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Article

Biotic and Abiotic Factors Affecting Soil C, N, P and Their Stoichiometries under Different Land-Use Types in a Karst Agricultural Watershed, China

by
Gang Hu
1,2,3,
Xiaoxing Huang
2,3,
Siyu Chen
1,
Cong Hu
1,
Chaofang Zhong
1,
Chaohao Xu
1 and
Zhonghua Zhang
1,2,3,*
1
Key Laboratory of Wildlife Evolution and Conservation in Mountain Ecosystem of Guangxi, Nanning Normal University, Nanning 530100, China
2
Key Laboratory of Environment Change and Resources Use in Beibu Gulf, Nanning Normal University, Ministry of Education, Nanning 530100, China
3
Guangxi Key Laboratory of Earth Surface Processes and Intelligent Simulation, Nanning Normal University, Nanning 530100, China
*
Author to whom correspondence should be addressed.
Agriculture 2024, 14(7), 1083; https://doi.org/10.3390/agriculture14071083
Submission received: 17 May 2024 / Revised: 27 June 2024 / Accepted: 1 July 2024 / Published: 5 July 2024
(This article belongs to the Section Agricultural Soils)
Browse Figures
Versions Notes

Abstract

:
Comprehending the impacts of land-use type on soil nutrition and stoichiometry in watersheds is crucial for effective regional ecosystem management. However, a deeper understanding of the influence of land-use type on soil stoichiometry in karst agricultural watersheds is still lacking. Here, we analyzed the contents, stoichiometries, and drivers of topsoil C, N, and P in a karst agricultural watershed in China, focusing on six land-use types: paddy fields, dry farmland, tussock land, shrubland, shrubby tussock land, and woodland. We found that woodland exhibited significantly higher soil organic carbon (SOC) content than other land-use types except shrubland. Moreover, woodland exhibited the highest total nitrogen (TN) and total phosphorus (TP) contents compared with other land-use types. C/N and N/P ratios did not vary significantly with land-use type, whereas dry farmland (18.68) showed a significantly lower C/P ratio than woodland (39), shrubland (39.92), and paddy fields (34.87). In addition, our results revealed that soil pH, catalase and invertase activity, and bacterial and actinomycetes abundance significantly influenced C, N, and P content and stoichiometry. These findings reveal that interactions between multiple biotic and abiotic factors drive variability in soil stoichiometry, offering valuable insight for land improvement and ecological management in karst agricultural watersheds.

1. Introduction

Soil plays a pivotal role in material cycling, energy flow, and information exchange within terrestrial ecosystems, thereby regulating vegetation structure, diversity, and productivity, and influencing the functioning of ecosystem services [1,2]. C, N, and P are essential elemental components of ecosystems; their levels affect enzyme and microbial activity in the soil, exert important impacts on soil reclamation, and promote vegetation growth and development [3,4,5]. Their contents and stoichiometries serve as crucial indicators for evaluating soil nutrient supply, organic matter decomposition rates, and nutrient limitations, reflecting C, N, and P cycling between the vegetation and soil, which is essential for maintaining soil quality, promoting ecosystem health, and sustaining biogeochemical cycles [6,7,8]. However, soil C, N, and P are highly susceptible to transport via erosion processes such as splash and runoff, resulting in problems such as water eutrophication and soil nutrient loss; soil C stock reduction promotes greenhouse gas emission from organic C, exacerbating the greenhouse effect [9].
Land-use change is a globally important issue with substantial impacts on agriculture, ecosystems, and the atmosphere [10]. It arises from both natural changes in the landscape and human activity and can alter soil physicochemical properties, substantially affecting soil nutrient content, microorganisms, and enzyme activity [11,12,13]. The conversion of forest to arable land has reportedly led to a notable decline in soil organic carbon (SOC) and total nitrogen (TN), an increase in total phosphorus (TP), and variable reductions in C/N, C/P, and N/P ratios [14]. On the Loess Plateau, land-use type significantly affects soil physicochemical properties, microbial biomass, and soil enzyme activity [12]. It significantly impacts soil C, N, and P contents and their stoichiometric ratios [15,16,17], suggesting that C/N/P stoichiometry can reflect the intensity of soil material cycling and transformation.
Soil C, N, and P contents and their stoichiometries are influenced by soil physicochemical properties (such as pH, moisture content, and bulk density), land-use type, climate change, topography (rocky outcrop rate, slope, and elevation), soil microorganisms (such as fungi, actinomycetes, and bacteria), and soil enzymes (such as catalase, invertase, and urease) [18,19,20,21,22,23]. While substantial progress has been made in understanding the effects of diverse land uses on soil C, N, and P contents and their stoichiometric ratios, these studies have focused predominantly on non-karst regions, with few addressing these dynamics for the karst region of southwestern China.
Karst represents a unique geographic landform. The karst region of southwestern China, which exemplifies rocky desertification, represents an important aggregation of carbonate rock with extensive karst features [24]. In karst regions, human activity is increasingly causing rocky desertification, which is aggravated by the fact that the karst comprises soluble carbonate rock. This has resulted in intensified soil erosion, diminished soil fertility, and a substantial reduction in biodiversity, leading to serious ecological and environmental issues [21]. Therefore, vegetation restoration and the prevention of rocky desertification are urgently required in karst regions of China. Over the past three decades, projects such as the Karst Rocky Desertification Restoration Project and Natural Forest Protection Project have been successively implemented, and preliminary results have been published [25,26,27,28,29], revealing that adjusting land use improves soil properties and quality, while also enhancing the level of control over soil erosion and rocky desertification.
The Chengjiang Watershed (Guangxi, China) is a typical karst agricultural watershed characterized by a unique habitat and a delicate ecological environment [30]. Owing to its geology and intense karst processes, the soil in this area forms slowly, leading to shallow and fragmented layers and rapid hydrological processes [31]. The vegetation is highly sensitive to human disturbance, making recovery after damage difficult. Spatial variation in meteorological and hydrological factors, combined with prolonged unsustainable land use and excessive cultivation by the inhabitants, have severely compromised the stability of this watershed ecosystem, leading to widespread vegetation degradation, extensive rock exposure, intensified soil erosion, increased water and soil loss, the continuous exacerbation of rocky desertification, and other ecological issues [32]. To address these factors for the Chengjiang Agricultural Watershed, we examined the effects of six land-use types (woodland, shrubland, shrubby tussock land, tussock land, dry farm, and paddy fields) on topsoil C, N, and P contents and their stoichiometric ratios. The objectives of the present study were to: (1) analyze the differences in soil C, N, and P contents and their stoichiometric ratios among different land-use types; and (2) explore the biotic and abiotic factors influencing soil C, N, and P contents and their stoichiometric ratios in the Chengjiang Agricultural Watershed.

