Applied and Environmental Soil Science

Applied and Environmental Soil Science / 2020 / Article

Research Article | Open Access

Volume 2020 |Article ID 8241739 | https://doi.org/10.1155/2020/8241739

Benjapon Kunlanit, Laksanara Khwanchum, Patma Vityakon, "Land Use Changes Affecting Soil Organic Matter Accumulation in Topsoil and Subsoil in Northeast Thailand", Applied and Environmental Soil Science, vol. 2020, Article ID 8241739, 15 pages, 2020. https://doi.org/10.1155/2020/8241739

Land Use Changes Affecting Soil Organic Matter Accumulation in Topsoil and Subsoil in Northeast Thailand

Academic Editor: Filippo Ubertini
Received10 Jul 2019
Revised22 Apr 2020
Accepted19 May 2020
Published24 Jun 2020

Abstract

The objectives of this study were to investigate effects of land use on accumulation of soil organic matter (SOM) in the soil profile (0–100 cm) and to determine pattern of SOM stock distribution in soil profiles. Soil samples were collected from five soil depths at 20 cm intervals from 0 to 100 cm under four adjacent land uses including forest, cassava, sugarcane, and paddy lands located in six districts of Maha Sarakham province in the Northeast of Thailand. When considering SOM stock among different land uses in all locations, forest soils had significantly higher total SOM stocks in 0–100 cm (193 Mg·C·ha−1) than those in cassava, sugarcane, and paddy soils in all locations. Leaf litter and remaining rice stover on soil surfaces resulted in a higher amount of SOM stocks in topsoil (0–20 cm) than subsoil (20–100 cm) in some forest and paddy land uses. General pattern of SOM stock distribution in soil profiles was such that the SOM stock declined with soil depth. Although SOM stocks decreased with depth, the subsoil stock contributes to longer term storage of C than topsoils as they are more stabilized through adsorption onto clay fraction in finer textured subsoil than those of the topsoils. Agricultural practices, notably applications of organic materials, such as cattle manure, could increase subsoil SOM stock as found in some agricultural land uses (cassava and sugarcane) in some location in our study. Upland agricultural land uses, notably cassava, caused high rate of soil degradation. To restore soil fertility of these agricultural lands, appropriate agronomic practices including application of organic soil amendments, return of crop residues, and reduction of soil disturbance to increase and maintain SOM stock, should be practiced.

1. Introduction

Soil organic matter (SOM) is a key integral indicator of soil quality [1, 2]. Both soil organic carbon (SOC) and soil organic nitrogen (SON) are attributes of SOM used to describe SOM various functions [1]. The SOM dynamics are dependent on native vegetation, climatic conditions, soil types, management practices, land use history, and time of land conversion [3, 4]. Conversion of forest to agricultural land as a result of increasing population which creates a growing need of land for agricultural production has been occurring for decades [3]. Land use change affects soil ecosystems and their component microbial communities which, in turn, affects soil C and N availability [5, 6]. According to Assefa et al. [7], land use change could affect environmental conditions, such as soil temperature and moisture, which ultimately reduced the accumulation of SOC and SON, especially in sandy soil.

Numerous studies around the world have shown that land use change encompassing changes in vegetation cover, crop type, and agricultural practices has bearings on SOM accumulation. In Ethiopia, SOM stock in forest soil at 0–20 cm depth was higher than in agricultural land (i.e., eucalyptus plantation, grazing land, and cropland) [3, 7, 8]. In New Zealand, Ross et al. [9] also found that forest soil had a higher total N content (2.90 g·kg−1) than that under pine tree plantation (2.70 g·kg−1). In the Northeast of Thailand, Tangtrakarnpong and Vityakon [10] as well as Kunlanit et al. [11] found that forest soils at 0–15 cm had significantly higher SOM content than agricultural soils. These findings were similar to those studied in China. Wang et al. [12] found that forest soil had higher SOM than upland crop soil. Most studies showed that leaf litter decomposition contributed to SOM accumulation in forest topsoil [13, 14]. However, some reports showed contrasting results. In Ethiopia, SOM accumulation in the lowland area under forest was lower than in cropland [7]. The reason put forward was that lowland forest soil had higher sand and lower clay contents than the cropland soil. Additional reason was burning of grass cover in lowland forest which lower SOM content. In China, N content in 0–10 cm soil depth increased after conversion from forest (Pinus yunnanensis Franch) (1.48 g·kg−1) to wheat-maize rotation (1.85 g·kg−1) [15]. The higher N in the wheat-maize rotation resulted from N fertilizer input and returning of crop residues to the soil. In Brazil, Ultisols with moderate clay contents had higher SOC stock in 0–100 cm under 35-year-old rubber tree plantation than that in secondary forest [16]. Accumulation of SOC in Ultisol soils was more pronounced in 0–40 cm soil depth than in the subsoils in which the accumulation of SOC decreased from 40 downward to 100 cm. Another study in Brazil on land use affecting SOM was that of coconut orchard treated with chemical-organic fertilizer application, leguminous cover crops, and mulching compared with forest soil. The coconut soil had higher SOM in 0–30 cm depth than the native forest soil [17]. In addition, surface soil layer (0–10 cm) from coconut field had higher SOM than in lower soil layer (10–30 cm).

