was found to be significant. Similar results were found in case of AP and AK (p = 0.001). However, the interaction effect of these factors did not have a significant influence on soil parameters as they did when considered individually (Table 2).
Chemical properties of soil among land use types across seasons and soil depths.
Land use type
Seasons
Depths (cm)
pH
SOC %
TN %
AP (kg ha-1)
AK (kg ha-1)
Agricultural land
Pre-monsoon
0-10
4.97±0.33βaB
2.59±0.32αaA
0.20±0.16αaA
57.41±22.09αaA
491.20±40.74αaB
10-20
5.13±0.32αaC
2.40±0.36αaA
0.19±0.04αaA
42.86±21.41αbB
404.97±47.15αabB
20-30
5.13±0.25αaB
1.83±0.64αbA
0.18±0.07αaA
46.76±25.31αbAB
321.33±15.38αbAB
Monsoon
0-10
6.21±0.19βaA
2.63±0.23αaA
0.21±0.05αaA
72.16±15.91αaA
636.55±44.25αaA
10-20
6.22±0.08βaA
2.26±0.43αabA
0.16±0.05αabB
64.08±9.85αabA
473.42±51.67αabA
20-30
6.17±0.17βaA
1.88±0.41αbA
0.15±0.05bαAB
56.44±8.06αbA
435.28±43.68αbA
Post-monsoon
0-10
5.83±0.46αaA
2.26±0.37αaA
0.14±0.04αaA
36.69±4.31βaB
260.03±29.36αaC
10-20
5.84±0.37αaB
1.91±0.48αbA
0.13±0.05αaC
33.13±9.85αaB
237.54±25.05αbC
20-30
5.97±0.45αaA
1.88±0.75αbA
0.10±0.03αbB
34.40±5.67αaB
222.92±19.01αbB
Abandoned land
Pre-monsoon
0-10
5.08±0.15αbC
1.56±0.28βaA
0.12±0.06βaB
51.09±11.53βaA
388.06±67.37βaA
10-20
5.21±0.15αaC
1.37±0.19βabA
0.08±0.05βbB
34.22±3.82αbA
287.55±40.46βbA
20-30
5.34±0.20αaC
1.28±0.03βbA
0.08±0.07βbA
31.13±11.39αbA
287.44±34.92βbA
Monsoon
0-10
6.43±0.07αaA
1.57±0.40βaA
0.15±0.05βaA
53.84±6.37αaA
402.45±25.34βaA
10-20
6.43±0.05αaA
1.39±0.14βabA
0.12±.06αabA
32.79±3.65βbA
320.23±38.00βbA
20-30
6.48±0.03αaA
1.11±0.12βbAB
0.09±0.03βbA
31.12±3.23βbA
253.88±33.37βcA
Post-monsoon
0-10
5.62±0.26αbB
1.50±0.39βaA
0.11±0.02αaB
46.23±11.76αaA
258.31±35.62αaB
10-20
5.87±0.20αabB
1.24±0.35βabA
0.12 ±0.04αaA
35.45±8.56αbA
216.09±36.12αabB
20-30
5.95±0.20αaB
0.92±0.51βaB
0.10±0.04αaA
29.29±5.67αbA
186.13±49.81αbB
Three- way ANOVA
F value
p value
F value
p value
F value
p value
F value
p value
F value
p value
Land Use (LU)
6.74
0.010
184.65
0.001
3.59
0.001
22.37
0.001
328.70
0.001
Season (S)
294.37
0.001
4.69
0.011
3.59
0.03
22.37
0.001
328.70
0.001
Depth (D)
4.88
0.009
24.09
0.001
5.56
0.005
22.31
0.001
133.20
0.001
LU×S
5.44
0.005
0.27
0.764
5.63
0.004
16.50
0.001
63.17
0.001
LU×D
0.83
0.439
0.78
0.461
0.04
0.958
2.52
0.083
1.81
0.167
S×D
1.09
0.365
0.29
0.883
0.66
0.615
1.01
0.404
11.71
0.001
LU×S× D
0.39
0.814
1.31
0.269
0.26
0.901
0.50
0.734
4.83
0.001
Values are mean ± SE. Different alphabets ‘a, b, c’ represent the significant differences across depths within the season; ‘A, B, C’ represent the significant differences across seasons within the same depth (One-way ANOVA); and ‘α, β’ represent significant differences between land use types within the same season and depth (independent sample t-test). SOC: Soil Organic Carbon, TN: Total Nitrogen, AP: Available Phosphorous, AK: Available Potassium, LU: Land use, S: Seasons, D: depth.
