Storage and spatial patterns of organic carbon of soil profiles in Guangdong province, China.
Global soil organic carbon (SOC) storage is within the range 1200-2500 Pg, which is twice the C in the atmosphere, and two- to threefold greater than that stored in vegetation (Intergovernmental Panel on Climate Change (IPCC) 1990; Schlesinger 1991; Lai 1999; Watson and Noble 2001). SOC plays a significant role in the global C cycle and global warming, and is an important determinant of the physical and chemical properties, as well as productivity, of agricultural soils (Singh et al. 2007). Many factors affect SOC content, such as parent materials, soil texture, climate, soil pH, land use, management, topography and drainage. Optimisation of some factors, especially land use, management and drainage, can increase C sequestration in soils and mitigate climate change (Smith et al. 2000; Lai 2004).
Although routine soil surveys collect C stock data to a depth of 1 m, some studies have focussed primarily on the A horizon, which usually contains the highest soil organic matter (SOM) content (Pan et al. 2003; Wang et al. 2003; Yan et al. 2007; Yu et al. 2007). SOC storage in the 30-100 cm soil horizon accounts for 46-63% of total SOC storage in the first 1 m of the world's soil (Batjes 1996). Tarnocai et al. (2009) observed that, in the northern circumpolar, at least 61 % of total soil C is stored below 30 cm depth. Subsoil C may be more important as a C source or sink than surface soil C (Rumpel and Kogel-Knabner 2011). Subsoil horizons with low C contents may not be saturated in organic C; therefore, they may have the potential to sequester organic C, for example through higher C input into subsoil by roots and dissolved organic carbon (DOC; Lorenz and Lai 2005). Recent studies have concentrated on the stabilisation of organic matter (OM) in subsoils, where subsoil C may become available for microbial decomposition bccause of new C input (Fontaine et al. 2007) or respond to land use or management changes (Guo and Gifford 2002; Wright et al. 2007; Wiesmeier et al. 2015).
SOC storage in China has been reported at the national level. Fang et al. (1996) estimated the national SOC storage at 185.7 Pg, whereas the estimate of Pan (1999) of 50 Pg C represents the lowest value among all the published data for China. Other estimated values are 92.4 Pg (Wang et al. 2001), 70.3 Pg (Wu et al. 2003), 89.14 Pg (Yu et al. 2007) and 83.8 Pg (Li et al. 2007). Few studies have investigated subsoil organic C of soil profiles on a large scale. Because of significant uncertainty induccd by the large variability in soil characteristics throughout the country, it is ncccssary to further estimate SOC at a regional scale. The present study was conducted to: (1) estimate the SOC storage for different soil types and land uses in Guangdong Province; (2) investigate movement trends of SOC from the surface soil to lower horizons in the study area; (3) evaluate the contribution of soil degradation and erosion as driving forces of SOC redistribution and export to the surrounding water. Such results would provide useful information for a rational estimate of SOC storage and environmentally sound management of SOC in the study area.
Materials and methods
Guangdong Province is located in the southern part of south China (Fig. lb; 20[degrees]10'-25[degrees]31'N, 109[degrees]41'-l 17[degrees]17'E). The area has a subtropical monsoon climate with an average annual precipitation of 1336 mm, average annual evaporation of 1100 mm, average annual temperature ranges between 17 and 27[degrees]C and average sunshine of 1828 h. From north to south, the landscape changes from mountain to plateau to flood plain. Hilly areas occupy approximately 60% of the total land area.
The soil area of Guangdong Province is 150 457 [km.sup.2]. The forest area is approximately 116 465 [km.sup.2], accounting for 77.4% of the total soil area, with a high diversity of forest types (Zhou et al. 2008). The area of paddy soil is 16 652 [km.sup.2], accounting for 11.0% of the total area. Pasture and vegetables occupy 10.4% of the total soil area (Fig. la).
Based on the Chinese Soil Taxonomy (National Soil Survey Office (NSSO) 1998), the soils in the study area are classified as Ferrallisols, Anthrosols, Amorphic soils and some other soil types (e.g. semi-hydromorphic soil, hydromorphic soil and saline-alkali soil). Ferrallisols are the most widely distributed soil type across the study area, covering 113 540 [km.sup.2] or approximately 75.5% of the total soil area. The Ferrallisols include four soil great groups: Latosols (main land uses forest and dryland), corresponding to Acrisols in the World Reference Base for Soil Resources by IUSS Working Group WRB (2014); Latosolic Red soils (main land uses forest and dryland), also corresponding to Acrisols (IUSS Working Group WRB 2014); Red soils (main land use forest), corresponding to Cambisols (IUSS Working Group WRB 2014); and Yellow soils (main land use forest), also corresponding to Cambisols (IUSS Working Group WRB 2014). These soils have obvious zonal features across the study area. The horizontal zonal feature consists of (from south to north) Latosols, Latosolic Red soils and Red soils. The vertical zonal feature is that soil groups change from Latosolic Red soils to Red soils to Yellow soils with increasing elevation (Fig. 1 d).
Paddy soils are the major soil group of the Anthrosol class in the study area, and are a unique soil type in China's taxonomy, with a long history of rice cultivation under irrigation (Gong 1999). Generally, a paddy soil profile consists of a cultivated horizon overlying a plough pan. The cultivated horizon shows sorted soil aggregates, vesicular pores and a specific Munsell colour. The plough pan (P-horizon) has a platy structure and a bulk density that is at least 10% higher than that of the cultivated horizon (Huang et al. 2015). Ploughing and puddling are the most common practices of land preparation for rice cultivation. Repeated ploughing and puddling by water buffalos or machines over long periods of time lead to the formation of a compacted P-pan, which reduces percolation and improves water and nutrient efficiency in the paddy fields. Fertiliser application is another important management practice for paddy cultivation to improve soil fertility and increase ricc yield.
The Amorphic soils are the third soil type in the study area, covering an area of 16 502 [km.sup.2] or approximately 10.9% of the total soil area. These soils correspond to the IUSS Working Group WRB's (2014) Cambisols. The other soil classes (semihydromorphic soil, hydromorphic soil and saline-alkali soil) occupy only approximately 3.2% of the total soil area (Fig. 1 d).
Soil samples used in the present study were collected from locations shown in Fig. 1 c. All 211 sample sites were located far from contaminated or urbanised areas. Each soil profile was divided into A, B and C horizons, according to the pedogenic process. All soil samples, free of plant roots, were air dried and crushed by a wooden stick, and then one portion, used for analysis of SOM and total N, was sieved through a 20-mesh nylon screen (aperture size 1 mm) and stored at room temperature (25[degrees]C). A second portion was sieved through a 2-mm nylon screen for analysis of grain size fraction.