Most of the earlier studies have focused on investigation of changes in SOM contents under land use changes in topsoil (0–20 cm) only. There were few studies focusing on SOM accumulation in soil profile (0–100 cm) under different land uses. Conversion from forest (close nutrient cycling system) to various crop cultivations (open system) with different agricultural practices alter soil processes involved in SOM formation and accumulation in topsoil and subsoil layers (>20–100 cm soil depth) of sandy soils.

Sandy soils cover a large area of Maha Sarakham province in the Northeast of Thailand, which was accounted for 35.6% (188,361 ha) of total area of this province. They are low fertility soils. The land of the province used to be predominantly covered by the dry dipterocarp forest dominated by various dipterocarp tree species. Conversion of forests to agricultural land has been carried out for close to, or in some areas more than, a century [18]. Paddy rice, cassava, and sugarcane are the most important major crops in this region. Dynamics of SOM under these rice paddy and upland crop systems are inherently different. Paddy soils are under periodically anaerobic conditions, while field crop soils (e.g., cassava and sugarcane) are totally under aerobic conditions [19]. Moreover, there were different agricultural practices among the land uses and different locations in this province. Conversion from forests to agricultural lands of various types is likely to affect the process of SOM formation and accumulation differently in top-subsoils. In this study, we hypothesized that land use change from forest to cropland reduces SOM stock in soil profile. We further hypothesized that patterns of SOM distributions among agricultural land uses are different since selected locations had different agricultural practices and soil textures. In order to test this hypothesis, we examined stocks of SOM in the soil profile (0–100 cm) as influenced by land use changes in the selected locations.

2. Materials and Methods

2.1. Study Locations

Six study locations were in six districts of Maha Sarakham province in the Northeast of Thailand. These districts including Muang, Kantharawichai, Kosum Phisai, Kut Rang, Borabue, and Wapi Pathum were selected for this study (Figure 1). Each location had four land uses, including secondary dry dipterocarp forest, and three agricultural land uses, cassava converted from the forest for five years, sugarcane converted from the forest for seven years, and rice paddy lands converted from the forests for more than 15 years. These land use plots in each location were located adjacent to each other.

The paddy fields are mostly situated at the lowest topographic positions in comparison to the other land uses (Table 1). Deciduous dipterocarp species were dominant trees in all locations for the forest land use in this study. Information obtained from interviews with the farm owners showed that agronomic practices for cassava, sugarcane, and paddy were different among locations (Table 1). Burning of rice stover and sugarcane leaves was practiced in the years that the rice stover and sugarcane leaves were excessive. However, cassava leaves were never burned. The fertilizer rates applied to the crops were provided in ranges based on estimates by farmers at each location (Table 1).


Study locationLand use typeSampling area (ha)Altitude (masl)/1Agricultural practices

MuangForest6192/2Secondary dry dipterocarp forest.
Cassava3193/3Cassava (Kasetsart50 or KU50 variety) was cultivated yearly in the early rainy season (May to June). Nitrogen fertilizer, urea (46–0–0), was applied to the crop at the rate of 113 kg·ha−1 at planting and fertilizer formula 15–15–15 of N–P2O5–K2O at the rate of 313 kg·ha−1 was applied three months after planting (MAP). The crop was harvested from March to May of the following year.
Sugarcane3198/4Sugarcane KK3 variety was cultivated yearly in the late rainy season from October to February. Fertilizer formula 15–15–15 of N–P2O5–K2O was added to the crop in two split applications at planting and 4 to 6 MAP. Cattle manure was also added in some years.
Paddy5174/5Glutinous rice (RD6 variety) and nonglutinous rice (KDML 105 variety) were cultivated yearly by transplanting seedlings in June. Urea (46–0–0) was applied to the crop at the rate of 150–180 kg·ha−1 at planting and fertilizer formula 16–16–8 of N–P2O5–K2O was applied at the rate of 125–156 kg·ha−1 at the tillering stage. The crop was harvested during November to December.

