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Keywords:

  • atomic C:N:P ratios;
  • land-use types;
  • landscapes;
  • microbial biomass;
  • soils;
  • southern subtropical China

Abstract

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Materials and Methods
  5. 3. Results and Discussion
  6. 4. Conclusions
  7. Acknowledgments
  8. References
  9. Supporting Information

[1] Does the soil microbial biomass (SMB) in terrestrial ecosystems present well- constrained atomic carbon:nitrogen:phosphorus (C:N:P) ratios, analogous to the planktonic biomass in marine ecosystems? How do soil microbes respond to changes in the soil environment in terms of their elemental stoichiometry? Following up on the work of Cleveland and Liptzin (2007), we examined the stoichiometry of C, N and P in the soil and SMB and their relationships at both the landscape and land-use levels in subtropical terrestrial ecosystems. 1,069 soil samples were collected at a depth of 0–20 cm from three typical landscapes (a karst mountain, a low hill and a lowland) in southern subtropical China. The landscapes presented various land-use types (e.g., paddy field, upland, woodland, etc.) and intensities of anthropogenic activity. The samples were analyzed to determine soil organic C, total soil N and total soil P contents as well as SMB C, SMB N and SMB P. On average, atomic C:N:P ratios of 80:7.9:1 in the soil and 70.2:6:1 in the SMB were obtained for the region. A clear descending trend of the soil C:N:P ratios (not the SMB C:N:P ratios) was observed across the three landscapes in the order: karst mountain > low hill > lowland. Although significant variations primarily related to human activities were observed in the soil and SMB atomic C:N:P ratios across the landscapes and land-use types, a significant correlation (r = 0.56,p< 0.001) was found between the soil and SMB C:P ratios in the entire data set; however, the correlation for the comparable N:P ratios was not evident. Significant correlations between the soil and SMB C:N, C:P and even N:P ratios (mainly in the woodland) were also observed variably at the finer level of the landscape or land-use. The tendency for a C:N:P stoichiometric relationship to exist between microbes and the soil environment found in this study might suggest possible non-homeostasis of elemental stoichiometry in the SMB of the terrestrial ecosystems in southern subtropical China.

1. Introduction

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Materials and Methods
  5. 3. Results and Discussion
  6. 4. Conclusions
  7. Acknowledgments
  8. References
  9. Supporting Information

[2] Investigation of the Redfield ratio (106:16:1), which is an atomic carbon (C), nitrogen (N), phosphorus (P) ratio found consistently in both plankton and marine waters [Redfield, 1934, 1958], has led to a deep understanding of the biological processes occurring in ocean ecosystems. Whether a similar stoichiometric relationship exists between the organisms and soil environment in terrestrial ecosystems remains underexplored [Elser et al., 2000; McGroddy et al., 2004; Cleveland and Liptzin, 2007]. Gaseous C and N primarily enter terrestrial ecosystems through photosynthesis, N fixation and rainfall deposition, while P is always a fundamental building block of soil minerals weathered from parent materials. Unlike marine ecosystems, which are characterized by strong wave-mixing, terrestrial ecosystems invariably exhibit a significant spatial heterogeneity of biogenic elements (i.e., C, N and P). This spatial heterogeneity is attributed to both long-term ecological differences, such as geology, topography and climate, and short-term ecological disturbances, such as natural disasters and anthropogenic activities [Jenny, 1941]. Meanwhile, these biogenic elements in terrestrial systems are continuously mixed on the Earth's surface by a number of weak forces, such as plant uptake and litterfall/residue return, biogeochemical transformations in the soil, transport via the surface and subsurface water movement, soil-atmosphere exchange and human land management practices [e.g.,Neff et al., 2000; McGroddy et al., 2004; Tian et al., 2010].

[3] As a response to the nutrient supply in the soil environment, plants on the Earth's surface are well-known to exhibit a clear resource-dependent chemical composition [Sterner and Elser, 2002; McGroddy et al., 2004]. Underground, the soil microbial biomass (SMB), which accounts for approximately 1–5% of soil organic C (SOC), is regarded as an important indicator of soil fertility and biological quality [Jenkinson, 1990]. Not only is SMB a part of the nutrient cycles in terrestrial ecosystems, but it also plays a vital role in soil nutrient transformations, acting as a labile pool of plant-available nutrients. Measurements of SMB can serve as an early indication of changes in SOC and total soil nitrogen (TSN) long before they can be reliably detected [Powlson et al., 1987], as well as regarding stresses on the soil environment [Barajas Aceves et al., 1999]. The response of SMB to the soil environment, particularly the relationship between C, N and P in SMB and the soil environment, which is expressed as the C:N:P ratio, is very important to understand microbial nutrient limitations in soils [Ilstedt and Singh, 2005; Gnankambary et al., 2008; Ehlers et al., 2010; Bünemann et al., 2011]. Sterner and Elser [2002] put forth a hypothesis to describe the stoichiometric relationships between organisms and the environment under which organisms can be characterized by either strict homeostasis (where organism stoichiometry is independent from resource stoichiometry) or weak homeostasis (where resource stoichiometry controls organism stoichiometry). An early attempt to identify the functional relationships between soil microbial chemistry and soil processes was made by Waksman and Starkey [1931]. More recently, Cleveland and Liptzin [2007]compiled a global data set composed of 186 observations of soil and SMB atomic C:N:P ratios from a comprehensive literature review, and at the global scale, they found well-constrained but very different atomic C:N:P ratios in the soil (186:13:1) and SMB (60:7:1) in grassland and forest soils. Based on the findings from their data set, they reported that the soil microbial community, as a broadly defined group, is homeostatic.Ehlers [2010]analyzed the effect of N and P fertilization on SMB elemental stoichiometry in a Ferralsol in Kenya and also found that microbial nutrient ratios were independent on the soil environment (or homeostatic). However, in these studies, other important land-use types, such as paddy fields and uplands, were given little consideration, largely because of limited data availability; additionally, terrain and landscape characteristics were not considered.

[4] Landscapes are essentially comprised of the visible features of an area of land, including the physical elements of landforms, such as mountains, hills and water bodies, and the living elements of land cover, such as the indigenous and cultivated vegetation. Landscapes also contain anthropogenic elements, including roads and buildings, and other transitory elements. Combining their physical origins and the cultural aspects of human presence, the character and quality of landscapes produce the unique image of a region [Daniels and Cosgrove, 1989]. The agricultural landscapes in subtropical and tropical regions, which are subjected to intensive land management through crop cultivation and fertilizer application, are regarded as some of the most active landscapes on the Earth. In these landscapes, the exchange of nutrients between the soil and SMB are expected to be highly intensive. However, few studies [e.g., Myers et al., 2001] have investigated the C:N:P ratios in soil and SMB and their relationships at the landscape scale.