The SOM content was measured using wet combustion with [Cr.sub.2][O.sub.7.sup.2-] (Walkley and Black 1934; Wen 1984). Total N was measured using the Kjeldahl method (Liu 1996). The pH of soil was measured by placing 10 g sample in 25 mL deionised water (Chinese National Standard Agency 1998). Soil bulk density was measured using the cylindrical core method (Blake and Hartge 1986). Soil particlc diameters (sand, silt and clay) were measured based on wet and dry sieving techniques and the pipette method (Gee and Bauder 1986).
Calculation of SOC density and SOC storage
SOC density (SOCD) was calculated using the following equation:
[SOCD.sub.ij] = [(1 - [[delta].sub.ij]%) x [[rho].sub.ij] x [C.sub.ij] x [T.sub.ij]]/100
where [SOCD.sub.ij] is the SOC density in the j horizon of the i soil profile, [[delta].sub.ij]% is the volumetric percentage of the >2 mm grain size fraction in the j horizon of the i soil profile, [[rho].sub.ij] is the bulk density in the j horizon of the i soil profile, [C.sub.ij] is the organic C content in the j horizon of the i soil profile and [T.sub.ij] is the thickness of the j horizon in the i soil profile. The organic C content was calculated by multiplying the SOM content by 0.58 (Hollis et al. 2012).
SOC storage in the i soil profile (SOCS,) and total SOC storage in the study area ([SOCS.sub.Total]) were calculated using the following equations:
[SOCS.sub.i] = [3.summation over (j=1)] [SOCD.sub.ij] x [Area.sub.i]
[SOCS.sub.TOTAL] = [N.summation over (i=1)][3.summation over (j=1)][SOCD.sub.ij] X [Area.sub.i]
where [Area.sub.i] represents the area of the i soil profile.
Data processing and statistical analyses
Because all data fit a log normal distribution with a positive skew value (Table 1; Fig. 2), SOC and soil total N contents were log transformed, and the geometric mean was used to represent the central tendency and variation of the data. Minitab version 14 (Minitab Inc, State College, Pennsylvania, USA) was used for all probability and statistical analyses of soil samples.
Results and discussion
SOC concentrations in A-horizon soils ranged from 0.04% to 5.03%, with a geometric mean of 1.18% and an arithmetic mean of 1.45%. In soils from the B horizon, the SOC concentration ranged from 0.02% to 5.24%, with a geometric mean of 0.71% and an arithmetic mean of 0.94%. The SOC concentrations in the C horizon ranged from 0.01% to 4.85%, with a geometric mean of 0.45% and an arithmetic mean of 0.66%. The highest SOC concentration was 5.24%, which was observed in the P-pan of paddy soil. All data had a high positive skew in each horizon soil (Table 1).
From the A to C horizons, soil density increased slightly from 1.16 to 1.17 to 1.20gem 3 respectively (Table 1). The highest soil density was in the P-pan of paddy soil (1.8 g [cm.sup.-3]). Yellow soils had the lowest soil density (arithmetic mean 0.74g [cm.sup.-3]) and highest SOC content (arithmetic mean 3.15%), whereas the Latosols had the highest soil density (arithmetic mean 1.26g [cm.sup.-3]) and the lowest SOC content (arithmetic mean 0.94%).
The mean soil clay content in the A, B and C horizons was 20.45%, 25.27% and 25.93% respectively (Table 1). The highest clay content was 85.22% in the Latosolic Red soils. Soil samples with a higher SOC content generally had a clay content in the range 10-30%. Moreover, in Latosols soils and Latosolic Red soils (WRB Acrisols), the SOC content had a better relationship with a soil clay content than in the other soil types. The possible reason for this phenomenon is that soil organic matter tended to be adsorbed by soil clay under conditions of intensive eluviation.
The mean thickness of the soil horizons increased from 17.0 cm in the A horizon to 29.5 and 48.9 cm in the B and C horizons respectively (Table 1). The highest value was 137 cm in the B horizon for Ferrallisols and Red soil great groups located in the north of the study area. Red soils had the highest soil thickness (arithmetic mean 72 cm). Thus, although Red soils had a low SOC content (arithmetic mean 0.59%), their SOCD was as high as 4.83 kg C [m.sup.-2].
Soil pH values in the A, B and C horizons were 5.77, 5.92 and 6.05 respectively (Table 1). Paddy soils had the lowest soil pH values in the cultivated horizon (3.4), P-pan (3.0) and C-horizon (2.8) in the study area.
Concentration, density and storage of SOC in soil profiles
In the study area, the geometric mean concentration of SOC in A-horizon soils was 1.18%, ranging from 0.04% to 5.03%. The geometric mean SOC concentrations in the B and C horizons were 0.71% and 0.44% respectively (Table 1). SOC storage in the total soil profiles was 1.25 Pg, of which approximately 0.41 Pg SOC was in A-horizon soils, 0.51 Pg SOC was in B-horizon soils and 0.33 Pg SOC was in C-horizon soils. The subsoil was the primary location for total SOC storage in the study area. The mean SOC density of 8.31 kg C [m.sup.-2] was close to that reported by Wu et al. (2003) in China (8.01 kg C [m.sup.-2]), but lower than that reported by Wang et al. (2001), i.e. 10.53 kg C [m.sup.-2].
In the study area, soil samples with high SOC density, primarily forest soils and paddy soils, were distributed in the north of Guangdong Province and soil samples with a low SOC density were distributed in the southern region of the study area (Fig. 3). This regional difference in SOC density was closely related to regional hydrothermal changes from south to north in the study area. The average annual temperature in the north of Guangdong Province is approximately 18.8[degrees]C, but in the Leizhou Peninsula (in the south of Guangdong Province) the average annual temperature is 23.2[degrees]C. Thus, the regional difference in SOC density observed in the present study may be the result of differences in the mineralisation rate of SOC controlled by regional temperature (Lai 2004). As such, this further confirms that SOC content is dependent on biomass production and the mineralisation intensity of organic matter in different soil types, which are controlled primarily by hydrothermal conditions (NSSO 1998; Wu et al. 2003). Although soil clay should have some effect on changes in SOC, only weak positive correlations were found in the present study between soil clay content and SOC (Table 2).Thesc weaker correlations may be the result of the very rapid weathering of parent rock in the study area. Because of the short soil formation process and intensive weathering, the soil clay content was predominantly controlled by the mineral components and texture of the parent rocks (GSGIO 1993; Zhang et al. 2008). Moreover, for paddy soils with a high SOC density in the northern region of the study area, the classical cultivation method consists of rice field-upland field rotation. A considerable proportion of rice straw is removed from soils after harvesting to make it easier to plant vegetables. The input of organic matter to soils is generally dependent on the use of fertilisers. Thus, agricultural activity, such as cultivation and fertilisation, are also important causes of differences in SOC density.