KantharawichaiForest6157/2
Cassava3159/3
Sugarcane3154/4Cattle manure was added in every single year before sugarcane plantation.
Paddy5156/5

Kosum PhisaiForest6190/2
Cassava3190/3
Sugarcane3189/4
Paddy5182/5

Kut RangForest6203/2
Cassava3198/3
Sugarcane3195/4
Paddy5198/5

BorabueForest6185/2
Cassava3181/3
Sugarcane3186/4Cattle manure was added in some years.
Paddy5174/5

Wapi PathumForest6185/2
Cassava3186/3Green and cattle manures were applied before cassava planting in some years.
Sugarcane3182/4Cattle manure was added in some years.
Paddy5182/5

/1 = meters above sea level.
2.2. Sampling Procedures

All locations had four land uses including forest, cassava, sugarcane, and rice paddy. These land use plots were located adjacent to each other. The areas for sampling ranged from 6 ha for the forest, 3 ha for cassava, 3 ha for sugarcane, and 5 ha for paddy (Table 1). The study sites encompassed five soil series all of which were coarse textured including Nam Phong, Khorat, Ubon, Roi Et, and Satuk. Soil characteristics are shown in Table 2.


Soil seriesSoil classification/4Soil depth (cm)Particles (%)Texture
SandSiltClay

Nam Phong/1Grossarenic Haplustalfs0–2090.96.52.6Sand
20–4090.96.52.6Sand
40–6091.22.16.7Sand
60–8091.22.16.7Sand
80–10091.22.16.7Sand

Khorat/2Typic (oxyaquic) Kandiustults0–2079.313.57.2Loamy sand
20–4077.511.411.1Sandy loam
40–6074.916.78.4Sandy loam
60–8067.120.112.8Sandy loam
80–10057.719.922.4Sandy clay loam

Ubon/2Grossarenic Haplustalfs0–2072.619.48.0Sandy loam
20–4069.218.012.8Sandy loam
40–6061.522.516.0Sandy loam
60–8065.021.413.6Sandy loam
80–10059.221.019.5Sandy loam

Roi Et/2Aeric Kandiaquults0–2073.916.99.2Sandy loam
20–4074.912.312.8Sandy loam
40–6075.511.313.2Sandy loam
60–8070.813.615.6Sandy loam
80–10066.312.312.4Sandy loam

Satuk/3Typic Paleustults0–2080.10.719.2Sandy loam
20–40N/AN/AN/AN/A
40–60N/AN/AN/AN/A
60–80N/AN/AN/AN/A
80–100N/AN/AN/AN/A

/1Toung et al. [20]; /2Saenya et al. [21]; /3Kaweewong et al. [22]; /4Soil Survey Staff [23]. N/A: not available.

Soil sampling was done at nine positions for each land use at each location. This brought about 36 positions for four land uses in each location and 216 positions in total for six locations. Soil samples were collected in the dry season in March 2018 using an auger. The soil sample of each position was divided into five soil layers at 20 cm intervals from 0 to 100 cm. There were 1,080 samples altogether. Each soil layer from three of the nine sampling positions situated in the same contour line was mixed into a single pile. Therefore, there were three replications based on contour lines in each land use which brought the total number of samples down to 360. The soil samples were air-dried and passed through a 2 mm sieve. Laboratory analysis of SOM content for each soil sample was done in duplicate.

2.3. Soil Analysis

Soil samples were analysed to determine SOM content using a wet oxidation method [24]. This method used potassium dichromate (K2Cr2O7) as the oxidizing agent with external heat and back titration to measure the amount of unreacted dichromate.

Corrections were made for the calculated soil SOM stock by comparing the soil mass [25, 26] from the agricultural land use with the mass from the original forest land use, both at 100 cm, according towhere Mf (g·cm−3) is the mean soil bulk density of the forest soil at a given depth, Mm (g·cm−3) is the mean soil bulk density for each studied layer after forest conversion at the same depth. After the equivalent soil layers were corrected, the stock of SOM (Sm) was calculated by

2.4. Climate and Temperature during the Experiment Periods

Average monthly precipitation and temperature over the soil sampling periods (July 2017–June 2018) are presented in Figure 2. The climate data were provided by the north–eastern meteorological center in Maha Sarakham province. The distribution of average monthly rainfall and temperature of the study sites were similar in which there was a precipitous drop in both climatic parameters during November–February period. The precipitation was the highest during July–October.

