1 Introduction

Soil organic carbon (SOC) is an important component of soil, also considered a measurable fraction of soil organic matter (SOM) that has a crucial role in maintaining soil productivity and providing ecological functions (Wiesmeier et al. 2019). Soil organic matter helps in nutrient and energy cycling, water storage, improves soil physical condition, climate regulation, fosters soil biodiversity, and regulates ecosystem functions (Vidojevic et al. 2017). Furthermore, SOC is a vital part of the terrestrial carbon (C) pool and soils can serve as a potential sink for the atmospheric C (Ali et al. 2019; Hou et al. 2019). Carbon content in soil that is stored in the organic form is three times more than that of the atmosphere and five times more than in biotic pools like plants, animals, and microorganisms (Lal et al. 2012). Soil holds the largest terrestrial pool of C, with global estimates ranging from 1115 × 109 to 2200 × 109 Mg C (Batjes 1996), and the top 100 cm of soil containing approximately 1462 × 109 to 1548 × 109 Mg C (Batjes 2014; Kirschbaum 2000). Padarian et al. (2022) estimated that the potential SOC storage in the top soils (0–30 cm) of global croplands ranges from 29 to 65 Pg C with the implementation of optimal management strategies. So, soil has the enormous capacity to store excess C from the atmosphere, which provides opportunities for soil health improvement and climate feedback in terrestrial ecosystems.

The SOC depends on various abiotic and biotic factors (Merino et al. 2015). The biotic factors include soil microorganism, their activity and interaction, plant species, root system, and fauna (Watts et al. 2005; Jensen et al. 2019). Soil microorganism involves the decomposition of organic matter, the process known as mineralization. Plant roots contribute to SOC accumulation through rhizodeposition, where plants release organic compounds into the soil and become stabilized as SOC through interactions with soil minerals or microbial processes (Wilson et al. 2009; Yang et al. 2022). Similarly, the abiotic or edaphic factors include soil texture, structure, particle size, gravel content, soil pH, and interaction with various nutrients in soil (Liu et al. 2010). Fine-textured (e.g., clay) soils have higher levels of SOC than coarse-textured (e.g., sandy) soil. Furthermore, SOC can be affected by microbial activities and total nitrogen (N) content in soil (Martinez et al. 2008). There is a proportional relationship between SOC and N in tropical soil environments, which can be attributed to the interaction between soil microorganisms, organic matter, and litter present in the soil (Cotrufo et al. 2019 and Averill et al. 2014). Additionally, the amount of C and N in soil also affects the N cycle, which has an important role in increasing ecosystem productivity and C sequestration (Liu and Greaver 2010). So, a multitude of factors affect the SOC balance in soil.

It is imperative to understand that the eventual SOC levels build-up in soil profile are generated by a combination of several factors, and thus researching individual factors could not fully underpin the mechanism of SOC accumulation (Xiong et al. 2014; Mayes et al. 2014). The total amount of SOC stored in soil is primarily determined by soil depth and turn over time (Wuest 2009). Depth of the soil influences the SOC storage due to the variation of their volume and mineral surface area that alters the adsorption of carbon and mineralization process. Studies showed that SOC tends to be higher in top soils, attributed to increased C cycling and sequestration processes (Baisden and Parfitt 2007; Burke et al. 1989). In top soils, C cycling refers to the movement of C between different forms of organic matter and atmosphere facilitated by various biological and chemical processes such as photosynthesis, respiration, decomposition and mineralization. However, some findings reported that deeper soil has greater potential of SOC storage. The higher potential of SOC in deeper soil layers is attributed to the slower decomposition rates compared to surface soils. This is facilitated by mineral protection, which helps to preserve SOC in deeper soil layers, leading to the accumulation of significant SOC stocks (Gill and Burke 2002; Jobbagy and Jackson 2000; Lal 2018). Similarly, because of microbial communities in the sub-surface soils, their physiology and enzymatic actions, climatic zones (Kochy et al. 2015; Wagai et al. 2013), litter and substrate quality (Fierer et al. 2007; Hartley and Ineson 2008) facilitate for the storage of SOC at sub-surface soils.