[5] Several decades ago, studies in New Zealand [Walker and Adams, 1958; Walker and Syers, 1976] indicated that the amount of plant-available P in soils largely controlled the levels of soil organic C and N that could accumulate over time. This suggests an especially important role for P, particularly through its effects on microbial activity and biological N fixation. Thus, it would be useful to evaluate the extent to which the amount of biologically available P can control the atomic C:N:P ratios in soils and in microorganisms.Tian et al. [2010] reported that, despite the large variations in C and N contents observed in their data set for the soils of China, the low total soil P (TSP) contents always led to high C:P and N:P ratios in soils. Herbert [1961] and Hupfer et al. [2007] suggested that chemical composition such as the P content in microbes might change with nutrient availability in the environment. The fact that the SMB C:P ratio is highly variable in the environment [e.g., Cross et al., 2005; Manzoni et al., 2010] might imply the existence of weaker homeostasis of the SMB elemental stoichiometry in soils under specific conditions.

[6] The present study investigated the relationship between soil and SMB atomic C:N:P ratios using intensive soil sampling across various landscapes and land-use types associated with different anthropogenic inputs (particularly N and P fertilizer inputs). The objectives were as follows: (i) to examine the geographical distribution pattern of the atomic C:N:P ratios in the soil and SMB; (ii) to investigate the relationships between the environmental and microbial elemental abundance, as defined previously bySterner and Elser [2002]; and (iii) to quantify the impacts of human activities on the soil and SMB atomic C:N:P ratios at both the landscape and land-use levels in southern subtropical China.

2. Materials and Methods

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Materials and Methods
  5. 3. Results and Discussion
  6. 4. Conclusions
  7. Acknowledgments
  8. References
  9. Supporting Information

2.1. Study Sites

[7] The three typical landscapes selected for this study were a karst mountain in Dacai, Guangxi Province, a low hill in Pantang, Hunan Province and a lowland in Yuanjiang, Hunan Province (Figure 1). These landscape types occur in most areas of southern subtropical China, and present various land-use types (e.g., paddy field, upland, woodland, etc.). Generally, each landscape studied has an area of 400–800 ha. In particular as depicted inTable 1, the Dacai landscape is a karst low mountain system with a parent material of limestone and mainly has four land-use types developed: the woodland (dominated by low-biomass shrubs and ferns) on mountains, the orchard and upland on slopes and the paddy field in lowlands. The Pantang landscape of low hill, which is developed from Quaternary red earth, has very similar land-use types to Dacai, but its woodland is dominated by high-biomass masson pine and shrubs on red soil hills. The Yuanjiang landscape is a monotonous and plain lowland system on the riverbank of the Yuanjiang river, which flows into the Dongting lake (the second largest China's freshwater lake), and is developed from the river and lake sediments. The major land-use type in Yuanjiang is the paddy field, accounting for over 90% of the total landscape area. Based on our field survey at the times of soil sampling, the intensification of anthropogenic activities (e.g., land management) of the three landscapes was clearly presented as the following order: Dacai < Pantang < Yuanjiang (Table 1).

image

Figure 1. The geographic locations of the three landscapes studied in southern subtropical China.

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Table 1. Description of the Three Typical Landscapes in Southern Subtropical China
LandscapeLocationAnnual Mean Temperature (°C)Annual Precipitation (mm)Elevation (m)Parent MaterialSoil TypeaLand-Use Typeb
  • a

    FAO/UNESCO soil taxonomy.

  • b

    The paddy fields are treated annually with 311, 322 and 404 kg N ha−1 of N fertilizers and 39, 50 and 68 kg P ha−1 of P fertilizers in Dacai, Pantang and Yuanjiang, respectively. The uplands are treated annually with 156, 192 and 365 kg N ha−1 of N fertilizers and 22, 43 and 90 kg P ha−1 of P fertilizers in Dacai, Pantang and Yuanjiang, respectively. The orchards annually receive 375 and 492 kg N ha−1 of N fertilizers and 52 and 71 kg P ha−1 of P fertilizers in Dacai and Pantang, respectively.

Dacai (Karst mountain)108°43′ E, 24°44′ N19.91389202–450LimestoneRegosolsDouble or triple rice for paddy field; maize, sugarcane and soybean for upland; and shrubs, ferns and masson pine for woodland.
Pantang (Low hill)111°31′ E, 29°15′ N16.8138081–112Quaternary red earthHaplic AlisolsDouble rice for paddy field; sweet potato, soybean and cotton for upland; orange for orchard; and masson pine and shrubs for woodland.
Yuanjiang (Lowland)112°24′ E, 29°05′ N16.5131335–45AlluvialFluvisolsDouble rice for paddy field; maize, cotton, sweet potato, sesame seed, soybean for upland; and no woodland.

[8] In the region, the paddy fields have been cultivated for rice production (double or triple rice cropping) for centuries and receive 311–404 kg N ha−1 and 39–68 kg P ha−1 of chemical fertilizers annually to produce 13,000 kg grain ha−1 per year on average. The uplands are sometimes rotated with paddy fields or are cropped with maize, soybean or sweet potato and receive 156–365 kg N ha−1 and 22–90 kg P ha−1 of chemical fertilizers annually. In the paddy fields and uplands, there is usually no cropping during the winter. There is generally an increasing trend of agricultural intensification and N and P fertilizer application rates across the three landscapes in the following order: Dacai < Pantang < Yuanjiang (Table 1). Most of the orchards in the region have been cultivated with citrus for decades, but some of the orchards are quite young (less than 10 years old). In the orchards, 375–492 kg N ha−1 and 52–71 kg P ha−1 of chemical fertilizers are applied annually. The woodlands are mainly redeveloped from the 1950s and are covered with masson pine, shrub, bamboo and fern. With no fertilization, the average biomass of the woodlands is 10,000–100,000 kg ha−1. In addition, due to the difference in inhabiting conditions, the woodland in Dacai has lower biomass than that in Pantang. Further information is detailed in Table 1.

2.2. Soil Sampling

[9] In each landscape, a total of 519–766 randomly distributed soil sampling points (approximately 3–4 points per ha for the paddy field and upland and 1 point per ha for the woodland and orchard) were established. Soil samples were collected at a depth of 0–20 cm during the period from July 2003 to March 2004. Each soil sample was consisted of a homogenized mixture of 6–10 surrounding soil cores, and the geographic position of the sample was recorded using GPS receivers. The analyses were completed within six months after sampling.

2.3. Chemical Analysis

[10] The SOC contents at Pantang (low hill) were measured via the combustion method using an automated C/N analyzer (vario MAX, Elementar, Germany). Because of the presence of CaCO3, the SOC contents in the Yuanjiang (lowland) and Dacai (karst mountain) soils were determined through a wet digestion method using potassium dichromate [Kalembasa and Jenkinson, 1973]. The TSN contents of the samples from the three landscapes were determined using an automated C/N analyzer, while the TSP contents were determined via a colorimetric method [Murphy and Riley, 1962] using an alkaline oxidation digestion procedure [Dick and Tabatabai, 1977]. The soil elemental contents were reported as mol kg−1.

