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2 Journal of Environmental Radioactivity 112 (2012) 125e132 Contents lists available at SciVerse ScienceDirect Journal of Environmental Radioactivity journal homepage: Using 137 Cs to study spatial patterns of soil erosion and soil organic carbon (SOC) in an agricultural catchment of the typical black soil region, Northeast China Haiyan Fang *, Qiuyan Li, Liying Sun, Qiangguo Cai Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing , China article info abstract Article history: Received 27 May 2011 Received in revised form 26 April 2012 Accepted 15 May 2012 Available online xxx Keywords: Black soil 137 Cs Soil redistribution Soil organic carbon (SOC) Catchment Understanding the spatial pattern of soil organic carbon (SOC) is of great importance because of global environmental concerns. Soil erosion and its subsequent redistribution contribute significantly to the redistribution of SOC in agricultural ecosystems. This study investigated the relationships between 137 Cs and SOC over an agricultural landscape, and SOC redistribution was conducted for an agricultural catchment of the black soil region in Northeast China. The spatial patterns of 137 Cs and SOC were greatly affected by the established shelterbelts and the developed ephemeral gullies. 137 Cs were significantly correlated with SOC when 137 Cs were >2000 Bq m 2, while no relation was observed between them when 137 Cs were <2000 Bq m 2. Factors other than soil erosion such as vegetative productivity, mineralization of SOC, landscape position and management induced their spatial difference of 137 Cs and SOC. Using 137 Cs technique to directly study SOC dynamics must be cautious in the black soils. The net SOC loss rate across the entire catchment during 1954e2010 was 92.8 kg ha 1 yr 1, with around 42% of the eroded SOC being redeposited within the catchment. Such information can help guide shelterbelt establishment or other land management to reduce SOC loss in the agricultural ecosystems. Ó 2012 Elsevier Ltd. All rights reserved. 1. Introduction Soil organic carbon (SOC) is recognized as a major soil fertility constituent and a key factor in sustainable soil use (Roose and Barthes, 2001; Polyakov and Lal, 2008). Soil erosion from agricultural land results in considerable loss of SOC. Depletion of SOC is usually followed by a deterioration of soil structure and a deficiency of plant nutrients. SOC represents globally significant carbon pool, and has the potential to influence global climate (Lal, 2003; Li et al., 2007). Spatial pattern of SOC greatly depends on soil redistribution, vegetative productivity, landscape position and management (Gregorich et al., 1998; Jacinthe et al., 2004). Soil erosion contributes significantly to the redistributions of soil and SOC across the landscape with both soil and SOC being redposited as well as being moved off the field (Ritchie et al., 2007). Because soil erosion is scale dependant (Renschler and Harbor, 2002) and SOC is preferentially removed by soil erosion (Lal, 2003; * Corresponding author. A11 Datun Road, Anwai, Chaoyang District, Beijing , China. Tel.: þ addresses: fanghy@igsnrr.ac.cn (H. Fang), lqymily@163.com (Q. Li), sunliying@igsnrr.ac.cn (L. Sun), caiqg@igsnrr.ac.cn (Q. Cai). Van Oost et al., 2008), evaluation on the fates of the eroded and buried SOC within agricultural landscape could be likely related to spatial scales. Resulting from soil erosion and its subsequent redistribution, upslope areas usually have lower SOC pool than downslope areas or lower locations (Fang et al., 2006a, b; Li et al., 2007). Understanding the spatial pattern of SOC and its dynamics is crucial for assessing the fate of the eroded SOC across the landscape. Although the question of the fate of the eroded SOC during transition from sediment source to sediment sink has been rained in the literatures (Fang et al., 2006a, b; Li et al., 2007), field data are less due to lack of direct measurements to investigate this dynamic process. There is an urgent need to obtain reliable quantitative data on erosion-induced SOC pattern for assessing the effect of soil redistribution on the fate of eroded SOC over the landscapes. The use of fallout radionuclides, especially for 137 Cs technique, has attracted increasing attention as an alternative approach to obtain quantitative estimates of eroded SOC redistribution over agricultural landscapes (e.g., Mabit and Bernard, 1998; Ritchie and McCarty, 2003; Li et al., 2007). 