Soil & Tillage Research 211 (2021) 105019

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Soil & Tillage Research

journal homepage: www.elsevier.com/locate/still

A meta-analysis of the impact of traffic-induced compaction on soil physical

properties and grain yield
Peter Bilson Obour a, b, *, Carmen M. Ugarte b
a
Department of Geography and Resource Development, University of Ghana, P. O. Box LG 59, Legon, Accra, Ghana
b
Department of Natural Resources and Environmental Sciences, University of Illinois at Urbana-Champaign, 1102 S. Goodwin Avenue, MC-047, Urbana, IL, 61801,
USA

A R T I C L E I N F O A B S T R A C T

Keywords: Soil compaction caused by wheel traffic is a major driver of soil degradation in modern agriculture and thus, a
Air permeability threat to agricultural sustainability. To improve the predictive capacity of compaction models and to support
Bulk density decision-making that implements site-specific practices for ameliorating soil compaction effects in modern
Degree of compactness
agriculture, we need quantitative syntheses of the effect of soil compaction on soil physical properties and crop
Volume of water filled pores at field capacity
Penetration resistance
types. In this work, we used a meta-analytical approach to summarize results from 51 published articles on the
Saturated hydraulic conductivity impacts of soil compaction attributed to machinery axle load, wheel passes, compaction events and tire inflation
pressure on soil bulk density (ρb), degree of compactness (DC), penetration resistance (PR), volume of water
filled pores at field capacity (θFc), air permeability (ka) at field capacity, saturated hydraulic conductivity (ksat),
and grain yield of corn (Zea mays L.), wheat (Triticum aestivum L.), barley (Hordeum vulgare L.) and soybean
(Glycine max L.). Results from this meta-analysis (MA) showed that compaction increased soil mechanical
strength shown by increased soil ρb, DC and PR. However, an increase in soil strength was more pronounced in
the medium- and coarse-textured soils, and mainly in the topsoil (0–30 cm depth). Penetration resistance for the
non-compacted soil (control) treatment was 1.21 MPa for the coarse-textured, 1.11 MPa for the medium-textured
and 0.93 MPa for the fine-textured soils. Soil compaction on average, increased PR by 99, 94 and by 41 percent in
the medium-, coarse- and fine-textured soils. Compaction decreased hydraulic conductivity characterized by ka
and ksat from the topsoil down to the subsoil (>40 cm depth), and grain yield of corn, wheat, barley, and soy­
bean. Overall, compaction decreased grain yield on average by 6–34 percent. Findings of the MA suggest that soil
hydraulic properties may be more sensitive indicators to reflect the impact of soil compaction on soil structure
and pore system functions in the soil profile. Future efforts should place a greater emphasis on the publication of
complete metadata that allows replication and accurate comparison of results across studies and on providing
open access to original datasets that can be used to improve our understanding of the effect of traffic-induced
compaction on soil functioning, including crop production.

1. Introduction soil profile, namely topsoil or surface compaction, upper subsoil

compaction, and subsoil or deep soil compaction, i.e., compaction
The use of agricultural machinery to conduct cultural practices has beyond the normal tilled zone (Abu-Hamdeh, 2003). The topsoil is the
increased in modern agriculture. Field traffic, particularly in wet con­ uppermost soil layer, generally comprising the top ~30 cm in depth. For
dition can cause soil compaction, defined as the densification and agricultural soils, the upper subsoil refers to the layer from approxi­
reduction in soil porosity, which alters soil structure, increases soil mately 30–40 cm depth. In no-tilled soils, the depth of the upper subsoil
strength, and reduces soil hydraulic conductivity (Soane and van and deep soil compaction is defined as the layers less affected by natural
Ouwerkerk, 1994). Susceptibility of agricultural soils to topsoil and compaction alleviating processes such as freezing and thawing and the
subsoil compaction has increased over the past decades due to a steady activities of soil biota (Schjønning et al., 2015).
increase in wheel load of agricultural machinery (Keller et al., 2019). In As compaction deforms soil structure, reduces porosity and alters
general, three regions of compaction could be identified throughout the pore morphology, it has cascading negative effects on water storage and

* Corresponding author. Email address: pbobour@ug.edu.gh or obourpb@gmail (P. B. Obour)

https://doi.org/10.1016/j.still.2021.105019
Received 26 August 2020; Received in revised form 10 March 2021; Accepted 13 March 2021
Available online 26 April 2021
0167-1987/© 2021 Elsevier B.V. All rights reserved.
P.B. Obour and C.M. Ugarte Soil & Tillage Research 211 (2021) 105019