There is a scarcity of studies regarding the profile distribution of SOC concentration and stock based on horizon analysis, particularly in the predominant soils of Nepal. Most studies conducted in Nepal characterized SOC stocks on fixed soil depths and land use types (Lamichhane and Ghimire 2022; Dahal and Kafle 2013). Previous studies primarily focused on topsoil C stock and C dynamics in deeper soil layers and driving factors behind the vertical distribution of SOC remain poorly understood (Ghimire et al. 2012; Ojha et al. 2021; Rumpel and Kobel-Knabner 2011) in major soils of Nepal. Soil types such as Inceptisols, Entisoils, Alfisols, and Mollisols dominate Nepal’s soil landscape (Bajracharya 2021) and the study area, Chitwan district, is dominated by Entisols, Inceptisols and Alfisols. This assessment of SOC across dominant soil orders offers insights into SOC status and influencing factors in Nepal.

Soil nutrient mining accompanied by loss of SOC in the soils of Chitwan district was reported, which is primarily due to extensive agriculture, low organic input, and lack of adaptive measures (Dahal 2012; Karki et al. 2021). In this context, study of several factors that control the SOC content in the soil profile of dominant soil orders can be helpful to understand the distribution of SOC and develop adaptive measures to maintain soil C level. Similarly, the study is crucial for maintaining agricultural productivity, environmental management, land use planning, and climate change resilience. Thus, this study aimed to investigate the distribution of SOC in the surface and sub-surface horizons, along with their primary controlling factors, within Inceptisols, Entisols, and Alfisols in the Chitwan district, Nepal.

2 Materials and methods

2.1 Site selection

The study was conducted in Chitwan district of Bagmati province, an Inner Tarai valley in the south of Nepal. Chitwan district lies between 83°35' to 84°55' E longitudes and 27°21' to 27°46' N latitudes covering an area of 2218 km2. The research area lies in a tropical humid climatic area having distinct four kinds of weather: monsoon (June to September), autumn (September to November), winter (November to February), and spring (February to May). The ten years (2010 to 2020) of meteorological data at the research area was recorded from the National Maize Research Program, Rampur, Chitwan. The 10-year average maximum and minimum temperatures at the research area were 33.87 °C and 18.39 °C, respectively. Similarly, the average rainfall recorded was 1943.04 mm with 97% relative humidity.

The soil orders were selected based on the soil map prepared by the NLUPP at a scale of 1:10,000. According to NLUPP, the dominant soil orders of Chitwan district are Alfisols, Entisols, and Inceptisols (LUPP 2020) and these soil orders were selected for the study. The southern part of Chitwan, Nepal characterized by a mix of agricultural or cultivated land, conservation area (Chitwan National Park), buffer zones, forestry, agroforestry, river and basins, settlements, and infrastructures. Three different land use types were identified for dominant soil orders such as cultivated land for Inceptisols, forest land for Alfisols, and river basins for Entisols. The topography for Inceptisols was almost flat (< 1°) and that for Entisols and Alfisols was undulating (1 to 4°). Inceptisols are mostly found in Tarai region and below 1500 m above sea level in the mountains and have the characteristics of low nutrient retention and thus require proper care and management (Fischer et al. 1960). Similarly, Entisols are soils characterized by youngest soil with little profile development and are formed by the recent deposition of river sedimentation (Vaidya et al. 2021). Alfisols are the most dominant soil order in dense broad leaf forest and are characterized by the accumulation of clay in the sub-surface horizons (Fischer et al. 1960).

