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Soil & Tillage Research xxx (2016) xxx–xxx

G ModelSTILL 3727 No. of Pages 11

Subsoil compaction assessed by visual evaluation and laboratorymethods

Peter Bilson Obour*, Per Schjønning, Yi Peng, Lars J. MunkholmAarhus University, Department of Agroecology, Research Centre Foulum, Blichers Allé 20, P.O. Box 50, DK-8830 Tjele, Denmark, Denmark

A R T I C L E I N F O

Article history:Received 18 April 2016Received in revised form 17 August 2016Accepted 19 August 2016Available online xxx

Keywords:Subsoil compactionSubVESSSoil pore characteristics

A B S T R A C T

Subsoil compaction is one of the majorcauses of land degradationworldwide and therefore a major threat tofuture crop productivity. The objective of this contribution was to evaluate the effects of compactiontreatments on soil structure based on the numerical visual evaluation of subsoil structure (SubVESS)method and on quantitative measurements of soil pore characteristics. The effect of soil compaction wasevaluated using treatments from a compaction experiment initiated in 2010 at Research Centre Flakkebjerg,Denmark, on a sandy loam soil using five levels of compaction. In this study we used i) non-compactedreference, ii) Treatment M3, where soil was subjected to multiple passes (five wheel passes per compactionevent annually) of a tractor-trailer combination with max. wheel load of �3 Mg, and iii) M8, with multiplepasses (four wheel passes per compaction event annually) of a tractor-trailer combination with max.wheel load of �8 Mg. The tire inflation pressure was generally above the recommended pressure in order tomimic the inflation pressures commonly used in practice. The treatments were applied track-by-track in thespring of 2010–2013 when the soil water content was close to field capacity. Spring barley (Hordeum vulgareL.) was established every year after a shallow secondary tillage to �0.05 m depth to loosen the uppermostlayer. Sampling and field evaluation were done on May 7, 2014, i.e. after four years of compactiontreatments (2010–2013) and one year of recovery. The soil profiles were evaluated at the same time as soilcores were sampled at 0.3, 0.5 and 0.7 m depth. In the laboratory, we measured water content, totalporosity, air-filled porosity (ea), air permeability (ka) and calculated pore organization indices (PO1= ka/eaand PO2 = ka/ea2) on the soil cores. We estimated the blocked air-filled porosity and pore continuity indexfrom the relationship between air permeability and air-filled porosity for �30 to �300 hPa matricpotentials. Assessment using the SubVESS method showed a marked effect of the M8 treatment on soilstructural quality down to �0.65 m depth, but the effects of the M3 were not significantly differentfrom the control at any depth. This was confirmed by the laboratory-measured data, which showed thatthe M8 treatment drastically reduced total porosity, air-filled porosity, air permeability, pore sizedistribution, pore tortuosity and continuity, especially at 0.3 and 0.5 m depths.Detailed measurements of the anisotropy of soil pore characteristics at 0.3–0.4 m depth showed that for

PO2 (pore size distribution) and blocked air-filled porosity the control soil was significantly anisotropic.Although compaction with the �8 Mg wheel load affected the vertically and horizontally-oriented poresdifferently, it did not significantly affect the anisotropy of the different pore characteristics. Our resultsshowed that in general, there was a good agreement between the field and laboratory methods and thus,the two can be combined to evaluate the effects of compaction in the subsoil.

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1. Introduction

Subsoil compaction is one of the major causes of landdegradation worldwide. Over the years, the problem of subsoil

* Corresponding author.E-mail addresses: [email protected], [email protected]

(P.B. Obour).

http://dx.doi.org/10.1016/j.still.2016.08.0150167-1987/ã 2016 Elsevier B.V. All rights reserved.

Please cite this article in press as: P.B. Obour, et al., Subsoil compaction as(2016), http://dx.doi.org/10.1016/j.still.2016.08.015

compaction has worsened due to the growing weight ofagricultural machinery (Alakukku, 1996; Schjønning et al., 2015).In Europe, for instance, about 33 million hectares of agriculturalsoil are degraded by soil compaction, including subsoil compaction(Oldeman et al., 1990).

Compaction increases soil bulk density and deforms soil, whichaffects physical functions such as air and water transport. Reducedaeration due to compaction may create anoxic microsites withinthe subsoil that contribute to the emission of greenhouse gases

sessed by visual evaluation and laboratory methods, Soil Tillage Res.

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mailto:[email protected]

http://dx.doi.org/10.1016/j.still.2016.08.015



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Table 1Predicted clay and organic carbon contents of the investigated field in Flakkebjerg.Depth (m)

Block Clay (<2 mm) (kg 100 kg�1) SOC (kg 100 kg�1)

0.3 1 14 0.82 12 0.73 23 0.34 20 0.6

0.5 1 22 0.32 19 0.33 24 0.24 22 0.3

0.7 1 23 0.12 20 0.23 22 0.24 22 0.2

2 P.B. Obour et al. / Soil & Tillage Research xxx (2016) xxx–xxx


such as N2O and CH4 (O’sullivan and Vinten, 1999). Densification ofsoil layers and degradation of physical subsoil properties resultingfrom compaction may slow crop emergence and root proliferation,which will have adverse effects on crop yields (Hamza andAnderson, 2005; Arvidsson and Hakansson, 2014).

Unlike erosion, salinization and topsoil compaction, the effectsof subsoil compaction are generally invisible and can persist formany years since recovery by natural processes is slow (e.g.,Berisso et al., 2012). Moreover, the alleviation of subsoil compac-tion by natural and mechanical subsoiling is problematic andexpensive as the benefits are usually short-lived (Olesen andMunkholm, 2007). Subsoil compaction has been shown to affectsoil anisotropy (Berisso et al., 2013), which is defined as the ratio ofgiven soil properties in the horizontal direction to those in thevertical direction (Pozdnyakov et al., 2009). Changes to soilanisotropy, particularly the pore system, can have adverse effectson soil properties such as flow and transport processes and putcrucial ecosystem services at risk (Berisso et al., 2012).

There have been several studies on subsoil compaction, but onlyfew have quantified the effects of compaction induced by heavyfield traffic in the soil profile (e.g., Arvidsson, 2001; Berisso et al.,2012). Traditionally, the effects of soil compaction have beenassessed by measuring changes to bulk density and penetrationresistance (e.g., Schjønning and Rasmussen, 1994). However, moredetailed information on the effects of compaction on the poresystem is needed to quantify effects on air and water transport, androot growth, especially at different depths in the soil profile.Moreover, assessment of the effects of soil compaction using fieldand laboratory methods are often done separately. However, acombination of the two methods is needed to understand how theresults from the field method and laboratory measurementscorrespond to each other. It will also help to capitalize on therespective strengths of the methods in evaluating soil physicalproperties.