2. Materials and Methods

2.1. Study Area

This study was conducted in the Chengjiang Agricultural Watershed in Duan County, Guangxi, southwestern China (23°48′48″–25°24′30″ N, 107°46′19″–108°18′50″ E; Figure 1). This serves as a representative region for controlling karst desertification and restoring ecosystems in southwestern China. The watershed covers an area of 986 km² and is 41 km long. The terrain exhibits distinct karst landforms, including peak-cluster depressions, peak-cluster valleys, and river valleys. The average annual temperature is 19.6 °C and average annual precipitation ca. 1700 mm. Rainfall is unevenly distributed in space and time, with most rainfall (ca. 80%) occurring between May and August. Geologically, it comprises primarily Permian and Triassic carbonate, with continuous limestone as the main parent rock. The dominant soil type is limestone soil, with a dense and sticky texture lacking a granular structure. According to the Chinese Soil Taxonomy, it can be further subdivided into the brown limestone soil subclass, which has properties that fall between those of the red limestone and black limestone subclasses, exhibiting either no liming reaction or only a weak one [33]. In contrast, the World Reference Base for Soil Resources (WRB) classification system classifies this soil as a Calcisol, characterized by a significant accumulation of calcium carbonate in the subsoil [34]. Typically, the soil pH exceeds 6.5. The vegetation in the study area is diverse, comprising secondary forests, shrubs, shrubby tussocks, and tussock land, predominantly comprising species accustomed to calcareous and drought-tolerant conditions. The study area encompasses six main land-use types: woodland, shrubland, shrubby tussock, tussock, dry farmland, and paddy fields. The vegetation in the first four types are in various stages of natural recovery following anthropogenic disturbances. The woodland is a secondary forest with a community height of 8–10 m and a canopy coverage of 85% and dominant tree species include Choerospondias axillaris, Radermachera sinica, Toona sinensis, and Picrasma quassioides. The shrubland is dominated by shrubs such as Pterolobium punctatum, Vitex negundo, and Alchornea trewioides, which typically reach a height of 3–4 m and have high coverage (about 73%). Shrubby tussocks are a transitional type of land between shrubland and tussocks, and in the study area features a mix of shrub species such as Vitex negundo and Alchornea trewioides, as well as herbaceous plants like Miscanthus floridulus and Bidens pilosa. The tussocks are predominantly made up of Artemisia japonica, Arthraxon hispidus, and Miscanthus floridulus. These two types of vegetation generally attain a height of about 1–2 m with a coverage of 67%. Dry farmland and paddy fields are agricultural lands subjected to prolonged tillage and fertilization practices. The dry farmlands are predominantly cultivated with Glycine max and Arachis hypogaea, whereas the paddy fields are dedicated to the long-term cultivation of rice (Oryza sativa).

2.2. Soil Sampling

Remote-sensing mapping was used to determine the spatial distribution of land-use types. Representative woodland, shrubland, shrubby tussock, tussock, dry farmland, and paddy fields were selected as sampling sites in the study area from July to August 2022. Plots (10 × 10 m) were established, with 5 for woodland, tussock land, and paddy fields, and 6 for shrubland, shrubby tussock land, and dry farmland, totaling 33 plots. Soil samples from the 0–20 cm layer of the mineral soil surface were collected at the four corners and center of each sample plot and thoroughly mixed to form a composite sample for each plot [35]. The composite samples were immediately placed in a cooler and transported to the laboratory. At the same time, undisturbed soil samples were collected using an auger in each plot. In total, 33 composite and 33 undisturbed soil samples were collected. At the laboratory, visible debris such as twigs, animal remains, gravel, and roots were removed. The soil samples were then sieved through a 2 mm mesh. The soil samples were divided into two portions: one portion was stored briefly in a refrigerator at 4 °C for the determination of soil microbial abundance and soil enzyme activity, and the other portion was air-dried at room temperature for the determination of soil pH, SOC, TN, and TP. The undisturbed soil samples were used to measure bulk density and moisture content. Information on land-use type, elevation, slope, and rocky outcrop rate was recorded.

2.3. Laboratory Measurements

Soil water content was determined by drying the undisturbed soil samples in an oven at 105 °C for 10 h to a constant weight; soil bulk density was then determined by calculating the ratio of soil mass to total augur volume [36]. Soil pH was measured using the immersion electrode method in a water suspension, using a 1:2 soil/water ratio [37], SOC content using the K2Cr2O7 oxidation method [38], TN content using the Kjeldahl method [39], and TP content using the NaOH fusion–molybdenum antimony anticolorimetric method [40].
Levels of catalase (an oxidoreductase) and invertase, urease, and protease (hydrolases), which are closely related to soil C, N, and P biogeochemical cycling, were examined. Catalase, invertase, urease, and protease levels were determined via potassium permanganate titration, 3,5-dinitrosalicylic acid colorimetry, indophenol blue colorimetry, and ninhydrin colorimetric method, respectively [40,41].
Three major groups of soil microorganisms (bacteria, fungi, and actinomycetes) were identified using the spread plate count method [42]. Beef extract peptone medium was used to culture bacteria, Martin’s medium to culture fungi, and Gause’s No. 1 medium to culture actinomycetes. First, a series of culture medium dilutions were prepared for the soil samples, and the diluted solution was then evenly spread on the corresponding culture media. During spreading, the Petri dishes were gently rotated to ensure uniform distribution of the diluted solution. The colonies that formed on the culture medium were counted. The number of colony-forming units per gram of soil (cfu∙g−1) was calculated by multiplying the average number of colonies by the dilution factor.