2.2 Soil survey and sample collection

Altogether, 12 different areas from the map given by NLUPP were selected randomly for three dominant soil orders (Alfisols, Entisols, and Inceptisols), by replicating each soil order four times. A total of 160 samples (80 for bulk density [BD] and 80 for other soil properties) were collected from different horizons of three soil orders by digging up of 1 m3 dimension soil pit in each area. At least one sample was collected from each of the diagnosed master soil horizons. Additionally, for precise and accurate measurement of soil characteristics, more soil samples were collected from a single horizon that was more than 15 cm deep. For BD, a 1 m long core ring was used to collect soil samples. A core ring was inserted adjacent to the soil pit and horizon horizon-wise bulk sample was collected for the measurement of BD.

2.3 Soil preparation, data collection and analysis

The collected soil samples were cleaned by removing debris such as roots, twigs, stones/pebbles, air dried, and ground to make it fine passing through a 2 mm mesh sieve in the laboratory for further analysis. The soil morphological features like order, horizon, horizon boundary, and soil color were observed and recorded in the field conditions and soil properties such as soil pH, BD, SOC, SOC stock, soil texture, and N were calculated at the soil lab of Agriculture and Forestry University, Chitwan, Nepal. Soil pH was measured using a digital pH meter with 1:2.5 soil–water suspension. Similarly, for BD, a soil sample was taken by using a core sampler with a ring and calculated Eq. (1) through Eusing a formula (Blake and Hartge 1986).

$$\mathrm{Bulk}\;\mathrm{density}\;\left(\mathrm g\;\mathrm{cm}^{-3}\right)=\frac{\mathrm w}{\mathrm v}$$
(1)

, where

W = weight of oven dried soil (g)

V = volume of soil core (cm3)

Soil organic matter (SOM) was calculated through Eq. (2) by using the Walkey and Black wet oxidation method (Walkey and Black 1934).

$$\mathrm{Organic}\;\mathrm{matter}\;\left(\%\right)=\frac{\left(\mathrm B-\mathrm S\right)\;\times\;\mathrm N\;\times\;3\times\;100\;\times\;100\;\times\;100}{\mathrm M\;\times\;1000\;\times\;77\;\times\;58}=\frac{\left(\mathrm B-\mathrm S\right)\;\times\;\mathrm N}{\mathrm M}\;\times\;0.67$$
(2)

, where 

B = Volume of Fe (NH4)2SO4•6H2O used in blank titration (ml)

S = Volume of Fe (NH4)2SO4•6H2O used for sample titration (ml)

N = Normality of Fe (NH4)2SO4•6H2O for blank titration

M = weight of the soil sample after moisture correction (g)

SOC was calculated through Eq. (3) based on SOM, as SOM contains 58% of the soil C (Tuohy et al. 2020).

$$SOC\left(\%\right)=\text{Soil organic matter }\left(\text{SOM}\right)\times 0.58$$
(3)

SOC stock was calculated through Eq. (4) by using the formula given by Chhabra et al (2003).

$$\mathrm{SOC}\;\mathrm{Stock}\;\left(\mathrm Mg\;\mathrm{ha}^{-1}\right)=\text{Soil organic carbon stock }\left(\text{SOC stock}\right)\times \text{Bulk density }\times \text{Horizon depth }$$
(4)

Total nitrogen was calculated through Eq. (5) by using Kjeldhal distillation method (Bremmer and Mulvaney 1982).

$$\%\;\mathrm N\;=\;\frac{7\;\times\;\mathrm N\;\times\;\left(\mathrm T-\mathrm B\right)}{\mathrm S}$$
(5)

, where

N = Normality of acid (0.05)

T = Volume of acid used in titration (ml)

B = Volume of acid in blank (two blank samples were prepared with the same procedure as in soil samples except that they were devoid of soil samples and an average of their titrated value was taken) (ml)

S = Sample weight (g)

Soil texture was recorded by hydrometer and textural classification system following the USDA system (USDA 1980).

