Defra SP1305 (CTE 1024)
Studies to inform policy development with regard to soil degradation:
Subproject A: Cost curve for mitigation of soil compaction
Paul Hallett, Bedru Balana and Willie Towers
The James Hutton Institute, Invergowrie, Dundee, DD2 5DA
[email protected]
Andrew Moxey
Pareto Consulting, 29 Redford Avenue, Edinburgh, EH13 0BX
[email protected]
Tim Chamen
CTF Europe, Church Cottage, Church Road, Maulden, Bedford, MK45 2AU
[email protected]
Total Defra SubProject Costs: £33034
Start Date: 01/04/2011
Submission Date: 30 March, 2012
End Date: 31/03/2012
Table of Contents
Executive Summary................................................................................................................................. 3
List of Acronyms ...................................................................................................................................... 5
Introduction ............................................................................................................................................ 6
Review of Hard Data on Soil Compaction – Impacts, Mitigation and Avoidance ................................... 7
Soil Compaction in England and Wales............................................................................................... 8
Cost benefit analysis of soil compaction and its mitigation ............................................................... 8
Yield Penalty.................................................................................................................................... 9
Fertiliser Demand.......................................................................................................................... 15
Cultivation Energy ......................................................................................................................... 16
Water ............................................................................................................................................ 18
Environmental Costs ..................................................................................................................... 19
Grazing Systems ............................................................................................................................ 20
Mitigation, Confinement and Avoidance .......................................................................................... 21
Low Ground Pressure Tyres .......................................................................................................... 22
The effectiveness and cost of different compaction mitigation measures ...................................... 23
Subsoiling ...................................................................................................................................... 23
Auto-drive GNSS farming machinery ............................................................................................ 25
Use of lighter machines ................................................................................................................ 25
Organic matter sequestration ....................................................................................................... 25
Controlled Traffic .......................................................................................................................... 26
Grazing: Stocking Rates and Timing .............................................................................................. 28
Overview of Available Hard Data ...................................................................................................... 30
Industry and Farm Specific Economic Information ............................................................................... 31
Introduction ...................................................................................................................................... 31
Compaction mitigation ..................................................................................................................... 32
Costs and returns for mitigation measures ...................................................................................... 35
Subsoiling ...................................................................................................................................... 35
Improved timeliness due to subsoiling ......................................................................................... 35
Loss of soil and nutrients .................................................................................................................. 37
Tramlines........................................................................................................................................... 38
Headlands ......................................................................................................................................... 38
Reduced cost of subsequent cultivations ......................................................................................... 39
Summary of subsoiling return on investment .................................................................................. 40
1
Deeper cultivations ........................................................................................................................... 41
Summary of deeper cultivation effects............................................................................................. 42
Low ground pressure tyres ............................................................................................................... 42
Summary of low ground pressure effects ..................................................................................... 43
Controlled traffic ............................................................................................................................... 44
Consequential benefits ................................................................................................................. 45
Summary of controlled traffic returns on investment .................................................................. 46
Satellite guidance and auto-steer ..................................................................................................... 46
Summary of recommendations for compaction mitigation and management .................................... 46
Mitigation...................................................................................................................................... 46
Management ................................................................................................................................. 46
Development of Economic Cost Curves ................................................................................................ 48
Recap of cost categories ............................................................................................................... 50
A winter wheat example ............................................................................................................... 51
Baseline yields, compaction penalties & mitigation effects ......................................................... 52
Diesel usage .................................................................................................................................. 55
Nutrient losses .............................................................................................................................. 59
Illustrative Cost curves ...................................................................................................................... 60
Wheat............................................................................................................................................ 60
Potatoes ........................................................................................................................................ 64
Onions ........................................................................................................................................... 68
Discussion.......................................................................................................................................... 73
Soil compaction and climate change ................................................................................................ 73
Policy support for mitigating soil compaction .................................................................................. 74
References ........................................................................................................................................ 76
APPENDIX .............................................................................................................................................. 85
2
Executive Summary
The project brought together a team of soil scientists, agricultural engineers and economists to
collate, analyse and discuss the economics of mitigating soil compaction in England and Wales. It
focussed first on operational costs, where the most definitive data are available. This includes the
costs associated with remediation/alleviation strategies such as sub-soiling. Next it considered the
costs of limiting the occurrence of compaction by limiting or avoiding it through the adoption of new
technologies. The social costs of soil compaction, through direct impacts at the farm gate on yields
and inputs, and indirectly on ecosystem services provided by soil were incorporated into indicative
cost-curves to assess the value of different approaches. Factors considered are the influence of soil,
farm management practice and novel approaches that are either in use or being developed. Current
trends in increasing machinery weight, new evidence of subsoil compaction, the uptake of Global
Navigation Satellite Systems (GNSS) and the shift towards reduced tillage were investigated.