[11] The SMB C and N contents were measured using the chloroform (CHCl3) fumigation-extraction (FE) method according toBrookes et al. [1985] and Wu et al. [1990]. For these measurements, three portions of pre-incubated soil (25 g on an oven-dried basis) were placed in a vacuum desiccator and exposed to alcohol-free CHCl3 vapor at room temperature for 24 h. The samples were then transferred to a clean desiccator, and residual CHCl3was removed by evacuation for 20 min. The fumigated portions, together with the equivalent non-fumigated portions, were extracted with 100 ml of 0.5 M K2SO4; 10 ml of the 0.5 M K2SO4 extracts were then used to analyze the organic C contents in an automated carbon analyzer (Phoenix 8000, USA), and 20 ml of the extracts were subjected to the analysis of total N after digestion in a flow injection analyzer (Foss, Sweden). Using a universal conversion factor of 0.45, we calculated the amounts of SMB C and N according to the increase in extractable C and N in the fumigated soil compared to the control [Wu et al., 1990].

[12] SMB P was determined according to Brookes et al. [1984]. With the exception that a 4.0 g soil sample (on an oven-dried basis) was used, the fumigation procedure was the same as for SMB C and N. The fumigated and non-fumigated portions were both extracted with 0.5 M NaHCO3. The 0.5 M NaHCO3 extracts were then analyzed to determine total P using a colorimetric method [Murphy and Riley, 1962]. At the same time, the recovery of P during the extraction was measured by adding a spike of inorganic P. Using a conversion factor of 0.40 and the recovery of an inorganic P spike, SMB P was calculated through measurement of the increase in extractable P in the fumigated soil compared to the extractable P in the control [Brookes et al., 1984]. Because of the cost and the time-consuming nature of measuring SMB, only 687, 516, and 192 soil samples were analyzed for Dacai, Pantang, and Yuanjiang, respectively. The SMB elemental contents were reported as mmol kg−1. The data set was further condensed by excluding some major outliers and land-use types with small sample sizes, as described in the following section.

2.4. Statistical Analysis

[13] R software (http://www.r-project.org) and the appropriate statistical packages were used for data analyses and graphing. Initially, because the data were highly scattered, the extreme values of SOC, TSN, TSP, soil C:N, soil C:P, soil N:P, SMB C, SMB N, SMB P, SMB C:N, SMB C:P, and SMB N:P in each land-use type of each landscape were iteratively removed when they were either larger than the third quartile plus three times the interquartile range (IQR) or less than the first quartile minus three times the IQR. The soil observations from the orchards at Pantang (12 samples) and the reclaimed lands at Yuanjiang (17 samples) were also removed because of the small sample size in each land-use type. As a result, the final data set was composed of 507 soil samples from Dacai, 431 from Pantang, and 131 from Yuanjiang, for a total of 1,069 soil samples. Of this total, 579 soil samples came from paddy fields, 276 from uplands, and 214 from woodlands (Tables 2 and 3). Both the Kolmogorov-Smirnov and Shapiro-Wilk tests of goodness of fit indicated that the statistical distributions and log-transformations of the above twelve soil variables all differed significantly from normality (data not shown); because of this finding, the second quartile (median or 50% quantile) results were used. Thus, as listed inTables 2 and 3, the descriptive statistics for the atomic C:N:P ratios in the soil and SMB are presented as sample minimum/maximum, medians, and coefficients of variance (CV, %). The Spearman correlation test was used to quantify the associations among the soil variables, while the nonparametric multiple comparison test (npmc, http://cran.r-project.org/web/packages/npmc/index.html) was used to examine the differences in the soil and SMB atomic C:N:P ratios between landscapes and between land-use types at the level ofα = 0.05.

Table 2. Descriptive Statistics for the Soil Atomic C:N, C:P and N:P Ratios in the Three Landscapes Associated With Various Land-Use Types in Southern Subtropical Chinaa
LandscapeLand-Use TypeSample SizeSoil C:NSoil C:PSoil N:P
MinimumMaximumMedianCV%MinimumMaximumMedianCV%MinimumMaximumMedianCV%
  • a

    The differences between the landscapes (Dacai, Pantang, and Yuanjiang) and between the land-use types (paddy field, upland and woodland) were tested with the nonparametric multiple comparison test, and significant differences (α= 0.05) are indicated with lowercase letters for landscapes and with uppercase letters for land-use types.

DacaiAll5076.914.610.8a12.027.1259.7100.5a43.63.420.89.1a37.8
Paddy field2958.613.511.17.658.4259.7128.930.05.620.811.727.2
Upland1596.911.89.611.027.1105.857.925.63.410.66.223.4
Woodland539.914.611.88.261.9196.3102.029.55.315.08.526.2
PantangAll4318.310.89.6c4.520.0133.171.5b32.92.413.47.5b31.6
Paddy field2148.910.79.73.451.3133.195.016.05.213.49.715.2
Upland568.510.69.64.232.5101.256.024.33.110.45.724.5
Woodland1618.310.89.45.320.093.351.722.72.49.15.520.9
YuanjiangAll1317.713.710.4b10.427.9116.163.7c28.02.611.15.9c27.9
Paddy field707.713.710.612.829.5116.171.122.03.011.17.023.1
Upland619.011.710.35.727.990.549.725.62.68.85.126.0
OverallAll10696.914.610.011.020.0259.780.046.12.420.87.939.4
Paddy field5797.713.710.4A9.729.5259.7101.2A34.43.020.810.0A29.3
Upland2766.911.89.8B9.827.1105.856.0B25.82.610.65.9B25.4
Woodland2148.314.69.6B13.120.0196.356.7B47.22.415.05.9B33.9
Table 3. Descriptive Statistics for the Soil Microbial Biomass Atomic C:N, C:P, and N:P Ratios in the Three Landscapes Associated With Various Land-Use Types in Southern Subtropical Chinaa
LandscapeLand-Use TypeSample SizeSoil Microbial Biomass C:NSoil Microbial Biomass C:PSoil Microbial Biomass N:P
MinimumMaximumMedianCV%MinimumMaximumMedianCV%MinimumMaximumMedianCV%
  • a

    The differences between the landscapes (Dacai, Pantang and Yuanjiang) and between the land-use types (paddy field, upland and woodland) were tested with the nonparametric multiple comparison test, and significant differences (α= 0.05) are indicated with lowercase letters for landscapes and with uppercase letters for land-use types.

