Using 137Cs measurements to investigate the influence of erosion and soil redistribution on soil properties

Applied Radiation and Isotopes 69 (2011) 717–726

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Using 137Cs measurements to investigate the influence of erosion and soil redistribution on soil properties P. Du a,b, D.E. Walling b,n a b

School of Geography, Beijing Normal University, Beijing, China Geography, College of Life and Environmental Sciences, University of Exeter, Amory Building, Rennes Drive, Exeter, EX4 4RJ, Devon, UK

a r t i c l e i n f o

abstract

Article history: Received 2 September 2010 Received in revised form 29 November 2010 Accepted 14 January 2011 Available online 21 January 2011

Information on the interaction between soil erosion and soil properties is an important requirement for sustainable management of the soil resource. The relationship between soil properties and the soil redistribution rate, reflecting both erosion and deposition, is an important indicator of this interaction. This relationship is difficult to investigate using traditional approaches to documenting soil redistribution rates involving erosion plots and predictive models. However, the use of the fallout radionuclide 137 Cs to document medium-term soil redistribution rates offers a means of overcoming many of the limitations associated with traditional approaches. The study reported sought to demonstrate the potential for using 137Cs measurements to assess the influence of soil erosion and redistribution on soil properties (particle size composition, total C, macronutrients N, P, K and Mg, micronutrients Mn, Mo, Fe, Cu and Zn and other elements, including Ti and As). 137Cs measurements undertaken on 52 soil cores collected within a 7 ha cultivated field located near Colebrooke in Devon, UK were used to establish the magnitude and spatial pattern of medium-term soil redistribution rates within the field. The soil redistribution rates documented for the individual sampling points within the field ranged from an erosion rate of  12.9 t ha  1 yr  1 to a deposition rate of 19.2 t ha  1 yr  1. Composite samples of surface soil (0–5 cm) were collected immediately adjacent to each coring point and these samples were analysed for a range of soil properties. Individual soil properties associated with these samples showed significant variability, with CV values generally lying in the range 10–30%. The relationships between the surface soil properties and the soil redistribution rate were analysed. This analysis demonstrated statistically significant relationships between some soil properties (total phosphorus, % clay, Ti and As) and the soil redistribution rate, but for most properties there was no significant relationship. This suggests that other factors, in addition to soil erosion and soil redistribution, are also important in causing spatial variability in soil properties, or that, because of the relatively deep soils, soil properties are relatively insensitive to soil redistribution processes. The importance of the erosional history of the field was explored using a simple model to predict changes in soil properties in response to the magnitude of the erosion or deposition rate and the length of the period during which the field had been subject to soil erosion and soil redistribution. & 2011 Elsevier Ltd. All rights reserved.

Keywords: 137 Cs Soil redistribution rate Soil erosion Deposition Soil properties Erosional history

1. Introduction Although the off-site impacts of soil erosion linked to diffuse source pollution and the impact of increased fine sediment loadings in streams on aquatic habitats have attracted increasing attention in recent years (e.g. Clark, 1985; Pimentel et al., 1995; Walling and Collins, 2008), the on-site impacts remain an important environmental concern in many areas of the world (Lal, 2001). Soil erosion results not only in a loss of surface soil and thus a reduction in soil depth and water holding capacity, but

n

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it can also cause changes in soil properties, due to selective mobilisation and redistribution of soil constituents as well as loss of topsoil. Changes in soil properties can result in reduced crop productivity and a deterioration in soil quality, which may impact on ecosystem functioning and the longer term sustainability of the soil resource (Karlen et al., 1997). On cultivated land in particular, soil erosion and associated soil redistribution can exert an important influence on the physical and chemical properties of the soil (e.g. Fullen, 1991; Fullen and Brandsma, 1995; Fullen et al., 1996) and may be a key factor in determining the range of variability of soil properties within fields (e.g. Kreznor et al., 1989; Lobb et al., 1995; Pennock, 1997, 1998; Van Oost et al., 2000; Ampontuah et al., 2006). On cultivated land, changes in the properties of surface soils due to erosion can reflect both the