transport, root growth and nutrient availability (Keller et al., 2017; changes in soil physical properties caused by compaction, and (iii)
Schjønning et al., 2017). These changes in turn negatively affect food provide a roadmap for future research. Hereafter, except where speci­
production, habitat for soil organisms, and several other ecosystem fied, the term traffic compaction is used to refer to compaction caused by
functions (e.g., regulation of climate and water provision and purifica­ machinery axle load, wheel passes, compaction events and tire inflation
tion) (Batey, 2009; Berisso et al., 2013). Compaction increases soil pressure.
mechanical strength, which can be quantified in terms of soil bulk
density (ρb) and penetration resistance (PR). Higher soil ρb or PR can 2. Materials and methods
delay plant emergence, impede root growth and proliferation, and limit
water and nutrient uptake (Bengough et al., 2011). In general, plant 2.1. Scope and literature review
growth can be limited when soil ρb exceeds 1.47 on clay, 1.75 on silt,
and 1.80 Mg m–3 on loam and sand (Arshad et al., 1996). As with soil ρb, Literature search for this work was done using the Web of Science
plant root growth can be slowed down or completely impeded at PR (Thomas Reuters, Philadelphia, Pennsylvania) and Google Scholar
values of 2 and 3 MPa, respectively (Boone et al., 1986; Willatt, 1986; search engines. We looked for peer-reviewed articles reporting results on
Dexter, 2004; Bengough et al., 2011). Changes in the soil pore system soil mechanical and/or physical properties, and crop yield published in
due to compaction can adversely affect key soil hydraulic properties and the period corresponding to January 1980 and March 2020. The
aeration such as saturated hydraulic conductivity (ksat) and air move­ following keywords and phrases were used: "Soil compaction or subsoil
ment in soil (Lipiec and Hatano, 2003). compaction", "compaction" and "mechanical/soil physical properties",
Either an increase in soil mechanical attributes or a decrease in soil "compaction" and "bulk density", "compaction" and "penetrometer or
hydraulic properties or a combination of these can affect soil physical penetration resistance" or "cone index", "compaction" and "soil pore
conditions that affect plant growth. According to Bengough et al. functions", "compaction" and "soil water retention or soil moisture
(2011), plants require root systems that deliver adequate water and characteristic or release curve", "compaction" and "hydraulic conduc­
nutrients for shoot growth, and to anchor them in the soil. Factors such tivity", "compaction" and "air permeability", "compaction" and "yields",
as root impedance, poor aeration, infiltration and water uptake, or a and "compaction" and "grain/cereal crop yields". The articles obtained at
combination of these factors in combination with weather conditions, the end of the search were screened based on whether full texts were
play a significant role in determining crop yield (Lipiec and Hatano, available, and whether they included relevant information on one or
2003). Some studies have shown that reduced levels of oxygen content more mechanical/soil physical properties of interest. For crop yield,
below 10% can seriously impair root and plant growth (Gill and Miller, preference was given to articles that reported compaction effects on
1956; Gliński and Stępniewski, 1985). In a greenhouse experiment, corn, soybean, wheat, and/or barley yield. To make sure we maximized
Bertrand and Kohnke (1957) reported that the amount of aboveground our search, we also reviewed the list of cited references in individual
dry biomass positively related to oxygen diffusion levels. Increase in articles and in key peer-reviewed publications of lead authors who
compaction of soils is reported to be one of the major drivers of yield conduct research on soil compaction.
stagnation of cereals such as corn (Zea mays L.), wheat (Triticum aestivum Only articles that reported compaction caused by machinery traffic
L.), barley (Hordeum vulgare L.) and soybean (Glycine max L.) during the were considered. In a MA, a control treatment is compared with alter­
last three decades in many European countries (Keller et al., 2019). native treatments. Accordingly, only studies that compared at least a
Research on the impacts of soil compaction on soil physical prop­ treatment (with experimental traffic or compaction) against a control
erties and crop yield has been widely conducted. Although several (which for the purposes of this manuscript refers to no experimental
studies have reported detrimental effect of compaction on crop yield (e. traffic) were retained. Out of 199 articles reviewed, 51 were selected
g., Håkansson and Reeder, 1994; Schjønning et al., 2016), others have based on the criteria stated for this MA, namely, (i) full text was avail­
reported an increase in yield following a slight level of compaction (e.g., able, (ii) included relevant information on one or more soil physical
Lindemann et al., 1982). Moreover, in most cases, studies investigated properties of interest, (iii) data on soil physical properties and grain
soil compaction caused by a single attribute of wheel traffic (i.e., either yield were reported in numerical format or legible graphical format, (iv)
axle load or number of machinery passes or number of compaction soil compaction was conducted by machinery traffic and (v) a control
events or tire inflation pressure), one soil type, crop type or in the same (non-compacted) treatment was compared with alternative treatments.
climatic region which limit the drawing of robust conclusions from such For studies where data were reported in a graphical format, data were
studies. Previous papers have provided qualitative reviews reporting the extracted using the GetData graph digitizer (GetData Graph Digitizer,
effect of soil compaction on soil physical properties and crop growth (e. 2013). For each study, the control group was compared against each
g., Wolkowski, 1990; Unger and Kaspar, 1994; Lipiec and Hatano, 2003; compaction treated group. Therefore, we ended with more than one
Hamza and Anderson, 2005; Nyeki et al., 2017). However, changes in paired-comparison within each study. The 51 articles generated 499
soil physical properties and crop yield were investigated without paired-comparisons broken down into three different depths and three
considering variations in soil attributes such as texture and depth. texture classes.
Further, to the best of our knowledge, no study has provided a quanti­
tative review of effect of compaction on soil physical properties and crop 2.2. Building the database
yield. By using this approach, one can use a wider range of published
studies to improve the predictive capacity of compaction effects on crop The data extracted were converted to the same unit to allow for
production, and to support decision making about the implementation comparison among different studies. The wheel load/axle load of ma­
of site-specific practices aimed to ameliorate soil compaction effects in chinery is not the only machinery-related driver of soil compaction, but
modern agriculture. also the number of wheel passes, tire inflation pressure and/or number
In this study, we performed a meta-analysis (MA) with data previ­ of compaction events. For the majority of studies, information on axle
ously published in peer-reviewed articles quantifying the effect of load was provided, therefore it was used instead of wheel load. In some
traffic-induced soil compaction on soil ρb, PR, saturated hydraulic cases, incomplete information was provided on machinery type and
conductivity (ksat), air permeability (ka), the volume of soil pores characteristics, namely axle load, tire type and inflation pressure so
retaining water at field capacity (θFc), and grain yield of corn, wheat, estimated values from online sources by searching for the machinery
barley and soybean across forms of traffic compaction, and soil texture specifications, and sourcing information on recommended load and tire
classes. A detailed MA is important to (i) provide a clear perspective and inflation pressure provided by major agricultural machine or tire man­
a better understanding of compaction impacts on soil physical functions ufacturers. The information on machinery and compaction treatments
and crop yield, (ii) improve our ability to model crop yield response to were then grouped as summarized in Table 1. For most studies,

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P.B. Obour and C.M. Ugarte Soil & Tillage Research 211 (2021) 105019

Table 1
Matrix indicating soil variables, control and treatment defined for meta-analysis, groups from the combined studies.
Soil properties Control to treatment comparison defined for meta-analysis