SOC content, density and storage by soil type Ferrallisols
The Ferrallisol area was 113 540 [km.sup.2], approximately 75.5% of the total soil area in the study area. Ferrallisols include four soil groups (Latosols, Latosolic Red soils, Red soils and Yellow soils), as described in the Chinese soil taxonomy (NSSO 1998).
Hydrothermal conditions have an obvious influence on changes in SOC content in the study area. From south to north, the temperature and rainfall in the study area decreased gradually. As the leaching and mineralisation intensity weakened along this gradient, the mean SOC content and mean SOC density of A-horizon soils increased; from Latosols to Latosolic Red soils to Ted soils, SOC content increased from 0.94% to 1.08% to 1.52% respectively, whereas SOCD increased from 0.91 to 2.15 to 2.53 kg C[m.sup.2] (Table 3). The Yellow soils in the study area generally developed in areas at high elevation (>800 m) because of the cooler conditions there that are favourable to the accumulation of soil organic matter. The mean A-horizon SOC content in the yellow soils was 3.15% and the mean SOC density and profile SOC density were 4.45 kg C[m.sup.-2] and 11.23 kg C[m.sup.-2], respectively.
In the study area, the SOC densities of the subsoil were significantly higher than in A-horizon soils, except for Yellow soils (Table 3). From Latosols, Latosolic Red soils to Red soils, the SOC storage of subsoils was approximately 3.4-, 2.7- and 1.9-fold higher than in corresponding A-horizon soils respectively. However, in the case of Yellow soils, the subsoil organic carbon storage was lower than in the A-horizon soil because of the higher SOC content of A-horizon soils, thinner soil thickness of B-horizon soils and weaker leaching compared with other soils. The profile SOC density increased with soil type from Latosols to Latosolic Red soils to Red soils and to Yellow soils as follows: 4.74, 8.11, 9.66 and 11.23 kg C[m.sup.-2] respectively. The profile SOC density should be closely related to zonal hydrothermal conditions. With a decrease in both rainfall and temperature, the leaching and mineralisation intensity weakened, and so SOC content and SOC density in the profiles increased along this gradient. As a result, SOC was primarily controlled by hydrothermal conditions in the study area.
For the Ferrallisols, the profile SOC density was approximately 8.60 kg C[m.sup.-2], slightly higher than the average level of Chinese soil (-8.0 kg C [m.sup.-2]; Wu et al. 2003). SOC storage in Ferrallisols was approximately 0.976 Pg for the total soil profile, accounting for 78.1% of total SOC storage, of which 0.313 Pg SOC was in A-horizon soils. The SOC storage of the subsoil was 2.12-fold higher than that of A-horizon soils in the study area.
Paddy soil is the major soil group of the Anthrosol class in the study area. The area of paddy soils accounted for approximately 11.0% of the total soil area. The SOC storage in paddy soils was 0.17 Pg, accounting for 13.47% of total SOC storage (Table 3), of which 0.054 Pg SOC was in the upper plough horizon, 0.044 Pg SOC was in the P-pan horizon and 0.07 Pg SOC was in the C-horizon.
Previous studies have indicated that both a high input of organic material (Yang et al. 2005) and reduccd decomposition rates under anaerobic conditions (Sahrawat 2003) contribute to the accumulation of organic carbon in paddy soils. In addition, some studies have shown that long-term rice cultivation could result in a downward transport of organic carbon from the surface horizon and its accumulation in subsoils (Brauer et al. 2013, 2012; Ci and Yang 2013). In the study area, the mean SOC content in C-horizon soils (0.81%) and in the P-pan horizon (1.14%) was much higher than in other soil types. This confirms that, at the regional scale, the SOC of surface soils in paddy soils can be transferred to the subsoil horizons more easily due to long-term ricc cultivation. As a result, the mean SOC density in the C-horizon was up to 4.74 kg C[m.sup.-2], much higher than that in the A-horizon soils (3.09 kg C[m.sup.-2]) and P-pan soils (2.73 kg C[m.sup.-2]). The profile SOC density was 10.21kgC[m.sup.-2], higher than that of the Ferrallisols (8.60 kg C[m.sup.-2]). The SOC storage of subsoils was approximately 2.1-fold higher than in the A-horizon soils in the paddy soil area.
The Amorphic soil area was 16 502 [km.sup.2], accounting for 10.9% of the total soil area. These soils are generally part of the Inceptisols in the soil classification system (Soil Survey Staff 1999). The SOC storage in Amorphic soils was 0.083 Pg (Table 3). The thickness of the A-horizon soil was approximately 14.5 cm, thinner than that of the other soil types because of the short time for soil formation and soil loss in the study area. The profile SOC density of Amorphic soils was 5.03 kg C [m.sup.-2], lower than that of other soil types. SOC storage in B-horizon soils was much higher than in A-horizon soils (0.040 vs 0.026 kg C [m.sup.-2] respectively). The subsoil was still the primary location of SOC storage in the Primarosol soil profile.
Effects of land use on SOC storage and sequestration Forest soil
Forest soil is the most important SOC pool. Dixon et al. (1994) noted that as much as two-thirds of terrestrial C in forest ecosystems is contained in soils. In Guangdong Province, the forest area is 116 465 [km.sup.2], accounting for 77.4% of the total soil area. Forest SOC storage was approximately 1.0 Pg, accounting for 80.27% of total storage. The B-horizon soils had the highest SOC storage (0.425 Pg), followed by the A- and C-horizon soils (0.33 and 0.246 Pg respectively; Table 4). The mean SOC density of forest soil profiles was 8.58 kg C [m.sup.-2] in the study area, much lower than the previously published value (14.3 kg C [m.sup.-2]) in China (Yu et al. 2007). Zhou et al. (2008) reported that the carbon storage of forest vegetation in Guangdong Province has increased steadily from 0.17 x 1012 kg in 1994 to 0.21 x 1012 kg in 2008, and that the ratio of soil C : plant C is approximately 5. This value is much higher than the ratio of 1.2 reported in China by Dixon et al. (1994) and Lai (2005), suggesting the forest vegetation still has a higher potential for C sequestration in Guangdong Province.