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selective mobilisation and removal of soil constituents and the effects of reduced soil depth in incorporating soil from below the original plough horizon into the plough layer. In addition, where soil redistribution involves deposition within a field, the properties of the deposited sediment may differ from those of the parent soil and therefore again cause changes in the properties of the surface soil. In order to explore in more detail the impact of soil erosion on soil properties, soil quality and crop productivity, there is a need to investigate the relationship between soil properties and the soil redistribution rate, which can reflect both erosion and deposition. This relationship can play an important role in defining soil loss tolerance (e.g. Larson et al., 1983), which is often seen as a key parameter in the design of effective soil conservation strategies. However, the precise form of the relationship will reflect a wide range of controls related to soil depth and other soil characteristics and to local land use practices. It may therefore be site specific and difficult to generalise. As a result, there will frequently be a need to explore the relationship empirically for a specific location. Because the influence of soil erosion and soil redistribution on soil properties will commonly reflect the operation of these processes over extended periods, it is difficult to design experiments to assemble this information directly. Soil samples could be collected from erosion plots and their properties related to measured erosion rates, but the timescale of such plot experiments may be too short to provide reliable data. Equally a substantial number of plots characterised by different erosion rates would be required. Furthermore, such plots only provide a spatially lumped assessment of the net downslope export of soil across the lower threshold of the plot. They are unable to provide information on the variability of erosion rates within the plot or on the incidence and magnitude of deposition and uncertainty may exist as to the extent to which a small bounded area can be representative of the wider landscape. Within such wider landscapes, sizeable areas of deposition are likely to occur and there is a need to consider these as an integral component of the soil erosion and soil redistribution system and to compare the properties of soils experiencing erosion and deposition and explore the relationship between soil properties and the rate of deposition for depositional sites. This is essentially impossible using erosion plots. In view of these and other problems in adopting an experimental approach, most studies take an inferential or inductive approach and relate the variability of soil properties within a field or small area to equivalent information on the ongoing rates of soil loss. The strength and rigour of the inductive approach will clearly depend heavily on obtaining reliable and relevant information on both rates of soil redistribution and soil properties. In some studies, a semi-quantitative approach has been adopted, wherein areas of high and low soil loss are identified within a field and the properties of soils within these areas are compared (e.g. Low, 1972; Ebeid et al., 1995; Fenton et al., 2005; Malo et al., 2005). However, in order to obtain a more detailed assessment of the relationship between soil properties and soil redistribution rate, more precise information on the magnitude of erosion rates, and ideally also deposition rates, is required. In several existing studies, models or erosion prediction procedures, including the USLE, WEPP and WaTEM have been used to estimate soil redistribution rates (e.g. Bacchi et al., 2003; Li et al., 2007). Use of such models removes the need for field monitoring and it is possible to estimate longer-term soil redistribution rates for a range of local conditions or management practices. However, they are most appropriate for obtaining estimates of the mean soil redistribution rate for a field or transect rather than a point specific value that can be linked to an individual soil sample used to document soil properties. Point specific estimates of long-term soil redistribution rates can sometimes be obtained by comparing the depth of the soil profile

above a specific horizon with the equivalent depth recorded at a point that is judged to have experienced neither soil erosion nor deposition (see Geng and Coote, 1991; Sidorchuk and Golosov, 2003). However, in order to estimate the rate of soil loss or accretion, there will be a need to specify the duration of the period over which erosion has occurred. In some locations, it may be possible to link the onset of significant erosion to a date representing the initiation of land clearance and soil cultivation, but in others the longer-term erosional history of a site may be uncertain. In addition, constraints may exist in assembling appropriate information on soil properties to link with estimates of soil redistribution rates. These will reflect the spatial scale associated with the estimate of the soil redistribution rate (e.g. point, transect or field) and the need to obtain equivalent representative information on soil properties. For cultivated soils, it is probably most appropriate to focus on the plough layer, since this should be fairly homogeneous as a result of mixing by tillage. If surface samples are collected, it is therefore important to ensure that these are representative of the plough layer. If deeper soil cores are collected (e.g. Nie et al., 2010; Afshar et al., 2010), it is important that the implications of sampling depth should be recognised. If cores extend to depths in excess of the plough layer, they are likely to incorporate subsoil and any measure of soil quality will reflect both the influence of the rate of erosion or soil redistribution on the properties of the plough layer and the amount of soil from beneath the plough depth included in the core. Variation in the latter could mask the former. Against this background, recent developments in the use of fallout radionuclides, and more particularly caesium-137 (137Cs), to estimate soil redistribution rates (cf. Walling, 1998, 2002; Zapata, 2002; Mabit et al., 2008) would appear to offer considerable potential for investigating the impact of soil erosion on soil properties. In particular, 137Cs measurements afford a means on estimating the mean annual rate of soil redistribution over the past ca. 50 yr at a specific point in the landscape. Early attempts to exploit the potential of 137Cs measurements in studies investigating the relationship between soil properties and soil redistribution rates, which include the work of Mabit and Bernard (1998), Pennock (2000), Ritchie et al. (2007) and Ge et al. (2007), focused on using values of 137Cs inventory as a surrogate for the soil redistribution rate. By comparing these values with the local reference inventory it was possible to identify points with erosion rates of different severity and points where there was evidence of deposition. Information on soil properties was readily obtained for the same points by collecting samples from those points. Such, attempts to explore the relationship between soil properties and the soil redistribution rate were essentially qualitative, since the relationship between soil redistribution rate and the 137Cs inventory is itself likely to be non-linear and the distinction between erosion and deposition is not readily apparent if a continuous scale is used for the 137Cs inventory. In these early studies, emphasis was often placed on comparing the spatial pattern demonstrated by 137Cs inventories with those shown by soil properties and pointing to similarities. Some studies, and particularly more recent studies, have used the measurements of 137 Cs inventory to provide quantitative estimates of the soil redistribution rate (e.g. Li and Lindstrom, 2001; Mabit et al., 2008; Afshar et al., 2010), which have been used in further analysis of the link between areas of erosion and deposition and soil properties. There have, however, been few attempts to undertake detailed analysis of the relationship between soil properties and soil redistribution rates and to distinguish erosion and deposition rates. The existing work outlined above has demonstrated that 137Cs measurements offer important advantages over more traditional