Visual assessments have proven valuable in detecting compac-tion in the topsoil and different methods have been developed forassessing the effects of management practices on soil quality. Forinstance, the visual evaluation of soil structure (VESS) (Ball et al.,2007) was developed purposefully to evaluate topsoils, whereasthe SOILpak method (McKenzie, 1998) is useful for evaluating bothtop and subsoils. The methods have their respective strengths andweaknesses in application. See Batey et al. (2015) for a detaileddescription of the methods as well as the strengths and limitations.

In general, visual evaluation of subsoil compaction is morechallenging, and the Visual Soil Examination and EvaluationWorking Group of ISTRO has therefore encouraged its developmentat their meetings in Peronne, France, in 2005 and in Flakkebjerg,Denmark, in 2011, resulting in the development of the numericvisual evaluation of subsoil structure (SubVESS) method as a toolfor assessing the quality of subsoils in relation to crop growth (Ballet al., 2015a). Further studies are needed to evaluate the ability ofthe method to assess the effects of severe soil compaction. Thispaper presents the results from a field experiment with repeatedtraffic passes over a four-year period on a sandy loam arable soil inFlakkebjerg, Denmark. The effects of compaction on crop yieldsand the natural amelioration of traffic-induced subsoil compactionare reported in separate studies by Schjønning et al. (2016a) andSchjønning et al. (2016b), respectively.

In this study, we combined field (SubVESS) and laboratorymethods to assess the effects of subsoil compaction induced by thetraffic treatments. The objectives were to: (1) conduct a visualevaluation of the subsoil structure of soils exposed to traffic withheavy agricultural machinery, (2) quantify the effects of field trafficon subsoil pore characteristics, and (3) quantify the effects of fieldtraffic on upper subsoil (�0.3–0.4 m depth) pore system anisotro-py. The following hypotheses were explored:


H1: There is a correspondence between subsoil structuralproperties evaluated by the SubVESS method and in the laboratory.

H2: Compaction due to field traffic affects subsoil porecharacteristics.

H3: Upper subsoil pore characteristics become more anisotropicdue to compaction.

2. Materials and methods

2.1. Soils

The soils used in this study were obtained from a compactionexperiment at Flakkebjerg, Denmark (WGS-83 coordinates:55�1904200N; 11�2402800E). The experiment was initiated in 2010and compaction treatments were carried out in each of the years2010–2013. Average annual precipitation and temperature (1961–1990) at the site are 586 mm and 7.5 �C, respectively (Patil et al.,2012). The soil is a sandy loam developed on Weichselian morainedeposits and classified as a Glossic Phaeozem according to theWorld Reference Base system (Krogh and Greve, 1999). Table 1shows the predicted clay and soil organic carbon (SOC) contents ofthe investigated field. Clay content varies between 12% in the uppersubsoil (0.3–0.4 m depth) to 23% in the subsoil, (0.7 m depth) andSOC decreasing from 0.8% to 0.1% at the same depths. There isvariability of clay and SOC content, especially in the upper subsoilfor the experimental blocks (Further details of the predicted clayand SOC of the investigated soil are provided in Supplementarymaterial, Table D). Schjønning et al. (2016a) reported a measuredsoil texture of the same soil. The authors reported increasing claycontent from approximately 150 g kg�1 in the plough layer to about190 g kg�1 in the 0.5–0.75 m layer. The coefficient of variation ofclay from 0 to 0.75 m depth was between 12 and 24%. Pleaseconsult Table 1 of Schjønning et al. (2016a) for details.

2.2. Experimental treatments

The design of the field experiment was a randomized blockeddesign in four replicates. Each block comprised five plotsmeasuring approximately 10 � 30 m. Treatment 1 represented inall blocks the control treatment, which was not subjected tocompaction treatment, and treatments 2, 3, 4 and 5 representeddifferent wheel loads. For this study, only treatments 1, 3 and 5were included. Treatment 3 consisted in all blocks of multiple (M)wheel passes (five wheel passes per compaction event annually) ofa tractor-trailer combination with a �3 Mg wheel load (denotedM3), and treatment 5 was in all blocks multiple passes (four wheelpasses per compaction event annually) of a tractor-trailercombination applying a maximum wheel load of �8 Mg (denoted



P.B. Obour et al. / Soil & Tillage Research xxx (2016) xxx–xxx 3


M8). The compaction treatments were applied track-by-trackacross the plots in the spring of 2010–2013 when the soil watercontent was close to field capacity. Spring barley (Hordeum vulgareL.) was subsequently established after a shallow secondary tillage(carried out in all the experimental plots, i.e. the control as well asthe compacted plots) to loosen the uppermost layer (�0.05 mdepth). In this case, the crop experienced the compaction effect inthe plough layer (except in the uppermost layer) and in the subsoil.Further details of the experimentation are given in Schjønninget al. (2016a,b).

2.3. Vertical stress in the soil profile

The machinery used for both the M3 and M8 treatmentsconsisted of a �300 HP tractor pulling a three-axle slurry tankerwith a 25 m3 capacity. For the M3 treatment, the tanker was empty,resulting in the loading characteristics listed in Table 2. For the M8treatment, the tanker was full. To achieve the �8 Mg wheel loads,the first axle of the trailer was hydraulically raised. The tireinflation pressure was generally above the recommended pressureto mimic the inflation pressures commonly used in practice.Table 2 shows calculated vertical stresses imposed by theexperimental machinery. Please consult Schjønning et al.(2016a) for details.

2.4. Field measurements

Soil profile pits of �3.4 m long � 1 m wide � 1 m deep were dugon May 7, 2014 (after four years of compaction treatments) on eachof the control plots and the plots that had been compacted with �3Mg and �8 Mg wheel loads (12 soil profile pits in total). Weassessed the subsoil structural quality (Ssq) using the SubVESSmethod described by Ball et al. (2015a). In brief, the side of the pitfacing the sun was cleaned with a knife to remove surfacescompacted or smeared during digging of the soil profile pit. Thedistinct layers were identified and recorded by observing forcontrasting color difference and soil hardness by poking a knifeinto the soil. Key diagnostic factors, namely mottling, strength,porosity, the pattern and depth of root penetration, and aggregatesize/shape were used to arrive at an Ssq score of each of theidentified soil layers. A score from a SubVESS flow chart sheet wasgiven to each of these physical properties on a scale of 1–5, where 1is best and 5 is worst.