2.4 Statistical analysis

All the observed parameters were compared against soil types and soil horizons as the main factors. The significance level of the mean was calculated using one-way Analysis of Variance at a 5% level of significance in which the residuals met the assumptions of normality and equal variance. The relationship between SOC and other edaphic variables was studied using correlation and regression analysis. The determining edaphological factors for SOC formation in different soil types were identified using Principal Component Analysis (PCA). The graphs showed 95% confidence interval bars by multiplying standard error by 1.96 or respective values. All the statistical analysis was conducted in R Studio software using packages “ggplot2″ (for graphics), ‘factoextra” (for PCA analysis), and base R functions (for ANOVA and regression analysis) (RStudio Team 2020).

3 Results

3.1 Morphological characterization

Our study revealed that soil color hue was 10 YR in all soil profiles with variable value and chroma ranging from grey, moderately dark to light color. The value of Inceptisols and Alfisols ranged from 4 to 6 and 4 to 5, respectively, which indicates that the colors of the horizons soil of these soil orders were moderately dark to light color. The value of Alfisols ranged from 5 to 7 which indicates that Entisols soil horizons were light colored. The chroma of Inceptisols ranged from 1 to 8 which indicates that Inceptisols soils were grey, waterlogged to well-drained and oxidized soil. Similarly, the chroma of Entisols and Alfisols ranged from 1 to 2 and 3 to 4, respectively, which indicates that these soils are grey and wet or waterlogged (Table 1).

Table 1 Soil morphological properties of Inceptisols, Entisols and Alfisols across different horizons in studied areas
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Also, results showed that all soil orders had variable horizon depth from the surface to sub-surface horizons with the highest soil depth (60 cm) in sub-surface (C) horizons and the lowest in surface (A) horizons of the soil profile (Table 1). Inceptisols were dominated by ochric epipedon and cambic endopedon. Similarly, Alfisols were dominated by umbric epipedon, argilic, and kandic endopedon while Entisols were dominated by ochric epipedon. Soil texture in soil horizons of Inceptisols and Alfisols varied from sandy, sandy loam to sandy clay loam while Entisols soil horizons texture ranged from sandy loam to silty loam (Table 2).

Table 2 The proportion of sand, silt, and clay in Inceptisols, Entisols, and Alfisols orders in studied areas
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3.2 SOC concentration and stock

Alfisols had a significantly higher mean SOC concentration (10.1 ± 0.6 g kg−1), followed by Entisols (8.8 ± 0.3 g kg−1) and Inceptisols (7.2 ± 8.9 g kg−1) (Fig. 1a). Similarly, the A horizon had the highest SOC concentration followed by the C horizon. Alfisols soil had the greatest average SOC concentration in A horizon followed by Inceptisols and Entisols. Similarly, the average SOC concentration of the B horizon in Alfisols soil was higher than Inceptisols. Alfisols soil had the greatest average SOC concentration in the C horizon followed by Entisols and Inceptisols (Fig. 1a).

Fig. 1
figure 1

Distribution of SOC concentration (a) and SOC stock (b) in horizons of Alfisols, Entisols and Inceptisols in studied areas. The error bar represents 95% confidence interval range

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The maximum cumulative SOC stock was found in the profile (0 to 100 cm) of Alfisols (200.01 t ha−1), followed by Entisols (124.67 t ha−1) and Inceptisols (113.27 t ha−1) (Fig. 1b). The average SOC stock of A horizon was highest in Alfisols soil followed by Entisols and Inceptisols. Similarly, the average SOC stock of B horizon was also highest in Alfisols soil followed by Inceptisols. The average SOC stock of C horizon was highest in Alfisols soil followed by Entisols and Inceptisols (Fig. 1b).

