Patterns of soil nitrogen storage in China

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Patterns of soil nitrogen storage in China

Hanqin Tian,

1

Shaoqiang Wang,

2

Jiyuan Liu,

2

Shufen Pan,

1

Hua Chen,

1

Chi Zhang,

1

and Xuezheng Shi

3

Received 20 January 2005; revised 28 July 2005; accepted 31 October 2005; published 5 January 2006.

[1]

We have investigated the storage and spatial distribution of soil nitrogen (N) in China

based on a data set of 2480 soil profiles and a map of Chinese soil types at a spatial

resolution of 1:1,000,000. Our estimate indicates that the total N storage in China is

8.29

10

15

g, representing 5.9– 8.7% of the total global N storage. The total N storage in

China is on average or slightly above the average of its share in the global N storage, even

though low nitrogen content soils cover a large area in China. N density varies

substantially with soil types and regions. Peat soils in the southeast of Tibet, southwest

China, show the highest averaged N density with a value of 7314.9 g/m

3

among all soil

types. This is more than 30 times of the lowest N density of brown desert soils in the

western desert and arid region. The highest N storages among all the soil types are

the felty soil in southeast of Tibet, dark-brown earths in northeast China, and red

earths in southeast China with values of 921.1, 611.4, and 569.6 Tg, respectively. N

density also varies with land cover types in China. Wetlands in southwest China

exhibit the highest N density at 6775.9 g/m

3

and deserts in northwest China have the

least at 447.5 g/m

3

. Our analysis also indicates that land cover types are poor

predictors of N content. Further research is needed to examine how transformation

from organic agriculture to increased use of fertilizers and pesticides has influenced N

storage in China.

Citation: Tian, H., S. Wang, J. Liu, S. Pan, H. Chen, C. Zhang, and X. Shi (2006), Patterns of soil nitrogen storage in China,Global Biogeochem. Cycles,20, GB1001, doi:10.1029/2005GB002464.

1.

Introduction

[2] Nitrogen (N) is a major nutrient for all living organisms on Earth and plays a central role in regulating the composition, structure, and function of ecosystems [Galloway et al., 2004;Holland et al., 2005]. The produc-tivity and dynamics of many natural and managed terrestrial ecosystems, including most agricultural and managed-forest ecosystems, are limited by the supply of biologically available N [Vitousek and Howarth, 1991; McGuire et al., 1995; Melillo, 1996; Tian et al., 1999; Galloway et al., 2004]. The enrichment experiments of carbon dioxide further indicate that N limitation directly influences carbon sequestration of terrestrial ecosystems [Lutze and Gifford, 2000;Oren et al., 2001;Hu et al., 2001; Schlesinger and Lichter, 2001]. Increased nitrogen availability increases productivity and biomass accumulation substantially, at least for the short-term [Vitousek and Howarth, 1991]. Similarly, increased N deposition could have the effect of attenuating atmospheric CO2by stimulating the

accumula-tion of forest biomass [Turner et al., 1995;Speicker et al., 1996; Holland, 1997;Jenkinson et al., 1999; Giardina et al., 2003]. Most N within a terrestrial ecosystem is stored in soil organic matter [Schlesinger, 1997]. The amount of N stored in soil is related to climate through biotic processes associated with the productivity of vegetation and decom-position of organic matter [Post et al., 1985;Batjes, 1996]. Other factors such as N deposition, nitrogen fixation, and losses of inorganic N due to leaching contribute to the variability of N storage [Schlesinger, 1997]. N in terrestrial ecosystems is particularly sensitive to human activities, including fertilization, land-use changes, and climate change [Stevenson, 1982; Batjes and Dijkshoorn, 1999;

Ellis et al., 2000; Parfitt et al., 2003; Wang et al., 2004]. Given the size of soil organic matter, small changes in soil N concentration can transform ecosystems from N sink to source or vice versa, with potentially large impacts on global biogeochemical cycles [Stevenson and Cole, 1999;

Galloway and Cowling, 2002;Galloway et al., 2004;Tian et al., 2003;Holland et al., 2005].