3.3. Microbial biomass carbon and nitrogen
Range of microbial biomass carbon (MBC) was 80.08 ± 6.68 to 465.82 ± 43.10 μg g-1, and microbial biomass nitrogen (MBN) varied from 4.51 ± 0.32 to 48.58 ± 4.59 μg g-1 of soil (Table 3). Land use type, season, and depths altered the MBC and MBN significantly (p = 0.001). Both parameters were high during the monsoon, followed by pre- and post-monsoon seasons. In comparison to the abandoned land, higher concentrations of MBC and MBN were observed in agricultural land, while they were decreased in deeper layer soils in both land-use types across the seasons (Table 3). The ratio of MBC: MBN ratio ranged from 9.61 ± 0.62 to 19.41 ± 1.57 μg g-1 (Table 3). Each of the factors influenced the ratio but interaction of them did not result in significant alteration in the ratio (Table 3). Agriculture soil exhibited lower MBC: MBN ratio during the monsoon than the abandoned land, while it was higher during post-monsoon season. Overall, the agricultural land, monsoon season, and surface-layer soil enhanced microbial biomass.
Microbial biomass carbon (BMC) and microbial biomass nitrogen (MBN) among land use types across the seasons and depths.
Land use type
Seasons
Depths (cm)
MBC (μg g-1 soil)
MBN (μg g-1 soil)
MBC: MBN
Agricultural
Pre-monsoon
0-10
317.64±49.35αaB
26.03±2.49αaB
12.23±1.87βaB
land
10-20
220.43±57.60αbB
15.69±4.29αbA
14.71±4.41αaA
20-30
146.50±26.06αcB
11.02±2.11αcB
13.69±3.07αaB
Monsoon
0-10
465.82±43.10αaA
48.58±4.59αaA
9.61±0.62αbC
10-20
308.61±91.88αbA
20.05±3.99αbA
15.28±3.17αaA
20-30
219.02±29.92αcA
18.93±3.25αcA
11.66±1.07βbB
Post-monsoon
0-10
287.73±14.38αaB
17.73±1.77αaC
16.35±1.59αaA
10-20
155.60±13.88βbB
9.47±1.99βbB
17.03±3.57βaA
20-30
82.26±8.56αcC
4.51±0.32βcC
18.30±2.28αaA
Abandoned
Pre-monsoon
0-10
288.04±7.83βaB
18.94±0.88βaB
16.28±0.66αbA
land
10-20
248.01±9.39αbA
16.66±2.37αbA
17.07±2.46αaA
20-30
160.13±68.16αcA
10.23±5.20αcA
16.11±2.09αbB
Monsoon
0-10
310.49±9.42βaA
24.22±1.19βaA
14.00±0.70βbB
10-20
241.85±7.64βbA
17.64±3.05αbA
16.82±2.44βaA
20-30
96.68±8.34βcB
9.35±2.24βcA
15.40±2.97αabB
Post-monsoon
0-10
235.94±6.06βaC
15.81±1.08βaC
17.37±1.25αbA
10-20
170.06±10.75αbB
11.86±1.84αbB
18.17±1.43αabA
20-30
80.08±6.68αcB
7.47±2.45αcA
19. 41±1.57αaA
Three-way
F value
p value
F value
p value
F value
p value
ANOVA
Land Use (LU)
53.52
0.001
99.168
0.001
44.51
0.001
Season (S)
116.32
0.001
243.64
0.001
41.71
0.001
Depth (D)
363.83
0.001
391.94
0.001
12.59
0.001
LU×S
42.917
0.001
79.794
0.001
3.415
0.036
LU×D
13.166
0.001
60.027
0.001
1.365
0.259
S×D
6.04
0.001
31.264
0.001
4.157
0.003
LU×S×D
0.506
0.731
12.265
0.001
0.615
0.653
Values are mean ± SE. Different alphabets ‘a, b, c’ represent the significant differences across depths within the season; ‘A, B, C’ represent the significant differences across seasons within the same depth (One-way ANOVA); and ‘α, β’ represent significant differences between land use types within the same season and depth (independent sample t-test).