2.4. Statistical Analysis

The explanatory variables were soil pH, moisture content, and bulk density; soil enzyme levels (catalase, invertase, protease, and urease); soil microbial abundances (actinomycetes, bacteria, and fungi); and topographic factors (elevation, slope, and rocky outcrop rate). These 13 environmental factors were examined as potential drivers of soil C, N, and P contents and their stoichiometric ratios. The C/N, C/P, and N/P ratios represent SOC/TN, SOC/TP, and TN/TP ratios, respectively.
First, the Shapiro–Wilk test was used to assess the normality of all variables. For variables that did not meet the assumption of normality, logarithmic transformation (base 10) was performed. One-way analysis of variance and the least significant difference (LSD) test were used to evaluate the significance of differences in the various soil parameters and topography among the land-use types, using SPSS 27.0 (SPSS Inc.; Chicago, IL, USA). Pearson correlation analysis was performed using the “psych” package [43] in R 4.0.3 to investigate the relationships between soil C, N, and P and their stoichiometric ratios and the 13 environmental factors. Redundancy analysis (RDA) was conducted using CANOCO 5.0 to further examine the effects of the 13 environmental factors on soil C, N, and P and their stoichiometric ratios. Variance partitioning analysis (VPA) was performed using the “vegan” package [44] in R 4.0.3 to elucidate the relative importance of the selected soil properties, enzymes, microorganisms, and topographic factors in explaining the differences in C, N, and P and their stoichiometric ratios among the land-use types. Differences were considered significant at p < 0.05.

3. Results

3.1. Soil C, N, and P and Their Stoichiometries

Land-use affected soil SOC content (Figure 2). Woodland had the highest SOC content (45.23 g∙kg−1), significantly higher than that of shrubland, tussock land, dry farmland, and paddy fields (p < 0.05). SOC content was lowest for dry farmland (16.66 g∙kg−1), significantly lower than that of woodland and shrubland (p < 0.05), while it was similar among shrubland, tussock land, and paddy fields. Soil TN was significantly higher for woodland than for the other land-use types (p < 0.05), and was similar among the other land-use types. Soil TP content did not vary significantly with land use, but was highest in woodland (1.31 g∙kg−1). The C/N and N/P ratios were similar among the land-use types. The C/P ratio was lowest for dry farmland (18.68), significantly lower than for woodland, shrubland, and paddy fields (p < 0.05), but not significantly different from that of tussock land and shrubland (p > 0.05). As shown in Table 1, the coefficient of variation ranges for the soil C, N, and P contents and their stoichiometric ratios are 19.07–74.93%, 16.98–62.41%, 16.13–61.21%, 20.23–55.11%, 23.51–54.81%, and 24.78–44.06%, respectively.

3.2. Environmental Variables

The land-use types differed significantly in invertase levels, moisture content, actinomycetes abundance, slope, and rocky outcrop rate, but not in catalase, protease, or urease levels, soil bulk density, pH, bacterial or fungal abundance, or elevation (Table 2). Woodland exhibited the highest catalase and invertase activity, at 0.17 and 1.18 mL∙g−1∙min−1, respectively; invertase activity was significantly higher in woodland than in shrubland, dry farmland, and paddy fields. Protease and urease activity was lowest in woodland, at 0.36 and 0.4 mL∙g−1∙24 h−1, respectively. Shrubland had the highest protease activity (0.55 mL∙g−1∙24 h−1), while dry farmland had the highest urease activity (0.94 mL∙g−1∙24 h−1). Moisture content was highest for paddy fields (27.34%), significantly higher than that of shrubby tussock land, tussock land, and dry farmland, and was lowest for dry farmland (17.36%), which was significantly drier than woodland and paddy fields. Soil bulk density was highest for tussock land (1.5 g∙cm−3) and lowest for woodland (1.35 g∙cm−3). pH was highest for paddy fields (7.63) and lowest for woodland (6.21). Bacterial count was highest for woodland (0.17 cfu∙g−1) and lowest for shrubland (0.05 cfu∙g−1). Actinomycetes and fungal counts were lowest for woodland (0.44 and 0.36 cfu∙g−1, respectively). Actinomycetes count was significantly lower for woodland than tussock land, dry farmland, and paddy fields. Slope was lowest for paddy fields (at zero), was significantly higher for woodland, shrubland, shrubby tussock land, and tussock land, and was highest in woodland (38°; p < 0.05 vs. dry farmland and paddy fields). Rocky outcrop rate was significantly lower for paddy fields than for the other land-use types, and was highest for shrubby tussock land (49.5%; p < 0.05 vs. paddy fields).