DacaiAll5073.233.313.3a49.57.3249.384.3a51.81.220.76.5b47.0
Paddy field2956.233.317.028.812.6249.3106.836.71.411.26.227.9
Upland1593.217.67.242.87.3155.250.358.51.219.86.958.4
Woodland533.810.66.126.411.7125.455.447.52.520.78.844.5
PantangAll4313.926.811.9a37.110.7151.359.0c44.41.218.34.8c49.4
Paddy field2145.926.814.925.910.8129.867.232.11.77.64.825.9
Upland563.924.19.841.314.2151.364.742.11.218.36.657.5
Woodland1614.517.58.826.210.7127.139.555.01.213.34.553.3
YuanjiangAll1313.714.08.4b22.321.7162.771.5b35.74.017.88.7a28.6
Paddy field704.412.28.518.829.6134.375.530.04.514.49.320.7
Upland613.714.07.926.021.7162.762.541.84.017.88.036.3
OverallAll10693.233.311.245.77.3249.370.251.91.220.76.049.1
Paddy field5794.433.315.2A33.410.8249.385.7A41.71.414.45.7A35.4
Upland2763.224.17.8B41.57.3162.755.9B51.81.219.87.2B53.5
Woodland2143.817.58.0B30.210.7127.142.4C54.31.220.75.5A60.0

3. Results and Discussion

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Materials and Methods
  5. 3. Results and Discussion
  6. 4. Conclusions
  7. Acknowledgments
  8. References
  9. Supporting Information

3.1. Soil Atomic C:N:P Ratio

[14] Across the entire data set, SOC varied from 0.44 to 3.74 mol kg−1, with a median of 1.39 mol kg−1 and a moderate CV of 44.6%; TSN ranged from 0.05 to 0.31 mol kg−1, with a median of 0.14 mol kg−1 and a CV of 38.2%; and TSP ranged from 0.006 to 0.045 mol kg−1, with a median of 0.016 mol kg−1 and a CV of 39.6% (Figure 2a). As depicted in Figure 2b, all three parameters showed a weak normal distribution, including their log transformations (data not shown). The Spearman correlation between SOC and TSN was highly significant and positive (r = 0.98, p < 0.001) and presented a strongly isometric shape (Figure 2c). Although the correlations between SOC and TSP (r = 0.40, p < 0.001) and between TSN and TSP (r = 0.44, p < 0.001) were positive and significant (Figure 2c), their magnitudes were smaller than that between SOC and TSN. Nevertheless, considering the large sample size of 1,069, the relatively weak correlations of TSP with SOC and TSN still supported the notion that the amount of soil plant-available P might have a significant influence on the levels of the accumulation of SOC and TSN in the soils [Walker and Adams, 1958; Walker and Syers, 1976].

image

Figure 2. (a) Variation, (b) distribution, and (c) relationships of C, N, and P in the soils of the three landscapes studied.

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[15] Although the SOC content was highly variable in the investigated subtropical ecosystems, the soil C:N ratio was remarkably well constrained (Table 2 and Figure 4a). The CV of the C:N ratio was only 11.0%, which was much lower than that of the soil SOC content. However, the soil atomic C:P and N:P ratios were more variable. In the whole data set, the soil C:N ratios varied from 6.9 to 14.6, with a median of 10.0 and a CV of 11.0%; the soil C:P ratios varied from 20.0 to 259.7, with a median of 80.0 and a CV of 46.1%; and the soil N:P ratios varied from 2.4 to 20.8, with a median of 7.9 and a CV of 39.4%. On average, an atomic C:N:P ratio of 80:7.9:1 (equivalent to 31:3.6:1 on a mass basis) was obtained for these soils from the southern subtropical region of China. Tian et al. [2010]used 2,384 soil profiles and over 8,000 soil layers from the Chinese National Soil Inventory data set to calculate an average (area- and depth-weighted) atomic C:N:P ratio of 61:5.2:1 (not well-constrained) for all of the soils of China, 78:6.4:1 for the soils in the tropical and subtropical climatic zones of China and 136:9.3:1 (well-constrained) for the 0–10 cm organic-rich layer of all of the soils of China. Our analysis of the average atomic C:N:P ratio for subtropical soils is in good agreement with the ratio estimated byTian et al. [2010] for a similar region. However, our analysis yielded a slightly higher N:P ratio, even though this ratio was estimated for the whole soil profile (down to 2.5 m deep). Of particular note, the C:N:P ratios in the soils investigated in the present study are close to half the ratio reported for global soils (186:13:1) by Cleveland and Liptzin [2007], which was considered to be well-constrained. Although the global data set used by the last authors covered more regions with various soil types, only two vegetation types (grass and forest) were included and received limited anthropogenic P inputs. Importantly, the soil atomic C:N:P ratios detected in the present study were higher than those found in acidic red soils from southern China [Chen and He, 2004], which were included in the global data set.

3.2. Atomic C:N:P Ratio in Soil Microbial Biomass

[16] The SMB results spanned several orders of magnitude. For the entire data set, SMB C varied from 2.02 to 365.49 mmol kg−1, with a median of 54.48 mmol kg−1 and a large CV of 95.1%, which accounted for 3.54% of SOC on average; SMB N ranged from 0.16 to 17.67 mmol kg−1, with a median of 4.74 mmol kg−1 and a moderate CV of 66.5%, which was 3.29% of TSN on average; and SMB P varied from 0.05 to 3.83 mmol kg−1, with a median of 0.81 mmol kg−1 and a moderate CV of 64.9%, which was 4.49% of TSP on average (Figure 3a). Figure 3b indicates that including their log transformations (data not shown), SMB C, N, and P all presented skewed distributions. The Spearman correlations among SMB C, N, and P were highly significant and positive, with coefficient values ranging from 0.79 to 0.88 (p < 0.001) (Figure 3c). Compared with the relationships between SOC, TSN, and TSP (Figure 2c), the association between SMB C and SMB N was scattered, whereas the relationships between SMB C and SMB P and between SMB N and SMB P were constrained.

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Figure 3. (a) Variation, (b) distribution, and (c) relationships of C, N, and P in soil microbial biomass in the soils of the three landscapes studied.