Variables Group No. of paired comparisons Variable Group Description

Coarse-textured 42 Control No experimental traffic

Medium-
Texture 305 Lightly loaded 1 – 6 Mg
textured Axle load
Fine-textured 152 Moderately loaded 7 – 14 Mg
0 – 30 304 Severely loaded >14 Mg
30 – 40 85 Control No experimental traffic
> 40 110 Few number of passes 1– 3 passes
Machinery passes per experiment
Moderate number of passes 4 – 8 passes
Multiple number of passes >8 passes
Control No experimental traffic
Sampling depth (cm) Compaction events during experimental One event 1 event
period Moderate number of events 2 – 3 events
Multiple number of events >3 events
Control No experimental traffic
Low tire pressure 75 – 140 kPa
Tire inflation pressure
Medium tire pressure 140 – 300 kPa
High tire pressure >300 kPa

compaction treatments were applied at soil water content around field either the range of depth or the definition assigned will be used
capacity (FC), considered here as soil water content retained at –10 to interchangeably.
− 33 kPa (Razzaghi et al., 2020). Thus, the volume of pores retaining
water at FC (θFc, m3 m–3) corresponds to a range of pore sizes ranging
from 9 and 30 μm. 2.3. Statistical analysis
The following additional calculations were performed to harmonize
the data for further analysis: Statistical analyses were performed on sets of paired-comparisons of
treatments contrasted against their assigned control. To evaluate the
(a) In cases where only data on total porosity were provided, soil ρb effect of compaction (in terms of axle load, number of machinery passes,
was calculated assuming a particle density value of 2.65 Mg m–3. number of compaction events, and tire inflation pressure) on soil ρb, DC,
(b) In studies where only soil organic matter (SOM) was reported, PR, θFc, ka at FC, ksat and grain yield of corn, wheat, barley and soybean,
SOM was converted to soil organic carbon (SOC) assuming that the response ratio (RR) was determined as:
58% of SOM was SOC: Xtrt
RR = (5)
SOM = 1.72×SOC (1) Xctrl

where, Xtrt is the mean of a compaction treated group and Xctrl is the
(c) In studies where SOM was not reported, but did report clay
mean of the control group reported in the studies included in the MA.
content, SOM was predicted using the pedotransfer function
For each variable, a RR > 1 indicated that compaction resulted in an
developed by Dexter (2004):
increase, while RR < 1 showed a decrease in the metric of interest with
SOM = 1.58 + 0.048 clay, (2) respect to the control. The RRs were transformed using the natural
logarithm (ln) and were used in computing the overall effect size with
95% confidence interval for each group. The mean effect size was
considered significantly different from a log ratio of one (i.e., zero) if its
(d) The degree of compactness (DC, %) was calculated according to confidence interval did not overlap zero (Koricheva et al., 2013).
Håkansson (1990): In a MA, typically, studies are weighted against their variance. Here,
ρb in the absence of this statistics in the majority of published articles, we
DC = × 100, (3) assumed a value of 1 as the log-ratio standard deviation across the
ρbref
paired experiments. We then used the log-ratio of the outcome effect size
where ρbref is the reference dry bulk density of the same soil. ρbref, which to the number of replicates as proxies of the standard error for each
expresses the densest state of the soil (Håkansson, 1990) and was paired-comparison (Neyeloff et al., 2012).
calculated from clay and SOM (Naderi-Boldaji and Keller, 2016): To test the null hypothesis that all studies have common effect size,
the Q statistics or test was performed, calculated as the weighted sum of
ρbref = 1.9 − 0.000529 clay − 0.00342 SOM, (4) squared differences between individual study effects and the pool effect
To ensure optimal group comparisons, the data were re-grouped by across all studies (Borenstein et al., 2009; Neyeloff et al., 2012):
texture and depth. Soil texture was grouped into three group categories ∑( ∑
) [ (w ∗ es) ]2
according to the USDA particle size distribution. These comprised Qtest = w ∗ es2 − ∑ , (6)
w
coarse-textured (Loamy sand and Sand), medium-textured (Loam, Sandy
loam, Silt loam, Sandy clay, and Sandy clay loam) and fine-textured where, w is the individual study weight and es is effect size, which is the
(Clay, Clay loam, Silty clay, Silt, and Silty clay loam) groups. For natural logarithm of the response ratio. Statistical significance of the
studies that measured soil water retention (SWR) and ka, only data Qtest was done by comparing the results of the Qtest against a critical
measured at FC were included in the MA. Because studies reported re­ value, computed as the product of the inverse of the Chi-square test at an
sults on soil physical properties from different sampling depths, the alpha value of 0.05 and the degrees of freedom (DF) calculated based on
dataset was categorized into three sampling depths: 0–30, 30–40 and > the total number of possible comparisons for each group. A higher Qtest
40 cm depth. With this we define studies reporting data from the topsoil value than the critical value indicates a significant p-value. In other
or plow layer, upper subsoil, and the subsoil, respectively. Hereafter, words, the studies do not share a common effect size (Borenstein et al.,

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P.B. Obour and C.M. Ugarte Soil & Tillage Research 211 (2021) 105019