3.3. Correlations between Environmental Variables and Nutrient Traits

SOC was significantly positively correlated with TN, the C/N and C/P ratios, and invertase (p < 0.01) and was significantly negatively correlated with actinomycetes abundance (p < 0.05; Figure 3). TN was significantly positively correlated TP, the N/P ratio, catalase, invertase, and bacterial abundance (p < 0.05) and was significantly negatively correlated with pH (p < 0.05). TP was significantly positively correlated with urease, elevation, and rocky outcrop rate (p < 0.05) and significantly negatively correlated with bulk density (p < 0.05). The C/N ratio was significantly positively correlated with the C/P ratio and moisture content (p < 0.05) and significantly negatively correlated with the N/P ratio (p < 0.05). The C/P ratio was significantly negatively correlated with actinomycetes abundance (p < 0.05). The N/P ratio was significantly positively correlated with catalase and bacterial abundance (p < 0.01).
RDA revealed that topographic factors, soil properties, soil enzymes, and soil microorganisms explained, respectively, 15.09%, 16.36%, 26.74%, and 22.65% of the variation in soil C, N, and P, and their stoichiometries, on the first two ordination axes (Figure 4). Rocky outcrop rate and slope explained 44.5% and 34.9% of the variation, respectively (Figure 4A). pH significantly affected the contents and stoichiometric ratios of C, N, and P and was an important influencing factor, explaining 51% of the variation (p = 0.022; Figure 4B). Catalase and invertase significantly affected C, N, and P contents and stoichiometries, explaining 51.6% and 33.6% of the variation, respectively (p = 0.004 and p = 0.002, respectively; Figure 4C). Bacterial and actinomycetes abundances were important influencing factors, explaining 54.2% and 36.2% of the variation, respectively (p = 0.014 and p = 0.024; Figure 4D). The contributions of the other environmental factors were relatively low.
The VPA results (Figure 5) reveal that the environmental factors (soil enzymes, soil physicochemical properties, soil microorganisms, and topographic variables) explained only 16% of the variation in SOC content, with the majority of the variation attributed to the interactive effects of soil enzymes and physicochemical properties (17%) and soil microorganism abundance and topography (12%). Environmental factors accounted for 41% of the variation in TN content, which was more affected by SOC than by the interaction between soil enzymes and physicochemical properties. TP content was more affected by the interactions between topography and soil enzymes, physicochemical properties, and microorganism abundance, which explained 9%, 9%, and 8% of the variation in TP, respectively. Collectively, the environmental factors explained 21% of the variation in the TP content. Together, the environmental variables explained 5%, 33%, and 57%, and soil enzymes 9%, 14%, and 13%, of the variance in the C/N, C/P, and N/P ratios, respectively. The C/P ratio was influenced primarily by interactions between soil microorganism abundance and topography, which together explained 22% of the variation. The N/P ratio was affected primarily by the interactions between soil enzymes and microorganism abundance, which accounted for 39% of the variation.

4. Discussion

This study examines C, N, and P contents and stoichiometries under different land-use types in a karst agricultural watershed in southwestern China. These findings elucidate nutrient cycling and balance mechanisms in karst watershed ecosystems, provide reference data for environmental protection, and assist in optimizing land use and soil system management.

4.1. Effects of Land-Use Type on Topsoil C, N, and P Content

Variations in land-use types exert distinct influences on the input and output dynamics of soil nutrients, primarily mediated by differential rates of accumulation and release of C, N and P in soil [45,46]. The decomposition rate of plant residues and litter, driven by soil microbes and enzymes, profoundly influences soil nutrient content [12]. Paddy soils showed higher variability in SOC and TN contents compared to other land-use types, with coefficients of variation of 74.93% and 62.41%, respectively (Table 1). This variability likely arises from the interaction of various factors, including agricultural practices (fertilization, irrigation, and tillage), inputs of organic matter (crop residues and organic fertilizers), soil properties (texture, structure, and pH), and environmental conditions (temperature and precipitation). This variability not only indicates the influence of agricultural practices and environmental factors on soil nutrient levels but also offers valuable insights for future agricultural management and environmental protection efforts. Furthermore, SOC and TN contents were highest in woodland, significantly higher than in shrubby tussock land, tussock land, dry farmland, and paddy fields (Figure 2). In contrast, in the Nianchu River Basin, Tibet, woodland TN content was lower than that of tussock land, possibly owing to differences in other factors such as the soil layer, climate, geology, landform, or soil type [47]. However, our finding is consistent with findings for the karst region of southwestern China, in which SOC and TN contenst were significantly higher in woodland than in shrubland and grassland [48,49].
Woodland ecosystems harbor a variety of vegetation types, including tree shrubs, dwarf shrubs, and low grasses. Woodland is characterized by lush foliage, extensive root systems, and exhibits diverse species composition and structure, which effectively reduces surface runoff, prevents erosion of the fertile soil surface, and minimizes nutrient loss. Its high vegetation coverage promotes the production and release of large amounts of organic matter into the soil via photosynthesis, thereby greatly increasing soil SOC and TN [50]. Higher soil enzyme activity and microbial abundance usually indicate a stronger capacity for organic matter decomposition [51,52]. Here, soil SOC and TN were significantly positively correlated with invertase activity (Figure 3) and negatively correlated with actinomycetes abundance. Woodland exhibited the highest invertase activity and lowest actinomycetes abundance (Table 2). The superior hydrothermal conditions and slightly alkaline pH of the soil in this small watershed are conducive to microbial reproduction and growth. This potentially accelerates litter decomposition and nutrient release in the woodland, explaining why it exhibits the highest SOC and TN. Dry farmland had the lowest SOC content, significantly lower than that of woodland and shrubland. This may be due to the failure to replenish organic and inorganic fertilizers after harvest, or to the persistent application of inappropriate tillage practices, which destroy soil aggregates, accelerate soil organic matter decomposition and loss, and exacerbate soil C and N consumption during crop growth and harvest [53,54,55], thus reducing soil fertility.
Compared with the other land-use types, woodland, shrubland, and shrubby tussock land contained more litter, which supplies rich organic matter to the soil. The dry farmland exhibited severe water and soil loss, with sparse surface vegetation and exposed rock, causing litter to be scarce and resulting in lower SOC and TN than in woodland and shrubland. TN content was significantly higher in woodland than in the other land-use types, which exhibited similar TN content. This similarity in TN may be due to the small differences in the total microbial quantity and enzyme activity among the five land-use types, resulting in similar decomposition of soil humus (Table 2). Fertilization of agricultural land may increase soil TN in other land-use types, leading to relatively small differences in TN content among the various land-use types.
Soil P originates primarily from the weathering of rocks, and is mainly influenced by the soil parent material, pedogenesis and leaching processes, and climatic conditions [56]. Soil TP content was similar among the various land-use types, consistent with prior findings for karst regions [48,57]. Our finding thus supports the stability of TP content across the three land-use types: woodland, shrubland, and tussock land. Consistent with this, for subtropical tidal wetland soils, TP content was similar in tussock land and paddy fields [58]. For our findings, this may be primarily because soils within this small watershed developed from the same parent material, and have been subjected to similar climate conditions. In the soil, P is known to be sedimentary and exhibits low mobility, resulting in relatively small variability in its content [59]. The high TP content observed here for woodland may be due to the interaction of various ecological factors. First, the dense and complex vegetation in woodland provides favorable conditions for the accumulation of soil organic matter. Under the influence of microorganisms and enzymes, this organic matter decomposes, releasing various nutrients, including P, thereby enriching the soil. Second, the well-developed root systems of trees not only stabilize the soil and prevent erosion, but also promote microbial activity and the decomposition of organic matter via the secretion of organic acids and enzymes, thereby enhancing the release and absorption of P in the soil. Finally, there is limited human disturbance in woodland, reducing the risk of soil erosion and P loss, thereby maintaining a higher TP content. Woodland therefore exhibits stable and fertile conditions. Additionally, organic P plays a crucial role in the P-cycle. Derived from decomposed plant and animal residues, organic P is a vital component of the soil P pool. Soil microorganisms mineralize organic P into inorganic forms that plants can absorb [60]. This process is essential for maintaining P availability in the soil, especially in ecosystems like woodlands where organic matter content is high.