3.3 SOC relation to edaphic factors

A significant correlation (p < 0.001) was observed between SOC and soil clay content, with a positive and highly significant correlation coefficient of 0.68 (Fig. 2a). Moreover, it was found that a 45% variation in SOC (adjusted R2 = 0.45) was contributed by the clay content of the soil. There was a significant correlation (p < 0.001) between SOC and N content of the soil. The correlation coefficient between SOC and N content was found to be 0.914 which was positive and highly significant (Fig. 2g). It was observed that 83% variation in SOC (adjusted R2 = 0.83) was contributed by the N content of the soil. There was a significant and negative correlation (p = 0.048, r = -0.22) between SOC and BD of the soil (Fig. 2e). It was observed that a 4% variation in SOC (adjusted R2 = 0.04) was contributed by BD of the soil. Likewise, there was a significant and negative correlation (p < 0.001, r = -0.436) between SOC and sand content of the soil. It was observed that only 18% variation in SOC (adjusted R2 = 0.18) was contributed by the sand content of the soil. Non-significant correlation of silt content, soil pH, and aggregate size of the soil was found with SOC (Fig. 3)

Fig. 2
figure 2

Relationship between SOC and observed variables (a-g) in different soil orders in studied areas. The straight line represents linear regression with 95% confidence interval bands. The R2 is adjusted R square value obtained from multiple linear regression of the variable with SOC along with their respective p-values

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Fig. 3
figure 3

Correlogram showing the relationship between the variables and their differences in the soil types in studied areas

Full size image

3.4 Principal component analysis (PCA)

Three principal components were identified to cover 87% of the total variance with the disposition of 43.1%, 29.2%, and 14.7% in the first, second, and third components, respectively (Table 3). The first component showed a higher positive value for aggregate size (0.824) and sand (0.783) with positive factor loading whereas silt (-0.923) and pH (-0.833) have negative factor loading contributing negative association of the variables with the component. Similarly, the second component showed positive factor loading for clay (0.887) and N (0.959) contributing positive association of the variables with the component (Table 4).

Table 3 Variance analysis of principal component of soil properties
Full size table
Table 4 Vector analysis of principal component of selected edaphic factors on all soil types
Full size table

The PCA graph of variables showed how strongly the soil properties are associated with each other and with the principal components (Fig. 4). Soil properties like N and clay have a strong influence on the second component whereas sand and aggregate size have a strong influence on the first component. The angle between two vectors signifies the direction of correlation between the variables. Lesser angle between vectors signifies positive correlation (e.g., between soil properties like silt and pH), right angle signifies no correlation (e.g., N and sand), and straight angle signifies negative correlation between variables (e.g., aggregate size with silt and pH). In Entisols soil, it shows that SOC is positively correlated with N and clay content (Fig. 4b). There is a strong positive correlation between SOC and N. In Inceptisols, SOC is positively correlated with N and clay whereas SOC is negatively correlated with bulk density and sand content (Fig. 4c). In Alfisols soil, it shows that SOC is positively correlated with clay and N while negatively correlated with sand content (Fig. 4d).

Fig. 4
figure 4

Principal component analysis of selected edaphic variables on different soil types