[3] Global soil N storage has been estimated primarily using two approaches. The first one is the C/N ratio conversion approach that N is calculated from organic carbon storage with a given C/N ratio [Burns and Hardy, 1975; Soderlund and Svensson, 1976; Delwiche, 1977;

Sweeney et al., 1978; Meybeck, 1982; Stevenson, 1982;

McElroy, 1983]. For example, an early inventory of N in global soils suggested a stock of about 220 Pg (1 Pg =

1

School of Forestry and Wildlife Sciences, Auburn University, Auburn, Alabama, USA.

2Institute of Geographic Sciences and Natural Resources Research,

Chinese Academy of Sciences, Beijing, China.

3State Key Laboratory of Soil and Sustainable Agriculture, Institute of

Soil Science, Chinese Academy of Sciences, Nanjing, China. Copyright 2006 by the American Geophysical Union. 0886-6236/06/2005GB002464$12.00

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1015g), which was estimated from the total organic C data in the soils of the world by assuming that the average C/N ratio was 10 for mineral soils and 30 for organic soils [Stevenson, 1982]. Other estimates of N in the organic matter of terrestrial soils are about 300 Pg in the work by

Soderlund and Svensson [1976] and 550 Pg in the work by Burns and Hardy [1975]. The second approach is to use measured N data for soil profiles to estimate global N storage [Post et al., 1985; Batjes, 1996; Batjes and Dijkshoorn, 1999]. For example, Post et al. [1985] esti-mated that the global N storage in the depth to 1 m was 95 Pg using global 3100 soil profiles data. Batjes [1996] used the data of 4353 soil profiles to obtain the total global N storage of 133 – 140 Pg for the upper 1 m. Regardless of which approach used, the discrepancy between the maximum and minimum estimates of N was approximately 750 Pg, suggesting substantial uncer-tainty in the estimates of global N storage due to the complexity of soil, the reliability of the various data sources, and the different spatial scaling approaches used. [4] China has an area of approximately 9,600,000 square kilometers, covering about 50 degrees of latitude and 60 degrees of longitude. Within this vast territory, various soil types have developed under different bioclimatic con-ditions and have been derived from various parent materials in diversified topographical environments. In recent years, the large-scale land transformation in China has significantly influenced biogeochemical and hydrological cycles [Tian et al., 2003;Liu et al., 2005]. Previous studies have indicated that land-use change has led to losses of soil carbon [Wang et al., 2003] and soil phosphorus [Zhang et al., 2005] in China. The N storage in Chinese soils have been studied at some sites [Zheng et al., 1995; Ellis et al., 2000; Zhou, 2000;Wang et al., 2004], but the nationwide estimates of N have not been done yet. Here we report the results of the first comprehensive analysis of nationwide N storage, based on a large database of soil samples in China. The objectives of this study include: (1) to estimate the total N storage in China, (2) to examine the variability of N among soil and land cover types, and (3) to characterize the spatial distribution of N storage across China.

2.

Data and Methods

2.1. Data Sources

[5] The data we used for this study are from the second national soil survey of China [National Soil Survey Office, 1993, 1994a, 1994b, 1995a, 1995b, 1996, 1998]. This database is composed of records of 2473 typical soil profiles across China (see Figure 1), each of which represents soil species in the Genetic Soil Classification of China (GSCC) [Shi et al., 2004b]. Each soil profile is divided into A, B and C horizons as depth increases. Each horizon may be further divided into several subhorizons. Soil properties examined include geographic location, elevation, vegetation, terrain position, soil depth, organic content, parent material, bulk density, land cover and meteorological index [National Soil Survey Office, 1995a, 1995b]. Physical and chemical soil properties were recorded for each subgroup by horizon. The database characterizes the diversity of agricultural and

nonagricultural soils, which spans from tropical to temper-ate to boreal ecosystems. To better represent the large diversity of soils across the nation, we included records of soil profiles from seven other studies which were collected from both peer-reviewed papers and other publications such as research reports [Fang et al., 1996;National Soil Survey Office, 1998].