4.2. Effects of Land Use on Topsoil C, N, and P Stoichiometries

Soil nutrient stoichiometry, which reflects nutrient cycling characteristics and supply limitation in the soil microenvironment, is central to assessing soil organic matter composition and quality [61]. Compared with the national average topsoil C/N (11.9), C/P (61), and N/P (5.2) ratios for China [62], the C/N ratio observed here (11.31) was close to the national average, whereas those for C/P and N/P were lower, at 31.13 and 2.96, respectively. This indicates that there is insufficient C and N content in the soil of the study area, severely restricting the growth of vegetation and crops. Therefore, increasing the C and N content of the soil is a key factor for ecological restoration in this region. The primary reason for this outcome is likely the exacerbation of karst rocky desertification, which has substantially reduced the vegetation cover, increasing the soil surface area. This has removed the soil’s natural protective barrier, thus increasing the removal of C and N via wind and water. Anthropogenic factors such as deforestation, overgrazing, excessive cultivation, and improper fertilization have disrupted the soil’s ecological balance, increasing soil erosion and nutrient loss, leading to soil degradation and further reductions in C and N content. The characteristic high-intensity rainfall and periods of drought of this region have profoundly affected its soil-nutrient cycling. The intense rainfall rapidly washes away the soil and nutrients, exacerbating soil erosion, while drought limits nutrient release and vegetation growth, hindering soil-nutrient cycling. Together, these extremes hamper the replenishment and retention of soil C and N. The low C and N that we observed here is consistent with findings for the Liudao Gully watershed on the Loess Plateau [8], indicating that land-use in watersheds may have similar effects on soil ecological stoichiometry, regardless of the geographical background. Higher ratios have been reported for the karst region of southwestern China (C/N, 13.46; C/P, 80.17; N/P, 5.60) [57]. This indicates that, under similar climatic conditions, nutrients accumulate more slowly in the karst watershed than in the karst non-watershed areas. This may result from the major impact of river erosion and intense precipitation in the study area, exacerbating soil erosion and causing strong leaching, increased surface runoff, and the substantial loss of soil nutrients. Additionally, human-induced deforestation in the watershed has caused a significant decline in natural forests, which have been replaced by secondary forests. Severely degraded areas have transitioned to vegetation dominated by shrubs, grasses, and woody vines, with some regions further deteriorating into barren hills and ridges, exacerbating rock desertification. This further weakens the soil’s water and nutrient retention capacity, consequently reducing the soil’s nutrient accumulation rate, resulting in lower nutrient values relative to those in other karst areas.
Here, woodland, shrubland, and paddy fields exhibited higher C/N and C/P ratios than shrubby tussock land, tussock land, and dry farmland (Figure 2). This suggests that, within this watershed, these land-use types undergo higher rates of organic matter decomposition, leading to greater nutrient accumulation. The importance of soil enzymes and microorganisms in facilitating plant–soil nutrient cycling may explain this outcome. Compared with the other land-use types, woodland and shrubland typically have higher vegetation coverage, greater biodiversity, and abundant organic matter such as litter. This both helps to prevent soil erosion and provides the conditions and nutrient sources to support enzymatic activity and microorganism growth in the soil; this complexity thus promotes organic matter decomposition and transformation [3]. In this woodland and shrubland, decomposition of the abundant litter, comprising leaves and branches, contributes substantial amounts of organic matter to the soil. This undergoes chemical reactions under the action of enzymes and microorganisms, thus enhancing soil nutrient release and cycling. The complex interwoven root systems of woodland and shrubland improve the soil structure, enhance its water retention and permeability, and help to retain and replenish soil nutrients [63]. In paddy fields, the irrigation system, high moisture content, and anaerobic environment provides favorable conditions for the activity of soil enzymes and microorganisms. Moderate soil moisture and pH enable some enzymes and microorganisms to operate efficiently, accelerating organic matter decomposition and thereby increasing soil nutrient content, explaining the higher C/N and C/P ratios observed here in woodland, shrubland, and paddy fields. In contrast, the lower vegetation coverage of dry farmland increases its surface runoff, potentially weakening the soil structure, causing poor water retention and permeability; this affects the soil’s nutrient accumulation, reducing its SOC content and thus reducing its C/N and C/P ratios. Therefore, in dry farmland, these ratios could indicate soil degradation, particularly reflecting the depletion of SOC due to the scarcity of fresh plant residues available for mineralization. The lower C/N and C/P ratios of shrubby tussock land and tussock land may be mainly due to the low diversity of their vegetation, less complex root structures, and low biomass [3]; these factors alter soil nutrient accumulation and distribution, influencing its stoichiometry. The N/P ratio was similar among the six land-use types, potentially owing to their relatively stable and similar soil TN and TP content, soil enzyme activity, and microbial abundance (Table 2), causing them to have similar rates of organic matter decomposition and nutrient-utilization efficiency.
Environmental factors such as pH, topography, and climate may indirectly influence soil stoichiometry by affecting its physicochemical properties and processes such as nutrient dissolution, transformation, and loss [64]. The relative stability of the N/P ratio may therefore arise from the combined effects of these biotic and abiotic factors. In summary, land-use type may regulate nutrient cycling, altering soil stoichiometry, by influencing soil enzymes and microbial activity.