3.4. Principal component analysis (PCA)
The PCA revealed overall influence of the explanatory variables on the soil physicochemical and microbial properties. Figure 2A shows the percentage of variance explained. PC1 and PC2 axes explained 35.5% and 12.4% of the total variations. Agricultural and abandoned lands were distinctly separated owing to the higher concentrations of SOC, AP, AK, TN, EC, and soil temperature in the agricultural land against soil pH, BD, and MBC: MBN ratios associated with the abandoned land (Fig. 2B). Soil properties like clay percentage, MBC, MBN, AP, AK, and temperature were associated with the monsoon season which distinguished it from the pre-and post-monsoon seasons, which were characterized by higher contents of SOC, EC, and silt (Fig. 2C). Likewise, soil characteristics including SOC, MBN, AP, and TN in the topsoil (0-10 cm) differentiated it from the soil sublayers (Fig. 2D).
PCA biplot shows effects of seasons, depths, and land-use types on soil physicochemical and microbial properties. Figure 2A explains the percentage of variations, 2B explains the impact of land use, 2C explains the impact of seasons, and 2D describes the effect of soil depths. Mois: soil moisture, BD: bulk density, SOC: soil organic carbon, N: total nitrogen, P: available phosphorous, K: available potassium, MBC: microbial biomass carbon, MBN: microbial biomass nitrogen.
Figure 2.4. DISCUSSION
Current results displayed that the soil temperature varied across land-use types, seasons, and soil depths. The highest mean temperature occurred in abandoned land during the pre-monsoon season, and it decreased with depth in both the pre-monsoon and monsoon seasons, but increased in the post-monsoon season. Soil temperature variations reflect the complex relationship between land use, seasonal changes, and soil depth. During the pre-monsoon season, abandoned lands, being less vegetated and more exposed, absorb and retain heat more efficiently, resulting in higher temperatures (Pokharel & Hallett, 2015). As the season transitions into the monsoon and post-monsoon periods, soil moisture levels increase, affecting temperature. Temperature decreases with depth in the pre- and monsoon seasons, which may be due to the direct sunlight and warmer air temperatures at the surface. Increased soil moisture after the monsoon season can enhance thermal conductivity in deeper layers, resulting in rising temperatures with depth (Roxy et al., 2010). Vegetation cover also acts as a thermal insulator, significantly affecting soil temperature (Onwuka, 2018).
The maximum soil moisture content (MC) was observed in agricultural land during the monsoon season, while the minimum was found in the pre-monsoon season. High soil moisture may be linked to low hydraulic conductivity (Rendana et al., 2021). MC also shows an increasing trend of increment with soil depth. Potential factors affecting the MC are precipitation during monsoon, SOM, soil texture, and BD, which directly affect the water-retention capacity of soil (Feifel et al., 2024). Additionally, the pre-monsoon season is characterized by lower soil moisture, which contributes to increased BD, consistent with findings by Enkova and UrÍK (2012) that soil moisture reduces BD. As water moves downward due to gravity and there is less evaporation from deeper soil layers, the MC increases with depth (Gautam & Mandal, 2013).
High BD was found in abandoned land at greater depths during the pre-monsoon season. This finding aligns with earlier findings (Lei et al., 2019; Rodríguez-León et al., 2021). These studies reported higher BD in abandoned land than in agricultural land. The higher BD in abandoned land may be due to lower SOM content and grazing activities. The negative correlation between bulk density and SOM, as observed by Athira et al. (2019), indicates that BD decreases as SOM increases. Higher BD in deeper soil layers is also attributed to the reduced SOM, which compacts the soil below (Bangroo et al., 2017; Gautam & Chettri, 2020; Kafle, 2019). Regarding soil texture, the percentage of sand and silt decreased with increasing soil depth. This process causes clay to accumulate in deeper soil horizons, while larger particles like sand and silt remain in the upper layers due to their size and weight (Gautam & Mandal, 2013; Zhang et al., 2014).