Mottling is indicative of the degree of anaerobism. It wasrevealed by the presence of patches or spots of orange/rusty redcolor and grey/blue in the soil. A good score (1/3) was given whenthere was no mottling or mottling was faint and diffuse, i.e.aeration in the layer is not likely to affect productivity. A poor score(4/5) shows the presence of mottling associated with anthropicwaterlogging such as compaction induced by heavy machinery.Strength is the resistance of the soil to penetration by a knife or theresistance to the removal of soil fragments. Layers where soil was

Table 2Characteristics of machinery used for compaction treatments and maximum modeled veet al. (2016a) for details.

Treatment Maximum wheel load Tire inflation press

Mg kPa

M3 �3.0 290

M8 �8.0 290


easy to breakdown and fall apart when removed was given a goodscore (1/2). Intermediate score (3) was given when soil keep theirshape, but were easily broken, and poor scores (4/5) given whenfragmented soil had angular shape and were difficult to extract.Porosity was determined by evaluating the presence of visiblepores between and within aggregates or fragments, tube-likeworm, and/or root channels, and vertical cracks or fissures. Goodscores (1/2) corresponds to layers that had pores occurringthroughout. Intermediate scores (3) were given to layers thathad larger pores which were mainly cracks and earthworm holes,and poor scores (4/5) were given when porosity was low or was notvisible. Rooting was determined by the frequency and distributionof roots in the soil and the extent of any distortion of the roots as aresult of soil resistance induced by compaction. We gave a goodscore (1/2) where roots grew throughout the layer without anyrestrictions, intermediate scores were given when the roots werelocalized within cracks and worm channels, and poor scores (4/5)when the roots were thick or there were no roots due to highpenetration resistance of the soil. Aggregate shape/size reveals thesoil structure. It was assessed by crumbling or breaking apart soilfragments. Good score (1) was given to layers which had small,rounded and friable soil aggregates. Intermediate scores (2/3) weregiven when the fragmented soil aggregates were large and moreangular. Poor scores (4/5) were given to layers which had densefragmented soil aggregates and angular or the soil layer was tough,massive, plastic, hard to fragment and where knife marks werevisible.

The overall Ssq for each subsoil layer was produced based on themost frequently occurring quality structure scores of the fivediagnostic factors stated above to establish the presence orabsence of subsoil compaction characteristics. An overall score ofSsq 1 indicates a very good quality, Ssq 2–4 shows intermediate soilquality, and Ssq 5 indicates a very poor quality (Ball et al., 2015b).

2.5. Sampling

Undisturbed soil cores were taken from the soil profile pits atthe same time as the field evaluation. We sampled from threepositions in each plot. The vertical and horizontal planes weresampled at 0.3–0.4 m depth with steel cylinders (rings) of 100 mmdiameter and 80 mm height (called large soil cores in thefollowing). For the large soil cores, six soil cores per plot weretaken (three soil cores per sampling position, vertical andhorizontal) from only the control and M8 treatments resultingin a total of 48 large soil cores. In addition, �100 cm3 soil cores(called small soil cores in the following) were sampled only in thevertical direction at �0.3, �0.5 and �0.7 m depth from the control,M3 and M8 treatments. For each plot, nine soil cores were taken foreach treatment and each depth (giving a total of 324 small soilcores). The large and small soil cores were useful to obtaininformation on the effect of scale on soil physical functions andpore characteristics. The cylinders were carefully retrieved from

rtical stresses (kPa) below wheels at different soil depths. Please consult Schjønning

ure Soil profile depth Maximum vertical stress

m kPa

0.3 1080.5 620.7 40

0.3 2200.5 1410.7 92





the soil to avoid disturbing the soil cores. Cores were then trimmedusing a knife before fitting plastic lids to both ends of the cylindersto prevent evaporation. All soil cores were kept at 2 �C untillaboratory measurements and analyses. Loose soil samples weretaken at 0.3, 0.5 and 0.7 m depth at each sampling position in allinvestigated plots to estimate soil organic carbon and claycontents.

2.6. Laboratory measurements

The undisturbed soil cores were placed on sandboxes andslowly wetted with ordinary tap water for three days to removeentrapped air in the soil pores. They were saturated for a weekbefore drained to �30 and afterwards to �100 hPa matricpotentials. The large soil cores were also drained to �300 hPamatric potential by the use of ceramic plates.

Air permeability (ka) was measured at the following matricpotentials: �100 hPa for the small soil cores and at �30, �100 and�300 hPa for the large soil cores. Air permeability was measuredusing a steady-state method as described by Iversen et al. (2001a).Pressurized air at 5 hPa was applied to the soil samples and airflowthrough the samples was read from mechanical flow meters or anelectronic flow meter. Prior to the measurement, the soil at theedges of the steel ring was gently pressed to reduce air leakagealong the edges of the steel ring. Air permeability was calculatedusing Darcy’s equation as described by Ball and Schjønning (2002).All the soil samples were oven-dried at 105 �C for 24 h. Stone-washing was performed on the dried large soil cores by wetting thesamples and thereafter sieving to 2 mm to obtain the actual weightof soil (defined here as particles <2 mm) for each soil core. Theloose air-dried soil was also passed through a 2 mm sieve andbulked for each combination of plot and depth before estimatingclay and SOC contents.

2.7. Estimation of soil organic carbon and clay

The soil organic carbon and clay contents were determined byvisible near-infrared reflectance spectroscopy (vis-NIRS) on theloose air-dried soil (<2 mm).The spectral data were obtained witha NIRS 2500 instrument (FOSS, Hillerød, Denmark). Details ofmeasurements are given in Peng et al. (2014). Partial least squaresregression (Martens and Næs, 1992) was applied for chemometricmodeling. The geographically closest re-sampling strategy (Penget al., 2013) was applied to select calibration samples based on theDanish National Spectral Library. The best calibration models forclay content and SOC were based on 121 and 116 samples,respectively. The final SOC and clay contents were directlypredicted from the models.