In the study area, pasture and vegetables occupy 10.4% of the total area. The SOC storage in drylands was only 0.073 Pg, accounting for 5.81% of total SOC storage. The profile SOC density was low, at 4.65 kg Cm 2. The SOC storage in the subsoil horizon was approximately 3.3-fold higher than in Ahorizon soils (Table 4). Lai (2005) noted that agricultural soils, and especially eroded agricultural soils, usually contain store less SOC than their potential capacity. Afforestation of these degraded soils can mitigate some of the degradation processes and lead to C sequestration and SOC storage (Ross et al. 2002).
Compared with dryland cultivation, irrigation-based rice cultivation in Guangdong has led to significant enrichment of SOC storage (0.17 Pg) in paddy soils (Table 4). In Guangdong Province, approximately 57% of SOC storage (0.3 Pg) is in paddy soils (Pan et al. 2003). Pan et al. (2003) estimated that the current C sequestration rate in the plough horizon was 0.022 kg C [m.sup.-2] annually in Guangdong Province based on data from national soil monitoring sites of paddy soils and some long-term pilot experiments. According to this rate, the SOC sequestration potential in the paddy area in Guangdong Province is approximately 3.56 Tg C annually.
Generally, subsoil is important for SOC storage regardless of land use type. Soil cultivation is not generally associated with a strong decline in SOC because tillage can promote the formation of organic-mineral associations, and dilution of SOC caused by a deepening of the topsoil probably decreases SOM decomposition (Don et al. 2013; Wicsmeicr et al. 2015).
Correlations between SOC, soil total nitrogen and other soil properties
Pearson correlation coefficients for correlations among SOC, total nitrogen (TN) and soil properties are given in Table 2. Linear trends between soil properties (soil density, clay content and soil pH) and SOC concentrations were mostly nonsignificant (Table 2). Pearson correlation coefficients between SOC and soil TN in the A, B and C horizons were 0.86, 0.87 and 0.62 respectively (Table 2). These correlations indicate that, in the study area, soil samples with high soil TN have a higher capacity for SOC sequestration, whereas soil samples with low soil TN have a limited capacity for SOC sequestration. Kirkby et al. (2011, 2014) pointed out that there was a constant stoichiometric ratio of C: N in SOM across a wide range of global soils. Such a ratio may imply that SOC levels could be limited by the supply of N and not just by C input. In subsoils, the C: N ratio is generally characterised by very low organic matter contcnt, and high N content may be related to the presence of mineral N sorbed to clay surfaces (Jenkinson and Coleman 2008), which could suggest subsoils still have a large potential for C sequestration.
There were significant correlations between SOC content in different horizons, with correlation coefficients of 0.767 between the A and B horizons and 0.774 between the B and C horizons. There were also significant correlations between TN in different horizons with r-values of 0.731 between the A and B horizons and 0.632 between the B and C horizons (Fig. 4). These correlations could suggest that there is movement of SOC and soil TN from A-horizon soils to much lower horizons because of farming practices and intensive eluviation in the study area. Fontaine et al. (2007) reported that the movement of SOC from the surface soil to the lower horizon increases the distribution of fresh C along the soil profile; the delivery of fresh C to the subsoil could stimulate the loss of ancient buried C. Thus, SOC storage in the subsoil at the large regional scale may be decided by both the potential for C sequestration and the loss of ancient buried C.
SOC export and redistribution induced by soil erosion and degradation
Soil erosion is a global issue that is responsible for the removal of considerable quantities of topsoil (Lai 2001), which may continue and perhaps be exacerbated by projected extremes. Many studies have indicated that water, tillage and wind erosion contribute significantly to the loss and redistribution of SOC across the landscape, with both soil and SOC being redeposited within the field, as well as being moved off the field (Smith et al. 2001; McCarty and Ritchie 2002; Ritchie et al. 2007). Most degraded soil, which has lost a large fraction of the SOC pool, can be restored by adopting judicious land use practices (Lai 2004). Moreover, Chappell et al. (2016) indicated that SOC erosion was an important factor in estimating global SOC cycling schemes.
In the study area, the area of soil erosion and degradation is approximately 14 200 [km.sup.2] and is primarily distributed along the Hanjiang, Bcijiang, Dongjiang and Jianjiang watersheds (Wan 2005). The median value of sediment delivery ratio is 0.39 in the Pearl River Watershed (Li and Liu 2006). The geometric mean of SOC density in A-horizon soils is 2.13 kg C[m.sup-2]. According to these data, as a rough estimate, approximately 1.18 x 1010 kg SOC enters the river water annually because of soil degradation and erosion, accounting for 2.9% of the SOC storage of A-horizon soils. Approximately 1.85 x [10.sup.10]kg SOC was redistributed in surfacc soils of the study area each year. Recent studies indicate that soil erosion and subsequent redistribution within fields can stimulate C sequestration in agricultural ecosystems (Ritchie et al. 2007; VandenBygaart 2001; Hao et al. 2001). Therefore, restoring degraded soils and ecosystems could have high potential for sequestering soil C in these areas.
Based on the data of soil profiles investigated, we have comparatively examined the distribution and storage of SOC among different soil and land use types. The results reveal that the forest has the largest SOC storage, and paddy soils have the highest SOC density in Guangdong Province. Because of intensive eluviation, the SOC of surfacc soils can enter subsoils along a soil profile. Subsoil is an important SOC storage, with SOC storage in subsoils approximately twofold higher than that in A-horizon soils. Soil degradation and erosion have caused significant SOC loss in A-horizon soils in the study area, with the amount of SOC loss estimated to be 11.8 Tg annually. Improved land management, restoring degraded soil and controlling soil erosion in the study area may contribute significantly to the sequestration of C from the atmosphere.
This work was funded by grants from the National Natural Science Foundation of China (31270516, 41171387, 41171446), the Natural Science Foundation of Guangdong Province, China (S2012030006144), the Science and Technology Planning Project of Guangdong Province, China (2012A020100003 and 2011B030900013), the Science and Technology Planning Project of Guangzhou (2013J2200003) and the National Key Technologies R&D Program in the 12th Five year Plan of China (2012BAH32B03-5).
Batjes NH (1996) The total C and N in soils of the world. European Journal of Soil Science 47, 151 163. doi:10.1111/j.1365-2389.1996.tb01386.x
Blake GR, Hartge KH (1986) Bulk density. In "Methods of soil analysis'. (Ed. A Klute) pp. 363-376. (American Society of Agronomy: Madison, Wl)
Brauer T, Grootes PM, Nadeau MJ, Andersen N (2012) Downward carbon transport in a 2000-year rice paddy soil chronosequence traced by radiocarbon measurements. Nuclear Instruments & Methods in Physics Research. Section B, Beam Interactions with Materials and Atoms 294, 584-587. doi:10.1016/j.nimb.2012.07.012
Brauer T, Grootes PM, Nadeau MJ (2013) Origin of subsoil carbon in a Chinese paddy soil chronosequence. Radiocarbon 55, 1058-1070. doi: 10.2458/azujs_rc.55.16367
Chappell A, Baldock J, Sanderman J (2016) The global significance of omitting soil erosion from soil organic carbon cycling models. Nature Climate Change 6, 187 191. doi:10.1038/nclimate2829
Chinese National Standard Agency (1998) Determination of pH value in forest soil. GB 7859-87, UDC 634.0.114:631.422 171-173. Standardization Administration of the People's Republic of China, Beijing.