The soil was found to be slightly acidic across land use types, seasons, and depths. Our results showed an increase in pH with increasing soil depth. Typically, lower pH values are observed in topsoil due to higher SOM and the decomposition process, which produces organic acids and thus lowers the pH (Zhou et al., 2019). Assefa et al. (2020) also found acidic soils at the surface. The dilution effect has been seen in the soil as the pH tends to decrease during the rainy season (Acharya & Shrestha, 2015).
Higher concentrations of NPK during the monsoon season are attributed to enhanced microbial activity and decomposition (Agbeshie et al., 2020; Lepcha & Devi, 2020). Similarly, Sharma and Kafle (2020), Magar et al. (2020), and Zhang et al. (2021) also reported high values of SOC, AP, and AK in the surface layer, with declines at greater depths. Tree litter fall, which decomposes on the surface, contributes significantly to the increment of SOC and other nutrients (Amgain et al., 2020; Ganai et al., 2018). High concentrations of MBC and MBN were found in agricultural land during the monsoon and are low in abandoned land during the post-monsoon. Both MBC and MBN decreased with increasing soil depth across both land use types. These results align with Agbeshie et al. (2020) and Liu et al. (2020), who found low concentrations in abandoned land. High MBC and MBN in agricultural land are likely due to the accumulation of organic manure and carbon present in the soil, which tends to lead to a higher MB.
Seasonal variations in MBC and MBN were observed, with peak values during the rainy season and their low contents during the post-monsoon (Table 3). Elevated temperature during the monsoon season accelerates litter decomposition and microbial activity, leading to increased nutrient immobilization by microbes (Lepcha & Devi, 2020; Tripathi & Singh, 2013). Reduction in MBC and MBN in deeper soils might be due to the corresponding decline in organic matter (Limbu et al., 2020; Padalia et al., 2018). In agricultural land, the lower MBC: MBN ratio during the monsoon suggests a relative decrease in carbon due to increased nitrogen availability from organic matter decomposition, whereas in the post-monsoon, the higher MBC: MBN ratio may be due to the reduced nutrient leaching (Manral et al., 2023). Ratio of microbial C: N is an important indicator of the organization and composition of the microbial community, which reflects the dynamics of organic matter decomposition in soil (Tao et al., 2020). A low MBC: NBN ratio suggests a higher bacterial population, while a high ratio indicates fungal dominance (Campbell et al., 1991; Ravindran & Yang, 2015). Our findings indicate that the microbial population is dominated by fungi.
The concentration of both SMBC and SMBN in both land types decreased with increasing depth. The increasing SMBC:SMBN ratio, as shown by this study with respect to soil depth, indicates slow decomposition of organic matter. Li et al. (2013) also reported a significant increase in the SMBC to SMBN ratio with increasing depth in the soil layer. Higher MBN and MBC contents in the surface layers of agricultural lands indicate that the surface soil has higher microbial activity, indicative of good soil quality.
PCA showed relationships among soil parameters and various land use types. It proved to be an effective method for examining how the changes in land use affect specific soil characteristics (Biro et al., 2013). PCA revealed the influence of the explanatory variable (land-use, seasons, and depths) on soil physicochemical and microbial characters (Fig. 2). Soil silt content and higher values of MBC, MBN, AP, AK, SOC, and temperature were positively correlated with agricultural land. The pre-monsoon season was characterized by association with SOC values, whereas the parameters MBC, MBN, K, and Clay percentage were found to increase during the monsoon. This pattern of temporal variations in soil parameters further illustrated a distinct effect of depth through PCA.
CONCLUSION
The study revealed that the soil's physicochemical and microbial characteristics varied with land-use types, seasons, and soil depths. During the pre-monsoon season, mean soil temperatures were higher across land use types. The temperature decreased with increasing depth during both the pre- and monsoon seasons. However, during the post-monsoon period, the temperature increased with increasing depth. During the monsoon, higher soil moisture was recorded in agricultural land, increasing with depth. Bulk density in abandoned land increases in the pre-monsoon season but decreases in the post-monsoon season. Agricultural land exhibited the highest silt and clay content, whereas abandoned land had a higher proportion of sand. Similarly, pH, SOC, TN, available phosphorus, and available potassium were increased in soil during the monsoon season in agricultural land. The role of soil physiochemical properties and microbial biomass carbon and nitrogen is crucial for soil nutrient dynamics, thereby affecting plant and crop productivity. Therefore, the results can inform sustainable soil management practices in agricultural and abandoned lands.
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