137 Cs is an artificial radionuclide (half-life 30.2 years), and has been applied to provide independent measurements of soil redistribution in a wide range of environments (Ritchie et al., 1974; Elliot et al., 1990; Nouira et al., 2003) X/$ e see front matter Ó 2012 Elsevier Ltd. All rights reserved. doi: /j.jenvrad

3 126 H. Fang et al. / Journal of Environmental Radioactivity 112 (2012) 125e132 Literatures have demonstrated that both of the 137 Cs fallout and SOC can be strongly adsorbed onto soil particles and move with almost the same physical mechanism in the soils over the agricultural environment (Mabit and Bernard, 1998; Ritchie and McCarty, 2003). The use of 137 Cs fallout as a surrogate could give us a good method to detect erosion-induced SOC pattern and to estimate the fate of the eroded SOC. The black soil region in Northeast China suffers severe soil erosion. According to Fan et al. (2005), the thickness of the A- horizon of black soils has decreased from 60 to 70 cm from its initially cultivated period to 20e30 cm presently. Although the erosion of black soil results in intense soil and SOC redistributions (Liu et al., 2006), less work has been conducted with the exceptions being the studies by Fang et al. (2006a, b) who studied the dynamics of SOC on the slopes. Until now, no work was done at a catchment scale for assessing the patterns of SOC and its fate due to the paucity of quantitative data. Understanding the spatial pattern of SOC and its process across agricultural landscapes is crucial to disclose the fate of the eroded SOC as well as the development models that can predict SOC distribution patterns over the landscape (Polyakov and Lal, 2004). Retrospective information on the dynamics of the eroded SOC by using 137 Cs technique can compensate for the lack of SOC data in Northeast China for the past decades. The objectives of this research are to: (i) explore the spatial patterns of soil and SOC in cultivated agricultural ecosystems; (ii) validate the relationship between 137 Cs and SOC at an agricultural catchment in the black soil region; and (iii) estimate SOC fate at a catchment scale as a result of soil redistribution. 2. Materials and methods 2.1. Study catchment The catchment is located at the Heshan Farm, Heilongjiang Province, China ( E, N; Fig. 1). The catchment has an area of 28.5 ha, with an elevation of 320e360 m. The mean slope gradient is 4.1% ranging from 0.2 to 10.3%. The climate of the region is semihumid and continental with a long and cold winter. Mean January and July temperatures are 20 C and 21 C, respectively. The mean annual precipitation is 534 mm, of which approximately 67% occurs from June to August. The main soil type is Luvic Phaeozem in the FAO/UNESCO system (Zhang et al., 2007a, b). The parent materials of the Phaeozem are Quaternary lacustrine and fluvial sand beds or loess sediments that lie below the Phaeozem (Sun and Liu, 2001). The main textural classes of the top soil are silt clay loam to clay loam (8e27% sand, 29e66% silt, and 26e40% clay) (Wu et al., 2008). This kind of soil texture is highly erodible (Torri et al., 1997), and the soil erodibility is even larger than that of the loess soil on the Chinese Loess Plateau (Zhang et al., 2007a, b). Most of the land in Heshan Farm was historically covered by bush wood. Large scale land reclamation has been carried out in the black soil regions with increasing population since 1950s. The study area has not been substantively