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approaches to documenting rates of soil erosion and redistribution for use in investigations of the impact of soil redistribution rate on soil properties. More particularly, 137Cs measurements can: (a) Provide spatially distributed data, and, more particularly, point estimates of the soil redistribution rate at the sampling point that can be readily linked to the properties of a soil sample collected from the same point. (b) Provide time-integrated estimates of medium-term (i.e. ca. 50 yr) soil redistribution rates, which are likely to be consistent with measurements of contemporary soil properties, which will reflect the longer-term erosional history of the site. (c) Provide estimates of soil redistribution rates associated with sampling points representing both eroding and depositional areas. (d) Generate retrospective information on soil redistribution rates on the basis of a single site visit, thereby avoiding the need for extended periods of monitoring. (e) Generate estimates of soil redistribution rate for points distributed across natural landscapes, without the need to disturb the landscape or construct installations and install equipment that might interfere with the natural processes operating within the landscape. This contribution reports the results of a recent study undertaken in Devon, UK aimed at exploiting further the potential for using 137Cs measurements to investigate the relationship between soil properties and soil redistribution rate, by focusing on the nature of the relationship for a range of soil properties and more explicitly distinguishing erosion and deposition rates.

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associated with typical brown earth soils of the Crediton series. The mean annual average temperature and mean annual rainfall (1961–90) for the location are ca.9.9 1C and 811 mm, respectively. At present and in the recent past, the field has been used for cereal cultivation with a periodic grass ley. The field is typically ploughed in the late summer or early autumn after harvest (plough depth ca. 22 cm) and sown with autumn-sown cereals. No significant Chernobyl fallout was recorded in this area of the UK (Allen, 1986). Bulk soil cores were collected from 52 points within the study field located along eight transects (see Fig. 1), using a motorised percussion corer equipped with a 6.9 cm diameter steel core tube. The cores extended to a depth of 40 cm over most of the field, but this depth was increased to 60 cm in areas where there was evidence of deposition or deposition could be expected. Separate composite samples (ca. 200 g) of the surface soil (0–5 cm), subsequently used for analysis of soil properties, were collected from points immediately adjacent to the coring points, using a stainless steel trowel, which was repeatedly cleaned to avoid cross-contamination of the samples. In addition, larger diameter cores were collected with the percussion corer from 3 positions on the upper, middle and lower slopes of the field (see Fig. 1), using an 11 cm diameter PVC core tube for subsequent sectioning. These cores were sectioned into 2 cm increments to provide information on the vertical distribution of 137 Cs within the profile. Nine additional bulk soil cores and a further large diameter core for sectioning were collected from a nearby (ca. 600 m) undisturbed flat area under permanent grassland that was judged to have been unaffected by erosion or deposition over the past 60 yr and which served as a reference site. All samples were collected during August 2009, immediately after the harvesting of the cereal crop. 2.2. Laboratory analysis

2. Materials and methods 2.1. Description of the study area and field sampling The study focused on a 7 ha cultivated field located near Colebrooke, Devon, UK (501470 N, 31450 W (Fig. 1). The local area is underlain by Permian sandstones and marls, which are

The samples collected from the study field were returned to the laboratory, where the four larger diameter cores were sectioned into 2 cm increments. All samples were subsequently air dried, disaggregated using a pestle and mortar, sieved to o2 mm and homogenised. In the case of the 52 samples of surface soil collected for analysis of soil properties, a small aliquot

Fig. 1. The study field near Colebrooke, Devon, UK, showing its location within the UK, its DEM and the distribution of the 52 points from which bulk soil cores and samples of surface soil were collected. The locations of the three sectioned cores, representative of the upper, middle and lower slopes, collected from the field are also shown by crosses.

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of ca. 10 g was sieved to o 0.063 mm. This o0.063 mm fraction was used for analysis of all soil properties, with the exception of grain size, where the analysis was undertaken on the o2 mm fraction. Small (ca. 150 g) aliquots of the 34–36 cm depth increment from the sectioned cores collected from the upper and middle slopes of the field were also retrieved and processed as indicated above, in order to provide information on the properties of the subsoil. Analysis of the 137Cs mass activity density (Bq kg  1) associated with the o2 mm fraction of the bulk cores and the depth increments of the sectioned cores was undertaken by gamma spectrometry using ORTEC high-resolution, low-background, n-type, coaxial germanium detectors. The detectors were calibrated for 137Cs measurements at 662 keV, using soil/sediment standards prepared using certified liquid standards. The 450 g sub-samples obtained from the bulk cores were loaded into Marinelli beakers for gamma counting, whereas the 120 g subsamples obtained from the depth incremental samples were placed into plastic pots for counting. Depending on sample activity, count times ranged from 80,000 to 100,000 s, providing a counting precision of less than 6% at the 95% level of confidence. Minimum detection activities were  0.3 Bq kg  1. The measured 137 Cs mass activities (Bq kg  1) were converted to values of areal activity density (Bq m  2). Soil bulk density was estimated using the air-dry weight of the core samples and the depth and cross-sectional area of the cores. Total nitrogen and total carbon were determined using a Carlo

Fig. 2. The depth distribution of slopes (d) of the study field.