2.8. Calculations

Soil bulk density (rb) was calculated from the mass of the soildivided by the total soil volume. For the large cores this meant theuse of soils free of stones (<2 mm). We estimated soil particledensity (rd) from the soil content of clay and SOC by a recentlydeveloped pedotransfer function (Schjønning et al., 2016c). Totalporosity (F) was calculated from rb and rd for each spot:F = 1 � rb/rd. In addition, the volumetric water content (u, m3m�3)was calculated for each matric potential by multiplying the rb andthe respective gravimetric water content. Air-filled porosity (ea) ateach matric potential was calculated by subtracting u from F. Twoindices of pore characteristics were derived from the relationbetween ka and ea (Groenevelt et al.,1984), which relate to the termpore organization (PO) (Blackwell et al., 1990): PO1 = ka/ea andPO2 = ka/ea2. Detailed explanation of the indices is given in the


discussion (Section 4). Volume of pore size ranges were derivedfrom the water retention measurement assuming:

d ¼ �3000’m

ð1Þ

where d is tube-equivalent pore diameter (mm) and ’m is thematric potential in cm in a water column.

Air permeability is related to ea in a simple exponential modelby Millington and Quirk (1961) and Ball et al. (1988):

Ka ¼ MeaN ð2Þwhere M and N are constants. N could be considered to reflect porecontinuity index, which describes opening of continuous porepaths with increased drainage of water-filled pores (Ahuja et al.,1984). Soils with ka of 1 mm2 or less is considered as effectivelyimpermeable. The intercept on the abscissa, ka = 1 mm2 (log ka = 0)may be regarded as an estimate of blocked air-filled porosity (eb)(Ball et al., 1988), equivalent to:

eb ¼ 10�logM=N ð3Þ

2.9. Statistical analysis

Air permeability and the indices of pore organization (PO1 andPO2) data were log-transformed so that it conformed to a normaldistribution. Normality was tested also for all the other data sets.The factor of anisotropy (FA) was determined from the ratiobetween a given soil property in the horizontal and verticaldirections. Anisotropy was considered to prevail when the FA forthe soil property differed significantly from 1 (Berisso et al., 2013).Prior to the transformation of the measured ka values, all zerovalues (measurements too small to be detected by the flow meter)were replaced by 0.01 mm2 (close to the detection limit of theapparatus) because zero values affect the means and induce bias tostatistical analyses of the results (Berisso et al., 2012). We usedlinear regression models and analysis of covariance (ANCOVA) in R(R Core Team, 2015) to analyze the data. Multiple comparison(Tukey’s test) and t-test were used to determine the differences inthe means of treatments at the significance level P = 0.05.

3. Results

3.1. Visual evaluation of subsoil structure

The subsoil structural quality (Ssq) score of layers in each soilprofile pit was evaluated separately. In the first layer (Table 3), soilsin all treatments were well aerated, which implies that the soillayers had no distinctive presence of mottling associated withanthropic waterlogging such as compaction induced by the M3 andM8 treatments. The control soil and the M3 treatment had similarscores for soil strength, porosity, rooting and aggregates shape/sizeat all the depths studied and the overall Ssq score for the M3treatment did not differ significantly from the control treatment atany depth. Conversely, the soils that were severely compacted (M8treatment) had poor score for soil strength, rooting and aggregatesshape/size and for overall Ssq compared to the control for the 0.20–0.45 m and 0.45–0.65 m layers—the difference being almostsignificant (P = 0.08) for the 0.20-0.45 m layer (especially forrooting) and statistically significant for the 0.45–0.65 m layer. Forthe third layer (0.65–0.90 m depth) overall Ssq scores wereidentical for all treatments (Ssq = 2.9–3.0). This could be inter-preted to mean that, in general, there was no detectablecompaction effect beyond �0.65 m depth. The compaction treat-ments affected the rooting depth of the spring barley cropestablished after the compaction treatments. Average rooting



Table 3Least squares means of subsoil structural quality (Ssq) score of control and compacted soils at Flakkebjerg.

Layer Depth (m)a Treatment Soil structural properties

Mottling Strength Porosity Rooting Aggregates Ssq score

1 0.20–0.45 Control 2.2a (0.20) 2.4a (0.39) 2.9a (0.22) 2.2a (0.50) 2.7a (0.28) 2.6a (0.29)0.20–0.45 M3 3.0a (0.21) 2.8a (0.41) 2.8a (0.23) 2.7a (0.52) 2.9a (0.29) 2.9a (0.30)0.20–0.45 M8 2.4a (0.20) 3.7a (0.39) 3.5a (0.22) 4.0a (0.49) 3.6a (0.28) 3.7a (0.29)

2 0.45–0.65 Control 3.6a (0.38) 2.0a (0.35) 2.9a (0.16) 2.7a (0.32) 2.4a (0.23) 2.9a (0.18)0.45–0.65 M3 3.6a (0.40) 2.5ab (0.37) 2.9a (0.17) 2.7a (0.33) 2.7ab (0.24) 2.8a (0.19)0.45–0.65 M8 3.4a (0.39) 3.5b (0.36) 3.3a (0.17) 4.2b (0.32) 3.4b (0.23) 3.7b (0.19)

3 0.65–0.90 Control 3.8a (0.48) 2.2a (0.33) 3.0a (00) 3.1a (0.35) 2.6a (0.28) 3.0a (0.20)0.65–0.90 M3 3.9a (0.47) 2.7a (0.32) 3.0a (00) 3.0a (0.35) 2.9a (0.27) 3.0a (0.19)0.65–0.90 M8 3.5a (0.49) 2.8a (0.33) 3.0a (00) 3.9a (0.36) 2.5a (0.29) 2.9a (0.20)

Average rooting depth of block combination for treatments: Control: �0.7 m, M3: �0.65 m and M8: �0.45 mTreatments labelled with same letters in the same layer for each column are not significantly different (Tukey’s test, P < 0.05).Italic numbers in parentheses give the standard errors.

a Please consult Supplementary material (Tables A, B and C) for specific depths of layers for individual blocks.



depths (starting with the largest) were in the order: control >M3 > M8, although the differences were not significant. For theseverely compacted soils (M8), average rooting depth wasrestricted to �0.45 m. Please see Supplementary Tables A, B andC for Ssq scores of individual blocks for the different treatmentsand depths.

