Controlling factors for the spatial variability of soil magnetic susceptibility across England and Wales

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Abstract

We review the nature and importance of soil factors implicated in the formation of secondary ferrimagnetic minerals in soils and palaeosols worldwide. The findings are examined with respect to temperate regions through a comprehensive analysis of over 5000 samples of surface soil from England and Wales taken from a 5 × 5 km grid. Over 30 soil and environmental attributes are considered for each sample as proxies for soil forming factors. Measurements of low field magnetic susceptibility (mass specific) and frequency dependent susceptibility (mass specific and percentage) on each sample provide estimates of the concentration and grain size of ferrimagnetic minerals.

Maps of soil magnetism across England and Wales show non-random distributions and clusters. One subset of data is clearly linked to contamination from atmospheric pollution, and excluded from subsequent analyses. The concentration of ferrimagnetic minerals in the non-polluted set is broadly proportional to the concentration of minerals falling into the viscous superparamagnetic domain size range (~ 15–25 nm). This set shows clusters of high magnetic concentrations particularly over specific parent materials such as schists and slates, mudstones and limestones.

Bivariate analyses and linear multiple regression models show that the main controlling factors are parent material and drainage, the latter represented by soil drainage classes and particle size. Together these two factors account for ~ 30% of the magnetic variability in the complete dataset. A second group of factors, including climate (mean annual rainfall), relief (slope and altitude), and organisms (land use, organic carbon and pH) have subordinate control. Climate, as represented by mean annual temperature, and also pedogenic time are deemed not relevant at these spatio-temporal scales.

The findings are consistent with a largely abiotic system where the role of iron-reducing bacteria appears minor. At coarse spatial and temporal scales, secondary ferrimagnetic mineral formation is controlled by the weathering capacity to supply Fe to the surface soil. At finer scales, soluble Fe precipitates as ferrihydrite before transformation in response to periodically anaerobic conditions into other minerals including nanoscale magnetite.

Section snippets

Introduction and aims

Magnetic properties of soils are commonly used in earth and environmental sciences in diverse ways (Thompson et al., 1980, Thompson and Oldfield, 1986): as ‘fingerprints’ of sediment sources in fluvial, limnic and marine sediments (e.g. Thompson et al., 1975, Walling et al., 1979, Dearing et al., 1985, Bloemendal et al., 1988, Dearing, 1999, Dearing, 2000); as records of atmospheric pollution (Oldfield et al., 1978, Hay et al., 1997); as tools for archaeological mapping and prospecting (e.g.

Soil forming factors and magnetism

Factors of soil formation as outlined by Jenny (1941) are used conventionally to provide a framework within which to analyse the variability of soil properties.S=f(Cl,O,R,P,T)

    S

    Soil

    Cl

    Climate

    O

    Organisms/Vegetation

    R

    Relief

    P

    Parent material

    T

    Time

In theory, the Jenny equation can be used to explain the role of individual environmental factors on a soil attribute but in practice the factors are normally inter-dependent. The following paragraphs review current knowledge about the role of each factor on

Field sampling and sample analysis (see also Supplementary Information)

Soil samples from the NSI archive have been employed in this project. Field sampling of soils for the NSI was originally undertaken at sites 1000 m north and 1000 m east of 5 × 5 km grid intersections (based on the UK Ordnance Survey National Grid) across England and Wales by soil surveyors between 1978 and 1982, with some later re-sampling in the mid 1990s. At each site, a total of 25 soil cores to a depth of 15 cm from within a 20 × 20 m grid were amalgamated together in the field, and a single

Magnetic data

The complete dataset of χLF 10 6 m3 kg 1) values (n = 5656) spans three orders of magnitude (− 0.01–32.70) but is highly skewed towards the median of 0.37 with only 2% of values greater than 6.29 (Table 1). Values of χFD 10 9 m3 kg 1) also cover at least three orders of magnitude (0.00–2329.32) and are positively skewed. Values of χFD% exhibit a more normal distribution with values between 0 and 13.6% and are therefore not transformed. The reduced dataset (Table 1) has a lower median χLF value

Considerations

The presence of large numbers of organic rich soils presents an especially nonlinear response with respect to the magnetic data. Thus statistical analyses for the whole data set (Model 1) are supplemented by analysis of a data subset from which highly organic samples are excluded (Model 2). Model 2 is run with and without particle size data (Models 2a and 2b respectively). Finally, to address concerns that the impact of some environmental factors such as MAR is masked by effects of

Parent material

Both bivariate and multivariate analyses place Parent material as the factor with the highest level of explanation at this spatial scale of analysis, reaffirming the ranking of parent material as a first order control in the conceptual model (Fig. 1). The mean magnetic value for each Parentmaterialexplains a high proportion of variance in both magnetic parameters (typically ~ 23–33% depending on applied constraints). Importantly, Parent material also accounts for the most unique variance in all

Conclusions

A comprehensive analysis of soil factors and three magnetic susceptibility parameters in surface soils across England and Wales at a spatial resolution of 5 × 5 km shows that the importance of factors is broadly: 1) parent material and drainage; 2) mean annual rainfall, slope and altitude, land use, organic carbon and pH. Mean annual temperature and time (> 103 years) do not appear to be significant factors at these spatial and temporal scales. About 11% of the samples, mainly from areas close to

Acknowledgements

The research was sponsored by the UK Defence Science and Technology Laboratory, and Natural Environment Research Council (grant no. NE/D000963/2). We thank the UK National Soils Resources Institute at Cranfield University for access to the National Soil Inventory database and sample set.

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    Present address: School of Geography, University of Southampton, Southampton SO17 1BJ, United Kingdom.

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