2009; Neyeloff et al., 2012). Table 3

Borenstein et al. (2009) suggested that I2 statistics, proposed by Heterogeneity test (Qtest) and I2 for evaluating the effect of compaction on
Higgins et al. (2003), is useful to quantitatively compute inconsistency selected soil physical properties at three depths, and grain yield for studies
or heterogeneity across the findings of multiple studies. Accordingly, the conducted on medium-textured soils. Degree of freedom (DF) were calculated
I2 statistics was performed to quantify the heterogeneity across the based on the total number of possible paired-comparisons for each depth and
crop type.
findings of studies included in this work. The I2 value was computed as:
Parameters Sampling DF Qtest I2 p-
(Q − DF) depth (cm) index value
I = test
2
(7)
Qtest
0 – 30 92 1324.7 93.1 0.0001
According to Higgins et al. (2003) and Huedo-Medina et al. (2006), I2 Bulk density 30 – 40 23 338.5 93.2 0.0001
> 40 41 534.2 92.3 0.0001
values of 25, 50, and 75% indicate a low, medium and high heteroge­ 0 – 30 75 1056.4 92.9 0.0001
neity, respectively. Degree of compactness 30 – 40 22 322.0 93.2 0.0001
> 40 40 528.3 92.4 0.0001
3. Results 0 – 30 55 763.8 92.8 0.0001
Penetration resistance 30 – 40 14 219.1 93.6 0.0001
> 40 24 396.5 93.9 0.0001
3.1. Overview of data characteristics and stratification 0 – 30 5 64.6 92.3 0.0001
Volume of water-filled
30 – 40 nd nd nd nd
pores at field capacity
The grouping of data based on texture provided 42, 305 and 152 > 40 9 159.7 94.4 0.0001
paired-comparisons for the coarse-, medium- and fine-textured soils, 0 – 30 19 286.0 93.4 0.0001
Air permeability at field
30 – 40 6 46.1 87.0 0.0001
respectively. For data groupings based on sampling depths, there were capacity
> 40 18 292.8 93.9 0.0001
304 paired-comparisons for the 0–30 cm depth, 85 for the 30–40 cm 0 – 30 11 208.3 94.7 0.0001
Saturated hydraulic
depth, and 110 paired-comparison for the >40 cm depth (Table 1 and 30 – 40 4 137.3 97.1 0.0001
conductivity
supplementary Tables S1–S3). > 40 12 227.9 94.7 0.0001
corn 25 410.4 93.9 0.0001
Geographically, the 51 articles included in the MA covered studies
soybean 13 193.0 93.3 0.0001
conducted in 20 different countries, and located in five different conti­ Grain yield
wheat 13 198.7 93.5 0.0001
nents (Europe, North America, South America, Africa, Asia, and barley 62 936.5 93.4 0.0001
Australia). The experimental duration of the studies ranged from 1 to 29
nd: indicates no data available for this category based on our search criteria.
years. The variability of the response ratios quantified using the Qtest and
I2 index within depths and crop type are presented in Tables 2–4 for
coarse-, medium- and fine-textured soils. The I2 index ranged from Table 4
72.7–94.2, 87.0–97.1, and 77.8–96.1 for the dataset partitioned into Heterogeneity test (Qtest) and I2 for evaluating the effect of compaction on
coarse-, medium- and fine-textured soils, respectively. Overall, there selected soil physical properties at three depths, and grain yield for studies
was a significant heterogeneity across the studies in the data in each conducted on fine-textured soils. Degree of freedom (DF) were calculated based
sampling depth and crop type (p < 0.01). on the total number of possible paired-comparisons for each depth and crop
type.
Parameters Sampling DF Qtest I2 p-
depth (cm) index value

0 – 30 64 845.2 92.4 0.0001

Bulk density 30 – 40 11 169.0 93.5 0.0001
Table 2 > 40 2 51.7 96.1 0.0001
Heterogeneity test (Qtest) and I2 for evaluating the effect of compaction on 0 – 30 38 492.9 92.3 0.0001
selected soil physical properties at three depths, and grain yield for studies Degree of compactness 30 – 40 5 nd nd nd
conducted on coarse-textured soils. Degree of freedom (DF) were calculated > 40 2 nd nd nd
based on the total number of possible paired-comparisons for each depth and 0 – 30 44 610.5 92.8 0.0001
crop type. Penetration resistance 30 – 40 18 381.9 95.3 0.0001
> 40 3 27.1 88.9 0.0001
2
Parameters Sampling DF Qtest I p- 0 – 30 15 219.3 93.2 0.0001
depth (cm) index value Volume of water-filled
30 – 40 nd nd nd nd
pores at field capacity
> 40 nd nd nd nd
0 – 30 25 209.4 88.1 0.0001
0 – 30 nd nd nd nd
Bulk density 30 – 40 9 154.0 94.2 0.0001 Air permeability at field
30 – 40 nd nd nd nd
> 40 3 nd nd nd capacity
> 40 nd nd nd nd
0 – 30 2 88.9 88.7 0.0001
0 – 30 4 34.3 88.4 0.0001
Degree of compactness 30 – 40 6 108.0 94.4 0.0001 Saturated hydraulic
30 – 40 2 9.0 77.8 0.0110
> 40 3 nd nd nd conductivity
> 40 2 27.9 92.8 0.0001
0 – 30 11 168.0 93.5 0.0001
corn 17 272.7 93.8 0.0001
Penetration resistance 30 – 40 5 60.0 91.7 0.0001
soybean 9 139.3 93.5 0.0001
> 40 nd nd nd nd Grain yield
wheat 24 588.0 95.9 0.0001
0 – 30 nd nd nd nd
Volume of water-filled barley 2 45.2 95.6 0.0001
30 – 40 nd nd nd nd
pores at field capacity
> 40 nd nd nd nd nd: indicates no data available for this category based on our search criteria.
0 – 30 nd nd nd nd
Air permeability at field
30 – 40 nd nd nd nd
capacity
> 40 nd nd nd nd 3.2. Effects of soil compaction on soil physical properties, and grain yield
0 – 30 nd nd nd nd
Saturated hydraulic
30 – 40 nd nd nd nd Overall, compaction increased soil ρb for the three soil texture
conductivity
> 40 nd nd nd nd
corn nd nd nd nd
groups at the surface depth (0– 30 cm). Increase in soil ρb was more
soybean nd nd nd nd pronounced in the coarse- and medium-textured soils compared with the
Grain yield
wheat nd nd nd nd fine-textured ones (Fig. 1a–c). For the coarse-textured soils and based on
barley nd nd nd nd our search criteria, there was no data collected for the severely loaded,
nd: indicates no data available for this category based on our search criteria. multiple passes and high inflation pressure treatments. The available

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P.B. Obour and C.M. Ugarte Soil & Tillage Research 211 (2021) 105019