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Erba NA2500 Elemental Analyser. Total phosphorus and inorganic phosphorus were measured using a Unicam 5625 UV/VIS spectrometer following the procedure described by Mehta et al. (1954). Concentrations of potassium and a range of metals and trace elements (Mg, Mn, Mo, Fe, Cu, Zn, Ti and As) were measured using an ICP-MS following direct digestion with aqua regia. Particle size was measured using a Micromeritics 5200 laser digisizer following H2O2 treatment to remove organic matter and chemical and ultrasonic dispersion.

3. Results and discussion 3.1.

137

Cs activity

The values of 137Cs areal activity density obtained for the cores collected from the field varied greatly and ranged from 1109 to 3389 Bq m  2, with a mean value of 1833 Bq m  2. Based on the inventories measured for the multiple bulk cores (9) and the sectioned core collected from the reference site (CV 8%), the 137Cs reference inventory for the study area was estimated to be 19507100 Bq m  2 at the 95% level of confidence. Fig. 2 shows the depth distribution of the 137Cs mass activity in soil cores collected from the undisturbed reference location adjacent to the study site (a), from upper- and mid-slope areas of the study field experiencing soil loss (b and c) and from a depositional area on the lower slope (d). The 137Cs depth distribution associated with

Cs documented for an undisturbed reference site adjacent to the study field (a), and for points on the upper (b), middle (c) and lower

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the undisturbed reference site depicted in Fig. 2a demonstrated the expected exponential decline in 137Cs activity with depth. No 137 Cs activity was detected below 30 cm depth in this sectioned core and ca. 95% of the total 137Cs inventory was found in the 0–20 cm depth increment. Fig. 2b and c, which presents depth distributions from the cultivated field provides clear evidence of mixing within the plough layer, which extends to a depth of 20–22 cm. The 137Cs depth distributions for these cores also confirm that the sub-samples collected from the 34–36 cm depth increment can be seen as representative of the subsoil below the plough layer. In Fig. 2d, the zone of near homogeneous 137Cs activity, which is characteristic of the plough layer, extends well below the plough depth indicated by cores a and b and provides clear evidence of progressive accumulation of 137Cs-bearing soil eroded from upslope. This core indicates that ca. 16 cm of soil has been deposited since the main period of 137Cs fallout and therefore in the last ca. 50 yr. 3.2. Spatial patterns of soil redistribution The values of 137Cs inventory or areal activity density associated with the individual sampling points within the study field have been converted to estimates of soil redistribution rates (t ha  1 yr  1) using Mass Balance Model 2 (MBM 2; Walling and He, 1999; Walling et al., 2002). This conversion model compares the measured inventory with the local reference inventory and determines the erosion or deposition rate required to account for the depletion or increase of the measured inventory, relative to the reference inventory. Site specific parameters used with MBM 2 for the study field were g ¼0.7, H¼4 kg m  2, dm ¼170 kg m  2, P and P0 ¼1.0. The estimates of soil redistribution obtained reflect the effects of soil redistribution by both water erosion and tillage erosion and represent mean annual values for the past ca. 50 yr. The estimated soil redistribution rates for the 52 individual sampling points ranged from a maximum erosion rate of 12.9 t ha  1 yr  1 to a maximum deposition rate of 19.2 t ha  1 yr  1. Fig. 3 shows the spatial pattern of soil redistribution within the study field derived by interpolating the values obtained for the individual sampling points using the Surfer Golden 9.0 software package. A greater density of cores is ideally required to define in detail the spatial pattern of soil redistribution within the study field, but Fig. 3 is deemed to provide a meaningful representation of this pattern.