4.3. Factors Affecting soil C, N, and P Contents and Stoichiometries

RDA analysis revealed that rocky outcrop rate, slope, soil pH, catalase and invertase activity, and bacterial and actinomycetes abundance were the main environmental factors influencing C, N, and P contents and their stoichiometries. This is consistent with the findings for a karst rocky desertification ecosystem in southwestern China, where land cover, elevation, rocky outcrop rate, soil temperature, and humidity significantly affected the soil stoichiometry [19]. Soil texture and pH affect soil C, N, and P contents and stoichiometric ratios [43], and in subtropical regions of southern China, soil microorganisms have been reported to affect C, N, and P stoichiometry [65]. Our findings thus corroborate those of earlier studies, emphasizing the collective role of environmental factors in regulating soil nutrient cycling and ecological balance. For instance, elevation can indirectly influence plant community structure, species composition, and water and thermal conditions by altering the distribution of temperature, humidity, and light, thereby changing microbial community structure and function, and thus altering soil C, N, and P contents and stoichiometries. Soil pH affects the release of C and N via decomposition by regulating microbial and enzyme activities, substantially affecting their stoichiometric ratios. Within the optimal pH range, heightened microbial and enzymatic activity enhances organic matter breakdown in the soil, thus influencing soil C, N, and P content. Deviations from the optimal pH suppress microorganism and enzyme activity, impeding decomposition, and altering C, N, and P contents and stoichiometric ratios.
Bacteria and fungi act as decomposers in the soil, altering nutrient content by decomposing organic matter such as litter and animal residues, releasing CO2, N, and P. Their metabolic by-products can interact with minerals in the soil, forming organic–inorganic complexes, further influencing soil stoichiometry [66]. Rocky outcrops exacerbate soil erosion, resulting in rapid nutrient loss that hinders vegetation recovery; they elevate soil surface temperatures, reducing microbial and enzyme activity and thus affecting soil nutrient content and stoichiometry.
Based on VPA, the complex interactions among these environmental factors exerted a greater impact on soil C, N, and P content and stoichiometry than these factors separately, indicating that soil C, N, and P content and stoichiometry in karst watersheds are driven by multiple factors and their interactions. Variation in soil SOC and TN was primarily influenced by the interactive effects of soil enzyme activity and physicochemical properties. Factors such as soil texture, moisture content, pH, and temperature have been empirically shown to directly participate in and regulate soil organic matter mineralization and decomposition, significantly affecting SOC and TN accumulation and release [64].
Soil enzymes participate in the transformation of organic matter and biogeochemical cycle processes through catalysis, degradation, transformation, and synthesis [67], thus significantly affecting C, N, and P contents and their stoichiometries in the soil. The highly significant positive correlations between SOC and invertase, and between TN, invertase, and catalase (Figure 3), confirm the critical role of soil enzymes in soil C and N transformation and cycling. Interactions among topography, soil enzyme activity, microorganism abundance, and physicochemical properties collectively influence soil P. Soil enzymes and microorganisms enhance P availability primarily via organic P decomposition and dissolution of insoluble phosphate salts, while terrain features and physicochemical properties indirectly regulate P cycling and distribution by altering hydrological conditions and P sorption and desorption [68,69,70]. The combined effects of these factors thus determine P content and cycling status of the soil.
The environmental factors exerted relatively minor effects on the C/N ratio, but more significant effects on the C/P and N/P ratios (Figure 5). The C/P ratio was influenced primarily by the interaction between terrain features and soil microorganism abundance, possibly owing to the significant negative correlations between bacterial and actinomycetes abundance and slope and rocky outcrop rate (Figure 3). These correlations suggests that an increase in slope and rocky outcrop rate may reduce bacterial and actinomycetes abundance, thereby affecting SOC decomposition and P conversion, ultimately altering the C/P ratio. In contrast, the N/P ratio was primarily influenced by interactions between soil enzymes and microorganisms. As revealed by the highly significant positive correlation between the N/P ratio, catalase activity, and bacterial abundance (Figure 3), the N/P ratio increased with an increase in enzyme activity and microbial abundance. Therefore, the enhanced soil enzyme activity and increased microbial abundance collectively contributed to soil N and P cycling, affecting the N/P ratio by promoting the decomposition of N-containing organic matter, accelerating N transformation and release, and regulating microbial activity.

5. Conclusions

This study elucidates soil-nutrient cycling in a karst agricultural watershed in southwestern China, providing a potential basis for improved land management. Soil C, N, and P contents and their stoichiometries were affected by soil physicochemical properties, enzyme activity, microbial abundance, topography, and their interactions. These factors collectively determined the variation in C, N, and P contents and their stoichiometric ratios across the land-use types. Topsoil SOC and TN content were highest in woodland, owing to its higher vegetation cover and thicker litter layer. The abundant litter layer creates a favorable environment for soil microorganisms, accelerating the decomposition of organic matter and the conversion of N, which increase SOC and TN content. Soil TP exhibited a weaker response to land-use type. The C/P ratio exhibited relatively little variation, possibly because of the similar variability in SOC and TN. The C/N and C/P ratios were lower for dry farmland soil than in for the natural succession stages and paddy fields. This may be due to the lower SOC content, sparse vegetation, higher surface runoff, significant human disturbance, and lower fertilization rates of dry farmland. Soil pH, catalase and invertase activity, and bacterial and actinomycetes abundance significantly influenced soil C, N, and P contents and their stoichiometric ratios, and the effects were even stronger for the interactions among these drivers. This indicates that, in karst agricultural watersheds, the levels and stability of soil C, N, and P contents and their stoichiometric ratios are influenced by multiple interacting factors, including land-use type, soil physicochemistry, soil enzyme activity, soil microbial abundance, and topography. These findings elucidate soil nutrient dynamics and drivers in karst agricultural watershed ecosystems, and will help to guide ecological restoration and agricultural planting in karst areas.