2.5. Statistical Analysis

The statistical design for analysis of variance was general ANOVA with three factors including location (six levels), land use (four levels), and soil layer (five levels) and three replications. Data were analysed statistically using Statistix 8.0 software (Analytical Software, Tallahassee, FL, USA). The data were adjusted for normal distribution. Individual analysis of variance was first performed for each location. The error variances were compared for variance homogeneity. Because error variances were homogenous, combined analysis of variance was performed for all locations across location, land use, and soil layer. Means were also compared by the least significant difference (LSD).

3. Results and Discussion

3.1. Bulk Density and Soil Moisture Content

Data for soil bulk density are presented in Table 3. Most locations had several soil series except for Kosum Phisai and Wapi Pathum in which Khorat and Ubon soil series, respectively, were the only one found in all land uses of the respective locations.


LocationLand use typesSoil seriesBulk density (g·cm−3)
Soil depth (cm)
0–2020–4040–6060–8080–1000–100

MuangForestNam Phong1.601.501.491.541.551.54
CassavaNam Phong1.581.561.511.621.491.55
SugarcaneRoi Et1.501.631.571.561.621.58
PaddyRoi Et1.691.681.761.781.871.76

Mean1.591.591.581.631.63

KantharawichaiForestKhorat1.551.611.591.581.591.58
CassavaNam Phong1.541.591.631.591.601.59
SugarcaneRoi Et1.631.571.751.601.711.65
PaddyRoi Et1.621.831.701.771.871.76

Mean1.591.651.671.641.69

Kosum PhisaiForestKhorat1.441.341.401.451.471.42
CassavaKhorat1.491.521.491.511.651.53
SugarcaneKhorat1.441.491.561.581.751.56
PaddyKhorat1.621.671.601.611.631.63

Mean1.501.511.511.541.63

Kut RangForestNam Phong1.591.511.511.511.511.53
CassavaNam Phong1.501.651.591.741.731.64
SugarcaneUbon1.511.541.611.491.631.56
PaddySatuk1.711.591.561.871.631.67

Mean1.581.571.571.651.63

BorabueForestKhorat1.611.501.431.541.581.53
CassavaKhorat1.581.781.601.531.561.61
SugarcaneRoi Et1.551.581.551.951.841.69
PaddyRoi Et1.561.601.581.631.721.62

Mean1.581.621.541.661.68

Wapi PathumForestUbon1.641.641.651.581.511.60
CassavaUbon1.541.571.601.701.721.63
SugarcaneUbon1.431.471.501.561.611.51
PaddyUbon1.571.641.601.661.781.65

Mean1.551.581.591.631.66

The data were from one replication.

Soil bulk densities in the range of 1.34 to 1.87 g·cm−3 were observed across locations, land uses, and soil depths (Table 3). Soil bulk densities of all soil layers for Muang, Kantharawichai, and Kosum Phisai were higher in the paddy land use than the forest and upland crops land uses, whereas soil bulk densities for Kut Rang, Borabue, and Wapi Pathum did not show consistent patterns. Soil bulk densities showed trends of increase with soil depth for all locations although there were some inconsistencies, for example, in cassava land use in Kut Rang and in sugarcane land use in Borabue.

In a previous study, soil bulk density was highly and negatively correlated with intensity of land use [27]. Croplands have intensive agricultural practices [27] which can cause high soil bulk density while forest land use incurs little soil disturbance. The results, especially for Muang, Kantharawichai, and Kosum Phisai in this study, supported the previous finding. However, the results for Kut Rang, Borabue, and Wapi Pathum did not follow similar pattern and other factors may be more influential than agricultural practices. Water runoff in the rainy season may remove soil surface and increase soil bulk density in forest soil [28]. High frequency of fire in the dry season also reduces SOM in forest soil [29] and, thus, increases soil bulk density.

Soil bulk density is an important parameter for determining overall soil quality or soil health as it is associated with SOM and acidity [30, 31]. Furthermore, it is dependent on soil texture [32] and degree of soil compaction [33]. That is, coarser textured soils have higher bulk density than finer textured ones.

Soil moisture contents ranged between 0.66 and 21.16% across locations, land uses, and soil depths (Table 4). The patterns of changes in soil moisture contents across land uses and soil depths were much clearer than those of soil bulk density. The pattern across land uses showed that soil moisture contents of forest soils were consistently substantially lower than those of the agricultural soils, especially paddy soils in all locations. Evapotranspiration in forest soil was higher than in agricultural soils because of the higher density of natural vegetation and deeper root systems [34]. Furthermore, agricultural lands, especially paddy land, were located at lower altitudes indicating their higher water table than the forest land. The other pattern of soil moisture content changes was that along soil depth; that is, they increased with soil depth, which was found in all land uses.