3.2. Soil bulk density

The traffic treatments (M3 and M8) did not significantly affectthe soil bulk density in the upper subsoil (0.3–0.4 m depth) relativeto the control soil after the first two experimental years (2011;Schjønning et al., 2016a). However, after two years (2012 and 2013)of additional compaction treatments (this study), significanttreatment effects were found at 0.3 and 0.5 m in the form ofsignificantly higher bulk densities for the M8 treatment than forthe control and M3 treatments (Table 4).

3.3. Characteristics and functioning of soil pores

The heavy compaction with the �8 Mg wheel load resulted inconsiderable reductions in total porosity, volume of pores largerthan 30 mm (air-filled porosity) and air permeability at 0.3 and0.5 m depths compared to the control and M3 soils (Fig. 1). Wefound that the M8 treatment resulted in increased volume fractionof pores smaller than 30 mm compared to the control and M3

Table 4Least squares means of soil bulk density for control and compacted soils at different d

Depth Treatment Bulk density 2011 (small soil cores)b Bulk

(m) Mg m�3 Mg

0.3 Control 1.64a (0.02) 1.67M3 1.61a (0.02) 1.70M8 1.70a (0.02) 1.77

0.5a Control – 1.65M3 – 1.64M8 – 1.74

0.7a Control – 1.72M3 – 1.73M8 – 1.74

Treatments with the same letters at the same depth for each column are not significanterrors.

a Data on soil bulk density not available for 2011 for these depths.b Data from Schjønning et al. (2016a).


treatments (significant at 0.7 m depth). Also at 0.7 m depth, the M8treated soils had ka values that were significantly lower than boththe control and M3 treatment, but ea values were significantlydifferent only from the control. In fact, there were no significantdifferences between the M3 and the control soil at any depth forany of the soil properties measured.

The heavy compaction also affected soil pore organization(Table 5). The M8 treatment significantly reduced PO1 at 0.3 and0.5 m depths compared to the control and M3 treatments. UnlikePO1, for PO2, the effect of the M8 treatment was significantlydifferent from the control and M3 treatment only at 0.5 m depth.Again, the effect of the M3 treatment on PO1 was not significantlydifferent from the control soils at any depth.

3.4. Upper subsoil anisotropy

The heavy traffic on the soil over four-year period resulted insignificant decrease in ka and ea in the vertical and horizontaldirections at �30, �100 and �300 hPa matric potentials comparedto the control soils (data from large soil cores: Fig. 2). Please notethat data for ka at matric potentials �30 and �300 hPa are notshown. Values of N for the control soils indicate significantdifferences between the vertical and horizontal directions andcompaction did not significantly affect the anisotropy of N(Table 6). The proportion of blocked air-filled pores did not differsignificantly between the control and the M8-treated soils in either

epths.

density (2014) (small soil cores) Bulk density (2014) (large soil cores)

m�3 Mg m�3

a (0.01) 1.62a (0.01)a (0.01) –

b (0.01) 1.71b (0.01)

a (0.01) –

a (0.01) –

b (0.01) –

a (0.01) –

a (0.01) –

a (0.01) –

ly different (Tukey’s test, P < 0.05). Italic numbers in parentheses give the standard



Total po rosity (m3 m-3)0.00 0.35 0.40 0.45

Dep

th (m

)

0.0

0.2

0.4

0.6

0.8

1.0

Volume of pores <30 µm (m3 m-3)0.00 0.25 0.30 0.35

Dep

th (m

)

0.0

0.2

0.4

0.6

0.8

1.0Control M3 M8

Volume of po res >30 µm (m3 m-3)0.00 0.10 0.15 0.20

Dep

th (m

)

0.0

0.2

0.4

0.6

0.8

1.0

Air pe rmeab ility (µm2)0.1 1 10 10 0 100 0

Dep

th (m

)

0.0

0.2

0.4

0.6

0.8

1.0

a b b

a b b

aa

a

aa a

a a a

a ab b

b ba

a b b

baba

a b b

a bb

a b b

(a) (b)

(c) (d)

Fig. 1. (a) Total porosity, (b) volume of pores <30 mm, (c) volume of pores >30 mm and (d) air permeability at �100 hPa matric potential for control and compacted soils (datafrom small soil cores). Treatments with the same letters at each depth are not significantly different (Tukey’s test, P < 0.05). Dotted line indicates frequently-stated lowerthreshold values for air-filled porosity and air permeability.

Table 5Geometric means of air permeability (ka) and indices of pore organization, PO1 = ka/ea and PO2 = ka/ea2 at �100 hPa matric potential for small soil cores.

Depth (m) Treatment ka (mm2) PO1 (mm2) PO2 (mm2)

0.3 Control 8.96b [0.08] 91.94b [0.06] 944a [0.06]M3 10.57b [0.08] 91.35b [0.07] 789a [0.09]M8 0.89a [0.19] 23.78a [0.12] 619a [0.14]

0.5 Control 17.84b [0.07] 138.29b [0.06] 1072b [0.06]M3 18.80b [0.06] 166.98b [0.05] 1483b [0.06]M8 4.83a [0.10] 55.33a [0.07] 633a [0.05]

0.7 Control 8.47b [0.05] 86.29ab [0.04] 880a [0.04]M3 8.64b [0.07] 96.60b [0.05] 1080a [0.05]M8 4.82a [0.06] 63.04a [0.05] 825a [0.04]

Treatments with same letters at the same depth for each column are notsignificantly different (Tukey’s test, P < 0.05).Numbers in square brackets give the standard errors for the log-transformed data.



direction although there was a significant difference in poreblockage between the horizontal and vertical direction in thecontrol soil, which was not present in the M8 treated soil. Thecompaction treatment did not significantly affect the anisotropy ofblocked air-filled porosity (Table 6).

Heavy compaction affected the soil pore geometries: the M8treatment resulted in a considerable reduction of PO1 in bothvertical and horizontal directions as compared to the controltreatment. Compaction also tended to reduce PO2, although thiswas not significant for any of the sampling directions (Table 7). Ourresults also showed that for the control soil, PO2 was anisotropicand tended to be anisotropic for PO1. The M8 treatment did notsignificantly affect the anisotropy of PO1 and PO2, even though itsFA values differed more from 1 than for the control soil. Values forka and PO1 at 0.3 m depth tended to be lower (P = 0.05) for the smallsoil cores (Table 5) than for the large soil cores (Table 7).