Ci E, Yang L (2013) Paddy soils continuously cultivated for hundreds to thousands of years still sequester carbon. Acta Agriculturae Scandinavica, Section B - Soil and Plant Science 63, 1-10.
Dixon RK, Brown S, Houghton RA, Solomon AM, Trexler MC, Wisniewski J (1994) Carbon pools and flux of global forest ecosystems. Science 263, 5144.
Don A, Rodenbeck C, Gleixner G (2013) Unexpected control of soil carbon turnover by soil carbon concentration. Environmental Chemistry Letters 11, 407 413. doi: 10.1007/s 10311-013-0433-3
Fang JY, Liu GH, Xu SL (1996) Carbon cycling in terrestrial ecosystems in China. In 'Studies on emissions and their mechanisms of greenhouse gases in China'. (Eds GC Wang, Y Wen) pp. 129-139. (Environment Science Publishing House: Beijing, China)
Fontaine S, Barot S, Barre P, Bdioui N, Mary B, Rumpel C (2007) Stability of organic carbon in deep soil layers controlled by fresh carbon supply. Nature 450, 277 280. doi:10.1038/nature06275
Gee GW, Bauder JW (1986) Particle-size analysis. In 'Methods of soil analysis. Part 1. Physical and mineralogical methods'. (Ed. A Klute) pp. 377 382. (American Society of Agronomy: Madison, WI)
Gong Z (1999) 'Chinese soil taxonomic classification.' (China Science Press: Beijing, China)
Guangdong Soil General Investigation Office (GSGIO) (1993) 'Guangdong soil.' (Science Publish House: Beijing, China)
Guo LB, Gifford RM (2002) Soil carbon stocks and land use change: a meta analysis. Global Change Biology 8, 345-360. doi: 10.1046/j.1354-1013.2002.00486.x
Hao Y, Lai R, Izaurralde RC, Ritchie JC, Owens LB, Hothem DL (2001) Historic assessment of agricultural impacts on soil and soil organic carbon erosion in an Ohio watershed. Soil Science 166, 116-126. doi: 10.1097/00010694-200102000-00005
Hollis JM, Hannam J, Bellamy PH (2012) Empirically-derived pedotransfer functions for predicting bulk density in European soils. European Journal of Soil Science 63, 96 109. doi: 10.1111/j.1365-2389.2011. 01412.x
Huang LM, Thompson A, Zhang GL, Chen LM, Han GZ, Gong ZT (2015) The use of chronosequences in studies of paddy soil evolution: a review. Geoderma 237-238, 199 210. doi:10.1016/j.geoderma.2014.09.007
Intergovernmental Panel on Climate Change (IPCC) (1990) Climate change: the IPCC scientific assessment. In 'Report prepared for Intergovernmental Panel on Climate Change by Working Group I'. (Eds JT Houghton, GJ Jenkins, JJ Ephraums) pp. 287-309. (Cambridge University Press: New York. NY)
IUSS Working Group WRB (2014) World reference base for soil resources 2014. International soil classification system for naming soils and creating legends for soil maps. World Soil Resources Reports No. 106, FAO, Rome, Italy.
Jenkinson DS, Coleman K (2008) The turnover of organic carbon in subsoils. Part 2. Modelling carbon turnover. European Journal of Soil Science 59, 400-413. doi: 10.1111/j.1365-2389.2008.01026.x
Kirkby C, Kirkegaard J, Richardson E, Wade LJ, Blanchard C, Batten G (2011) Stable soil organic matter: a comparison of C:N:P:S ratios in Australian and other world soils. Geoderma 163, 197-208. doi: 10.1016/ j.geoderma.2011.04.010
Kirkby Ca, Richardson All, Wade LJ, Passioura JB, Batten GD, Blanchard C, Kirkegaard Ja (2014) Nutrient availability limits carbon sequestration in arable soils. Soil Biology & Biochemistry 68, 402-409. doi: 10.1016/ j.soilbio.2013.09.032
Lal R (1999) World soils and the greenhouse effect. Global Change Newsletter 37, 4-5.
Lal R (2001) Soil degradation by erosion. Land Degradation & Development 12, 519-539. doi: 10.1002/ldr.472
Lal R (2004) Soil carbon sequestration to mitigate climate change. Geoderma 123, 1 22. doi:10.1016/j.geoderma.2004.01.032
Lal R (2005) Forest soils and carbon sequestration. Forest Ecology and Management 220, 242 258. doi:10.1016/j.foreco.2005.08.015
Li ZG, Liu B (2006) Calculation on soil erosion amount of main river basin in China. Science of Soil and Water Conservation 4, 1-6.