LocationLand use typeSoil moisture (%)
Soil depth (cm)
0–2020–4040–6060–8080–1000–100

MuangForest1.571.411.802.413.012.04
Cassava1.201.271.929.6210.184.84
Sugarcane1.451.121.272.215.552.32
Paddy4.155.0510.7911.2211.328.51

Mean2.092.213.956.377.52

KantharawichaiForest3.952.923.333.944.283.68
Cassava10.603.852.265.075.605.48
Sugarcane5.506.604.897.7411.117.17
Paddy6.599.6413.0614.4013.9211.52

Mean6.665.755.897.798.73

Kosum PhisaiForest0.961.820.961.922.781.69
Cassava4.645.265.407.6815.987.79
Sugarcane4.135.746.109.4013.737.82
Paddy3.957.578.8711.1721.1610.54

Mean3.425.105.337.5413.41

Kut RangForest0.660.830.870.990.850.84
Cassava4.017.147.5612.9616.339.60
Sugarcane0.852.0710.916.1012.096.40
Paddy4.854.914.3913.8912.1310.03

Mean2.593.748.438.4910.35

BorabueForest1.381.432.157.977.834.15
Cassava1.376.356.727.337.115.78
Sugarcane4.733.473.5411.5812.277.12
Paddy1.171.974.649.4214.236.29

Mean2.163.314.269.0810.36

Wapi PathumForest2.265.075.474.79.845.47
Cassava5.063.7113.0718.3318.8011.79
Sugarcane7.128.029.2911.1514.5210.02
Paddy2.237.0716.3619.6617.4612.56

Mean4.175.9711.0513.4615.16

The data were from one replication.

In an earlier study, soil moisture content was found to be positively and significantly correlated with SOC [35]. Decomposition rates of SOM increased in aerobic condition relative to submerged conditions [36]. Anaerobic (soil water logged) condition reduced SOM decomposition rates due mainly to low soil oxygen [37]. Therefore, SOM in paddy land is better conserved than in other land use systems because it has a more extended wet period. However, forest land can conserve rainwater in the rainy season and reduce runoff as it had high natural vegetation cover.

3.2. Changes in Soil Organic Matter Stock across Locations, Land Uses, and Soil Depths

Three analyses of variance were performed for SOM stocks (Table 5). Analysis 1 was carried out for one soil depth (0–100 cm). Analysis 2 was carried out for two soil depths (0–20 and 20–100 cm), and analysis 3 was carried out for five soil depths at 20 cm intervals. All analyses showed significant differences among locations for SOM stocks, and the differences among land uses were also substantial. The difference between topsoil and subsoil was substantial and the differences among soil layers were also significant for SOM stocks.


Source of variationDegree of freedomMean squareF-ratio

(a) One soil depth (0–100 cm)
Location530493.50195.14
Land use type310480.4028.16
Location × land use type156533.7017.56

Error36372.10

(b) Two soil depths (0–20 and 20–100 cm)
Location515246.60195.17
Land use type35240.1047.37
Soil depth/1131368.50283.56
Land use type × soil depth/131232.3011.14
Location × soil depth/152737.9029.53
Location × land use type153266.9024.75
Location × land use type × soil depth/1151627.4014.71

Error84110.60

(c) Five soil depths (0–20, 20–40, 40–60, 60–80, 80–100 cm)
Location56098.70194.99
Land use type32096.3077.28
Soil depth/2428746.701059.78
Land use type × soil depth/212653.3024.08
Location × soil depth/2201224.9048.17
Location × land use type151306.8045.15
Location × land use type × soil depth/260292.0010.77

Error22827.10

Significant difference by LSD ().

All primary level interactions (location × land use, location × soil depth, and land use × soil depth) were significant for SOM stocks, and the secondary level interaction (location × land use × soil depth) was also significant. F–ratios indicated that soil depth was the greatest source of variation followed by location and land use, respectively, whereas the variations due to interactions were rather small. The significant interactions are important for the evaluation of SOM.

Across six locations, land uses for cassava, sugarcane, and rice paddy had significantly lower SOM stocks than undisturbed forests (Table 6). The finding of higher SOM stock in forest soil than the other agricultural soils is similar to many previous works [4, 811] which was likely due to the accumulation and decomposition of litter input from forest vegetation. Litterfall and remaining residues on soil surfaces are brought about high SOM stock in the forest soils [14]. In other studies, high input of surface litter led to high SOM accumulation in the topsoil horizon [14, 38].