[6] The total soil area of China, estimated after removal of the land area associated with surface waters, glaciers, perennial snow, bare rock, and gravel hills, is 877.63 106ha, which represents 91% of the total land area of China [National Soil Survey Office, 1998]. This national soil survey does not cover Taiwan province, which has an area of approximately 23.95106ha.

2.2. Methods

[7] Methods estimating N have been discussed by a number of scientists since the 1970s [Burns and Hardy, 1975; Post et al., 1985; Batjes, 1996]. The direct mea-surement approach is generally considered as more reli-able in estimating N storage than the C/N ratio conversion approach [Post et al., 1985; Batjes, 1996]. The direct measurement approach is to estimate N storage by multiplying soil depth, N density, and area. In this study, we have used the measured soil depth data in the calculation of soil nitrogen content instead of the uniform 1 m depth that has been employed in soil nitrogen studies [e.g., Post et al., 1985]. We did this by considering not only the depth of each sampled soil profile, but also the total nitrogen content of each soil horizon in the profile. In this study, the depth of most sampled soil profiles is less than 1 m. However, there are indeed many sampled profiles with a depth greater than 1 m, because of the large amounts of soil organic matter that lie below 100 cm in both mineral and organic soils [Sombroek et al., 1993]. By considering the variation in soil depth and

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corresponding nitrogen content, our approach may be able to deliver a more realistic picture in N estimation [Mikhailova et al., 2000].

[8] In this study, we took advantage of the large number of sampled soil profiles by considering the physical and chemical properties of every soil horizon. The soil profile data were integrated into a Geographical Information Sys-tem (GIS) database with their geographical locations and overlaid with base maps such as the soil map of China. The 2473 soil samples provide reliable estimates on nitrogen content for each soil subgroup. On the basis of this strategy, we first calculated the nitrogen content of different soil horizons in the same soil profile. Then we used the depth of each horizon as a weighting coefficient to derive the average physical and chemical properties of the soil profiles.

[9] For an individual soil profile with n layers, its N density (N) was calculated as

N¼ Pn i¼1 HiBiOi Pn i¼1 Hi ; ð1Þ

whereHiis the thickness (cm) of horizon i,Bi is the bulk density (g/cm3) of horizoni, andOiis the soil total nitrogen content (%) in horizoni. The average bulk density of a soil subgroup is used for soil profiles with no bulk density data. Grouping data by subgroups provides a better estimate than by soil groups because subgroups give good indications of climate, drainage, and soil textures [Li and Zhao, 2001]. Then we calculated the average N density of soil subgroup as Naj¼ Pn k¼1 HkNk Pn k¼1 Hk ; ð2Þ

where Naj is the average N density (g/m

3

) of soil subgroup j, kdenotes the soil profile,Nk is the N density of soil profilek(g/m3), and Hkis the depth of soil profile

k. N masses for each soil subgroup were obtained by multiplying the nitrogen content for each soil subgroup by the area of the respective soil subgroup. The total N

quantity of a soil subgroup in the measured depth was calculated as

SONt¼ Xn

j¼1

NajSjHj; ð3Þ

wherejdenotes the given soil subgroup,Ntis the nitrogen storage (Tg),Sj is the distribution area of soil subgroup j (Mha),Hjis the average depth of soil subgroupj(cm), andNaj is the average N density (g/m3) of soil subgroupj.

[10] On the basis of each soil profile’s location (e.g., longitude, latitude, and elevation) and vegetation types, we grouped soil profiles into different land cover types according to the vegetation classification system ofHou et al.[1982]. Land cover types in China have been classified into eight categories including dry land, paddy land, forest and wood-land, shrubs, steppe and grasswood-land, meadow, wetwood-land, and desert. We assigned soil profile data for each land cover category. The soil profiles without detailed vegetation infor-mation were excluded from the analysis.