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4 Discussion

4.1 Morphological characterization

Various shades of the brown and yellow–brown color of soil orders (Entisols, Inceptisols, and Alfisols) in surface and sub-surface horizons of soil profiles indicate a good drainage condition of soil profiles (Rehman et al. 2017; Mahajan et al. 2007). For example, cooler regions tend to have grayish to black top-soil due to the accumulation of humus. In moist-warm regions, soils tend to be more yellowish-brown to red depending on the hydration of ferric oxide and extensive weathering of the soil’s parental mineral (Jackson 2020). The variance in soil color was also caused by the visible drainage sequences (Senjobi 2007). In addition to the role of drainage on soil color variation, Majlis (1967) noted that soil color has been expressed as a function of iron and organic matter concentrations, pH, and clay mineral types in the soil. In all the soil orders (Entisols, Inceptisols, and Alfisols) surface soil structure ranged from fine weak granular to medium moderate crumb which could be due to continual soil management and OM addition in soil (Najar et al. 2009). Sub-angular to angular blocky soil structure in the sub-surface layers might be due to an increase in clay percentage and soil compaction (Sharma et al. 2004). Entisols were dominated by ochric epipedon, whereas Alfisols were characterized by ochric epipedon and argillic and kandic endopedon (Table 1) showing the different degrees of soil formation. A similar surface and sub-surface diagnostic horizon of Entisols and Alfisols was also given by Rehman et al. (2017). Inceptisols were dominated by ochric epipedon and cambic endopedon. This finding was also supported by Aydinalp and Fitzpatrick (2004). The pore area associated with aggregates frequently contains SOC, which contributes to C stability (Kinyangi et al. 2006). Aggregate-associated OM is a significant C source in some soils, accounting for SOC storage (Sarkhot et al. 2007). Differences in soil texture of Inceptisols, Entisols, and Alfisols soils (Table 1) were also given by Grauer-Gray and Hartemink (2016), Igwe (2005), and Rakesh et al. (2020). There was an increasing trend of fine textured soil from surface to sub-surface horizons which might be due to the alluvial deposition to the sub-surface horizons (Wani et al. 2009). Alfisols with higher sub-surface clay and silt aggregates exhibit resistance to microbial degradation of C, thereby promoting its retention in the soil (Skjemstad et al. 1993). The study conducted by Hartati et al. (2023) in North Galela, Indonesia on Inceptisols, Entisols, and Alfisols soil orders also reported a similar pattern of distribution of soil morphology properties like horizon depth soil texture and structure and BD across the soil horizons.

4.2 SOC concentration and stock

Alfisols (dominated with broad leaf forest) showed the highest SOC concentration and stock than Entisols and Inceptisols. A study carried out by Venkanna et al. (2014) also suggested that forested areas are mostly dominated by Alfisols with higher amounts of organic C. Higher SOC concentration and stock in the forest areas/ Alfisols soil order might be due to the higher amount of leaf litters, OM deposition for long period and high biological activities, whereas Entisols and Inceptisols have low organic residues and litter depositions. Mandal et al. (2005) also stated that the higher amount of organic C in Alfisols (forested areas) might be due to higher amounts of leaf litter and extensive root systems in the forested areas. Chahal et al. (2005) also showed similar results with our findings. Conversely, Tan et al. (2006) reported contrasting findings with ours, showing the highest SOC in Inceptisols followed by Entisols and Alfisols. They attributed this to the composition of surface sediments in two soil orders, Inceptisols and Entisols, within the flood plain. These considerable fluctuations in SOC with soil order show that pedogenic processes play an essential role in C sequestration because soil is a product of climate, vegetation, parent materials, and time (Jackson 2020). In contrast with our result, a study conducted by Gowthachand et al. (2023) on three different land use systems under each soil order (Entisols, Inceptisols, and Alfisols) in the Majha region of Punjab shows that SOC is not significantly different among different soil orders. According to them, Entisols had higher SOC than other soil orders (Inceptisols and Alfisols) due to more organic residues via leaf litter and other plant residues. Whereas in Alfisols and Inceptisols due to limited vegetation, prolong and intensive cultivation reduces the SOC content due to increased mineralization of organic residues and soil microorganisms. Dhaliwal et al. (2021) also reported a similar non-significant result.

Higher SOC in Alfisols might also occur due to higher clay content in the soil horizons of Alfisols than Inceptisols and Entisols. Alfisols with higher clay content can store more C than soils with a coarser texture (Bhatti et al. 2002). Higher SOC stock in Alfisols compared to Entisols and Inceptisols might be due to the higher soil mass obtained from Alfisols (average bulk density of 1420 kg m−3) than Entisols (average bulk density of 1350 kg m−3) and Inceptisols (average bulk density 1330 kg m−3). Differences in SOC stocks among soil types in the study might be due to different soil textures ranging from silty loam to sand (Davis et al. 2004). This can be explained by the stabilization effects of clay particles and associated iron oxides on soil OM (Von et al. 2006; Goh 2004). Variation of SOC stock in different soil orders is also affected by land use type such as forest, agriculture land and river basin (Wiesmeier et al. 2012). For instance, forest areas have higher biomass as compared to agriculture land and river basin and thus have higher SOC stock (Arunachalam and Pandey 2003).