Li ZP, Han FX, Su Y, Zhang TL, Sun B, Monts DL, Plodinec MJ (2007) Assessment of soil organic and carbonate carbon storage in China. Geoderma 138, 119-126. doi:10.1016/j.geoderma.2006.11.007
Liu G (1996) 'Soil physical and chemical analysis and description of soil profiles.' (Standards Press of China: Beijing, China) [in Chinese]
Lorenz K, Lai R (2005) The depth distribution of soil organic carbon in relation to land use and management and the potential of carbon sequestration in subsoil horizons. Advances in Agronomy 88, 35 66. doi: 10.1016/S0065-2113(05)88002-2
McCarty G, Ritchie JC (2002) Impact of soil movement on carbon sequestration in agricultural ecosystems. Environmental Pollution 116, 423-430. doi: 10.1016/S0269-7491 (01)00219-6
National Soil Survey Office (NSSO) (1998) 'Soils of China.' (China Agricultural Press: Beijing, China) [in Chinese]
Pan GX (1999) Estimates of soil organic and inorganic carbon pools of China. Bulletin of Science and Technology 15, 330-332. [In Chinese]
Pan G, Li L, Wu L, Zhang X (2003) Storage and sequestration potential of topsoil organic carbon in China's paddy soils. Global Change Biology 10, 79-92. doi: 10.1111/j.1365-2486.2003.00717.x
Ritchie JC, McCarty GW, Vcnteris ER, Kaspar TC (2007) Soil and soil organic carbon redistribution on the landscape. Geomorphology 89, 163-171. doi: 10.1016/j.geomorph.2006.07.021
Ross DJ, Tate KR, Scott NA, Wilde RH, Rodda NJ, Townsend JA (2002) Afforestation of pastures with Pinus radiata influences soil carbon and nitrogen pools and mineralisation and microbial properties. Australian Journal of Soil Research 40, 1303-1318. doi:10.1071/ SR02020
Rumpel C, Kogel-Knabner I (2011) Deep soil organic matter: a key but poorly understood component of terrestrial C cycle. Plant and Soil 338, 143 158. doi:10.1007/sl 1104-010-0391-5
Sahrawat KL (2003) Organic matter accumulation in submerged soils. Advances in Agronomy 81, 169-201. doi: 10.1016/S0065-2113(03) 81004-0
Schlesinger WH (1991) 'Biochemistry: an analysis of global change.' (Academic Press: San Diego, CA)
Singh SK, Singh AK, Sharma BK, Tarafdar JC (2007) Carbon stock and organic carbon dynamics in soils of Rajasthan, India. Journal of Arid Environments 68, 408 421. doi:10.1016/j.jaridenv.2006.06.005
Smith P, Milne R. Powlson DS, Smith JU, Falloon P, Coleman K (2000) Revised estimates of the carbon mitigation potential of UK agricultural land. Soil Use and Management 16, 293 295. doi: 10.1111/j.14752743.2000.tb00214.x
Smith SV, Renwick WH, Buddemeier RW, Crossland CJ (2001) Budgets of soil erosion and deposition for sediments and sedimentary organic carbon across the conterminous United States. Global Biogeochemical Cycles 15, 697-707. doi:10.1029/2000GB001341
Soil Survey Staff (1999) 'Soil taxonomy: a basic system of soil classification for making and interpreting soil surveys.' 2nd edn (US Department of Agriculture, Soil Conservation Service. U.S. Government Printing Office: Washington, DC).
Tarnocai C, Canadell JG, Schuur EAG, Kuhry P. Mazhitova G, Zimov S (2009) Soil organic carbon pools in the northern circumpolar permafrost region. Global Biogeochemical Cycles 23, GB2023. doi: 10.1029/2008 GB003327
VandenBygaart AJ (2001) Erosion and deposition history derived by depth-stratigraphy of [sup.137]Cs and soil organic carbon. Soil & Tillage Research 61, 187 192. doi: 10.1016/SO167-1987(01)00203-3
Walkley A, Black IA (1934) An examination of the Degtjareff method for determining soil organic matter, and a proposed modification of the chromic acid titration method. Soil Science 37, 29-38. doi: 10.1097/ 00010694-193401000-00003
Wan HF (2005) 'Environmental concerns and comprehensive control for the regional agriculture in China.' (Chinese Environmental Science Press: Beijing)
Wang S, Zhou C, Li K, Zhu S, Huang F (2001) Estimation of soil organic carbon reservoir in China. Journal of Geographical Sciences 11, 3-13. doi: 10.1007/BF02837371
Wang BS, Tian H, Liu J, Pan S (2003) Pattern and change of soil organic carbon storage in China: 1960s 1980s. Tellus 55B, 416 427. doi: 10.1034/j.1600-0889.2003.00039.X
Watson RT, Noble IR (2001) Carbon and the science-policy nexus: the Kyoto challenge. In 'Challenges of a changing Earth. Proceedings of the Global Change Open Science Conference', 10 13 July 2001, Amsterdam, The Netherlands. (Eds W Steffen, J Jager, D Carson, C Bredshaw) pp. 57-64. (Springer: Berlin, Germany)
Wen QX (1984) 'Study methods of soil organic matter.' (Agriculture Press: Beijing, China) [in Chinese]
Wiesmeier M, von Liitzow M, Sporlein P, Gculi U, Hangen E, Reischl A, Schilling B, Kogel-Knabner I (2015) Land use effects on organic carbon storage in soils of Bavaria: the importance of soil types. Soil & Tillage Research 146, 296-302. doi: 10.1016/j.still.2014.10.003
Wright AL, Dou F, Hons FM (2007) Crop species and tillage effects on carbon sequestration in subsurface soil. Soil Science 172, 124-131. doi: 10.1097/SS.0b013e31802d 11 eb
Wu H, Guo Z, Peng C (2003) Land use induced changes of organic carbon storage in soils of China. Global Change Biology 9, 305 315. doi: 10.1046/j.1365-2486.2003.00590.X
Yan H, Cao M, Liu J, Tao B (2007) Potential and sustainability for carbon sequestration with improved soil management in agricultural soils of China. Agriculture, Ecosystems & Environment 121, 325-335. doi: 10.1016/j.agee.2006.11.008
Yang C, Yang L, Ouyang Z (2005) Organic carbon and its fractions in paddy soil as affected by different nutrient and water regimes. Geoderma 124, 133-142. doi: 10.1016/j.geoderma.2004.04.008
Yu DS, Shi XZ, Wang HJ, Sun WX, Chen JM, Liu QH, Zhao YC (2007) Regional patterns of soil organic carbon stocks in China. Journal of Environmental Management 85, 680 689. doi: 10.1016/j.jenvman.2006. 09.020
Zhang HH, Li FB, Wu ZF, Li DQ, Xu DR, Yuan HX (2008) Baseline concentrations and spatial distribution of trace metals in surface soils of Guangdong province, China. Journal of Environmental Quality 37, 1752-1760. doi:10.2134/jeq2007.0531
Zhou C, Wei X, Zhou G, Yan J, Wang X, Wang C, Liu H, Tang X, Zhang Q (2008) Impacts of a large-scale reforestation program on carbon storage dynamics in Guangdong, China. Forest Ecology and Management 255, 847 854. doi:10.1016/j.foreco.2007.09.081
Huihua Zhang (A,D), Junjian Chen (A), Zhifeng Wu (A,B,D), Dingqiang Li (A), and Li Zhu (C)
(A) Guangdong Key Laboratory of Agricultural Environment Pollution Integrated Control, Guangdong Institute of Eco-Environmental and Soil Sciences, Guangzhou 510650, China.
(B) School of Geographical Sciences, Guangzhou University, Guangzhou 510006, China.
(C) Management School, Jinan University, Guangzhou 510632, China.
(D) Corresponding author. Email: email@example.com
Caption: Fig.1. (a) Land use types, (b) location of Guangdong Province China, (c) sampling locations and (d) soil types.
Caption: Fig. 2. Distribution frequency of soil organic carbon (SOC) content in (a, b) A-, (c, d) B- and (e, f) C-horizon soils in Guangdong Province, (a,c,e) Original data; (b,d,f) In-transformed data.