Fig. 1. Mean response ratio for the effect of soil compaction factors on bulk density for (a – g) coarse-textured, (b – h) medium-textured and (c – i) fine-textured soils
grouped according to sampling depths. Bars represent 95% confidence intervals, numbers in parenthesis indicate the number of paired-comparisons from the
extracted dataset, and nd indicates no data collected for that particular category. Bulk density (Mg m–3) for the control group is shown in square bracket, and ± is
standard deviation of the mean.

dataset showed that the greatest increase in soil ρb was observed in the significant in the coarse- and medium-textured soils (Fig. 1g–i). In
moderately loaded, moderate number of wheel passes and medium tire general, the magnitude of changes in the subsoil were small and the
inflation pressure, which on average increased by 17, 11 and 11 %, variation seems consistent across studies as reflected in the narrower
respectively compared to their controls. In several instances, the wider confidence intervals.
confidence intervals of these three classification variables overlap with In the topsoil, traffic compaction increased the degree of compact­
other paired-comparisons. It is also important to note the small number ness (DC) compared to the controls. The greatest overall effect was
of paired-comparisons with respect to their counterpart treatments that observed in the coarse- and medium-textured soils (Fig. 2a–c). For the
is likely contributing to the wider confidence intervals. For the medium- medium-textured soils, DC significantly increased in the moderately
textured soils, the moderately, lightly and severely loaded treatments loaded treatment (DC increased by 22%) compared to the control
increased soil ρb on average by 18, 7 and 2 %, respectively compared to treatment. In the upper subsoil, overall, for the fine-textured soils,
the control treatment. Also note the small number of paired- compaction increased DC compared to the control, whereas DC was, in
comparisons for the severely loaded compared to the moderately and general, unaffected by compaction in the coarse- and medium-textured
lightly loaded treatments (Fig. 1b). In the upper subsoil (30–40 cm soils (Fig. 2d–f). In the subsoil, overall, compaction did not significantly
depth), overall, the effect of traffic compaction was significant in coarse- change DC in neither soil texture groups (Fig. 2g–i).
and fine-textured soils (Fig. 1d–f). In the fine-textured soils, soil ρb In the topsoil, overall, compaction increased penetration resistance
increased by 8, 6 and 3 % for the severely loaded, moderately loaded, (PR) compared to the control treatment for all soil texture groups (by
and the lightly loaded treatments compared to the control. However, it is 99% in the medium-textured, 94% in the coarse-textured and 41% in the
important to note that the severely and moderately loaded treatments fine-textured soils) (Fig. 3a–c). In the coarse-textured soils, the greatest
have slightly fewer paired comparisons than the lightly loaded treat­ increase in PR was found in the multiple passes treatment — increased
ment (Fig. 1e). In the subsoil (>40 cm depth), overall, traffic compaction PR by 237% (note the small number of paired comparison compared to
significantly increased soil ρb compared to the control treatment in the the counterpart treatments). In the medium-textured soils, PR increased
fine-textured soils, while the overall effect of traffic compaction was not the greatest in the moderate number of passes by 245% (also note that

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P.B. Obour and C.M. Ugarte Soil & Tillage Research 211 (2021) 105019

Fig. 2. Mean response ratio for the effect of soil compaction on the degree of compactness (DC) for (a – g) coarse-textured, (b – h) medium-textured and (c – i) fine-
textured soils grouped according to sampling depths. Bars represent 95% confidence intervals, numbers in parenthesis indicate the number of paired-comparisons
from the extracted dataset, and nd indicates no data collected for that particular category. Degree of compactness (%) for the control group is shown in square
bracket, and ± is standard deviation of the mean.

there was no data for multiple passes) and in the high inflation pressure subsoil where compaction decreased ka by 62, 68, and 68 %, respectively
treatment (by 225%). In the fine-textured soils, PR increased most for compared to the control. In the topsoil and upper-subsoil, compaction
the moderate number of passes (by 105%) and surprisingly, the lightly attributed to axle load (except the lightly loaded treatment), number of
loaded and low tire inflation pressure treatments increased by 98%. wheel passes, number of compaction events and tire inflation pressure
Note that there was no data collected for the multiple passes treatment. decreased ka compared to the control (Fig. 5a and b). In the subsoil, the
In the upper subsoil, the greatest effect of compaction was observed in lowest ka was observed in the high tire inflation pressure treatment and
the coarse- and fine-textured soils (PR on average increased by 35% than surprisingly, the onetime soil compaction treatment compared to the
the control) compared with the medium-textured soils (average increase control (Fig. 5c).
by 22% than the control) (Fig. 3d–f). On average, compaction decreased ksat in both the topsoil and upper
In the medium-textured soils, θFc increased for the severely loaded subsoil of the medium-and fine-textured soils (Fig. 6a–d). The overall
soil while it decreased for the moderately and lightly loaded compared effect of compaction attributed to machinery axle load, number of wheel
to the control. Overall, compaction did not significantly change θFc in passes, number of compaction events and tire inflation pressure was
the medium-textured soils, while a significant increase in θFc was consistently significant in the topsoil of the fine-textured soils. For the
apparent in the fine-textured soils (Fig. 4a and b). In the fine-textured medium-textured soils, compaction treatments (with the exception of
soils, θFc increased significantly in the moderately loaded and medium the few number of wheel passes) significantly decreased ksat compared
tire inflation pressure (by 5%) compared to the control. Also note the to their control in the subsoil whereas the opposite was observed in the
small number of paired-comparisons in the dataset. fine-textured soils, which showed ksat significantly increased for the
The only data available for quantifying compaction effects on ka in compaction treatments than the control (Fig. 6e and f). It is important to
our MA is from the medium-textured soils. Fig. 5a–c presents the impact note the differences in the number of paired-comparisons for treatments
of compaction on ka in the topsoil, upper subsoil and subsoil. Overall, in the fine-textured soils compared with those in the medium-textured
compaction significantly decreased ka at all the considered sampling soils.
depths. The greatest overall effect was observed in the topsoil and upper In terms of grain yield of corn, wheat, barley and soybean, the only

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P.B. Obour and C.M. Ugarte Soil & Tillage Research 211 (2021) 105019

Fig. 3. Mean response ratio for the effect of soil compaction on penetration resistance (PR) for (a and d) coarse-textured, (b and e) medium-textured and (c – f) fine-
textured soils grouped according to sampling depths. Bars represent 95% confidence intervals, numbers in parenthesis indicate the number of paired-comparisons
from the extracted dataset, and nd indicates no data collected for that particular category. Penetration resistance (MPa) for the control group is shown in square
bracket, and ± is standard deviation of the mean.