Author Contributions

Conceptualization, G.H. and Z.Z.; Formal analysis, G.H., S.C., C.X. and Z.Z.; Funding acquisition, G.H., C.Z., C.X. and Z.Z.; Investigation, G.H., X.H., C.H., C.Z. and Z.Z.; Methodology, G.H., X.H., S.C. and C.H.; Writing—original draft, G.H., X.H.., S.C., C.X. and Z.Z.; Writing—review and editing, G.H., X.H., C.H., C.Z., C.X. and Z.Z. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Natural Science Foundation of Guangxi Zhuang Autonomous Region (2021GXNSFFA196005, 2021GXNSFAA196024, 2022GXNSFBA035633, 2022GXNSFBA035461) and the National Natural Science Foundation of China (31960275, 42201023, 42301073).

Data Availability Statement

The data that support the findings of this study are available upon request from the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

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Agriculture 14 01083 g001
Figure 1. Location of the study area and sampling sites in the Chengjiang Watershed, Guangxi, southwestern China. WL, woodland; SL, shrubland; STL, shrubby tussock land; TL, tussock land; DF, dry farmland; PF, paddy field.
Figure 1. Location of the study area and sampling sites in the Chengjiang Watershed, Guangxi, southwestern China. WL, woodland; SL, shrubland; STL, shrubby tussock land; TL, tussock land; DF, dry farmland; PF, paddy field.
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Figure 2. Soil nutrient contents and ratios under different land-use types. WL, woodland; SL, shrubland; STL, shrubby tussock land; TL, tussock land; DF, dry farmland; PF, paddy field; SOC, soil organic carbon; TN, total nitrogen; TP, total phosphorus; C/N, SOC/TN ratio; C/P, SOC/TP ratio; N/P, TN/TP ratio. Bars represent means ± standard errors. Different lowercase letters identify land-use types that differed significantly at the 0.05 level.
Figure 2. Soil nutrient contents and ratios under different land-use types. WL, woodland; SL, shrubland; STL, shrubby tussock land; TL, tussock land; DF, dry farmland; PF, paddy field; SOC, soil organic carbon; TN, total nitrogen; TP, total phosphorus; C/N, SOC/TN ratio; C/P, SOC/TP ratio; N/P, TN/TP ratio. Bars represent means ± standard errors. Different lowercase letters identify land-use types that differed significantly at the 0.05 level.
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Figure 3. Pearson correlations between soil C, N, and P contents and their stoichiometric ratios and environmental factors. SOC, soil organic carbon; TN, total nitrogen; TP, total phosphorus; C/N, SOC/TN ratio; C/P, SOC/TP ratio; N/P, TN/TP ratio. CAT, catalase; INV, invertase; PRO, protease; URE, urease; SWC, soil water content; BD, bulk density; BAC, bacterial abundance; ACT, actinomycetes abundance; FUN, fungal abundance; ELE, elevation, SLO, slope; ROR, rocky outcrop rate. * p < 0.05, ** p < 0.01, *** p < 0.001.
Figure 3. Pearson correlations between soil C, N, and P contents and their stoichiometric ratios and environmental factors. SOC, soil organic carbon; TN, total nitrogen; TP, total phosphorus; C/N, SOC/TN ratio; C/P, SOC/TP ratio; N/P, TN/TP ratio. CAT, catalase; INV, invertase; PRO, protease; URE, urease; SWC, soil water content; BD, bulk density; BAC, bacterial abundance; ACT, actinomycetes abundance; FUN, fungal abundance; ELE, elevation, SLO, slope; ROR, rocky outcrop rate. * p < 0.05, ** p < 0.01, *** p < 0.001.
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Figure 4. Redundancy analysis of soil C, N, P contents and stoichiometries with environmental factors. Effects of topographic factors (A), soil properties (B), soil enzymes (C), and soil microorganism abundance (D) on soil C, N, and P contents and stoichiometries. SOC, soil organic carbon; TN, total nitrogen; TP, total phosphorus; C/N, SOC/TN ratio; C/P, SOC/TP ratio; N/P, TN/TP ratio. CAT, catalase; INV, invertase; PRO, protease; URE, urease; SWC, soil water content; BD, bulk density; BAC, bacterial abundance; ACT, actinomycetes abundance; FUN, fungal abundance; ELE, elevation, SLO, slope; ROR, rocky outcrop rate. Blue line, response; red line, explanatory variable.
Figure 4. Redundancy analysis of soil C, N, P contents and stoichiometries with environmental factors. Effects of topographic factors (A), soil properties (B), soil enzymes (C), and soil microorganism abundance (D) on soil C, N, and P contents and stoichiometries. SOC, soil organic carbon; TN, total nitrogen; TP, total phosphorus; C/N, SOC/TN ratio; C/P, SOC/TP ratio; N/P, TN/TP ratio. CAT, catalase; INV, invertase; PRO, protease; URE, urease; SWC, soil water content; BD, bulk density; BAC, bacterial abundance; ACT, actinomycetes abundance; FUN, fungal abundance; ELE, elevation, SLO, slope; ROR, rocky outcrop rate. Blue line, response; red line, explanatory variable.
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Figure 5. Variance decomposition of the effects of soil enzymes, microorganism abundances, soil properties, and topographic factors on SOC, TN, and TP contents and their stoichiometries. SP, soil properties; SE, soil enzyme; SM, soil microorganism abundance; TV, topographic variable.
Figure 5. Variance decomposition of the effects of soil enzymes, microorganism abundances, soil properties, and topographic factors on SOC, TN, and TP contents and their stoichiometries. SP, soil properties; SE, soil enzyme; SM, soil microorganism abundance; TV, topographic variable.
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Table 1. The coefficient of variation (%) of soil C, N, and P contents and their stoichiometric ratios in different land-use types.
Table 1. The coefficient of variation (%) of soil C, N, and P contents and their stoichiometric ratios in different land-use types.
Land UseSOCTNTPC/NC/PN/P
WL22.816.9840.4829.4341.2133.8
SL19.0728.2916.1342.5524.6224.78
STL30.044437.6931.4242.5728.18
TL55.8345.0662.2120.2345.0533.41
DF36.752.9746.7955.1123.5139.12
PF74.9362.4135.3424.6454.8144.06
WL, woodland; SL, shrubland; STL, shrubby tussock land; TL, tussock land; DF, dry farmland; PF, paddy field.
Table 2. Soil and topographic characteristics under different land-use types in a karst agricultural watershed.
Table 2. Soil and topographic characteristics under different land-use types in a karst agricultural watershed.
Enzyme VariablesSoil VariablesMicrobial VariablesTopographic Variables
Land UseCAT (mL∙g−1∙min−1)INV (mL∙g−1∙min−1)PRO (mL∙g−1∙24h−1)URE (mL∙g−1∙24h−1)SWC (% vol.)BD (g∙cm−3)pHBAC (cfu∙g−1)ACT (cfu∙g−1)FUN (cfu∙g−1)ELE (m)SLO (°)ROR (%)
WL0.17 ± 0.07 a1.18 ± 0.04 a0.36 ± 0.14 a0.4 ± 0.25 a25.77 ± 1.1 a1.35 ± 0.03 a6.21 ± 0.25 a0.17 ± 0.07 a0.44 ± 0.17 b0.36 ± 0.14 a235.6 ± 5.04 a38 ± 8.36 a41 ± 19.1 a
SL0.05 ±0 a0.87 ± 0.1 ab0.55 ± 0.15 a0.83 ± 0.25 a21.57 ± 2.54 ab1.44 ± 0.05 a7.24 ± 0.32 a0.05 ± 0 a0.73 ± 0.06 ab0.5 ± 0.12 a210.17 ± 20.09 a33.83 ± 3.81 ab49.5 ± 13.66 a
STL0.09 ± 0.05 a0.64 ± 0.1 b0.39 ± 0.09 a0.52 ± 0.24 a18.85 ± 1.05 b1.38 ± 0.05 a7.42 ± 0.36 a0.09 ± 0.05 a0.64 ± 0.1 ab0.39 ± 0.09 a247.17 ± 46.08 a33 ± 6.65 ab44.33 ± 6.69 a
TL0.04 ± 0.01 a0.89 ± 0.19 ab0.49 ± 0.06 a0.6 ± 0.2 a19.37 ± 1.65 b1.5 ± 0.02 a6.65 ± 0.44 a0.08 ± 0.05 a1 ± 0.19 a0.49 ± 0.06 a237.4 ± 25.9 a26.4 ± 8.3 ab31.2 ± 10.29 a
DF0.12 ± 0.09 a0.81 ± 0.1 b0.52 ± 0.08 a0.94 ± 0.16 a17.36 ± 1.03 b1.39 ± 0.06 a7.15 ± 0.32 a0.14 ± 0.09 a1.08 ± 0.14 a0.62 ± 0.08 a201.33 ± 18.78 a7 ± 7 bc44.5 ± 11.36 a
PF0.04 ± 0.01 a0.68 ± 0.02 b0.44 ± 0.01 a0.68 ± 0.22 a27.34 ± 3.63 a1.49 ± 0.05 a7.63 ± 0.27 a0.14 ± 0.05 a1.01 ± 0.16 a0.64 ± 0.2 a171.6 ± 12.06 a0 ± 0 c0 ± 0 b
WL, woodland; SL, shrubland; STL, shrubby tussock land; TL, tussock land; DF, dry farmland; PF, paddy field; CAT, catalase; INV, invertase; PRO, protease; URE, urease; SWC, soil water content; BD, bulk density; BAC, bacteria; ACT, actinomycetes; FUN, fungi; ELE, elevation; SLO, slope; ROR, rocky outcrop rate. Lowercase letters indicate groups with significant differences among land-use types in the respective variable (p < 0.05). Values are the means ± standard errors.
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MDPI and ACS Style