Caption: Fig. 3. Spatial distribution of soil organic carbon (SOC) density in soil profiles in Guangdong Province.
Caption: Fig. 4. Fitted line plots showing correlations of soil organic carbon (SOC) and soil total nitrogen (TN) in the A, B and C horizons.
Table 1. Summary statistics of the data for 211 soil profiles in Guangdong Province, China GM, geometric mean; OC, organic carbon; TN, total nitrogen; [pH.sub.w], pH as measured in water No. of Minimum Median GM samples A horizon OC (%) 211 0.04 1.29 1.18 TN (%) 211 0.00 0.11 0.11 Soil density (g [cm.sup.3]) 211 0.52 1.19 Clay (%) 211 0.00 18.69 Thickness (cm) 211 3.0 15.0 [pH.sub.w] 211 3.4 5.5 B horizon OC (%) 203 0.02 0.75 0.71 TN (%) 203 0.00 0.07 0.07 Soil density (g [cm.sup.3]) 203 0.46 1.165 Clay (%) 203 0.00 23.51 Thickness (cm) 203 3.0 20.0 [pH.sub.w] 203 3.0 5.7 C horizon OC (%) 185 0.01 0.44 0.45 TN (%) 185 0.01 0.05 0.05 Soil density (g [cm.sup.3]) 185 0.40 1.25 Clay (%) 185 0.00 23.93 Thickness (cm) 185 5.0 46.0 [pH.sub.w] 185 2.8 5.8 Mean Maximum Skew (A) A horizon OC (%) 1.45 5.03 1.29 (0.91) TN (%) 0.12 0.41 1.18 (0.79) Soil density (g [cm.sup.3]) 1.16 1.66 0.37 Clay (%) 20.45 64.4 0.62 Thickness (cm) 17.0 40 0.97 [pH.sub.w] 5.77 9.1 0.87 B horizon OC (%) 0.94 5.24 2.51 (0.83) TN (%) 0.08 0.39 1.91 (-0.62) Soil density (g [cm.sup.3]) 1.17 1.8 -0.30 Clay (%) 25.27 85.22 0.96 Thickness (cm) 29.5 137.0 1.43 [pH.sub.w] 5.92 11.9 1.03 C horizon OC (%) 0.66 4.85 2.87 (-0.77) TN (%) 0.06 0.56 4.65 (-0.02) Soil density (g [cm.sup.3]) 1.20 1.77 -0.56 Clay (%) 25.93 74.31 0.70 Thickness (cm) 48.9 115.0 0.19 [pH.sub.w] 6.05 9.1 0.35 (A) Where two values are given, the data show untransformcd data with ln-transformed data in parentheses. Table 2. Pearson correlation coefficients (r) between soil organic-carbon (SOC) content and selected soil properties TN, total nitrogen SOC TN Density Clay pH A horizon SOC 1 TN 0.86 1 Density 0.15 -0.12 1 Clay 0.12 0.15 -0.14 1 PH 0.07 0.09 0.13 0.10 1 B horizon SOC 1 TN 0.87 1 Density 0.07 0.07 1 Clay 0.14 0.24 0.14 1 PH 0.02 0.08 0.16 0.02 1 C horizon SOC 1 TN 0.62 1 Density -0.06 0.03 1 Clay 0.15 0.13 0.08 1 PH 0.15 0.07 0.15 0.03 1 Table 3. Soil organic carbon content, density and storage by soil type in Guangdong soil profiles SOC, soil organic carbon; SOCD, SOC density; SOCS, SOC storage Soil type Area (A) Profile Clay (%) ([km.sup.2]) Ferrallisol Latosols 6530 (4.3%) A 19.72 B 26.70 C 31.56 Latosolic Red soils 65 870 (43.8%) A 25.30 B 34.66 C 33.86 Red soils 32 410 (21.5%) A 18.97 B 28.85 C 21.33 Yellow soils 8730 (5.8%) A 9.99 B 16.46 C 18.26 Anthrosols Paddy soil 16 652 (11.0%) A 21.35 P 23.67 C 26.16 Amorphic soils 16 503 (10.9%) A 18.62 B 24.31 C 20.49 Others 3762 (3.2%) A 17.43 B 19.55 C 16.82 Total 150457 A 20.50 B 25.27 C 25.93 Soil type Area (A) Profile Thickness ([km.sup.2]) (cm) Median Ferrallisol Latosols 6530 (4.3%) A 16.9 0.73 B 34.4 0.45 C 40.6 0.39 Latosolic Red soils 65 870 (43.8%) A 16.4 1.03 B 35.0 0.57 C 56.8 0.42 Red soils 32 410 (21.5%) A 16.9 1.56 B 73.3 0.59 C 32.8 0.42 Yellow soils 8730 (5.8%) A 19.1 3.16 B 46.8 1.04 C 44.0 0.21 Anthrosols Paddy soil 16 652 (11.0%) A 16.2 1.44 P 17.5 0.86 C 51.6 0.49 Amorphic soils 16 503 (10.9%) A 14.5 0.96 B 32.1 0.51 C 46.3 0.38 Others 3762 (3.2%) A 23.0 1.31 B 33.0 0.81 C 38.9 0.59 Total 150457 A 17.0 1.29 B 29.5 0.75 C 48.9 0.44 Soil type Area (A) Profile SOC (%) ([km.sup.2]) Mean Range Ferrallisol Latosols 6530 (4.3%) A 0.94 0.26-3.18 B 0.64 0.26-2.13 C 0.47 0.13-1.60 Latosolic 65 870 (43.8%) A 1.08 0.31-2.23 Red soils B 0.62 0.19-1.51 C 0.42 0.09-0.88 Red soils 32 410 (21.5%) A 1.52 0.04-3.05 B 0.59 0.02-0.99 C 0.42 0.01-0.73 Yellow soils 8730 (5.8%) A 3.15 2.05-4.34 B 0.95 0.37-1.21 C 0.34 0.16-0.66 Anthrosols Paddy soil 16 652 (11.0%) A 1.53 0.41-4.42 P 1.14 0.16-5.24 C 0.81 0.01-4.85 Amorphic soils 16 503 (10.9%) A 1.19 0.10-2.82 B 0.83 0.05-2.70 C 0.48 0.01-1.41 Others 3762 (3.2%) A 1.55 0.064-5.03 B 1.03 0.04-2.87 C 0.83 0.03-1.89 Total 150457 A 1.45 0.04-5.03 B 0.94 0.02-5.24 C 0.66 0.01-4.85 Soil type Area (A) Profile SOCD (kg C [m.sup.