[11] Statistical analysis including an error test was con-ducted according to a standard procedure [Jongman et al., 1995]. The standard deviation was calculated for N content for each soil subgroup. The standard error level was calcu-lated for the total nitrogen estimation. We calcucalcu-lated the error range for the N density for each soil subgroup using attest,

Error¼tSDffiffiffi n

p ; ð4Þ

where t is the distribution value at 0.05 significant levels (95% confidence interval),SDis the standard deviation of N density of soil subgroup, and n is the degree of freedom (number of samples).

[12] By using a newly developed Chinese soil type map at a resolution of 1:1,000,000 [Shi et al., 2004a, 2004b], finally, we extrapolate site-specific estimates of N into the entire nation. To do that, each soil subgroup type on the Major Soil Regions of the Chinese soil map was assigned a value of total soil N storage.

3.

Results and Discussion

3.1. Total N Storage in China

[13] Our estimates indicate that, for soils in China, the average N density is 944.4 g/m3and the average soil depth Table 1. Estimates of the Total SON Storage Globally and in China

References Global N (1015g) Method N in China (1015g)

This study NA direct measurement 8.29

Batjes[1996] 133 – 140 direct measurement 8.5 – 9a

Burns and Hardy[1975] 550 C/N ratio conversion 35.2a

Delwiche[1977] 760 C/N ratio conversion 48.6a

Meybeck[1982] 170 C/N ratio conversion 10.9a

McElroy[1983] 70 C/N ratio conversion 4.5a

Post et al.[1985] 95 direct measurement 6.1a

Soderlund and Svensson[1976] 300 C/N ratio conversion 19.2a

Stevenson[1982] 220 C/N ratio conversion 14.1a

Sweeney et al.[1978] 820 direct measurement 52.5a

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is 85 cm. Using the total land area of 8.78 108ha, we estimated that the total N storage is about 8.29 ± 3.39 1015g in China (Table 1).

[14] Our estimate of total N storage in China is com-parable to others derived from the same approach [Post et

al., 1985; Batjes, 1996], but much lower than the C/N ratio-based estimates (Table 1). The highest estimate of total N in China was 52.5 Pg, which was calculated according to the proportion of China’s land in global land area (6.4%) and the total global N (820 Pg) estimated by Table 2. N Density and Storage by Soil Types in China

Great Groups in Chinese Soil Taxonomy U.S. Soil Taxonomy na Area (106ha) Depth, cm