Fig. 4. Mean response ratio for the effect of soil

compaction on the volume of pores filled with
water at field capacity (θFc) for (a) medium-
textured and (b) fine-textured soils. Bars
represent 95% confidence intervals, numbers in
parenthesis indicate the number of paired-
comparisons from the extracted dataset, and
nd indicates no data collected for that particular
category. Volume of pores filled with water at
field capacity (m3 m–3) for the control group is
shown in square bracket, and ± is standard
deviation of the mean.

Fig. 5. Mean response ratio for the effect of soil

compaction on air permeability (ka) measured
at soil water content held at field capacity for
medium-textured soils grouped according to
sampling depths. Bars show 95% confidence
intervals, numbers in parenthesis indicate the
number of paired-comparisons from the
extracted dataset, and nd indicates no data
collected for that particular category. Air
permeability (μm2) for the control group is
shown in square bracket, and ± is standard
deviation of the mean.

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P.B. Obour and C.M. Ugarte Soil & Tillage Research 211 (2021) 105019

Fig. 6. Mean response ratio for the effect of soil

compaction on saturated hydraulic conductivity
(ksat) for (a – e) medium-textured and (b – f)
fine-textured soils grouped according to sam­
pling depths. Bars show 95% confidence in­
tervals, numbers in parenthesis indicate the
number of paired-comparisons from the
extracted dataset, and nd indicates no data
collected for that particular category. Saturated
hydraulic conductivity (cm/s) for the control
group is shown in square bracket, and ± is
standard deviation of the mean.

data collected in this MA is from the medium- and fine-textured soils. load, number of wheel passes, number of compaction events and/or tire
Overall, soil compaction decreased grain yield of corn, wheat, barley inflation pressure increased soil ρb in the topsoil (0–30 cm depth)
and soybean grown in both soil texture groups (Figs. 7 and 8). For the regardless of soil texture (Fig. 1a–c). However, it was observed that the
medium-textured soils, compaction, on average, decreased corn and greatest increase in soil ρb occurred in coarse- and medium-textured
soybean grain yield by 34%, grain yield of barley by 16%, and by 6% for soils. Surprisingly, the moderately loaded treatment increased soil ρb
wheat. In the fine-textured soils, soil compaction decreased grain yield more than the severely loaded treatment. These results need to be
by 15, 10, 9 and 7% for corn, wheat, soybean and barley, respectively. further verified as in the case of this particular work, our selection
However, there was no clear trends showing the impact of individual criteria, yielded only six paired-comparisons from two articles. In the
compaction factors on grain yield of the investigated crops. For example, upper subsoil, the overall impact of compaction was more pronounced
in the medium-textured soils, the greatest decrease in yield of barley was only in the coarse- and fine-textured soils. In general, compaction had
found in the moderate number of passes (by 27%) (Fig. 7c), whereas in minimal impact below the 40 cm depth in all soil texture groups. As
the fine-textured soils, the medium tire inflation pressure treatment mentioned elsewhere, it has been shown that plant growth can be
decreased grain yield of barely the most (by 14%) (Fig. 8c). limited when soil ρb exceeds 1.47 on clay, 1.75 on silt, and 1.80 Mg m–3
on sand and loam (Arshad et al., 1996), which suggests that the effect of
4. Discussion increase in soil ρb on plant growth could be more detrimental in the
topsoil and upper subsoil for the soils investigated here.
4.1. Effect of wheel traffic on soil physical properties Because soil ρb is strongly influenced by soil type (Reichert et al.,
2009), high ρb (compacted) for one soil may be a low ρb (loose) for the
Results from this MA showed that soil compaction attributed to axle other soil (Håkansson, 1990; Keller and Håkansson, 2010). Therefore,

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P.B. Obour and C.M. Ugarte Soil & Tillage Research 211 (2021) 105019

Fig. 7. Mean response ratio for the effect of soil compaction on grain yield of corn, wheat, barley and soybean for coarse-textured soils. Bars show 95% confidence
intervals, numbers in parenthesis indicate the number of paired-comparisons from the extracted dataset, and nd indicates no data collected for that particular
category. Grain yield (Mg ha–1) for the control group is shown in square bracket, and ± is standard deviation of the mean.