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[17] The analysis also indicated constrained atomic C:N:P ratios in the SMB (Table 3 and Figure 3b), with slightly larger CVs (varying from 45.7 to 51.9%) than those observed for the soil. For the whole data set, the SMB C:N ratios ranged from 3.2 to 33.3, with a median of 11.2 and a CV of 45.7%; the SMB C:P ratios ranged from 7.3 to 249.3, with a median of 70.2 and a CV of 51.9%; and the SMB N:P ratios varied from 1.2 to 20.7, with a median of 6.0 and a CV of 49.1%. Based on their CVs, the SMB C:P ratios were more dispersive than the other ratios. On average, an atomic C:N:P ratio of 70.2:6:1 (equivalent to 27.2:2.7:1 on a mass basis) was obtained for the SMB in southern subtropical China. This value was remarkably close to the ratio of 60:7:1 obtained by Cleveland and Liptzin [2007] for the SMB atomic C:N:P ratio at the global scale. These two C:N:P stoichiometries for SMB derived from different data sets may suggest that a constrained stoichiometric relationship, analogous to the marine Redfield ratio, exists in the SMB of soils, even though the environment inhabited by the SMB is completely different in terms of elemental availability, vegetation type, hydrological characteristics, climate and anthropogenic influences. However, it is not necessary to suggest that the soil microbial community is homeostatic because variations were observed among the elemental ratios in our data set for the SMB, particularly for the SMB C:P ratio, which presented a moderate CV (51.9%). Herbert [1961]reported that the chemical composition of SMB might change with environmental conditions (especially with nutrient availability). Additionally, it is well-known that SMB is not a homogenous pool because it is mainly composed of bacteria and fungi in the soil. Homeostatic regulation is considered to be strict in bacteria, but this characteristic might not apply to fungi [Sterner and Elser, 2002; Makino et al., 2003]. Accordingly, weak homeostasis could occur in the soil microbial community. As a result, the C:N:P ratio of SMB might vary with resource-dependent shifts in the population and composition of bacteria, fungi and other forms of SMB in the soil.

3.3. Relationships Between the Soil and Soil Microbial Biomass Atomic C:N:P Ratios

[18] For the entire data set, the present study suggests a highly significant positive correlation (r = 0.56, p < 0.001) between the soil and SMB C:P ratios. However, there is no significant positive correlation between their N:P ratios (Table 4 and Figure 4c). This finding indicates that to some extent, SMB might not be a homeostatic system in southern subtropical China because its C:P ratio changes positively with changes in the C:P ratio in the soil environment. In other words, if there is ample C availability, the P accumulated in SMB may respond positively to the biologically available P in the soil environment. This finding might also suggest that P is a limiting factor for biological productivity (i.e., SMB) in the soils of the region. Most of the soil P is believed to be strongly adsorbed or bound by soil calcareous, ferrous and aluminous complex compounds in these highly weathered and acidic soils, and thus soil P is expected to exhibit a very low biological availability in the region, similar to the availability in tropical soils [Vitousek, 1984]. Among a number of recent studies [e.g., Cleveland and Liptzin, 2007; Aponte et al., 2010; Ehlers, 2010], a significant positive correlation between the soil and SMB C:P ratios was rarely reported, which might be due to either the small sample sizes or one-site investigations employed in those studies. However, the SMB C:P ratio is expected to be highly variable in soils because SMB P has been found to turn over much more rapidly than SMB C [Kouno et al., 2002]. Cross et al. [2005] reported that bacteria (5–370) and fungi (300–1190) exhibited wider ranges of C:P ratios than those of C:N ratios. Based on a recent review, Manzoni et al. [2010] reported a broad SMB C:P ratio range of 60–860. Among these studies, Stark [1972], in particular, reported a C:P ratio range of 264–713 for litter decomposers in subtropical and tropical regions. Our data also indicated a considerably large SMB C:P ratio range of 7.3–249.3 in the three investigated landscapes and across three different land-use types (Table 3). All of these findings might simply underpin a fact that the SMB C:P ratio is resource-dependent on the soil environment. Otherwise, the SMB C:P ratio would be expected to be constrained, similar to the SMB C:N or N:P ratio. In aquatic systems,Tezuka [1990]found a positive relationship between the C:nutrient (including C:P) ratios of bacteria collected from lakes and coastal waters and their laboratory culture media, and speculated that the observed biomass stoichiometry could closely reflect the resource-environment stoichiometry (representing a weak homeostatic system).

Table 4. The Spearman Correlations Between the Atomic C:N, C:P and N:P Ratios of the Soil and Soil Microbial Biomass in the Three Landscapes Associated With Various Land-Use Types in Southern Subtropical China
LandscapeLand-Use TypeSample SizeSoil C:N Versus Soil Microbial Biomass C:NSoil C:P Versus Soil Microbial Biomass C:PSoil N:P Versus Soil Microbial Biomass N:P
rapbrprp
  • a

    r denotes the Spearman correlation coefficient.

  • b

    p is the probability of the Spearman correlation test.

DacaiAll5070.32<0.0010.59<0.001−0.070.100
Paddy field2950.190.0010.40<0.001−0.040.491
Upland159−0.190.0190.160.0420.070.415
Woodland530.130.3610.100.4890.110.438
PantangAll4310.160.0010.54<0.0010.070.154
Paddy field2140.070.2770.42<0.0010.140.035
Upland56−0.250.0640.330.012−0.200.136
Woodland161−0.060.4450.46<0.0010.47<0.001
YuanjiangAll131−0.060.5320.220.1000.040.673
Paddy field70−0.110.3490.000.969−0.020.901
Upland610.000.9950.170.191−0.240.059
OverallAll10690.20<0.0010.56<0.001−0.030.302
Paddy field5790.20<0.0010.52<0.001−0.080.052
Upland276−0.130.0360.140.019−0.080.187
Woodland214−0.40<0.0010.44<0.0010.59<0.001
image

Figure 4. Distributions of the atomic C:N, C:P, and N:P ratios in (a) soil and (b) soil microbial biomass and (c) their relationships in the soils of the three landscapes studied.

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[19] There was also a positive correlation (r = 0.20, p < 0.001) evident between the soil and SMB C:N ratios (Table 4 and Figure 4c), but this association was weak. The non-significant correlation between the soil and SMB N:P ratios observed in the present study (Table 4 and Figure 4c) is in agreement with the findings of Cleveland and Liptzin [2007] and Ehlers [2010], even though the soil samples studied here were collected across three different landscapes and several land-use types receiving various fertilizer N and P inputs. As can be observed from the histograms of the soil and SMB C:N ratios (Figures 4a and 4b), the much wider range of C:N ratios in SMB than that in the soil further supports the notion that the microbial community is a non-homeostatic system. Interestingly, the histograms for the C:P and N:P ratios of SMB are both similar to the ratios of their counterparts in the soil (Figures 4a and 4b). However, only the C:P ratios of the soil and SMB showed a significant correlation.