Nitrogen, g/m3 Storage Mean ± 1012g ±2 SEb

Latosolic red soils Ultisols 31 17.79 111 1048.8 307.6 207.91 60.98

Latosols Ultisols 23 3.94 108 1032.7 117.3 44.10 5.01

Red soils Ultisols 132 56.93 100 1003.9 180.7 569.64 102.51

Yellow soils Ultisols 78 23.26 88 1283.6 203.4 262.83 41.65

Yellow brown soils Alfisols 32 18.04 98 1336.4 572.3 237.13 101.55

Yellow cinnamon soils Inceptisols 25 3.81 122 695.2 113.4 32.30 5.27

Brown soils Alfisols/Inceptisols 87 20.16 99 1148.0 335.1 229.35 66.95

Dark-brown soils Alfisols/Inceptisols 59 40.21 87 1752.1 451.2 611.36 157.42

Bleached Beijiang Soils Alfisols 20 5.27 96 1190.0 582.5 60.15 29.44

Brown coniferous forest soils Inceptisols 9 11.66 76 2717.5 1972.0 240.55 174.56

Torrid red soils Inceptisols 15 0.71 92 669.7 368.5 4.38 2.41

Cinnamon soils Inceptisols 131 25.17 113 928.0 229.4 263.70 65.18

Gray-cinnamon soils Alfisols 19 6.18 96 2235.8 1450.3 133.23 86.42

Black soils Udolls 38 7.36 117 1422.0 385.7 122.85 33.32

Gray forest soils Alfisols 8 3.15 49 1277.3 477.9 19.70 7.37

Chernozems Cryolls 70 13.22 115 1336.2 454.2 202.88 68.96

Castanozems Ustolls 73 37.5 122 1006.2 256.4 459.38 117.08

Castano cinnamon soils Ustolls 16 4.82 148 522.3 314.4 37.26 22.43

Dark loessial soils Calci-great groups 18 2.55 148 875.5 264.8 32.96 9.97

Brown caliche soils Calci-great groups 17 26.51 83 683.8 104.5 150.50 22.99

Sierozems Inceptisols 33 5.38 107 815.5 320.6 47.01 18.48

Gray desert soils Calci-great groups 12 4.6 104 582.8 128.5 27.85 6.14

Gray-brown desert soils Calci-great groups 10 30.73 64 328.9 275.6 64.77 54.28

Brown desert soils Salic great groups 6 24.3 36 235.0 2.3 20.42 0.20

Loessial soils Orthents, Psamments 36 12.29 136 506.2 85.3 84.44 14.25

Red soils Ultisols 21 1.841 121 578.8 111.3 12.91 2.48

Neo-alluvial soils Fluvents 51 4.29 92 811.1 340.2 32.09 13.46

Takyr Aridisol 1 0.68 73 364.5 0.0 1.80 0.00

Aeolian soils Psamments 46 67.57 100 265.2 120.2 178.43 80.84

Skeletal soils Orthents, Psamments 44 26.11 56 1139.7 355.2 166.19 51.80

Limestone soils Orthents, Psamments 48 10.77 75 1681.5 537.9 135.48 43.34

Volcanic soils Andisols 12 0.19 76 2126.0 1779.8 3.07 2.57

Purplish soils Orthents, Psamments 80 18.9 77 922.6 151.2 133.95 21.96

Lithosols Orthents, Psamments 15 18.53 11 1450.1 1139.9 29.21 22.96

Meadow soils Aquic suborders/Udolls 103 25.09 99 1100.5 362.6 273.82 90.22

Fluvi-aquic soils Fluvents 210 25.68 109 652.4 99.6 181.95 27.79

Sajiang black soils (Lime concretion black soils) Vertisols 36 3.77 101 851.8 378.2 32.32 14.35

Shrub meadow soils Inceptisols 3 2.48 99 419.0 53.2 10.31 1.31

Mountain meadow soils Inceptisols 20 4.19 97 3418.9 2238.1 139.24 91.15

Bog soils Aquic suborders 38 12.63 90 2640.7 1424.7 299.28 161.47

Peat soils Histosols 8 1.48 110 7314.9 2893.1 119.24 47.10

Solonchaks Salic great groups 28 10.44 93 418.9 72.4 40.85 7.06

Coastal solonchaks Salic great groups 22 2.12 99 805.7 411.4 16.90 8.63

Acid sulphate soils Entisols-Fluvents 4 0.02 89 618.0 505.6 0.11 0.09

Desert solonchaks Salic great groups 9 2.87 79 543.9 196.0 12.35 4.45

Frigid plateau solonchaks Salic great groups 4 0.69 92 509.7 201.0 3.22 1.27

Solonetzs Salic great groups 20 0.87 103 575.4 195.9 5.14 1.75

Paddy soils Fluvents/Inceptisols 525 29.79 87 1274.1 215.9 328.86 55.73

irrigated silting soils Fluvents 25 1.27 127 1007.6 298.1 16.19 4.79

irrigated desert soils Fluvents 20 0.91 125 850.6 192.2 9.65 2.18

Felty soils (Alpine meadow soils) Inceptisols 22 53.54 70 2469.6 1673.1 921.08 623.99

Dark felty soils (subalpine meadow soils) Inceptisols 20 19.44 59 2429.0 1503.7 280.24 173.49

Frigid calcic soils Inceptisols 9 68.85 72 900.0 752.9 447.72 374.54

cold calcic soil Inceptisols 14 11.294 82 1376.4 353.4 127.71 32.79

Cold brown calcic soils Inceptisols 15 0.96 85 1223.5 349.7 10.04 2.87

Frigid desert soils Psamments 2 8.96 49 280.6 239.6 12.32 10.52

Cold desert soils Psamments 2 5.22 68 255.4 256.4 9.00 9.10

Frigid frozen soils Psamments 5 30.65 29 1468.5 281.5 131.42 131.73

Total 2480 8288.7 3392.6

a

Number of samplers.

b

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the C/N ratio conversion approach by Sweeney et al.