changed over the last 50 years (Wei, 2007). Soybean (Glycine max (L.) Merr.) is the major crop in the rotation with wheat (Triticum aestivem L.) and corn (Zea mays L.). A single tillage operation is used with a cultivator harrow to a depth of ca m after harvesting in autumn (late September) or before sowing (early May) in spring (Wei, 2007). From October to April, the cropland is left fallow with no vegetation cover for cold weather. Pinus shelterbelts were established in the 1970s to mainly protect crop from wind disaster (Fig. 1), while the shelterbelts within the catchment can also greatly impact soil and SOC redistributions (Zhang et al., 2006). Fig. 1. The locations of the study catchment and the reference site Soil sampling A multiple transects approach in conjunction with key points sampling method was used to document the spatial patterns of soil and SOC (Fig. 2). Reference site for determining the 137 Cs baseline value was selected in an uncultivated second-growth Quercus mongolica forest. It was not unaffected by soil erosion or deposition since 1950s (Fig. 1). Like the studies by Nearing et al. (2005) and Onda et al. (2007), a 5-cm-diameter hand operated core sampler was used to collect soil samples in late June, Totaled 61 samples were collected in the agricultural catchment and 5 samples at the reference site. The black soil depth was around 60e70 cm in the 1950s, while the artificial radionuclide 137 Cs was introduced into the environment primarily during the period from 1954 to mid-1970s. As a result of soil erosion and deposition, 137 Cs is mainly contained in the black soil layer. Therefore, the full depth of the 137 Cs profile can be ensured when the core sampler reaches the bottom of the black soil layer. Soil cores were taken to a depth of 40 cm on the eroded farmland and 60e100 cm in the deposition areas. The distances between two adjacent sampling points on the transects ranged from 50 to 100 m, while the distances between other two adjacent sampling points depended on the landforms Laboratory analysis The samples were air-dried, weighted, and divided into two parts, one passing through a 2 mm sieve for the measurement of 137 Cs activity, and the other passing through a 0.15 mm sieve for the measurement of SOC concentration (Li et al., 2007). The activities of 137 Cs in soil samples were determined through a hyper-pure coaxial Ge detector linked to a multichannel analyzer. 137 Cs activity was detected at 662 kev peak with counting time over 80,000 s

4 H. Fang et al. / Journal of Environmental Radioactivity 112 (2012) 125e Table Cs inventories at the reference site (Bq m 2 ). Sampling points R 1 R 2 R 3 R 4 R 5 Mean value providing an analytical precision of 5%. SOC concentration was measured by the wet combustion method Data treatment Standard deviation 137 Cs activity A.U Note: R 1 er 5 represent reference sampling sites and A.U. represents 137 Cs activity uncertainty. The original measurement of 137 Cs, expressed as activity per unit mass (Bq kg 1 ), was converted into the inventory (Bq m 2 ) by soil mass (kg) of the bulked core sample and the cross-section area of the sampling device. Similarly, the measured SOC concentration (g kg 1 ) was also converted into SOC inventory (t ha 1 ). The erosion-induced SOC displacement (t ha 1 yr 1 ) was calculated by multiplying SOC concentration (g kg 1 ) by soil redistribution rate (t ha 1 yr 1 ). The 137 Cs reference inventories varied from 2139 to 3281 Bq m 2 with a mean value of 2506 Bq m 2 (Table 1). The standard deviation (SD) gave the mean fluctuation amplitude of 449 Bq m 2 around the mean 137 Cs reference inventory (Huang, 2004). Independent sample t-test demonstrated that the differences between the mean 137 Cs reference inventory, the mean values with 137 Cs <2057 Bq m 2 (mean þ SD) and with 137 Cs >2955 Bq m 2 (mean SD) were significant at the 0.01 level. Therefore, catchment areas with 137 Cs <2057 Bq m 2 and >2955 Bq m 2 can be identified as being affected by soil loss