[20] Notably, both the SMB atomic C:N:P ratio obtained in the present study (70.2:6:1) and that reported by Cleveland and Liptzin [2007](60:7:1) are remarkably close to the overall area- and depth-weighted atomic C:N:P ratio (61:5.2:1) estimated for the soils of China from several thousand soil profiles [Tian et al., 2010] as well as the average atomic C:N:P ratio (57:5.1:1) of the topsoils of four Australian pastoral and cropped soils (recalculated from Kirkby et al. [2011, Table 2]). Because these data sets were frameworked differently for specific purposes, it is unclear whether the current finding is a coincidence or an indication of an intrinsic Redfield-like stoichiometric ratio in the soils and SMB of terrestrial ecosystems. In contrast toTian et al.'s [2010] investigation of the soil stoichiometric ratio, the present study and that of Cleveland and Liptzin [2007] used data collected at soil depths of either 0–10 or 0–20 cm. Moreover, the last study only used 186 observations to perform a global analysis. Thus, the soil samples only coming from topsoils and a few hundred samples might not be representative for this type of soil stoichiometric ratio analysis. To more firmly demonstrate that the atomic C:N:P ratios of SMB are analogous to the ratios of the entire soil profile, further studies are needed. Such studies should involve a large global data set including SOC, TSN, and TSP measurements for soil profiles and SMB C, N and P measurements in topsoils as well as an analysis of the vertical trend of the atomic C:N:P ratios for SMB in contrasting soil profiles.

3.4. Influence of the Landscape on the Soil and Soil Microbial Biomass Atomic C:N:P Ratios

3.4.1. Soil Atomic C:N:P Ratio

[21] Although the soil C:N ratios were well-constrained (6.9–14.6), significant differences were detected between the three landscapes (Table 2). The soil C:P and N:P ratios were also significantly different between the three landscapes. Compared to each other, the latter two ratios exhibited the following descending order: Dacai > Pantang > Yuanjiang (Table 2 and Figure 5a), corresponding to karst mountain > low hill > lowland (or floodplain) and following an increasing trend for P inputs to these subtropical ecosystems. On average, the soil atomic C:N:P ratios at Dacai, Pantang and Yuanjiang were 100.5:9.1:1, 71.5:7.5:1 and 63.7:5.9:1 (equivalent to 38.9:4.1:1, 27.7:3.4:1 and 24.7:2.7:1 on a mass basis), respectively, showing a clear descending trend (Table 2 and Figure 5a). Landscapes are usually characterized by landforms (e.g., mountains, hills, and plains) and their corresponding vegetation types, which are either naturally adapted (e.g., trees, shrubs, and grasses) or introduced by human activities (e.g., commercial tree and crop plantations). In terrestrial landscapes, C, N and P are often mixed via a number of weak natural forces (e.g., parent material weathering, plant uptake/litterfall return, biogeochemical transformation in soil, transport through surface/lateral/groundwater movement, soil erosion and deposition, soil-atmosphere exchange and even natural disasters such as earthquakes and landslides) and anthropogenic activities (e.g., land-use conversion, tillage, irrigation, fertilization and burning) [Jenny, 1941; McGroddy et al., 2008; Tian et al., 2010]. Therefore, in the long-term, an “elemental stoichiometric balance” or an “ecological elemental stoichiometry” could be established to bridge the ecological interactions of multiple chemical elements in terrestrial ecosystems [Elser et al., 2000; Sterner and Elser, 2002]. Each landscape could exhibit a unique atomic C:N:P ratio represented by its own elemental signature. This hypothesis appeared to apply in the present study. As mentioned previously, our three landscapes exhibited significantly different soil C:N:P ratios, which may have been due to the differences in their parent materials, soil types, land-use types and related land management, especially the P fertilizer inputs (Table 1). However, it is likely that this type of elemental signature for a specific landscape will evolve and be dynamic over time.

image

Figure 5. The soil and soil microbial biomass atomic C:P and N:P ratios summarized for (a) different landscapes and (b) different land-use types.

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3.4.2. Soil Microbial Biomass Atomic C:N:P Ratio

[22] As indicated in Table 3 and Figure 5a, the C:N:P ratios in the SMB did not exhibit a clear descending trend in all three landscapes. Importantly, in the Dacai and Pantang landscapes, the C:N:P ratios in the SMB were fully in parallel with the trend in the soil atomic C:N:P ratios. The SMB C:P ratios were significantly different between Dacai (84.3), Pantang (59.0) and Yuanjiang (71.5), as were the SMB N:P ratios between Dacai (6.5), Pantang (4.8) and Yuanjiang (8.7), suggesting that in addition to the soil environment, other factors might control the variation and pattern of the SMB atomic C:N:P ratios, such as the vegetation type and related land management practices, which might impact the SMB population and chemical composition [Ehlers, 2010].

3.4.3. Relationship Between the Soil and Soil Microbial Biomass Atomic C:N:P Ratios

[23] The correlations between the elemental ratios in the soil and SMB varied among the three landscapes. As indicated in Table 4, the strongest correlations (all significant) in the three landscapes were observed between the C:P ratios in the soil and SMB, while the weakest correlations (all non-significant) were found for the N:P ratios in the landscapes. All correlations between the soil and SMB C:P ratios were significant for Dacai (r = 0.59,p < 0.001), Pantang (r = 0.54, p < 0.001) and Yuanjiang (r = 0.22, p< 0.001). In contrast, correlations between the soil and SMB N:P ratios were non-significant, with correlation coefficients of −0.07 (p = 0.100), 0.07 (p = 0.154) and 0.04 (p = 0.673) for Dacai, Pantang and Yuanjiang, respectively. For the C:N ratios in the soil and SMB, significant correlations were observed for Dacai (r = 0.32, p < 0.001) and Pantang (r = 0.16, p < 0.001), but not evident for Yuanjiang (r = −0.05, p = 0.532). In general, there was an essential declining trend in the correlations of the C:N and C:P ratios (but not of the N:P ratios) between the soil and SMB in the following order: karst mountain > low hill > lowland, which was inversely related to the trend of increasing agricultural intensification characterized by increasing application rates of N and P fertilizers from the mountain to the lowland (Table 1).

3.5. Influence of Land-Use on Soil and Soil Microbial Biomass Atomic C:N:P Ratios

3.5.1. Soil Atomic C:N:P Ratio

[24] The obtained soil atomic C:N:P ratios indicated similar patterns for the land-use types considered. As depicted inTable 2, the soil C:N ratios for the upland (9.8) and woodland (9.6) were very similar, and both ratios were significantly lower than that for the paddy field (10.4). The soil C:P and N:P ratios were also very similar in the upland (56.0 and 5.9, respectively) and in the woodland (56.7 and 5.9, respectively) but were significantly lower than those in the paddy field (101.2 and 10.0, respectively) (Table 2 and Figure 5b). The soil atomic C:N:P ratios in the paddy field, upland and woodland were 101.2:10:1, 56:5.9:1 and 56.7:5.9:1 on average (equivalent to 39.2:4.5:1, 21.7:2.7:1 and 21.9:2.7:1 on a mass basis), respectively, and therefore, the dry land ecosystems (upland and woodland) exhibited almost identical atomic C:N:P ratios, which were much lower than that in the lowland paddy ecosystem (an artificial wetland system).