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The pattern of soil redistribution shown by Fig. 3 indicates that maximum erosion rates ( 10 to  15 t ha  1 yr  1) are generally found towards the lower areas of the transects, where slope gradients are steepest and are coupled with substantial slope lengths. Other areas with high erosion rates ( 5 to  10 t ha  1 yr  1) are located near the upper boundary of the study field, where slope gradients are relatively high but there is no opportunity for significant soil input from upslope because of the barrier provided by the hedge bank which forms the field boundary. In this case tillage erosion is likely to be a key process. The areas characterised by deposition largely coincide with the base of the slopes and particularly the depression, which extends upslope from the lower boundary. These areas of the field receive sediment mobilised from upslope and deposition rates of 410 t ha  1 yr  1 are found in several areas. Overall, Fig. 3 demonstrates that the area subject to erosion greatly exceeds the area where deposition is found and most of the field is characterised by an erosion rate between 0 and  10 t ha  1 yr  1. Spatial integration of the soil redistribution rates portrayed on Fig. 3 indicates a gross erosion rate for the 7 ha field of 3.3 t ha  1 yr  1 and a net erosion rate of 2.4 t ha  1 yr  1. Using these data, the sediment delivery ratio for the field is estimated to be 73%. The high value for the sediment delivery ratio emphasises that a major proportion of the sediment mobilised by erosion is exported from the field and this in turn suggests that tillage erosion is of limited importance as a driver of soil redistribution within the field. Soil mobilised and redistributed by tillage erosion will remain within the field. 3.3. Soil properties Table 1 summarises the results for the values of 137Cs inventory obtained for the 52 sampling points and for the properties of the samples of surface soil collected immediately adjacent to the coring points and of the 2 subsoil samples obtained from sectioned cores b and c. The results presented in Table 1 demonstrate that in terms of most properties the subsoil differs considerably from the surface soil. For the surface soil, the properties included in the investigation are characterised by coefficients of variation (CV) in the range 10–30%. The CV value for 137Cs (26.59%) lies towards the upper end of the range, suggesting that erosion and soil redistribution processes, exert a

Table 1 Summary data for the properties of the soil samples collected from the study field. Property

137

All surface samples (n¼ 52)

2

Cs (Bq m ) Sand (%) Silt (%) Clay (%) N (%) C (%) Pto (mg kg  1) Pin (mg kg  1) Por (mg kg  1) Mg (mg kg  1) K (mg kg  1) Mn (mg kg  1) Mo (mg kg  1) Fe (mg kg  1) Cu (mg kg  1) Zn (mg kg  1) Ti (mg kg  1) As (mg kg  1) Fig. 3. Soil redistribution rates within the study field estimated using the 137Cs measurements. Negative values represent erosion, whereas positive value reflect deposition.

Subsoil (n¼ 2)

Mean

SD

CV (%)

Mean

1833 24.63 56.34 19.03 0.43 2.16 1094 730 365 478 1120 1182 0.47 8719 16.56 37.18 8.83 4.52

487 5.76 3.98 2.96 0.03 0.25 139 101 108 57.60 158 387 0.10 1088 4.64 7.83 1.96 0.69

26.59 23.38 7.07 15.53 6.61 11.59 12.70 13.85 29.71 12.06 14.07 32.74 22.33 12.48 28.02 21.05 22.24 15.23

0 11.9 67.3 20.9 0.31 0.34 323 267 55.95 424 695 439 0.4 15,388 2.7 22.12 3.5 3.09

SD (Standard deviation), CV (Coefficient of Variation), Pto (Total phosphorus), Pin (Inorganic phosphorus), Por (Organic phosphorus).

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greater influence on the 137Cs inventory of the soil, than on many other properties. The sensitivity of 137Cs to erosion and soil redistribution is probably to be expected, since 137Cs is not a natural constituent of the soil, but was supplied to the soil surface by fallout largely during the period of bomb fallout in the late 1950s and 1960s and the stock has not subsequently been replenished. Nevertheless, several other soil properties are characterised by CV values of a similar magnitude.

analysis of the relationship between soil properties and soil redistribution rate is required to explore this influence further. Table 3 presents Pearson’s correlation coefficients between soil redistribution rate and the measured properties for all 52 samples and for the groups comprising eroding and depositional sites. In the former case, the redistribution rate is treated as a continuous variable extending from negative values for erosion to positive values for deposition. These results demonstrate that there are few statistically significant relationships between soil properties and soil redistribution rate. Significant correlations only exist for the total dataset. Here, however, only two properties (Ti and As) provide correlation coefficients significant at the 495% level and these are still relatively low (0.363 and 0.407). Two further properties (% clay and total phosphorus) provide correlation coefficients that are significant at the 490% level.

3.4. The influence of erosion and soil redistribution on soil properties In order to explore further the influence of soil redistribution processes on the soil property values and their spatial variability, the 137 Cs inventories associated with the 52 points from which samples of surface soil were collected have been subdivided into three groups, representing eroding points (137Cs inventories o1850 Bq m  2), depositing points (137Cs inventories 42050 Bq m  2) and stable points (137Cs inventories 1850–2050 Bq m  2). Table 2 presents the data subdivided in this way and provides the results obtained when using the Students t test to determine if there is a statistically significant difference between the soil property values for eroding and depositing points. The t test has been used, in preference to a non-parametric test, since the data for the individual properties were shown to be normally distributed. The results of the t test indicate that, at the 95% level of confidence, only 4 out of the 18 properties, including the 137Cs inventory (i.e. 22%) show a significant difference between eroding and depositing points, with the values for depositing sites exceeding those for eroding sites in 3 out of 4 cases. If the confidence level is reduced to 90%, the number of properties exhibiting a significant difference increases to 6, with values for depositing sites exceeding those for eroding sites in 5 out of 6. The above findings suggest that soil redistribution, as reflected by the presence of eroding and depositing sites, does not exert a major influence on soil properties in the study field. However, where a significant difference exists, the property values for depositing sites are generally greater than those for eroding sites. This could reflect either some feature of mobilisation and deposition processes, which increase the property values in depositional areas, or the effects of erosion in reducing the values for eroding areas. More detailed