comparing values of ρb across different soil textures when evaluating the soil texture group (Fig. 3a–f). However, the effect was more pronounced
critical limit of soil ρb for crop growth may be inappropriate (Lipiec and in the topsoil than in the upper subsoil. In the topsoil, overall, PR
Håkansson, 2000; Keller and Håkansson, 2010; Naderi-Boldaji et al., increased in the coarse- and medium-textured soils (on average by 94,
2013). Håkansson (1990) suggested using relative bulk density, e.g., and 99 %, respectively compared to the controls) than in the fine-
degree of compactness to describe soil compactness because it is virtu­ textured soils (on average by 41% compared to the control)
ally independent of soil texture. Results from this work showed that as (Fig. 3a–c). In the upper subsoil, overall, soil compaction increased PR in
with soil ρb, in the topsoil, the effect of compaction on DC was more the coarse- and fine-textured soils than in the medium-textured soils
pronounced in the medium- and coarse-textured soils (on average, DC (Fig. 3d–f). Although the dataset used here had uneven number of
increased by 11% and 5%, respectively compared to the control) than in paired-comparisons among the soil texture groups and soil compaction
the fine-textured soils (average increase by 3% compared to the control) caused by traffic factors, results suggest that the hardpan often observed
(Fig. 2a–c). In the medium-textured-soils, DC increased with the in the upper subsoil of the soil profile was stronger in the coarse- and
moderately loaded more than the severely loaded treatment, which is fine-textured soils, which may mechanically limit or impair root growth.
also probably due to the small number of paired-comparisons for the Findings can be useful for site- and soil-specific management to avoid or
severely loaded treatment compared with the moderately loaded treat­ ameliorate the detrimental effect of compaction on soil mechanical
ment. In the upper subsoil, the overall effect of compaction on DC was strength.
significant in the fine-textured soils (Fig. 2d–f). Results from this MA In general, soil ρb and PR are indicators that are relatively easy to
though did show similar trends for soil ρb and DC, it highlights the measure and can provide first clues to help identify probable causes of
usefulness of DC for characterizing soil compactness (Reichert et al., yield differences and/or poor water infiltration within fields (Shaw
2009). For practical applications, Håkansson (1990) showed that a DC et al., 1942).
value of 87% is the optimum for annually tilled mineral topsoils in Soil compaction decreases soil structural complexity by shifting pore
Sweden and maximum grain yield of spring barley was obtained at that space heterogeneity to a more homogenous distribution. Changes in soil
point. In a study on silty loam and a loamy sand soil in Poland, Lipiec structure consequently affect water storage and transport in soil. In this
et al. (1991) found that increased DC caused by wheel traffic resulted in MA, compaction impact on soil structure processes and functions were
high PR and poor soil aeration characterized by low air-filled porosity, characterized in terms of θFC, ka and ksat. Results showed that, in the
which limited root growth. topsoil, soil compaction significantly increased pore volume retaining
Our work showed that soil compaction increased soil PR in the water at matric potential ranging between –10 to − 33 kPa, considered
topsoil and upper subsoil compared with the control regardless of the here as field capacity compared to the control in the fine-textured soils.

9
P.B. Obour and C.M. Ugarte Soil & Tillage Research 211 (2021) 105019

Fig. 8. Mean response ratio for the effect of soil compaction on grain yield of corn, wheat, barley and soybean for fine-textured soils. Bars show 95% confidence
intervals, numbers in parenthesis indicate the number of paired-comparisons from the extracted dataset, and nd indicates no data collected for that particular
category. Grain yield (Mg ha–1) for the control group is shown in square bracket, and ± is standard deviation of the mean.

This corresponds to an increase in pore size <30 μm which are water on soil structure (Gliński and Stępniewski, 1985). Overall, in the
filled at FC. However, the same effect was not observed in the medium- medium-textured soils, soil compaction significantly decreased ka
textured soils, which showed that, overall, θFC did not significantly differ compared to the control in the topsoil down to the subsoil (Fig. 5a–c).
between the compacted soil and the control (Fig. 4a and b). With respect Further, results from this work showed that for the medium-textured
to describing the effect of soil compaction on SWR, studies have shown soils category, soil compaction significantly decreased ksat compared
that compaction generally decrease the proportion of large pores and to the control from the topsoil down to the subsoil (Fig. 6a, c and e). For
increase the proportion of small pores (Alakukku, 1996; Assouline et al., the fine-textured soils, compaction significantly decreased ksat in the
1997). For example, Canarache et al. (1984) reported that compared topsoil and upper subsoil, but significantly increased ksat in the subsoil
with the control, pore size distribution of the compacted soil after 30 compared to the control (Fig. 6b, d, and f). Since both ka and ksat are
wheel passes significantly decreased medium (30 – 0.2 μm) and larger governed by pore size (large soil pores) and pore geometry and conti­
(>30 μm) size pores. Some studies show that compaction reduced soil nuity, results point to the effect of compaction in shifting pore size
water content held at higher matric potentials (0 to − 10 kPa) and distribution of soil by decreasing soil macroporosity and increasing
increased soil water content held at low matric potentials (–250 to microporosity (Alaoui et al., 2011). Lassen et al. (2013) explained that
− 1550 kPa) (Domżał, 1983; Ferrero and Lipiec, 2000) cited in Lipiec soil compaction reduces ksat because at water content near saturation,
and Hatano (2003) and Alaoui et al. (2011). In the present work, in­ both the meso- and macropores contribute to water conductivity of
crease in θFC in the fine-textured soils could be interpreted as compac­ non-compacted soils. A decrease in soil hydraulic conductivity can lead
tion shifted the pore size distribution by decreasing the proportion of to lower wetting in the rooting zone, which can result in plants affected
macropores (i.e. at high matric potential) and increasing the proportion by water stress. Poor water infiltration can also lead to runoff and soil
of meso- and micropores (intermediate and low matric potentials) which losses due to water erosion (Young and Voorhees, 1982). Increase in ksat
are vital in the retention of water against the force of gravity. However, below 40 cm depth in the fine-textured soils can probably be attributed
high θFC signifies a decrease in air-filled pore volume at FC, suggesting to cracks created by compaction in the subsoil (Lowery and Schuler,
that soil compaction may compromise the balance between water and 1994), which leads to preferential flow.
air-filled pores leading to poor soil aeration, which can adversely affect In a nutshell, unlike the composite soil attributes (ρb, DC and PR),
soil microbial and root respiration. (Gliński and Stępniewski, 1985). which showed the effect of soil compaction was, in general, restricted to
This review showed that compaction attributed to axle load, wheel the topsoil and upper subsoil, the fact that hydraulic attributes, ka and
passes, compaction events and tire inflation pressure reduced soil con­ ksat reflected the effect of soil compaction in the topsoil down to the
ductivity quantified in terms of ka and ksat. Air permeability is an subsoil suggests that soil hydraulic properties may be better and more
important indicator used to characterize the effect of soil management sensitive indicators to reflect the status of soil compaction on soil