4. Discussion

4.1. Vertical stresses and visual evaluation of subsoil quality

The modeled vertical stresses in the soil profile (Schjønninget al., 2016a) exerted by the heavy tractor (�8 Mg wheel load)were, as expected, higher than for the light tractor (�3 Mg wheelload). It is noteworthy that the predicted maximum stresses for theM8 treatment were as much as 220, 141 and 92 kPa at 0.3, 0.5 and0.7 m depth, respectively. This is well above the critical thresholdrange (31–49 kPa) at field capacity for plastic deformation found byKeller et al. (2012). Critically high stress levels at 0.3 and 0.5 mdepth (108 and 62 kPa) were also predicted for the M3 treatment.The general lack of significant compaction effects from the M3treatment indicates that the 31–49 kPa threshold is too low for thesoil studied here. This is consistent with the studies by Schjønninget al. (2016a,b) who reported non-significant effect of the M3treatment after two consecutive years of experimentation for thesame soil.

Given the high subsoil stress levels predicted for the M8treatment it is not surprising that this treatment degraded the soilstructure more seriously than the M3 treatment. The SubVESSevaluations showed that M8 increased soil strength (penetrationresistance to knife), restricted rooting and resulted in theformation of massive soil aggregates at 0.20–0.65 m depth,although significant differences were only obtained at 0.45–0.65 m depth (Table 3). The Ssq scores varied markedly betweenthe experimental blocks, which may be attributed to variations insoil texture. The field exhibits variation of clay between and withinthe experimental blocks (Table 1 and Supplementary material,Table D). We found a strong effect of clay content on mottling at0.20–0.45 m and on rooting and soil aggregates at 0.45–0.65 mdepth (data not shown). Poorest scores for the M8 treatment were



Fig. 2. Air permeability (geometric mean) related to air-filled porosity (geometric mean), in a log-log plot for control and compacted soils (data from large soil cores). Dottedline indicates frequently-stated lower threshold values for air permeability. Solid lines indicate linear regression and N shows the slope of the regression. Details of theregression parameters are given in Table 6.

Table 6Regression parameters of air permeability (ka) as a function of air-filled porosity (ea). Values of 10�log(M)/N give blocked air-filled pores (m3m�3) or ka= 1 mm2 predicted fromthe equation: log(KA) = log(M)+ N log(eA) (Ball et al., 1988): vertical (V), horizontal (H) directions and Factor of Anisotropy (FA). Data are from large soil cores.

log(KA) = log(M)+ N log(eA)

Slope (N) 10�log(M)/N (blocked porosity, m3m�3)

Treatment Va Ha FAb P-valuec Va Ha FAb P-valuec

Control 4.01 (1.40) 5.82 (0.95) 1.45 0.004 0.06 [0.01] 0.09 [0.01] 1.56 0.004M8 4.21 (1.70) 6.40 (0.14) 1.52 0.097 0.06 [0.01] 0.07 [0.01] 1.13 0.919P-Value 0.29 0.55 0.59 0.48 0.15 0.11

a P-values in column are for effect of compaction.b P-values in column are for interaction between compaction and sampling direction (compaction effect on anisotropy).c P-values in column are for significance of the Factor of Anisotropy. (t-test, P < 0.05). Italic numbers in parentheses give the standard errors. Numbers in square brackets

give the standard errors for the log-transformed data.

Table 7Geometric means of air permeability (ka) and indices of pore organization, PO1 = ka/ea and PO2 = ka/ea2 at �100 hPa in vertical (V) and horizontal (H) directions. FA is Factor ofAnisotropy. Data from large soil cores.

Treatment ka PO1 PO2

mm2 mm2 mm2

Va Ha FAb P-valuec Va Ha FAb P-valuec Va Ha FAb P-valuec

Control 39 [0.11] 24 [0.08] 0.6 0.17 285 [0.08] 154 [0.08] 0.54 0.06 2094 [0.08] 1004 [0.09] 0.48 0.01M8 6 [0.26] 3 [0.36] 0.4 0.14 79 [0.17] 32 [0.28] 0.41 0.17 983 [0.14] 414 [0.23] 0.42 0.23P-value 0.01 0.01 0.66 0.01 0.03 0.72 0.06 0.14 0.85

Numbers in square brackets give the standard errors for the log-transformed data.a P-values in column are for effect of compaction.b P-values in column are for interaction between compaction and sampling direction (compaction effect on anisotropy).c P-values in column are for significance of the Factor of Anisotropy.(t-test, P < 0.05).



given in blocks 3 and 4 (please consult Supplementary materials A,B and C for detailed scores of individual experimental blocks). Forthe M3 treatment, critically high stress levels down to 0.5 m depthdid not result in changes in mottling, strength, porosity, rootingand aggregates. At 0.3 m depth this could perhaps be explained by ahigh degree of compacted soil before initiating the experiment: i.e.high stresses are apparently needed to compact the soil evenfurther at 0.3 m depth.

The M8 treatment restricted root growth to 0.45 m. Deforma-tion of soil structure and mechanical impedance to root and shootgrowth due to compaction may adversely affect crop yields(Håkansson et al., 1987). Schjønning et al. (2016a) found that boththe M3 and M8 treatments resulted in significant yield reduction ofspring barley compared with the control. The authors observedyield penalties of 0.4 Mg ha�1 and 1.3 Mg ha�1 for the M3 and M8treatments, respectively (full investigation is given by Schjønning


et al. (2016a)).The effects of subsoil compaction on crop yields varydepending on factors such as crop variety, sensitivity and rootsystem (Arvidsson and Hakansson, 2014).

4.2. Total porosity, pore system and functioning of pores

The M8 treatment resulted in bulk density levels as high as1.77 Mg m�3 for the small soil cores (at 0.3 m depth) and1.71 Mg m�3 for the large cores at 0.3–0.4 m depth (Table 4). Thedensification in the M8 treatment resulted in reduced macro-porosity (>30 mm pores) below the critical level of 0.10 m3m�3 atall depths (Fig. 1c). Most soil functions take place in air-filled porespaces and an ea volume below 0.10 m3m�3 is considered thecritical threshold for the ability of soil to support plant growth(Grable and Siemer, 1968; Lipiec and Hatano, 2003). Schjønninget al. (2003) reported that an ea of 10% is also a critical threshold for





the aerobic turnover of organic matter in soil. The strong negativeeffect of heavy compaction on macroporosity is consistent withmany other studies (e.g., Dexter and Richard, 2009). The M8treatment significantly reduced pores drained at field capacity(>30 mm) at 0.7 m depth, which – as stated– is due to compactionreducing the macroporosity. However, the trend is not as clear asfor the destruction of the large pores. Schjønning et al. (2016b) alsoreported that this trend was not significant after two years ofcompaction treatments.