Table 3 The correlation between soil properties and soil redistribution rate. Property

ra

re

rd

Sand Silt Clay N C Pto Pin Por Mg K Mn Mo Fe Cu Zn Ti As

0.134 0.026  0.296*  0.062 0.191 0.317* 0.160 0.258  0.104  0.130 0.004 0.247  0.198 0.159  0.068 0.363** 0.407**

 0.039 0.058  0.006  0.041 0.186 0.119 0.127 0.026  0.186  0.123  0.136  0.128  0.222  0.131  0.094  0.068 0.179

 0.397 0.312 0.326  0.406  0.21 0.288 0.061 0.346 0.299  0.236  0.374  0.053  0.188  0.332 0.117 0.165  0.145

ra: Correlation coefficient for all samples. re: Correlation coefficient for samples from eroding sites. rd: Correlation coefficient for samples from deposition sites. n

Correlation coefficient statistically significant at 490% probability. Correlation coefficient statistically significant at 495% probability.

nn

Table 2 Comparison of soil properties for samples from the study field subdivided into eroding, depositing and stable sites, based on their Property

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Cs (Bq m  2) Sand (%) Silt (%) Clay (%) N (%) C (%) Pto (mg kg  1) Pin (mg kg  1) Por (mg kg  1) Mg (mg kg  1) K (mg kg  1) Mn (mg kg  1) Mo (mg kg  1) Fe (mg kg  1) Cu (mg kg  1) Zn (mg kg  1) Ti (mg kg  1) As (mg kg  1) n

Cs inventories.

Eroding sites (n ¼35)

Depositing sites (n¼ 14)

Stable sites (n¼ 3)

Mean

SD

Mean

SD

Mean

SD

Comparison of eroding and depositing sites t test results

1560 23.30 56.66 20.04 0.43 2.12 1073 722 351 483 1131 1134 0.45 8809 15.60 37.66 8.22 4.30

209 5.53 3.99 2.64 0.03 0.28 143 110 115 63.19 177 412 0.11 1178 3.80 8.25 1.85 0.67

2491 26.42 56.14 17.44 0.43 2.22 1164 752 412 470 1109 1237 0.51 8562 19.16 36.54 10.06 4.98

385 5.08 4.12 2.26 0.02 0.16 118 87.01 82.84 42.87 102 291 0.11 958 6.02 7.54 1.77 0.51

1943 31.73 53.62 14.65 0.44 2.26 1019 718 301 453 1038 1484 0.48 8393 15.53 34.59 10.22 4.93

42.55 5.38 3.14 2.57 0.03 0.10 72.83 32.27 70.15 55.14 145 430 0.01 399 1.73 4.19 0.29 0.45

 10.942**  1.827 0.410 3.237**  0.004  1.226  2.099*  0.894  1.806 0.673 0.422  0.851  1.637 0.698  2.489* 0.438  3.178**  3.445**

t Statistics statistically significant at 490% probability. t Statistics statistically significant at 495% probability.

nn

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Fig. 4 provides further information on the relationships between soil properties and soil redistribution rate found for the study field. The relationship between organic carbon (%) and soil redistribution rate presented in Fig. 4a provides an example of the poor relationship with soil redistribution rate shown by most soil properties investigated in the current study. In contrast, the plots of % clay, total phosphorus, Ti and As versus soil redistribution rate presented in Fig. 4b–e, respectively, provide evidence of some relationship. In the case of % clay, the relationship is negative, but for the other three properties it is positive. The negative relationship shown by % clay indicates that the clay content of surface soil tends to be higher for eroding points (see Table 2) with the highest values being associated with the highest erosion rates. A similar situation was reported by Bacchi et al. (2003) for a study undertaken in Brazil. This situation is, nevertheless, perhaps unexpected, since selective erosion of fines might be expected to result in a reduced clay content at eroding sites. However, Table 1 suggests that the subsoil has an increased clay content relative to that associated with the surface soil at stable sites with no erosion, and thus the increased clay content found at eroding sites may reflect the incorporation of subsoil into the plough layer by tillage, as surface soil is removed by erosion. The increased clay content of surface soil from depositional sites, relative to stable sites, suggested by Table 2 could reflect the deposition of soil with a relatively high clay content mobilised from eroding areas upslope with a higher clay content. The positive relationships with soil redistribution rate shown by the other three soil properties in Fig. 4c–e suggests that erosion depletes the concentrations of these properties in the surface soil