or gain, respectively. However, catchment areas with 137 Cs ranging from 2057 to 2955 Bq m 2 can t be decided whether they were subject to soil gain or loss. Based on the Mass Balance Model 2 by Walling and He (2001), the rates of soil erosion and deposition for the sampling sites were calculated with site specific parameters where g ¼ 0.6, H ¼ 4kgm 2, d ¼ 312 kg m 2 (multiplied by tillage depth of 0.25 m by soil bulk density of 1250 kg m 3 ), p and p 0 ¼ 1.0. ArcGIS 9.3 was used with the location data of field measurements to create spatial patterns of 137 Cs (Bq m 2 ) and SOC inventory (t ha 1 ). SOC displacements (t ha 1 yr 1 ) were calculated by multiplying their concentrations by soil redistribution rates (t ha 1 yr 1 ). Using ArcGIS s algorithms, SOC (t ha 1 ), 137 Cs (Bq m 2 ), soil redistribution rates (t ha 1 yr 1 ) and SOC displacement (t ha 1 yr 1 ) were calculated for each grid cell. Statistical analyses of the field measurements and the calculated grid cell values were conducted, using SPSS 14.0 software Topographical factors for the sampling points The topographical map (scale: 1: 10,000) for the study region was digitized and a 10-m resolution digital elevation model (DEM) was produced using ArcGIS 9.3. Slope gradients and curvatures at the sampling points were extracted from the DEM to study the impacts of topographical factors on 137 Cs and SOC inventories. Slope gradient for each of the sampling points was described as a percentage. A positive curvature indicates an upwardly convex surface at the sampling point, while a negative curvature indicates a concave surface, and a value of zero indicates a flat surface at the sampling site. 3. Results 3.1. Spatial patterns of 137 Cs and SOC inventories The 137 Cs inventories for the 61 soil samples collected from the catchment ranged from 582 to Bq m 2, with a mean value of Bq m 2 (Table 2). The SOC inventories of the sampling points varied greatly that ranged from 35 to 486 t ha 1, with a mean value of 132 t ha 1 (Table 2). The skewness of the SOC inventories was comparable to that of 137 Cs inventories, implying that soil redistribution, represented by 137 Cs inventory, could exert remarkable impact on the dynamics of SOC. The spatial patterns of 137 Cs and SOC are shown in Figs. 2 and 3. The areas with 137 Cs >2955 Bq m 2 (indicative of soil gain) Fig. 2. Spatial pattern of 137 Cs inventories for the sampling points in the catchment.

5 128 H. Fang et al. / Journal of Environmental Radioactivity 112 (2012) 125e132 Fig. 3. Spatial pattern of SOC inventories for the sampling points in the catchment. appeared along the shelterbelts and at the catchment outlet, while areas with 137 Cs <2057 Bq m 2 (indicative of soil loss) mainly occurred behind the shelterbelts. Noticeably, ca. 42% of the catchment areas with 137 Cs ranging from 2057 to 2955 Bq m 2 appeared mainly between the shelterbelts and in other upslope areas. These areas couldn t be decided whether they were suffered soil loss or gain. Visual inspection indicates that the correlation between 137 Cs and SOC in Figs. 2 and 3 was weak. The disagreement between the spatial patterns of 137 Cs and SOC could result from other factors other than soil erosion, including vegetative productivity, mineralization of SOC, landscape position and management (Ritchie et al., 2007; Wang et al., 2010). However, soil erosion and its subsequent soil redistribution still contribute significantly to the dynamics of 137 Cs and SOC over the landscape. Based on the grid-calculated values, the mean loss or gain rates of 137 Cs and SOC for erosion and deposition areas as well as for the entire catchment are shown in Table 3. The averages of 137 Cs and SOC inventories in the deposition areas were significantly greater than the counterparts at the eroding sites Relationships between SOC and 137 Cs To further study the relationships between SOC and 137 Cs, SOC is plotted against 137 Cs using the sampling data. Fig. 4a demonstrates that SOC inventories are linearly correlated with 137 Cs inventories with a correlation coefficient of 0.77 at the significant level, using the entire sampling dataset. However, some exceptional Table 2 Statistical characteristics of SOC, soil redistribution and 137 Cs for the sampled field measurements within the study catchment. 