Hu, G.; Huang, X.; Chen, S.; Hu, C.; Zhong, C.; Xu, C.; Zhang, Z. Biotic and Abiotic Factors Affecting Soil C, N, P and Their Stoichiometries under Different Land-Use Types in a Karst Agricultural Watershed, China. Agriculture 2024, 14, 1083. https://doi.org/10.3390/agriculture14071083

AMA Style

Hu G, Huang X, Chen S, Hu C, Zhong C, Xu C, Zhang Z. Biotic and Abiotic Factors Affecting Soil C, N, P and Their Stoichiometries under Different Land-Use Types in a Karst Agricultural Watershed, China. Agriculture. 2024; 14(7):1083. https://doi.org/10.3390/agriculture14071083

Chicago/Turabian Style

Hu, Gang, Xiaoxing Huang, Siyu Chen, Cong Hu, Chaofang Zhong, Chaohao Xu, and Zhonghua Zhang. 2024. "Biotic and Abiotic Factors Affecting Soil C, N, P and Their Stoichiometries under Different Land-Use Types in a Karst Agricultural Watershed, China" Agriculture 14, no. 7: 1083. https://doi.org/10.3390/agriculture14071083

APA Style

Hu, G., Huang, X., Chen, S., Hu, C., Zhong, C., Xu, C., & Zhang, Z. (2024). Biotic and Abiotic Factors Affecting Soil C, N, P and Their Stoichiometries under Different Land-Use Types in a Karst Agricultural Watershed, China. Agriculture, 14(7), 1083. https://doi.org/10.3390/agriculture14071083

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