Land use typesSoil depths
1a2b5c

Forest192.80A (–)96.43A (–)38.57A (–)
Cassava142.30C (–26%)71.15C (–26%)28.46B (–26%)
Sugarcane172.40B (–11%)86.24B (–11%)34.49C (–11%)
Paddy144.64C (–25%)72.32C (–25%)28.93C (–25%)
CV (%)33.1112.9015.27

Means in the same column followed by the different uppercase letters are significantly different by LSD (). aOne soil depth (0–100 cm); btwo soil depths, including topsoil (0–20 cm) and subsoil (20–100 cm); cfive soil depths, including 0–20, 20–40, 40–60, 60–80, and 80–100 cm.

Not only higher litter input but also less removal in forest (close system) compared to agricultural fields (open system). For the latter system, organic residues in the form of harvested products are removed from the fields, which contributes to lower SOM content agricultural than forest soils.

The land for sugarcane had significantly higher SOM stock than those for cassava and rice paddy, and the reduction in SOM stock accounted for 11% compared to the forest land (Table 6). The lands for rice and cassava were similar in SOM stock, and the reductions in SOM stock accounted for 25 and 26%, respectively, compared to the forest land. Cultivated lands had lower SOM stock as indicated by lower mineralizable C and N than a forest land [30]. We had assumed that the highest reduction in SOM stock was in paddy land followed by sugarcane and cassava. This is because the periods of conversion were longest for rice paddy, intermediate for sugarcane, and the shortest for cassava. The results did not positively prove this assumption. It is plausible that the differences in agronomic practices were influential in affecting the changes in SOM stock after the conversion of forest to agricultural lands.

Cassava and rice paddy are annual crops, while sugarcane is a perennial crop based on its widely practiced ratoon crop cultivation of two or more crops after harvesting of the original planted crop. Therefore, soil under sugarcane is less disturbed than rice and cassava. Rice paddy soils showed a trend of having lower degradation than their cassava counterpart (Table 6) though the former had longer establishment than the latter system. Low degradation in paddy soil is due to anaerobic conditions during the wet season that reduced SOM decomposition [39]. Organic materials from higher lying areas (i.e., cassava and sugarcane fields and forest) are washed down in surface runoffs to accumulate in lower areas particularly in the rainy season, resulting in higher SOM stock in the lower-lying paddy land. Although paddy soil in some locations had higher clay contents (Roi Et and Satuk soil series), SOM stocks under paddy soils were not significantly different from upland soils (e.g., cassava and sugarcane land uses). In addition, paddy land could maintain higher SOM stock than the upland crop fields because of rice straw remaining in the fields, while the residues of cassava and sugarcane were removed from the fields after harvest.

The results of SOM stocks were further analysed to consider details of each location, land use, and soil depth (Sections 3.2.1 and 3.2.2).

3.2.1. Soil Organic Matter Accumulation in Topsoil (0–20 cm) and Subsoil (20–100 cm)

Stocks of SOM in topsoil and subsoil were significantly different not only among the different land uses, but also among the different study locations (significant interaction, Table 5). Figure 3 compares SOM accumulation in topsoil (0–20 cm) and subsoil (20–100 cm) in each land use and among land uses. The results did not show a consistent pattern of SOM accumulation in all land uses across locations. For example, in the forest, SOM stock in topsoil was higher than subsoil at one location (Muang), similar to subsoil at two locations (Kosum Phisai and Wapi Pathum) and lower than subsoil at three locations (Kantharawichai, Kut Rang, and Borabue).

Soil OM is the fraction of the soil consisting of plant or animal tissue in various stages of decomposition [40]. Theoretically, SOM accumulates largely in topsoil because it directly receives input from organic litter [41]. According to Esmaeilzadeh and Ahangar [42], SOM dynamics are influenced by different ecosystem properties in each soil layer. Therefore, SOM in topsoil can be similar to or lower than in subsoil for many reasons including the higher stabilization of SOM in lower soil layers with higher clay content [43], water erosion [44], soil moisture content [45], and soil texture [46]. For instance, in the current study, movement of SOM from a topsoil with lower clay content to a subsoil with higher clay content leads to SOM accumulation in the subsoil as seen by high SOM stock at the subsoil in all study locations, with the exception of Kosum Phisai location (Figure 3).