137 Cs inventory (Bq m 2 ) Soil redistribution (t ha 1 yr 1 ) SOC (t ha 1 ) Minimum Maximum Mean (35.4) 132 (78.9) ( ) CV (%) Skewness Values in parenthesis denote the standard deviation. CV is coefficient of variation. sampling data, such as the data with 137 Cs >10,000 Bq m 2, maybe greatly affect the established linear regression. To validate the regression between SOC and 137 Cs in Fig. 4a, the entire sampling dataset were separated into four sub-datasets: sub-datasets with 137 Cs <10,000 Bq m 2 (Fig. 4b), <4000 Bq m 2 (Fig. 4c), <2000 Bq m 2, and sub-dataset with 137 Cs ranging from 2000 to 4000 Bq m 2 (Fig. 4d). The linear regression parameters obtained from the sub-dataset with 137 Cs <10,000 Bq m 2 are much similar to the counterparts in Fig. 4a. However, when the sub-dataset with 137 Cs <4000 Bq m 2 is used, the linear regression parameters as well as their standard uncertainties in Fig. 4c are quite different from the corresponding parts in Fig. 4a and b although the correlation coefficient of 0.34 is still significant at the 0.01 level. When the exceptional high values of SOC >250 t ha 1 are deleted from the sub-dataset with 137 Cs <4000 Bq m 2, except for great changes of the regression parameters and their standard uncertainties compared to those in Fig. 4a,b and c, the correlation coefficient of 0.15 between SOC and 137 Cs becomes insignificant (p > 0.28; Fig. 4d). A closer analysis from Fig. 4c and d indicates that there is not any relationship between SOC and 137 Cs when 137 Cs inventories are <2000 Bq m 2. However, significant correlated relationships are found at the significant level between SOC and 137 Cs when the 137 Cs inventories range from 2000 to 4000 Bq m 2 (Fig. 4c and d) SOC displaced by soil redistribution Deriving from soil redistribution rate and SOC concentration, the spatial pattern of SOC displacements is shown in Fig. 5 and the SOC displacements based on the calculated grid-cell values are listed in Table 4. The spatial pattern of SOC displacements is identical to that of 137 Cs inventories (Figs. 2 and 5). Over the past 56 years (from 1954 to 2010), the mean SOC loss and gain rates in the erosion and deposition areas were 426 and 325 kg ha 1 yr 1 with variation coefficients of 46% and 95%, respectively (Table 4). In terms of the kriged, interpolated map of SOC displacement, around 37% and 21% of the catchment area presented SOC loss and gain, respectively. This means that around 42% of the eroded SOC was redeposited again within the catchment. The mean SOC loss rate

6 H. Fang et al. / Journal of Environmental Radioactivity 112 (2012) 125e Table 3 Statistical characteristics of SOC, soil redistribution and 137 Cs over the catchment based on the calculated grid-cell values. Area Percentage (%) 137 Cs (Bq m 2 ) Soil redistribution (t ha 1 yr 1 ) SOC (t ha 1 ) Mean CV (%) Mean CV (%) Mean CV (%) Erosion a (360) a (8.7) a (24) 21 Deposition b (648) b (12.6) b (46) 31 Total (805) (19.6) (31) 24.6 Sites with soil loss are listed as erosion grid cells while sites with soil gain as deposition grid cells. Values in parenthesis denote the standard deviation. CV is coefficient of variation. Means with different letters are significantly different at the 0.05 level of probability. Fig. 4. Relationships between SOC and 137 Cs inventories for all the samples (a), for the samples with 137 Cs <10,000 Bq m 2 (b), for the samples with 137 Cs <4000 Bq m 2 (c), and for the samples with 137 Cs <4000 Bq m 2 and SOC <250 t ha 1 (d). Note: u(a) and u(b) are standard uncertainties for parameters a and b in regression equation Y ¼ ax þ b. Fig. 5. Spatial pattern of SOC redistribution for the sampling points in the catchment.