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by removing surface soil and causing subsoil to be incorporated into the plough layer by tillage. Table 1 confirms that the concentrations of these three properties are lower in the subsoil than in the surface soil. Li and Lindstrom (2001) reported a similar positive relationship between the total P content of surface soil and the soil redistribution rate. Interestingly, studies of lake sediment cores aimed at reconstructing the environmental history of the upstream catchment have shown that Ti can provide a sensitive indicator of erosion intensity, with Ti concentrations increasing during periods of increased erosion within the catchment (Boyle, 2001), but it is difficult to link this phenomenon to the positive relationshp between Ti and soil redistribution rate demonstrated by Fig. 4d and Table 3. This relationship could suggest that soil mobilised from areas with the highest erosion rates would be depleted in Ti. However, Table 1 indicates that the Ti content of surface soil in the study field is considerably greater than in subsoil. Therefore if increased erosion rates caused an increase in the contribution of surface soil to the sediment input to a lake, relative to other sources with a lower Ti content, this could result in an increase in the Ti content of the deposited sediment. As indicated above, the reduced Ti content of surface soil from areas with higher erosion rates in the study field could be interpreted as reflecting loss of soil with a higher Ti content from these areas and its replacement by subsoil with a lower Ti content. This is consistent with Ti providing a signal of increased erosion in lake sediments. The limited contrast in the As content of surface soil and subsoil evidenced in Table 1 makes it less easy to account for the positive relationship between the As content of surface soil and the soil

Fig. 4. The relationships between several soil properties and soil redistribution rate for the study field.

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redistribution rate shown in Fig. 4e and Table 3. Surface inputs of As from phosphate fertilizer and atmospheric deposition (Hutton and Symons, 1986) could contribute to the behaviour demonstrated by As, since these inputs would be depleted in areas with higher erosion rates, resulting in lower As levels in surface soils. However, lack of detailed information on the magnitude of such inputs in the study area precludes further examination of this potential control. The lack of significant correlations between soil properties and soil redistribution rate for the study field demonstrated by Table 3, particularly for properties such as C, N, K and organic P, suggests that the impact of soil erosion and soil redistribution rates on soil properties is very limited at this location. Similar findings are reported by Mabit and Bernard (1998) and Mabit et al. (2008) for fields in France and Quebec, Canada, although in their case the independent variable was 137Cs inventory rather than the soil redistribution rate. The results presented for the current study suggest, firstly, that soil erosion and soil redistribution do not currently exert a significant influence on soil properties in the study field and, secondly, that soil erosion therefore does not represent a significant cause for concern in terms of its impact on the properties of the plough layer. It is, however, important to recognise that although the on-site impacts of soil erosion may be of limited importance, the off-site impacts linked to sediment transfer to streams may still be important. The estimates of soil loss obtained for the study field from the 137 Cs measurements undertaken on the soil cores shown on Fig. 3 indicate that soil loss rates in excess of 5 t ha  1 yr  1 are found over about 26% of the study field. Equally, rates of deposition in excess of 5 t ha  1 yr  1 occur over a significant area at the bottom of the field and in the upslope depression that exists in this zone. These rates are not particularly high, but a soil loss rate of 2 t ha  1 yr  1 is frequently cited for the UK as a critical threshold in terms of soil loss tolerance (Morgan, 1980). The lack of evidence of a significant effect of soil erosion and soil redistribution rates on the properties of the plough layer within the study field therefore merits further consideration. Three possible reasons for this situation are, firstly, that other factors give rise to spatial variability of soil properties across the study field and that these mask the effects of soil redistribution. The second possible reason is that when combined with the soil depth and the characteristics of the soil profile within the study field, the soil erosion rates are either of insufficient magnitude to cause significant changes in soil properties or the period over which the soils have been subject to such erosion rates is as yet insufficient to have caused significant changes in soil properties. The third possible reason is that there is temporal discrepancy between the measures of soil property and soil redistribution rate. For example, the estimates of soil redistribution rate provided by the 137Cs measurements represent average values for the past ca. 50 yr. However, it is possible that the soil properties reflect the resultant of soil redistribution occurring over a much longer period, with both the magnitude and the pattern of those rates differing from the estimates provided by the 137Cs measurements. Looking at the possible explanations for the lack of clear relationships between soil properties and soil redistribution rates in the study field, in more detail, the relatively homogeneous geology of the study area suggests that major local variability in soil properties due to geological controls is unlikely. However, the regolith properties could reflect the impact of periglacial processes in the Pleistocene. Turning to the second possible reason, the relatively deep soils and the lack of a well developed basal horizon close to the plough depth, suggest that the soil properties are unlikely to be highly sensitive to moderate rates of soil loss. Inspection of the sectioned cores collected from eroding sites