[1978], and then followed by 48.6 Pg [Delwiche, 1977]. These estimates are much higher than our estimate of N storage, 8.3 ± 3.39 Pg. Using the total N storage data determined from the direct measurement approach by

Batjes [1996] and Post et al. [1985], we estimated that the total N storage in China was 8.5 9 Pg and 6.1 Pg, respectively. The global N storage estimates using the C/ N ratio conversion method, clearly, were much higher than those derived from the direct measurement using global data set of soil profiles (Table 1). The direct measurement approach is generally considered as more reliable in estimating global N storage than the C/N ratio conversion approach [Post et al., 1985; Batjes, 1996]. Using the total global N storage data from Batjes [1996] and Post et al. [1985], China’s N storage (8.3 Pg) constitutes 5.9 – 6.2% and 8.7% of the total global N storage, respectively. Given the land area in China is 6.4% of the global terrestrial area, the total N storage in China is on average or slightly above the average of its share in global N storage.

3.2. N Storage by Soil Types

[15] The N density varies substantially with soil types and regions (Table 2, Figure 2, and Figure 3). The peat soils in the Tibet region of southwest China show the highest average N density of 7314.9 g/m3 among all soil types. This is primarily due to the slow decomposition of organic matter in cold and water-saturated soils. In the same region, the N density of felty soils (Alpine meadow soils) and dark felty soils is also very high with an average of 2469.6 g/m3 and 2429.0 g/m3, respectively. In northeast China, the N density of brown coniferous forest soils and dark-brown earths is high with a value of 2717.5 g/m3 and 1752.1 g/m3, respectively. In contrast,

the N density of brown desert soils in western desert and arid region only ranges from 56.7 g/m3 to 235 g/m3, the lowest among all soil types. We found that the N density in widely distributed Fluvo-aquic agricultural soils was much lower than the average N density in China (652.4 versus 944.4g/m3), suggesting that the N storage in these soils may decline owing to the transformation from traditional organic agriculture to contemporary agricultural practices since 1970. The averaged N density in Paddy soils, 1274 g/m3 (equivalent to 11 Mg N/ha), was much higher than the soil N density of 6.8 Mg/ha at Tai Lake region reported by Ellis et al. [2000]. In general, paddy soil N usually decreases when synthetic N is used without organic N inputs [Wang et al., 1993].

[16] The storage of N varies substantially with soil types, reflecting variations in both N density and distrib-uted area of the soil types (Table 2). The three soil types with the most N storages are the felty soil in the southeast of Tibet, dark-brown earths in northeast China, and red earths in southeast China with a value of 921.1, 611.4, and 569.6 Tg (1 Tg = 1012 g), respectively. They contribute to 11.1, 7.38, and 6.87% of the total N storage in China. However, these three soil types combined cover 17.16% of total land area. The three most widely distrib-uted soils are the frigid calcic soils, the Aeolian soils, and the red earths, covering 7.84, 7.7, and 6.48% of the total land area (Table 2). However, these three soil types contribute to 5.4, 2.15, and 6.87% of total N storage in China. Soil types with N density less than the national average N density occupy 60.44% (5.30108ha) of the total statistical area, but only contribute 42.35% (3.51 1015 g) of the total N stock of the country.