7 130 H. Fang et al. / Journal of Environmental Radioactivity 112 (2012) 125e132 Table 4 Erosion-induced SOC redistributions since 1954 over the catchment based on the calculated grid-cell values. Area Percentage (%) SOC (10 3 tha 1 yr 1 ) Mean CV (%) Erosion a (198) 46 Deposition b (309) 95 Catchment (384) 413 Sites with soil loss are listed as erosion grid cells while sites with soil gain as deposition grid cells. Values in parenthesis denote the standard deviation. CV is coefficient of variation. Means with different letters are significantly different at the 0.05 level of probability. across the investigated catchment was 92.8 kg ha 1 yr 1. During the past 56 years, the totaled net SOC loss of the investigated catchment was 148 t. 4. Discussion Gentle and long slopes characterize the black soil region in Northeast China. Soil redistribution, depending on the topography and land configuration (Li et al., 2007), can concentrate SOC in depositional areas. The impact of topography on SOC is assessed through plotting 137 Cs and SOC against slope gradient and curvature. The correlations are not significant between 137 Cs inventory and slope gradient and curvature (Fig. 6a,b), nor between SOC inventory and slope gradient and curvature (Fig. 6c,d). Similar findings were also reported by Fulajtar (2003), Bujan et al. (2003) and Afshar et al. (2010) for the fields in Slovakia, Argentina and Iran. Topographic factors greatly influence soil redistribution in literature (e.g., Li et al., 2007; Tiessen et al., 2009). However, in our present study, impacts of the shelterbelts and the developed ephemeral gullies on soil and SOC patterns can be so important that the influence of topographic factors on the redistributions of soil and SOC is insignificant. The shelterbelts were built during 1970s in the study area (Zhu, 1985, Fig. 1) that split the long slope into smaller ones. The shelterbelts within the agricultural catchment can greatly influence the redistributions of soil and SOC since the peak 137 Cs fallout occurred between 1962 and The shelterbelts can, on one hand, to some extent prevent the eroded soil and SOC from migrating downslope, and on the other hand, shelterbelts can also reduce water flow energy when runoff passes across the shelterbelts. Therefore, the areas without erosion or deposition occurred between the shelterbelts can be explained by the clauses mentioned above, while those occurred at the catchment boundaries maybe result from flat topography and short distance from slope summit (Figs. 2 and 5). In the study catchment, an ephemeral gully system behind the lower shelterbelt occurs twice a year, inducing severe soil loss from the lower catchment (Cui, 2007). The contribution of soil loss from the ephemeral gullies was estimated to be 31% during 2010 (Fang et al., in press). Importantly, besides slope gradient, one of the major factors influencing the development of ephemeral gullies is slope length (Zhang et al., 2007a, b). The development of ephemeral gullies in the lower catchment can disrupt the impacts of slope gradient and curvature on the redistributions of soil and SOC. Therefore, the weak relations of 137 Cs and SOC with slope gradients and slope curvatures can be explained firstly that soil and SOC maybe greatly influenced by the long and gentle slopes in the study region (Cui et al., 2007) and, secondly, the shelterbelts and the developed ephemeral gullies can greatly reduce the impact of slope gradient and curvature on the redistributions of soil and SOC. It is, however, important to recognize that although the on-site impacts of slope gradient and curvature maybe limited importance, the off- Fig. 6. Relationships between 137 Cs inventories and slope gradients (a) and curvatures (b), and between SOC inventories and slope gradients (c) and curvatures (d). Note: u(a) and u(b) are standard uncertainties for parameters a and b in regression equation Y ¼ ax þ b.