When topsoil and subsoil were compared across land uses, higher topsoil SOM stock than subsoil was found only in the forest soil in Muang (, Figure 3(a)). Topsoil SOM stocks were lower than subsoil in the other 13 land uses, consisting of three forests (Kantharawichai, Kut Rang, and Borabue), five cassavas (Muang, Kantharawichai, Kut Rang, Borabue, and Wapi Pathum), three sugarcanes (Kut Rang, Borabue, and Wapi Phatum), and two paddy fields (Kantharawichai and Wapi Pathum) (). Topsoil SOM stocks were comparable to subsoil for 10 land uses, including two forests (Kosum Phisai and Wapi Pathum), one cassava (Kosum Phisai), two sugarcanes (Muang and Kosum Phisai), and five paddy fields (Muang, Kantharawichai, Kosum Phisai, Kut Rang, and Borabue) ().

It is interesting to note here that topsoil had rather high SOM accumulation in forest soil, and it was rather low in agricultural soils in Muang and Kosum Phisai (Figures 3(a) and 3(c)). The differences were most pronounced under cassava fields. High SOM in the topsoil of forest soil has been reported in different regions [46, 47]. Decomposition of litterfall and fine root on soil surfaces enhances SOM in forest topsoils [15].

It is also worth mentioning that the subsoils had significantly higher SOM than the topsoils across most land uses (13 land uses) with exception of only one case, that is, the forest land use of Muang. The high SOM in subsoil was likely due to the movement of SOM from coarser textured topsoil to finer textured subsoil with higher clay content. The clay can adsorb and conserve SOM. As soil is a sink for C and N [48], the movement of SOM or SOC from topsoil to subsoil could reduce C and N emission to the atmosphere as CO2, CH4, and N2O [49]. Assefa et al. [7] reported that SOM sequestration in subsoil accounted for 40% of total SOM in 0–50 cm soil depth. According to Rumpel and Kögel-Knabner [50] and Deng [51], the interaction of OM with soil mineral surfaces led to stabilization of OM in subsoil horizons. Soil OM is preferentially associated with clay in the subsoil, which generally has high clay particles [52]. The interaction of SOM with clay mineral is a reason to store SOM in the subsoils which contain high clay content [53].

Rice paddy was more comparable to forests for SOM accumulation in topsoil. Soil OM under the forests and rice paddies were mainly derived from leaf litter and rice stubbles, respectively. The results in this study were similar to those in previous reports [7, 8, 10].

3.2.2. Soil Organic Matter Stock in the Whole Soil Profile down to 100 cm Depth

Stocks of SOM in soil profile (0–100 cm) were not only significantly different across the different land uses, but also across the different study locations (significant interaction, , Table 5). Three of six forest soils including Kosum Phisai, Kut Rang, and Borabue had higher SOM in the whole soil profile (0–100 cm) than agricultural soils () (Figures 4(c)4(e)). Forest and sugarcane soils were not significantly different for SOM stocks at Muang and Kantharawichai locations, but they were higher than paddy and cassava soils (Figures 4(a) and 4(b)). Soil OM stock in cassava soil was the highest at Wapi Pathum location followed by sugarcane, forest, and paddy soils, respectively, and SOM stocks in all land uses were significantly different () (Figure 4(f)).

The authors compared SOM stock in the whole soil profile to gain an overview of effects of the changes in land use on SOM stock. Forest soil was still the prominent land use type that could maintain high SOM stock in most locations. The lower SOM stock in Wapi Pathum location could be due to several factors that reduced SOM stock in forest soil there. One outstanding feature was high soil bulk density at 0–60 cm depth (Table 3) indicating soil compaction which could result in low soil aeration and low activity of microorganisms for organic material decomposition.

Sugarcane soil showed a trend of having higher SOM stock than cassava and paddy soils in five out of six locations. Sugarcane has deep fibrous root system which permeates widely and deeply in soil. It is also a ratoon crop that can be harvested more than one time after planting which lessen soil disturbance due to annual planting. On the other hand, cassava and rice are annual crops which entail more frequent soil disturbance at planting than sugarcane. Soil disturbance through plowing lower SOM content as it breaks soil aggregate thereby lessens physical protection of SOM [5456] and increases microbial activities through increasing aeration [54]. Cassava agronomic practices involve removal of plant-derived organic materials from the fields including harvestable products, that is, tubers, and planting materials for the next growing season, that is, aboveground stems to be used as cuttings. Sugarcane produced higher leaf litter fall than cassava as shown by an earlier similar study [10].

Although paddy soil had the longest period since land use change from forest to agriculture had taken place, the SOM in paddy soil was still high compared to soils under the upland crops, which had shorter durations since the land use conversion. Paddy soil in these areas had higher clay contents than upland soils. Soil OM is preferentially adsorbed to clay, resulting in high SOM in paddy soil as compared to other land uses. According to Christensen [57] and Six et al. [58], clay was quantitatively more effective in sequestering SOM than sand.