[25] Due to the differences in parent materials and land management practices, the three land-use types all individually exhibited a clear trend in the soil atomic C:N:P ratio in the three landscapes (Tables 1 and 2). For instance, the soil C:N:P ratios of the paddy field presented the following order: Dacai > Pantang > Yuanjiang, because of, we believe, different parent materials and fertilizer N and P application rates, so did those of the upland; whereas for the woodland (only in Dacai and Pantang), only the difference in parent materials (limestone versus Quaternary red earth) was regarded as playing a determining role in differentiating the soil C:N:P ratios.

[26] Within each landscape, the different land-use types presented different soil atomic C:N:P ratios (Table 2). Such different ratios were mainly due to the differences in elevation, vegetation type and land management practices (e.g., fertilizer N and P application and irrigation) (Table 1). The soil C:N:P ratio in the woodland (51.7:5.5:1) in Pantang, which was lower than those in the paddy field and upland, was also of note. Because the TSP content in red soils developed from highly weathered Quaternary red earth is usually very low, a high soil C:N:P ratio in the woodland is normally expected; unfortunately, this pattern was not observed in Pantang. There might be two reasons for this discrepancy in the Pantang woodland: (i) the SOC content is abnormally low, as was confirmed (see Data Set S1 in the auxiliary material); or (ii) the soil is subject to P fertilizer application, which seems unlikely in this woodland, though it might have occurred during 1950s–60s in the tumultuous Chairman Mao era. Compared with the present study, previous studies reporting differences in soil C:N:P ratios focused more on land-use. For example, in the global data set of 186 samples,Cleveland and Liptzin [2007] found that the average soil atomic C:N:P ratio in forest (212:15:1) is significantly greater than that in grassland (166:12:1). Aponte et al. [2010] presented a Spanish data set indicating that the average soil C:N:P ratio in forest is slightly greater than that in woodland (recalculated from Aponte et al. [2010, Table 2]).

3.5.2. Soil Microbial Biomass Atomic C:N:P Ratio

[27] Diverse patterns of SMB C:N:P ratios were obtained from different land-use types. As indicated inTable 3, the pattern of SMB C:N ratios observed among the land-use types was similar to that in the corresponding soils. The SMB C:P ratios, however, were significantly different between land-use types (Table 3 and Figure 5b), and they presented the following clear descending order: paddy field (85.7) > upland (55.9) > woodland (42.4). Although the SMB N:P ratios in the paddy field (5.7) and woodland (5.5) showed very little difference, they were both significantly lower than that in the upland (7.2). In general, there was essentially a decreasing trend for the SMB C:N:P ratios in the paddy field (85.7:5.7:1), upland (55.9:7.2:1) and woodland (42.4:5.5:1) in the study region.

[28] Unlike the soil C:N:P ratios (Table 2), the SMB C:N:P ratios found for the three land-use types did not present an obvious trend across the landscapes characterized by parent materials or land management (Table 3). This finding might suggest that the chemical composition of SMB at a specific time is highly complex. Moreover, in addition to the parent material, land-use type and related land management practices, other factors beyond the scope of our current data framework (such as the nutrient balance or manure application) may also play a role and be included for analysis.

[29] Within each landscape, different land-use types exhibited different SMB C:N:P ratios (Table 3), although the trend of these ratios between land-use types was poorly explained systematically by the information listed inTable 1. Similar to the soil C:N:P ratio, the SMB C:N:P ratio in the woodland in Pantang (39.5:4.5:1) was also the lowest among the three land-use types and all three landscapes (Table 3). The reasons underlying this finding could be similar to the previously described factors determining the soil C:N:P ratio in the woodland in the same landscape. Overall, the findings of this study might support the work done by Paul and Clark [1996], Yeates and Saggar [1998], Cleveland and Liptzin [2007], and Aponte et al. [2010]that different land-use types (or vegetation types) associated with various ecological processes and land management practices may contribute to differences in the community structure and biomass of soil microbes. For instance,Yeates and Saggar [1998] found that the conversion of pine forest to native grass in New Zealand resulted in a ∼40% decline in SMB C and a ∼30% increase in the SMB C:P ratio, which suggests that changes in land use can influence SMB elemental stoichiometry. Cleveland and Liptzin [2007] also reported a significant difference in the SMB C:N:P ratios between grasslands (48:5:1) and forests (74:9:1) at a global scale, and Aponte et al. [2010] indicated different SMB C:N:P ratios existing between woodlands (75:9:1) and forests (85:11:1) in a Spain data set.

3.5.3. Relationship Between the Soil and Soil Microbial Biomass Atomic C:N:P Ratios

[30] The correlations between the soil and SMB elemental ratios under the three land-use types were much more informative than the results from the three landscapes. As indicated inTable 4, the strongest correlations (all significant) for the three land-use types were observed between the C:P ratios in the soil and SMB, while the weakest correlations were found between the soil and SMB N:P ratios. All of the correlations between the soil and SMB C:P ratios were significant for the paddy field (r = 0.52,p < 0.001), upland (r = 0.14, p = 0.020), and woodland (r = 0.44, p < 0.001). Additionally, the correlations between the soil and SMB C:N ratios were all significant for the paddy field (r = 0.20, p < 0.001), upland (r = −0.13, p = 0.036) and woodland (r = −0.40, p < 0.001). Regarding the correlations between the soil and SMB N:P ratios, a significant relationship was only found for the woodland (r = 0.59, p < 0.001). There were no significant correlations found for the paddy field (r = −0.08, p = 0.052) or upland (r = −0.08, p= 0.187). Woodland is a special and widely distributed land-use type in southern subtropical China and one where there are generally no external anthropogenic inputs of applied N and P fertilizers or other types of land management practices performed. The significant positive correlation between the atomic C:P ratios in the soil and SMB in the woodland is not surprising because this correlation existed in the paddy field and upland as well. However, the correlation between the N:P ratios in the soil and SMB (r = 0.59,p < 0.001) in the woodland is of particular interest because it is the only significant association detected between the soil and SMB N:P ratios in this study. The two significant positive correlations noted above might indicate that the soil microbes in the woodland in southern subtropical China exhibited weak homeostasis and that their chemical C, N, P composition is dependent on the resources in the soil environment. However, the negative significant correlation between the soil and SMB C:N ratios in the woodland is clear (r = −0.40, n = 214, p < 0.001), but difficult to explain. This finding could indicate the existence of C limitation in the woodland soil. C limitation may occur when woodland ecosystems, dominated by coniferous masson pines in southern China, produce very low quality litter and thus result in a very small amount of litter C contributing to the soil humus C [Yan et al., 2006], which may well be theoretically governed by the SMB ability of adapting to poor nutrient conditions (such as very low P, see Data Set S1 in the auxiliary material) by greatly reducing their C use efficiency [Manzoni et al., 2010]. Additionally, N deposition in the region has been substantially increased either by air pollution or by increased anthropogenic reactive N emissions in recent years [Liu et al., 2011]. However, the actual mechanism underlying this significant negative correlation between the soil and SMB C:N ratios in the woodland remains unclear; to clarify this mechanism, further investigations and more specific experiments are required. Although large amounts of N and P fertilizers were applied to the fields to ensure high yields for crop production, the SMB in the paddy field and upland clearly showed N and P dependence on the soil environment. However, the nutrient removal by grain harvest and a number of process losses (e.g., gas emissions, leaching, soil erosion, etc) from the cropping systems in southern China were substantial, particularly with respect to N [Zhu and Chen, 2002; Zhang et al., 2003]. In the study region, there is usually one crop season each year in the upland, involving crops such as sweet potato or maize, while the paddy field is always double rice cropped. Thus, compared to the paddy field, the upland receives approximately half the amount of N, the same or a greater amount of P fertilizer and very little return of crop residues (Table 1). Consequently, based on the correlations between the soil and SMB C:N and C:P ratios found for these two land-use types, the SMB in the upland exhibited weaker N and P dependence on the soil environment compared to the SMB in the paddy field (Table 4).