8 H. Fang et al. / Journal of Environmental Radioactivity 112 (2012) 125e site impacts linked to sediment transfer downslope may still be important. The soil redistribution across the catchment results in SOC loss at the erosion sites and SOC gain in the deposition areas (Fig. 5). The kriged, interpolated catchment data yielded a net SOC loss rate of t ha 1 yr 1 during 1954e2010. The SOC loss rate is much lower than that on the cultivated hillslope of the Chinese Loess Plateau (0.24 t C ha 1 yr 1 ; Li et al., 2007). This can be attributed to the gentle slope and the established shelterbelts. In our present study, over 42% of the eroded SOC was redeposited within the catchment. This portion of SOC should be taken into account when SOC budget is determined for agricultural soils. The remaining 58% of the carbon lost through erosion can have either been transported out of the catchment or lost through decomposition. SOC redeposition over the landscapes for agricultural soils can be a source of the apparent missing C sink. Literatures demonstrated that SOC and 137 Cs had the same physical mechanism moving in the soils over the cultivated hillslope (Ritchie et al., 2007; Li et al., 2006, 2007). However, although significant relationships between SOC and 137 Cs are found when the entire sampling dataset or some sub-datasets are used, the dataset with 137 Cs <2000 Bq m 2 shows no relationship between SOC and 137 Cs (Fig. 4c and d). The changeful parameters and standard uncertainties for the linear regressions in Fig. 4 indicate that using 137 Cs technique to directly study SOC dynamics must be cautious in the black soils. In our present study, the sub-dataset with 137 Cs <2000 Bq m 2 corresponds to the erosion areas. This finding agrees with the proposed assertion that SOC and its redistribution directly relate to the quantity of eroded soil (Kreznor et al., 1992; Pennock and Frick, 2001). The disagreement between SOC and 137 Cs with 137 Cs <2000 Bq m 2 can be contributed to other factors, such as vegetative productivity, mineralization of SOC and land management, as mentioned earlier. These factors can greatly influence less 137 Cs-involved soils compared to the 137 Cs-rich soils. Moreover, 37.5% of the investigated catchment suffered erosion area (Table 4). These conditions could explain the difference of spatial patterns of 137 Cs and SOC (Figs. 2 and 3). Whether there is indeed no relationship between SOC and 137 Cs when 137 Cs is <2000 Bq m 2? The samples in our present study seem less, more and denser samples in larger areas should be collected to verify this finding in the typical black soil region of Northeast China. Soil redistribution rate at a site is estimated from the difference between 137 Cs remaining in the profile and the 137 Cs reference level, and SOC displacement is determined by soil redistribution and SOC concentration. Therefore, although there are no general relations between SOC and 137 Cs as mentioned in Figs. 4 and 6, they can t influence the estimate of SOC displacements over the catchment landscape, and the spatial pattern of SOC displacements is identical to that of 137 Cs inventories (Figs. 2 and 5). 5. Conclusions In the study catchment, the relationships between 137 Cs and SOC inventories were complicated. Significant relationships occurred when 137 Cs were >2000 Bq m 2, while no relations were observed when 137 Cs were <2000 Bq m 2. Vegetative productivity and SOC mineralization of eroded versus deposited soils contributed greatly to the difference of SOC and 137 Cs spatial patterns across the landscape. The use of 137 Cs for directly assessing SOC redistribution must be cautious over the agricultural landscapes of the black soil region. The shelterbelts and the development of ephemeral gullies within the catchment can greatly influence the spatial patterns of soil and SOC. The deposition soils along the shelterbelts and at the catchment outlet have significantly higher SOC inventories than erosion areas. The mean SOC loss and gain rates in the erosion and deposition areas were 426 and 325 kg ha 1 yr 1, respectively. The net SOC loss of the catchment during 1954e2010 was around 148 t with ca. 42% of the eroded SOC being redeposited within the catchment. The redeposited SOC within the agricultural ecosystem must be considered while assessing the global carbon budget. Acknowledgments This work was financially supported by projects , , and , the Open Fund of Key Laboratory of Mollisols Agroecology, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences (grant number 2011ZKHT-15) and the Special Foundation of President of the Chinese Academy of Sciences. The authors are grateful to the anonymous reviewers for their valuable comments that improved the manuscript. 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