3.3. N Density by Land Cover Types

[17] The density of N varies with land cover types in China (Figure 3 and Table 3). In the northeast, the N density of wetlands was the highest (3789.0 g/m3), followed by the forests and woodlands (1507.8 g/m3), and scrubs soil ranked the lowest. In the north, the highest N density occurred in the forests and woodlands, with a value of 1668.2 g/m3, followed by wetland soils (1459.9 g/m3), and the dry land soil ranked the lowest (739.5 g/m3) (Table 3). The surprisingly high N density of the desert (1021.4 g/m3) is probably caused by the small sampling number. In the northwest, the N density of the wetlands was the highest (2660.3 g/m3), followed by meadow soil (2401.8 g/m3), and desert soil ranked the lowest (447.5 g/m3) (Table 3 and Figure 3). In the east, the decreasing order of N density of land cover types was paddy land, steppe and grassland, shrubs, forest and woodland, and dry land soil (Table 3 and Figure 3). Differences in N density between land cover types were small in this region. Moreover, the N density was generally low as results of the long-term human activity history in east China. In the south, N density of a meadow soil was much higher than the N density of other land cover types based on a limited number of soil profiles.

[18] For the entire country, wetlands in southwest China had the greatest N density at 6775.9 g/m3while deserts in

Figure 2. Spatial distribution of soil nitrogen storage in

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the northwest had the least at 447.5 g/m3. Forests and woodlands, ranging from 1052.1 g/m3 in the east to 1933.0 g/m3 in the southwest, tended to have greater N than steppes and grasslands. Scrubs and cultivated land, including dry land and paddy land, had lower N content

than forests, steppes, meadows and wetlands (Table 3 and Figure 3).

[19] The high variation in N density within the land cover types (Table 3) indicates that there was substantial heterogeneity in soil types within each land cover. Kern

Figure 3. Soil nitrogen density for major land cover types in the six subregions of China. Numbers 1

through 8 represent the desert, dry land, steppe and grassland, shrubs, meadow, forest and woodland, wetland, and paddy land, respectively.

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[1994] has suggested that the land cover types are poor predictors of N content because of the great soil hetero-geneity. Meanwhile, the selection of soil sampling loca-tion has contributed to the varialoca-tions. Northwest China is

a semi-arid and arid region with large area of semideserts and deserts. The N density in this region should have been lower than other regions, but many soil profiles were taken from mountains, steppes and meadows, which Table 3. N Density Under Various Land Cover Types in the Six Regions of Chinaa

Land Cover Type Number of Samples

Depth, cm

Standard Deviation

of Depth Bulk Density, g/cm3 Nitrogen Density,g/m3 of Nitrogen DensityStandard Deviation