[31] Individually, significant correlations between the soil and SMB C:N:P ratios in the paddy field were only found in Dacai (karst mountain) and Pantang (low hill) and not in Yuanjiang (lowland) (Table 4), where the agricultural activity was much more intensive (Table 1). Because there was a low nutrient demand in the upland, the SMB associated with this land-use type only exhibited N and P resource dependence in Dacai; additionally, SMB only exhibited P resource dependence on the soil environment in Pantang. For the woodland, which is a special category of land-use in the region, significant correlations between the soil and SMB C:P (r = 0.46,p < 0.001) and N:P (r = 0.47, p < 0.001) ratios were observed only in Pantang and not in Dacai. This result could be explained by the differences in nutrient availability and plant nutrient demand between the woodlands in these two landscapes. On average, the SOC (1.894 mol C kg−1), TSN (0.161 mol N kg−1) and TSP (0.0198 mol P kg−1) contents in the woodland in Dacai were almost twice the contents (0.755 mol C kg−1, 0.082 mol P kg−1 and 0.0148 mol P kg−1, respectively) in Pantang (see Data Set S1 in the auxiliary material). The Dacai woodland was covered with lower-biomass shrubs, ferns and masson pines, and consequently it had less nutrient demand. In contrast, the Pantang woodland was associated with higher-biomass masson pines and greater nutrient demand.

[32] The correlations of the C:N:P ratios between the soil and the SMB varied differently in each landscape. For instance, in Dacai (karst mountain), a descending trend of the correlations between the soil and SMB C:N and C:P ratios was observed in the following order: paddy field > upland > woodland. This trend paralleled the decreasing intensification of anthropogenic activities. However, in Pantang, this trend was only observed in the paddy field and upland, but not in the woodland. There was also no clear trend of the correlations of the C:N:P ratios between the soil and the SMB observed among the land-use types in Yuanjiang.

[33] In summary, the relationships between the soil and SMB C:N:P ratios under three different land-use types found in the present study were statistically significant, suggesting a possible weak homeostasis in the SMB in the region. This finding might ultimately be related to the balance of nutrients in the soils, which was attributable to litterfall patterns or land management practices (e.g., crop rotations, N and P fertilizer use) applied to these land-use types.

4. Conclusions

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Materials and Methods
  5. 3. Results and Discussion
  6. 4. Conclusions
  7. Acknowledgments
  8. References
  9. Supporting Information

[34] In three typical landscapes associated with three different land-use types in southern subtropical China, the atomic C:N:P ratios in the soil (80:7.9:1 on average) and SMB (70.2:6:1 on average) were both considered constrained. The latter elemental ratio was remarkably close to the overall area- and depth-weighted atomic C:N:P ratio (61:5.3:1) for the soils of China [Tian et al., 2010] and to the global average SMB atomic C:N:P ratio (60:7:1) reported by Cleveland and Liptzin [2007]. In our data set, we found significant correlations between the soil and SMB C:N, C:P, and even N:P (mainly in woodland) ratios variably at the region, landscape and land-use type levels, in accordance with the differences in the landscape parent material, land-use type and related land management practices, such as N and P fertilizer application. Weak homeostasis might exist regarding the elemental stoichiometry of the SMB in southern subtropical China.

[35] Our data covered only a small proportion of the subtropical region of China. We believe that the true pattern regarding the relationship between the soil and SMB atomic C:N:P ratios on the Earth will only be revealed when more data associated with various land-use types and large sample sizes are obtained from different climatic zones in countries of all continents around the world and systematically analyzed. Then, the puzzle regarding what is actually regulating SMB elemental stoichiometry can be solved.

[36] Caution is required in the use of data on SMB C, N and P measured using FE procedures, which are fully dependent on laboratory-determined k conversion factors [Ross et al., 1996]. Because the soil microbial community is so diverse, the k conversion factors may vary with the soil types and the seasons when the soil samples are collected. Other SMB extraction methods, such as the cell extraction procedure [Bakken and Lindahl, 1995], could be used for comparison [Ehlers et al., 2010].

Acknowledgments

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Materials and Methods
  5. 3. Results and Discussion
  6. 4. Conclusions
  7. Acknowledgments
  8. References
  9. Supporting Information

[37] This research was financially supported by the National Basic Research Program of China (2011CB100506) and the Chinese Academy of Sciences (KZCX2-YW-423 and the 100 Talents Program). J. Keith Syers, who suddenly passed away in 2011, is sincerely remembered for his invaluable academic contributions to the early version of this manuscript.

References

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Materials and Methods
  5. 3. Results and Discussion
  6. 4. Conclusions
  7. Acknowledgments
  8. References
  9. Supporting Information

Supporting Information

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Materials and Methods
  5. 3. Results and Discussion
  6. 4. Conclusions
  7. Acknowledgments
  8. References
  9. Supporting Information

Auxiliary material for this article contains one data set showing mass and atomic C:N, C:P and N:P ratios of soil and soil microbial biomass in southern subtropical China.

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gbc1938-sup-0001-readme.txtplain text document2Kreadme.txt
gbc1938-sup-0002-ds01.xlsExcel spreadsheet515KData Set S1. The mass and atomic C:N, C:P and N:P ratios of soil and soil microbial biomass in the three landscapes associated with various land-use types in southern subtropical China.
gbc1938-sup-0003-t01.txtplain text document1KTab-delimited Table 1.
gbc1938-sup-0004-t02.txtplain text document2KTab-delimited Table 2.
gbc1938-sup-0005-t03.txtplain text document2KTab-delimited Table 3.
gbc1938-sup-0006-t04.txtplain text document1KTab-delimited Table 4.

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