4.3 SOC concentration and stock variation with soil horizons

Our results showed a subsequent decline in SOC concentration from surface (A) horizon to sub-surface horizons (B and C). Rehman et al. (2017) also found the highest SOC concentration and stock in the A horizon of Alfisols followed by Entisols and subsequent decline of SOC concentration and stock in Alfisols and Entisols soil order with sub-surface horizon. Higher organic C in the surface horizons of Alfisols might be due to the continuous addition of OM in the forested area. For example, leaf litter and other forest products in the forest areas fall and decompose, which increases the OM content of the surface soil in the forest. Decline of SOC in the B horizon might be due to the decrease in organic sources as compared to the surface (A) horizon. Najar et al. (2009) also reported that the greater values of SOC in surface strata were attributed to continual organic manuring, addition through vegetation, and low mineralization rates in the surface horizon. A slight increase in SOC content in the sub-surface (C) horizon in our study might be due to higher clay content in C horizon of Alfisols. This is because clay particles can store more C than coarse particles (Hoyle et al.), also in sub-surface horizon (Bhatti et al. 2002). Similarly, higher SOC in Entisols in surface (A) horizon might be due to the recently deposited sediments and debris which is a good source of OM (Chhabra et al. 2003). Our study of Inceptisols soil order was in agriculture land. The highest SOC in A horizon of Inceptisols followed by B and C horizons was due to continuous manuring and addition of organic sources in agriculture land during cultivation and agricultural practices (Aydinalp and Fitzpatrick 2004).

Soil organic C stock depends on SOC, BD and horizon thickness (Cotching 2012). The highest SOC stock in A, B and C horizons of Alfisols was due to the higher SOC concentration in the respective horizons and their depths. Increased BD results in soil compaction and sampling from the compacted soil led to higher sample mass. Soil samples from higher sampling depth result in greater sampled soil mass and soil C are linked and thus sampling more soil mass yields higher SOC stocks (Davidson and Ackerman 1993). VandenBygaart (2006) also concluded that variability of SOC stocks is commonly related to horizon thickness. Our study revealed that BD in sub-surface horizons was higher, and the interplay among BD, SOC content, and horizon thickness contributed to variations in surface and sub-surface SOC stocks. Don et al. (2007) have also given the similar relationship between SOC stock and SOC, horizons BD and horizons thickness. The low BD in the surface horizon of Alfisols soil was due to high OM content in the surface soil. This inverse relation between soil OM and BD and their effect on SOC stock in soil profile of Alfisols was also given by Curtis and Post (1964) and Chaudhari et al. (2013). We observed that the surface (A) and sub-surface (B) horizons of Inceptisols had comparatively lower BD while the BD of the B horizon was slightly higher. The lower BD in the surface horizon may result from ongoing agricultural activities, rendering the soil more fragile and looser. Conversely, the higher BD in the sub-surface (C) horizon could stem from soil compaction due to the continuous use of heavy agricultural machinery and equipment, in agreement with Schäffer et al. (2007). In the context of Entisols soils, lower SOC stock than other orders in the surface horizon might be due to the domination of sandy textured soil which possesses lower SOC and lower BD value. Hairiah and Noordwijk (2000) also reported that sand correlated negatively with SOC implying that, where sand is high, clay is expected to decrease resulting in decreased SOC stock.