-2]) ([km.sup.2]) Median Mean Ferrallisol Latosols 6530 (4.3%) A 1.15 0.91 B 1.92 2.58 C 1.84 2.47 Latosolic 65 870 (43.8%) A 1.80 2.15 Red soils B 1.93 2.55 C 3.00 2.93 Red soils 32 410 (21.5%) A 2.20 2.53 B 4.47 4.83 C 1.08 1.48 Yellow soils 8730 (5.8%) A 3.75 4.45 B 2.81 3.61 C 1.29 1.07 Anthrosols Paddy soil 16 652 (11.0%) A 2.51 3.09 P 1.09 2.73 C 2.94 4.74 Amorphic 16 503 (10.9%) A 1.18 2.02 soils B 1.68 2.58 C 1.82 2.61 Others 3762 (3.2%) A 2.70 4.06 B 2.86 3.85 C 2.72 3.74 Total 150457 A 2.29 2.87 B 1.68 3.00 C 2.45 3.75 Soil type Area (A) Profile SOCD SOCS ([km.sup.2]) (kg C [m.sup.-2]) Range (Pg) Ferrallisol Latosols 6530 (4.3%) A 0.48-5.78 0.007 B 0.55-10.39 0.014 C 0.32-9.73 0.01 Latosolic 65 870 (43.8%) A 0.42-6.82 0.146 Red soils B 0.20-8.12 0.174 C 0.43-6.97 0.214 Red soils 32 410 (21.5%) A 0.05-5.31 0.107 B 0.23-12.6 0.195 C 0.06-4.81 0.011 Yellow soils 8730 (5.8%) A 2.47-7.67 0.053 B 0.85-8.27 0.041 C 0.37-1.64 0.004 Anthrosols Paddy soil 16 652 (11.0%) A 0.29-10.68 0.055 P 0.13-11.9 0.044 C 0.24-31.28 0.071 Amorphic 16 503 (10.9%) A 0.07-7.92 0.026 soils B 0.15-8.02 0.040 C 0.05-8.11 0.017 Others 3762 (3.2%) A 0.13-15.50 0.010 B 0.09-13.34 0.007 C 0.17-14.58 0.004 Total 150457 A 0.05-15.51 0.41 B 0.09-41.92 0.51 C 0.05-31.28 0.33 Soil type Area (A) Profile Profile SOCD Profile ([km.sup.2]) (kg SOCS (Pg) Ferrallisol C[m.sup.-2]) Latosols 6530 (4.3%) A 4.74 0.031 B C Latosolic 65 870 (43.8%) A 8.11 0.534 Red soils B C Red soils 32 410 (21.5%) A 9.66 0.313 B C Yellow soils 8730 (5.8%) A 11.23 0.098 B C Anthrosols Paddy soil 16 652 (11.0%) A 10.21 0.17 P C Amorphic 16 503 (10.9%) A 5.03 0.083 soils B C Others 3762 (3.2%) A 5.58 0.021 B C Total 150457 A 8.31 1.25 B C (A) Values in parentheses indicate the percentage of total soil area. Table 4. Soil organic carbon content and storage in four land use types in Guangdong soil profiles SOC, soil organic carbon; SOCD, SOC density; SOCS, SOC storage Land use Area (A) ([km.sup.2]) Profile Clay (%) Thickness (cm) Forest 116465 (77.4%) A 21.50 17.5 B 28.50 45.5 C 27.19 44.1 Paddy 16 651 (10.8%) A 21.92 16.2 B 24.43 17.5 C 26.72 51.6 Dryland 15 707 (11.0%) A 14.23 16.4 B 21.27 28.7 C 22.47 52.7 Total 150457 A 20.50 17.0 B 25.27 29.5 C 25.93 48.9 Land use Area (A) ([km.sup.2]) Profile Soil density (g [cm.sup.-3]) Median Forest 116465 (77.4%) A 1.09 1.29 B 1.14 0.66 C 1.15 0.40 Paddy 16 651 (10.8%) A 1.20 1.44 B 1.18 0.86 C 1.22 0.49 Dryland 15 707 (11.0%) A 1.25 0.86 B 1.28 0.50 C 1.30 0.38 Total 150457 A 1.16 1.29 B 1.17 0.75 C 1.20 0.44 Land use Area (A) ([km.sup.2]) Profile SOC (%) Mean Range Forest 116465 (77.4%) A 1.59 0.04-5.03 B 0.78 0.02-2.62 C 0.51 0.01-1.87 Paddy 16 651 (10.8%) A 1.53 0.41-4.42 B 1.14 0.16-5.24 C 0.81 0.01-4.85 Dryland 15 707 (11.0%) A 0.94 0.24-2.59 B 0.61 0.04-2.70 C 0.40 0.03-1.15 Total 150457 A 1.45 0.04-5.03 B 0.94 0.02-5.24 C 0.66 0.01--4.85 Land use Area (A) Profile SOCD (kgC[m.sup.-2]) ([km.sup.2]) Median Mean Range Forest 116465 (77.4%) A 2.35 2.96 0.05-15.51 B 2.61 3.64 0.19-13.3 C 1.61 2.67 0.05-14.58 Paddy 16 651 (10.8%) A 2.51 3.09 0.29-10.68 B 1.09 2.73 0.13-41.9 C 2.94 4.74 0.24-31.28 Dryland 15 707 (11.0%) A 1.28 1.98 0.42-8.41 B 1.06 1.98 0.09-7.65 C 2.21 2.80 0.17-12.34 Total 150457 A 2.29 2.87 0.05-15.51 B 1.68 3.00 0.09-4.92 C 2.45 3.75 0.05-31.28 Land use Area (A) Profile SOCS Profile SOCD ([km.sup.2]) (Pg) (kgC[m.sup.-2]) Forest 116465 (77.4%) A 0.33 8.58 B 0.43 C 0.25 Paddy 16 651 (10.8%) A 0.055 10.21 B 0.044 C 0.071 Dryland 15 707 (11.0%) A 0.017 4.65 B 0.042 C 0.014 Total 150457 A 0.41 8.31 B 0.51 C 0.33 Land use Area (A) ([km.sup.2]) Profile Profile SOCS (B) (Pg) Forest 116465 (77.4%) A 1.01 (80.27%) B C Paddy 16 651 (10.8%) A 0.17 (13.47%) B C Dryland 15 707 (11.0%) A 0.073 (5.81%) B C Total 150457 A 1.25 B C (A) Values in parentheses indicate the percentage of total soil area. (B) Values in parentheses indicate the percentage of total SOCS.
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|Author:||Zhang, Huihua; Chen, Junjian; Wu, Zhifeng; Li, Dingqiang; Zhu, Li|
|Date:||Jul 1, 2017|
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