located in the upper and middle slopes of the study field and depicted in Fig. 2b and c indicated that the subsoil extended to a depth of 450 cm, with little evidence of change in the nature of the soil profile between the depths of 25 and 50 cm. Considering that the plough layer extends to 20–22 cm and that the maximum erosion rates documented over significant areas of the field (i.e. 5–10 t ha  1 yr  1) are equivalent to an annual loss of ca. 0.5–1 mm yr  1 from the plough layer, the associated incorporation of subsoil from the base of the plough layer is unlikely to result in a substantial change in the properties of the plough layer, at least in the medium-term. To take the sand content of the plough layer as an example, Table 2 indicates that the sand content of the plough layer in a stable area unaffected by erosion is ca. 32% and Table 1 indicates that the equivalent value for subsoil from beneath the plough layer is ca. 12%. Assuming an erosion rate of 10 t ha  1 yr  1 (i.e. ca. 1 mm yr  1) and that this rate of erosion has operated over a period of ca 50 yr represented by the 137Cs measurements and has not involved the selective removal of the finer fractions, erosion will have removed ca. 25% of the plough layer and replaced this with subsoil from below the plough layer. If, for simplicity, it is assumed that this removal and replacement occurred instantaneously, rather than progressively, replacement of 25% of the plough layer with subsoil containing 12% sand would only reduce the sand content of the plough layer to ca. 27%. Over much of the field the reduction would be substantially less due to the lower erosion rates, and therefore essentially undetectable. The potential influence of the period over which erosion has occurred on changes in the properties of the plough layer has been explored further using a simple mass balance model based on an annual timestep, that takes account of the progressive replacement of the soil removed from the plough layer by subsoil and the ongoing mixing of the subsoil into the plough layer viz.   R R Ci ¼ Ci1 1 þ Csub Bd Bd where Ci is the predicted property content in year i, R the mean annual soil loss (kg m  2 yr  1), B the bulk density of soil (kg m  3), d the plough depth (m), Csub the property content for the subsoil. The model assumes complete mixing of the plough layer each year and a constant plough depth from year to year. The model has been applied to two properties of the plough layer representative of physical and geochemical properties, namely sand content and Ti content. The simulation has assumed a starting property value equivalent to the value associated with a stable uneroded site in Table 2 and has used the equivalent subsoil property value shown in Table 1. Periods of 55 yr, equivalent to the period covered by the 137Cs measurements, and an arbitrary 400 yr have been simulated. In view of changes in tillage methods and the use of horse dawn ploughs prior to ca. 1940, a shallower plough depth of 15 cm has been assumed for the period prior to 1940 in the longer simulation. The model has been used to simulate the changes in the properties of the plough layer that would be expected at each of the eroding points within the study field based on the erosion rates estimated for those points using the 137Cs measurements. The results are presented in Fig. 5, which compare the simulated property values with the measured values. In viewing Fig. 5 and interpreting the results presented, it is important to recognise that the simulation involves a number of simplifying assumptions, including uniform soil properties within the plough layer across the field at the beginning of the simulation, uniform subsoil properties for all points within the field and constant erosion rates for individual points across the period of simulation, despite changes in land use practices and tillage equipment. Emphasis is therefore placed on the variance of the observed

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Fig. 5. The relationships between observed soil properties at eroding points within the study field and those simulated for the same points, using the simple mass balance model described in the text.

and predicted values, rather than degree of agreement between the predicted and observed values. In this context, it should be noted that the results of the 55 year simulation are characterised by only limited variance when compared to the measured values of sand content and Ti content. This implies that a short period of erosion produces only a limited affect on soil properties. However, when the period of simulation is increased to 400 yr, the variance of the observed and predicted datasets are more similar. This in turn suggests that current erosion rates would need to operate for an extended period of several hundred years to produce a substantial impact on soil properties and their variation across the field. As indicated above, there is not good agreement between the observed and predicted values in Fig. 5. This is likely to reflect, at least in part, the simplifying assumptions of the model and its application. However, it is also worthy of note that the highest predicted values of sand content and Ti content after 400 yr are still ca. 25% lower than the observed values, suggesting that other processes in addition to simple replacement and mixing may be involved. To date it has not been possible to obtain information on the cultivation history of the study field, although it is known that this extends back to the 1940s. The results provided by the simulation model suggest that a much longer period of cultivation (e.g. several hundred years) would be required to cause significant changes in soil properties within the study field, and this may be an important factor in explaining the apparent lack of a clear relationship between soil properties and soil redistribution rate.

4. Conclusions This study has attempted to demonstrate the potential for using 137Cs measurements to generate information on soil erosion and soil redistribution rates for use in investigating the influence of erosion and soil redistribution on soil properties. The use of 137 Cs measurements to obtain estimates of soil redistribution rates offers many advantages over conventional approaches. In particular, the ability of 137Cs measurements to provide point estimates of medium-term average rates of soil redistribution for the ‘natural’ landscape, including both erosion and deposition rates, both retrospectively and on the basis of a single site visit, must be seen as essentially unique. The results from the case study failed to demonstrate well defined relationships between the measured soil properties and soil redistribution rates in the study field and the absence of such

relationships has been linked to the potential influence of other factors in causing variability in soil properties and the relatively low erosion rates and substantial soil depths associated with the study field. In addition, it is important to recognise that the variation of properties across a field may reflect a long erosional history and estimates of the magnitude and pattern of recent or medium-term erosion rates may not be representative of that longer history. Information on the longer-term erosional history of the study field was unavailable but it is likely that significant rates of soil loss are a product of recent land use change. In this context, a simple mass balance model was used to simulate the impact of current rates of soil loss on the properties of the plough layer and the results obtained suggested that a considerable period of erosion, extending over several hundreds of years, is likely to be required to generate substantial changes in soil properties within the study field.

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