The M8 treatment considerably reduced ka at all depthscompared to the control and M3 treatments. An air permeabilityof less than 1 mm2 has been suggested as a critical limit and infersimpermeable soils, which may restrict the water and air transportnecessary for many biological processes in the soil (Ball et al.,1988). Critically low ka was measured for the M8 treatment in thesmall cores at 0.3 m depth (Fig. 1d). Air permeability was alsostrongly reduced in the large soil cores, but not to a level below1 mm2 (Table 7). Iversen et al. (2001b) also found significantlylower estimates of ka for the 100 cm3 compared with the 6 dm3 soilcores, which are identical to the large soil cores in this study. Thedifferent trends in ka for the small and large soil cores could be aneffect of scale: i.e. (i) the probability of continuous pathways getsgreater with the large cores than the small soil cores because thereare higher chances of the presence of macropores such as bioporesand (ii) tilted pores are less constrained by the sample cylinderwalls in the large cores as compared to the small soil cores.

The pore organization indices, PO1 and PO2, can be used todescribe the effects of soil management on pore size distribution,tortuosity and continuity of air-filled porosity (Groenevelt et al.,1984). According to Groenevelt et al. (1984), soils with similar PO1

values have an identical pore-size distribution and pore continuitysince ka is normalized only with respect to the volume of air-conducting pores. In contrast, soils with similar PO2 values onlyhave identical pore size distribution. This means the differencesbetween PO1 and PO2mainly relate to pore continuity independentof the pore-size distribution (Ball et al., 1988). Our results showedthat the values of PO1 and PO2 for the large soil cores were higherthan the small soil cores for both the control and M8 treatments.This could be interpreted as scale effect as discussed already. Wefound a significant effect of the M8 treatment on PO1 relative to thecontrol treatment for both small and large soil cores (Tables 5 and7). The effect of the heavy compaction on PO2 was significant onlyat 0.5 m depth (data from small soil cores, Table 5). The drasticreduction of PO2 at 0.5 m depth for the M8 treatment is an indicatorof considerable changes to the pore size distribution. Moreover,lower values of PO1 for the M8 treatment at all depths indicate thatthe soils have experienced measurable changes in pore tortuosityand continuity due to the heavy compaction treatment. Again, theeffect of the M3 treatment on PO1 and PO2 could not be significantlydistinguished from the control treatment at any depth (data fromsmall soil cores, Table 5). Schjønning et al. (2016b) found nosignificant effect of M8 treatment on PO1 and PO2 after the secondyear of experimental treatments.

In the light of the previous findings, our results indicate thattwo additional years of M8 treatments markedly increased thecompaction impact, which consequently changed the subsoil porecharacteristics as we hypothesized. Our interpretations are that (1)the changes induced after two years of traffic with �8 Mg wheelload may be too small that it was not detectable, but remarkableafter the two additional years of traffic, and (2) the traffic eventsduring the first two years may have made the soil vulnerable tonext compaction events as reported by Schjønning et al. (2016a)resulting in drastic damages to the subsoil pore characteristics.Berisso et al. (2012) reported that the effects of compaction on thesoil pore size distribution and tortuosity can persist for many years,which can have adverse effects on the ability of soil to support


ecological processes. In contrast to the M8 treatment, our studyshowed, however, that the M3 treatment had only minor effects onsoil total porosity, the pore system and pore functioning and couldnot be significantly distinguished from the control soil at anydepth.

4.3. Anisotropy of upper subsoil aeration and pore system

The values of slopes (N) for the control soils in our studydiffered significantly between the vertical and horizontal direc-tions, which is an indication of anisotropy. Higher values of N in thehorizontal direction compared to the vertical direction isinterpreted as the opening of continuous pore paths with increaseddrainage of water-filled pores. Blocked porosity (eb) was aniso-tropic for the control soil (data from large soil cores). Blocked air-filled pores are isolated, i.e. disconnected from the gas transportpathway (Schjønning et al., 2013). In the compacted soil there wasno significant difference between blocked air-filled pores in thevertical and horizontal directions. Neither did heavy compactionsignificantly affect the anisotropy of blocked porosity (Table 6). Ourfindings are consistent with those of Berisso et al. (2013), who alsofound significant anisotropy of N and blocked porosity for thecontrol soil at 0.3 m depth, with consistently higher values in thehorizontal direction than in the vertical direction.

The factor of anisotropy (FA) had values below 1 (i.e. 0.41–0.54)for the pore organization indices (PO1 and PO2), althoughsignificant anisotropy was found only for PO2 for the control soil.Our results revealed that the M8 treatment affected the verticallyand horizontally-oriented pores differently at the measured soilwater potentials. Unlike the control soil, the FA values of slope (N),PO1 and PO2 for the M8 treatment were not significantly differentfrom 1. This implies that the compaction did not significantlyincrease the anisotropy of the upper subsoil pore characteristics:i.e. the results did not support hypothesis three of our study. Therewas no anisotropic effect on ka for the control and the M8treatments (Table 7). This is in contrast to Berisso et al. (2013) whofound significant anisotropic behavior of ka for the non-compactedsoil, but not for the compacted soil on sandy clay loam soil inSweden at 0.3 m depth.

4.4. Correlation between visual evaluation and laboratory analysis ofsubsoil quality

The overall Ssq scores displayed a strong linear correlation withF, ea and ka, which indicates a good correspondence between thesimple SubVESS method and the quantitative results fromlaboratory measurements (data from small soil cores). Forindividual treatments, the relationship between the overall Ssqscores and laboratory-measured data was quite weak for thecontrol and M3 treatment (Table 8), which had mostly good andmoderate Ssq scores (1–3). The M8 treatment, which had mostlymoderate and poor Ssq scores (3–5), however, showed a quite astrong inverse linear relationship between the overall field scoresand the laboratory-measured data (i.e. the linear model explainedbetween 37 and 52% of the variance of the soil properties studied)(Fig. 3). We also related the Ssq score for porosity and thelaboratory-measured data for F and ea (data from small soil cores)(Table 9). Again, a good correlation was found between Ssq score ofporosity for the M8 treatment and the laboratory-measured F andea. The coefficient of determination of the linear regression modelfitted to the data (Ssq score of porosity vs F and ea) for the M8treatment were 0.50 and 0.44, respectively (Fig. 4).