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P.B. Obour and C.M. Ugarte Soil & Tillage Research 211 (2021) 105019

structure and pore system functions in the soil profile. 5. Conclusions

4.2. Soil compaction and grain yield — influence of physical attributes This paper used a meta-analytical approach to synthesize a body of
literature on the impacts of soil compaction attributed to machinery axle
This MA suggests that compaction significantly reduced grain yield load, wheel passes, compaction events and tire inflation pressure on bulk
of corn, wheat, barley and soybean (Figs. 7 and 8). In the medium- density (ρb), degree of compactness (DC), penetration resistance (PR),
textured soils, yield reduction ranged from 6% for wheat to 34% for volume of water filled pores at field capacity (θFc), air permeability (ka)
corn and soybean, and in the fine-textured soils, it ranged from 6% for at field capacity, saturated hydraulic conductivity (ksat), and grain yield
barley to 15% for corn. Although there were no clear trends showing the of corn, wheat, barley and soybean. Soil compaction, in general,
individual effect of axle load, wheel passes, number of compaction adversely affected the soil physical properties investigated in coarse-,
events and tire-inflation pressure on grain yield, the low tire pressure medium-, and fine-textured soils, particularly in the topsoil. Overall,
treatment increased yield of barley compared to the control in the compaction decreased grain yield of corn, wheat, barley and soybean by
medium-textured soils (however, it is important to note the small 6–34%. The main take home messages drawn from this work suggest
number of paired comparisons for this specific group and treatment) that:
(Fig. 7c). In the fine-textured soils, the severely loaded treatment
decreased grain yield of wheat whereas the low tire inflation pressure 1 The level of resolution varies when considering soil strength attri­
increased grain yield of wheat (Fig. 8b). butes (ρb and PR) and hydraulic properties (ka and ksat). Although
The final yield of crops is affected by complex interacting soil and the former properties are relatively easy to measure, they are com­
environmental factors. Soil conditions include non-impedance me­ posite properties and provide little firsthand clues on changes in pore
chanical resistance to root growth, accessibility to soil water and nu­ structure and associated functions. Considering that hydraulic in­
trients, and adequate diffusion of gases (e.g., oxygen concentration in dicators were more sensitive in characterizing changes in soil
air) and soil moisture (Colombi and Keller, 2019; Esteban et al., 2019). structure in the soil profile as evidenced by ksat, it is important for
According to Bengough et al. (2011), plants require root systems that compaction studies to also consider the measurement of soil hy­
deliver adequate water and nutrients for shoot growth, and to anchor draulic properties in addition to mechanical strength attributes.
them in the soil. Soil compaction effect on poor growth and yield is 2 There is a small number of studies that investigated traffic compac­
attributed to soil physical stresses due to mechanical impedance (Hamza tion impact on both soil physical properties and grain yield — most
and Anderson, 2005; Bengough et al., 2006). Non-restrictive soil PR studies investigated either changes in soil physical properties or crop
enhances the ability of roots to avoid oxygen-depleted soil strata attributes, while only a few investigated both. Consequently, there is
through oxytropism or orient towards water through hydrotropism not enough published data to robustly relate the two. It is pertinent
(Porterfield and Musgrave, 1998). However, the relative importance of that, whenever possible, both soil and crop properties are measured
these limitations varies depending on other factors such as crop species to better understand plant physiological responses to soil compaction
and climatic conditions (da Silva et al., 1994). Crop species and cultivars and underlying changes in crop yield.
within species differ in their rooting system and in their phenotypic 3 In some of the studies, incomplete or no information on soil, and/or
response to compaction (Singh and Sainju, 1998). Some authors have machinery and compaction characteristics were provided, thus,
reported that restrictive root growth due to soil strength does not always limiting their use in multi-study evaluations. We recommend re­
translate into stunted growth and low yield (Reichert et al., 2009). For searchers to consider publishing complete metadata that allows
instance, plant species with deep tap root systems usually have an replication and accurate comparison of results across studies.
improved ability to penetrate compacted soil layers (Hamza and 4 The state of traffic-induced compaction in relation to soil physical
Anderson, 2005). da Silva et al. (2004) demonstrated that in a soil with a quality for plant growth is often characterized using a spectrum of
wide range of texture classes and soil organic matter content, corn soil and crop indicators. Considering that measurement of many
growth only slowed down, but was not inhibited at air-filled porosity of indicators can be both time consuming and cost prohibitive, the soil
0.10 m–3 m–3 and PR of 2 MPa, which are frequently regarded as critical science community can benefit from open access to original data that
values. Voorhees et al. (1989) predicted that for every 0.1 Mg m–3 in­ should be published as supplementary material or in appropriate
crease in bulk density above 1.3 Mg m–3 in a soil with 30–40% clay, corn external databases. This type of access to original data can contribute
grain yield decreased by 18%. Beutler et al. (2004) reported that grain to build robust local and regional datasets and improve our ability to
yield of soybean decreased by 60% when PR increased from 0.4 to 4.2 characterize the effects of soil compaction in agricultural fields.
MPa.
On the contrary, other studies have shown that some level of Declaration of Competing Interest
compactness (slight to moderate compaction) may be beneficial to
improve crop growth and increase yield (Etana and Håkansson, 1994). The authors report no declarations of interest.
For instance, Lindemann et al. (1982) reported that in a clay loam soil,
compaction caused by 1–3 tractor passes increased grain yield of soy­ Acknowledgements
bean (an average of 2.18 ton/ha) compared to the non-compacted
control (1.98 ton/ha). In this MA, we observed an overall decrease in We gratefully thank Clare Darnall for assisting with data organiza­
grain yield of corn, wheat, barley and soybean in relation to the crops tion during the extraction of data from articles.
responses to soil compaction impact on soil ρb, PR and DC, but given the
limitations in the constructed dataset, it was not possible to establish a Appendix A. Supplementary data
meaningful relationship between the studied soil physical properties
and grain yield. The lack of consistent trends showing the effect of levels Supplementary material related to this article can be found, in the
of axle load, wheel passes, number of compaction events and online version, at doi:https://doi.org/10.1016/j.still.2021.105019.
tire-inflation pressure on grain yield could partly be interpreted as the
influence of environmental covariates that also have an effect on crop References
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