4.4 SOC related to edaphic factors

Our result showed that SOC changed in the opposite direction with the horizon depth. Similar results of changes in total SOC up to 100 cm depth were also found significantly different by Yu et al. (2014). The inverse relation between SOC and soil depth might be due to the variation of vegetation biomass and microbial decomposition as depth increases. A similar change due to vegetation biomass and microbial decomposition with soil depth was also given by Schlesinger and Adrienne (1998). The decrease of SOC with the depth of soil also depends on climate and topography. The decrease in SOC with the increase in soil depth of Hills and Tarai regions of Nepal was also reported by Pandey and Bhusal (2016). Also, Ghimire et al. (2018) reported higher SOC in top layer and decreased SOC with increased depth in Tarai region of Nepal.

Our result showed a significant and positive correlation between SOC and clay content which was in accordance with Hassink (1994). The silt and clay size fractions could protect SOC in soil aggregates (Gulde et al. 2008; Hassink 2016). Soil minerals, particularly clay minerals, are crucial for SOC dynamics because they offer surfaces for organic molecules to adsorb. They also have a considerable impact on the pore system and micro-structure of soil, as well as being actively involved in the development and dynamics of aggregates, which protect SOC from biodegradation (Hassink 1994). The presence of clay and fine silt particles assists in maintaining soil organic matter, thereby establishing a positive correlation between SOC concentration and clay and silt content in the soil (Baldock and Skjemstad 2000). Likewise, Principal Component Analysis revealed the positive relation of SOC with clay content. Additionally, similar component analyses were conducted among SOC, clay content, and N in three different soil orders (Alfisols, Entisols, and Inceptisols) by He et al. (2019). Clay particles are thought to protect some of the more quickly degradable organic compounds from microbial decomposition by encrustation and trapping, thereby establishing a proportionate relationship with SOC (Tisdal and Oades 1982).

From the current study, we observed a positive correlation between SOC, clay content, and N in all three types of soil, i.e., Alfisols, Entisols, and Inceptisols. Alfisols soils in the study are characterized by forested soil and high C content in this soil is due to deposition of the leaf litters and OM. The attribution of low SOC due to low C:N ratio is due to microbial immobilization of N and loss of C through respiration (Aber and Melillo 1980; Staaf and Berg 1982). A proportional relation between SOC and N content was also reported by Santruckova et al. (2010) and Bown et al. (2011). Nitrogen content in the study was highest in Alfisols, attributed to their base rich nature, high-quality litter with concentrated nutrients, and superior water storage capacity, facilitating high rates of decomposition (Vesterdal 1993). Soil organic C exhibited a substantial link with soil N in our study; a similar pattern was observed in research by Kooch et al. (2014).

A negative correlation between SOC and soil pH (r2 = 0.132, p < 0.058) was also found by Yu et al. (2014) and Wang et al. (2016). The inverse relationship between SOC and soil pH might be because soil pH alters the decomposition and dynamics of SOC primarily via physical, chemical, or biological processes. For example, low microbial activities occur in acidic soil (low soil pH) which leads to low SOC. Motavalli et al. (1995) also reported that a low pH decreases microbial activities and decomposition of soil organic matter which decreases the SOC content in soil. Moreover, at low soil pH, the solubility of SOC decreases which decreases the adsorption of SOC onto soil particles (Garbuio et al. 2011).

5 Conclusion

Alfisols soil order had the highest accumulation of SOC concentration and stock followed by Inceptisols and Entisols. Horizon-wise distribution of SOC concentration showed that surface (A) horizons of all three soil orders were found with significantly higher SOC than sub-surface (B and C) horizons. In the Alfisols, the horizons were found rich in clay content and the accumulation of SOC is particularly influenced by clay content, N of the soil. However, in Inceptisols and Entisols, where sand content is high in the horizon, accumulation of SOC is influenced by N, soil pH, and soil BD. Thus, all soil properties (physical, chemical and biological) should be considered, and their accurate and precise estimation is suggested for estimation and prediction of factors controlling organic C content in horizons of different soil orders.