The linear relation between the Ssq scores and laboratory datain our study demonstrates the large potential of using the SubVESSmethod to evaluate the effects of different management systemson soil structural quality. These results support our hypothesis that



1 2 3 4 5

Tota

l por

osity

(m3 m

-3)

0.0

0.1

0.2

0.3

0.4

Con trolM3M8

Overall Ssq score1 2 3 4 5

Air-

fille

d po

rosi

ty, (

m3

m-3

)

0.0

0.1

0.2

0.3

0.4

Overall Ssq score1 2 3 4 5

Air p

erm

eabi

lity

(µm

2 )

0.01

0.1

1

10

100

Overall Ssq score

Layer 1Layer 2Layer 3

y= -0.014x+0.3965R2= 0.432

y= -0.036 x+0.2043R2= 0.369

y= -0.6746x+2.70 5R2= 0.523

Fig. 3. Overall subsoil structural quality score (Ssq 1–5) related to total porosity, air-filled porosity and air permeability at �100 hPa matric potential for control andcompacted soils (data from small soil cores). Dotted line indicates frequently-stated lower threshold values for air permeability and air-filled porosity. Solid lines are linearregression lines between overall Ssq scores and total porosity, air-filled porosity and air permeability for the M8 treatment.

Table 8Overall Ssq scores from the numeric visual evaluation of subsoil structure (SubVESS) related to laboratory-measured total porosity (F), air-filled porosity (ea) and airpermeability (ka) at �100 hPa matric potential for control and compacted soils (data from small soil cores).

Treatment Overall Ssq score vs F (m3m�3) Overall Ssq score vs ea(m3m-3) Overall Ssq score vs ka(mm2)

r P-value-F-stats r P-value-F-stats r P-value-F-stats

Combined data � 0.49 0.003 � 0.47 0.004 � 0.65 <0.001Control � 0.15 0.64 � 0.19 0.55 0.10 0.76M3 � 0.08 0.82 0.05 0.88 � 0.05 0.88M8 � 0.66 0.02 � 0.61 0.04 � 0.72 0.01

Table 9Ssq scores for porosity from the numeric visual evaluation of subsoil structure (SubVESS) related to laboratory-measured total porosity (F) and air-filled porosity (ea) at�100 hPa matric potential for control and compacted soils (data from small soil cores).

Treatment Ssq score of porosity vs F (m3m�3) Ssq score of porosity vs ea (m3m�3)

r P-value-F-stats r P-value-F-stats

Combined data � 0.43 0.004 � 0.43 0.01Control � 0.04 0.91 � 0.02 0.96M3 � 0.08 0.82 � 0.05 0.88M8 � 0.71 0.01 � 0.66 0.02

Ssq s core of porosity1 2 3 4 5

Tota

l por

osity

(m3

m-3

)

0.0

0.1

0.2

0.3

0.4

Con trolM3M8

Ssq score of poro sity1 2 3 4 5

Air-

fille

d po

rosi

ty (m

3m

-3)

0.0

0.1

0.2

0.3

0.4Layer 1Layer 2Layer 3

y= -0.0265x+0.434 7R2=0.503

y= -0.069x+0.3053R2=0.439

Fig. 4. Correlation between Ssq scores of porosity and laboratory-measured total porosity (F) and air-filled porosity (ea) at �100 hPa matric potential for control andcompacted soils (data from small soil cores). Dotted line indicates frequently-stated lower threshold values for ea. Solid lines are linear regression lines between Ssq scores ofporosity and F and ea for the M8 treatment.



there is a correspondence between subsoil structural propertiesevaluated by the SubVESS method and in the laboratory.

It is worth mentioning that the relatively strong inverse linearrelationship between both the overall Ssq score and the Ssq scoreof porosity vs. laboratory-measured F, ea and ka for the M8treatment as compared to the control and M3 treatments impliesthat the SubVESS method can be used as a simple, quick and cost-


effective method for evaluating severe levels of structurallydegraded soils. Conversely, the method may not be very suitablefor evaluating less deformed soils, mainly because less degradedphysical and structural soil properties may not be very discerniblefrom the evaluation. Our results confirmed the findings of Ball et al.(2015a), who reported that the SubVESS method is suitable forevaluating subsoil structural degradation.





5. Conclusions

Effects of compaction were measured visually by the numericvisual evaluation of subsoil structure (SubVESS) method andquantitatively in the laboratory, with good agreement between thetwo methods. Compaction with the �8 Mg wheel load (M8) forfour years was shown to drastically reduce total porosity (F), air-filled porosity (ea), air permeability (ka), pore size distribution andcontinuity, especially at 0.3 and 0.5 m depths.

Deterioration of these physical and structural soil propertiesmay inhibit soil functioning that support crucial ecosystemservices. Detailed measurements of the anisotropy of soil porecharacteristics at 0.3–0.4 m depth showed that the control soil wasstrongly anisotropic for N, blocked air-filled porosity and PO2 andless so for PO1. Although the M8 treatment affected the verticallyand horizontally-oriented pores differently, it did not significantlyaffect the anisotropy of ka, PO1 and PO2 at �100 hPa matricpotential. In this study we only related the subsoil structuralquality (Ssq) scores from the visual evaluation to laboratory-measured F, ea and ka on small soil cores. Further studies areneeded on large soil cores to understand the effect of scale onaccuracy of assessment.

Acknowledgements

We gratefully appreciate the technical assistance of Stig T.Rasmussen, Michael Koppelgaard and Jørgen M. Nielsen, who didthe sampling and Bodil B. Christensen, who took care of all thelaboratory measurements. The field experiment was part of aseries of trials ran by SEGES, a national Danish agriculturalconsultancy agency. We are grateful for the cooperation with JanneÅ. Nielsen, who was in charge of the trials. The assistance of Jens J.Høy and Henning S. Lyngvig, who were in charge of machineryselection and management, is much appreciated. The specific fieldexperiment was managed by Uffe Pilegaard. The work was fundedpartly by ‘Promilleafgiftsfonden’ and ‘Landdistriktsmidlerne’ andpartly by the European Union Seventh Framework Program (FP7/2007-2013) via the RECARE project under grant agreement no.603498.

Appendix A. Supplementary data

Supplementary data associated with this article can be found, inthe online version, at http://dx.doi.org/10.1016/j.still.2016.08.015.

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