Additionally, soils rich in silt and clay contents had high SOM accumulation, and clay also had a positive correlation with SOM accumulation [7, 59]. Also, the remaining rice stubble is an input to SOM formation and accumulation in the paddy soil in the current study. Input of surface residues and dense root system contributed to a large amount of SOM in A horizon (topsoil) [57, 60]. Furthermore, topographic position of paddy fields at lower-lying areas than forest and upland fields is conducive to receiving deposits of sediments and organic materials from the upper areas as found earlier by Tangtrakarnpong and Vityakon [10].

Considering stocks of SOM in each of the five soil layers, they were significantly different among all land uses and all study locations. In addition, the location x land use x soil depth interaction was also significant (, see (c) in Table 5). When considering each soil layer (Figure 5), topsoil layer (0–20 cm) had higher SOM stocks than each deeper soil layer in all locations (). Forest soils in all locations except Borabue had high SOM accumulation in topsoils than subsoils due to high litter input which enhanced SOM stocks in forest topsoils in Muang, Kantharawichai, Kosum Phisai, and Wapi Pathum locations (Figure 5). Meanwhile, in sugarcane land use in Kantharawichai location, incorporation of cattle manure to soil every single year before sugarcane plantation (Table 1) brought about high SOM stocks in topsoil (Figure 5(b)). Similar to the forest, paddy had higher SOM accumulation in topsoils than subsoils in all locations except Wapi Pathum (Figure 5) which was due to input of rice stubbles remaining after harvesting. The results of this study supported previous findings that high accumulation of SOM was in the topsoil [58, 61]. However, it was found in forest and paddy land uses in Borabue and Wapi Pathum, respectively, that SOM stocks in topsoils were not different than subsoils (Figures 5(e) and 5(f)). Soil texture of the mineral horizon, that is, horizon below top organic horizon (topsoils), has been found to influence SOM distribution and SOM stock in the lower soil layer. Finer textured subsoil layers as indicated by higher content of fine fraction (<0.05 mm or silt + clay) led to higher accumulation of soil organic C in subsoil (mineral horizon) than the coarser textured counterpart [62].

Considering pattern of changes in SOM stocks of each soil layer, we found a uniformly SOM decline pattern with soil depth at all locations. The declines in SOM stocks with reference to the upper layer were larger in the second soil layer (20–40 cm), whereas those in the deeper soil layers were smaller. Nevertheless, at Wapi Pathum location cassava and sugarcane fields did not show the declines in SOM stocks in the soil layer below the second soil layer (20–40 cm). The Wapi Pathum location had applications of cattle manure in the upland crop fields (Table 1) which could have enhanced the subsoil SOM stocks. The application of manure at high rate could increase SOM stock in the subsoil to the levels similar to that in topsoil [63, 64].

Soil depth is an important factor influencing the variation in SOM [49], and lower soil layers have been found to contribute to longer term storage of C than topsoils as the loss of soil C in lower soil layers is less than their upper layer counterpart [65, 66].

4. Conclusions

Our results have shown conclusively that land use exerted significant influence on SOM stocks in soil profiles. Forest land use had significantly higher total SOM stocks in 0–100 cm (193 Mg·C·ha−1) than agricultural land uses (142–172 Mg·C·ha−1), including cassava, sugarcane, and paddy fields in all studied locations. General pattern of SOM stock distribution in soil profiles was such that the SOM stock declined with soil depth. This is due to deposition of organic materials and their decomposition in topsoils which was partly transported to be stabilized in the finer textured (higher clay and silt contents) subsoils. However, agricultural practices, notably applications of organic materials, such as cattle manure, could increase subsoil SOM stock as found in some agricultural land uses (cassava and sugarcane in Wapi Pathum) in our study. Although SOM stocks decreased with depth, the subsoil stock contributes to longer term storage of C than topsoils as they are more stabilized than those of the topsoils. We have shown that soil degradation as indicated by reduced SOM takes place when forest is converted to agricultural land use. Appropriate use of land and agronomic practices are important to maintain high soil fertility and high crop productivity. These involve application of organic soil amendments and reduction of soil disturbance to increase and maintain SOM stock. Upland agricultural land uses, notably cassava, cause high rate of soil degradation and need to be urgently restored by higher and more frequent applications of organic amendments, returns of crop residues, and reduction of soil disturbance.

Conflicts of Interest

The authors declare that there are no conflicts of interest regarding the publication of this article.

Acknowledgments

This research was financially supported by Mahasarakham University 2018 and the Soil Organic Matter Management Research Group, Khon Kaen University.

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