Northeast

Desert NA NA NA NA NA NA

Dry land 183 115 34.82 1.36 1112.2 550.8

Steppe and grassland 32 86 36.62 1.37 1044.3 819.7

Shrubs 9 80 67.59 1.44 998.8 1903.3

Meadow 46 92 36.94 1.34 1279.5 838.7

Forest and woodland 55 79 43.50 1.33 1507.8 994.8

Wetland 18 100 34.75 1.04 3789.0 3013.0

Paddy land 20 79 35.77 1.32 1076.1 986.4

North

Desert 6 125 27.39 1.36 1076.9 1021.4

Dry land 268 115 24.67 1.38 739.5 381.9

Steppe and grassland 43 103 42.31 1.32 974.1 645.9

Shrubs 23 89 38.85 1.34 814.0 911.1

Meadow 27 98 34.73 1.32 1077.2 1241.7

Forest and woodland 19 95 37.04 1.35 1668.2 1012.8

Wetland 4 104 4.79 1.24 1459.9 607.8

Paddy land NA NA NA NA NA NA

Northwest

Desert 70 75 30.43 1.34 447.5 340.1

Dry land 232 126 40.37 1.32 932.6 646.4

Steppe and grassland 41 102 40.76 1.30 1192.7 1208.4

Shrubs 10 100 60.19 1.34 1257.2 1088.7

Meadow 20 74 30.43 1.25 2401.8 1849.2

Forest and woodland 31 95 29.19 1.29 1659.2 1221.1

Wetland 13 88 28.83 1.27 2660.3 3042.6

Paddy land 17 128 29.13 1.32 1054.1 388.0

East

Desert NA NA NA NA NA NA

Dry land 103 100 27.36 1.38 765.1 442.0

Steppe and grassland 31 82 33.49 1.38 1248.3 1496.0

Shrubs 39 80 35.42 1.33 1176.7 933.2

Meadow NA NA NA NA NA NA

Forest and woodland 65 97 37.00 1.33 1052.1 782.5

Wetland NA NA NA NA NA NA

Paddy land 210 82 29.97 1.33 1276.3 1382.3

South

Desert NA NA NA NA NA NA

Dry land 75 95 19.07 1.34 948.4 431.9

Steppe and grassland 19 118 42.19 1.32 958.0 504.0

Shrubs 38 87 19.25 1.30 1158.5 1041.4

Meadow 3 85 18.58 1.24 5358.7 2716.4

Forest and woodland 65 98 30.35 1.31 1213.9 729.7

Wetland NA NA NA NA NA NA

Paddy land 163 93 20.52 1.29 1163.8 657.9

Southwest

Desert 17 56 32.96 1.34 661.4 902.7

Dry land 178 81 23.86 1.33 1336.7 777.1

Steppe and grassland 24 83 20.67 1.31 939.9 739.7

Shrubs 29 68 31.79 1.31 2106.2 3172.8

Meadow 28 68 19.49 1.21 2408.6 1754.0

Forest and woodland 51 85 29.80 1.24 1933.0 1398.2

Wetland 6 76 28.67 1.16 6775.9 3852.2

Paddy land 92 78 20.01 1.29 1478.4 865.1

a

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have high organic accumulations; thus the N density of wetlands, meadows and forests was very high in the northwest (Table 3).

4.

Uncertainty and Future Research

[20] N storage estimation in soils is complicated by a number of factors: (1) the complexity of the soil nitrogen cycle; (2) lack of reliable, complete and uniform data for soils, especially for bulk density; (3) soil sampling and laboratory analysis methods; (4) the spatial variation in nitrogen content and physical-chemical property of soils; (5) differences in N storage calculation methods and scaling approaches; and (6) the comprehensive effects of climate, relief, parent material, vegetation and land cover. Our study is based on soil sample data derived from a variety of previous research projects, which may have adopted differ-ent criteria for soil classification, mapping scales, and degrees of representatives of soil profiles. Considering this, the data on measured soil properties may be inconsistent. Moreover, the lack of sufficient data on bulk density of soil horizons, climate and land cover also limits the accuracy of the results.

[21] The unprecedented combination of economic and population growth since the early 1980s have led to a dramatic land transformation across the nation [Liu et al., 2005]. The large-scale land transformation has important implications for cycles of carbon [Tian et al., 2003;Wang et al., 2003] as well as nitrogen [Zheng et al., 2002]. Clearly, there is an important need to further investigate how land-use change influences N storage and its spatial distribution across China.

[22] In the past 3 decades, China’s croplands have expe-rienced dramatic changes in agronomic practices, including a transformation from traditional organic agriculture to increased use of chemical compounds [Luo and Han, 1990; Zheng et al., 2002]. Increased use of fertilizers has led to a tripling of the emission of nitrous oxides in the three decades, according to field experiments and simulation [Qi and Dong, 1999]. It is of critical importance to assess how the transformation from organic agriculture to increased use of chemical materials influences N storage in China and its contribution to global N storage.

[23] Acknowledgments. This study has been supported by the Minis-try of Science and Technology (MOST) 973 Program (2002CB412501), the CAS Knowledge Innovation Key Project (KZCX1-SW-01-19), the IGSNRR Land-Use/Land-Cover and Terrestrial Carbon Process Program (CXIOG-E01-02-02), NASA Interdisciplinary Science Program (NNG04GM39C), the CAS Oversea Distinguished Scholar Program, and the NSFC International Cooperative Program (40128005). We thank Art Chappelka, Pete Smith, and two anonymous reviewers for very helpful comments and suggestions.

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