Hard data were collected mainly from refereed scientific literature since the information could be
trusted to be robust. Some supplemental information from government and institute reports was
also collated. A large amount of information on soil compaction mitigation and minimisation was
found in the scientific literature, with over 130 articles cited, but little of this considered economic
costs and benefits. Moreover, reported results were often highly context-specific. In controlled soil
compaction experiments, yield losses of up to 60% were found if entire field plots were compacted
by high stress machinery.
However, these experiments represented extreme conditions atypical of conventional farming
operations. Yield losses of 10-25% were more commonly found, with large differences found
between subsequent years due to climate and between sites due to soil type. Other major direct
economic threats of soil compaction on arable farms included increased fuel, fertiliser and water
use, as well as equipment wear and labour costs. Sub-soiling is the most commonly used mitigation
strategy, but research found it to be ineffective at restoring yield other than for spring sown crops.
Various studies, however, demonstrated a natural resilience to topsoil compaction within about 5
years. Soils were not resilient, however, to subsoil compaction, with a permanent 10% yield penalty
reported. Economic data for compaction caused by grazing was minimal.
Fourteen different farms representing a range of soil types and typologies were assessed directly to
determine soil compaction mitigation strategies used in practice and their economic cost. In
addition, industry data on the cost of machinery or compaction reducing technologies such as low
ground pressure tyres were collated. A lack of relevant data on grazing systems precluded detailed
analysis of compaction under grassland, meaning that the focus remained on arable systems.
Illustrative cost-curves for the mitigation of soil compaction selected enterprises (wheat, potatoes
and onions) in England and Wales were generated. These relied on a combination of hard and grey
data, including information gleaned from farm visits and direct consultation with industry.
Precise quantification of compaction impacts is difficult and the cost-curves necessarily invoke a
number of assumptions: for example, baseline effects on yields, fuel usage and nutrient losses
attributable to compaction and to the net effect of mitigation actions in countering such problems.
Results are sensitive to variation in these assumptions, but some general conclusions can be drawn.
3
First, the higher the yield, fuel and nutrient losses attributable to compaction, the greater the
likelihood that any given mitigation option will be cost-effective, even more so if prevailing input and
output prices are high. Second, the greater the efficacy of any given option at countering negative
effects, the greater the likelihood of it being cost-effective - again more so if output and/or input
prices are high.
Third, in many cases (but not all, and dependent on assumptions), the net on-farm cost of mitigation
is negative. This means that there are win-win possibilities for improving enterprise profitability
whilst simultaneously reducing environmental loadings. Fourth, alleviating compaction tends to be
more costly than avoiding it in the first place. Hence options such as low ground pressure tyres or
CTF are likely to be more cost-effective than options such as untargeted sub-soiling.
Although plausible, the validity of these general conclusions and the applicability of them to specific
farm-situations could be tested by further empirical research. In particular, impacts on both
profitability and environmental loadings are highly sensitive to assumed nutrient losses attributable
to compaction. Given that nutrient losses are dependent on a number of factors, including weather
conditions, fertiliser application rates and other management practices, further investigation is
merited. Similarly, although the sensitivity of results is less severe, variation in fuel usage across
different soil types would also benefit from further investigation.
However, despite data gaps, the cost-curves are sufficiently robust to support the main points
revealed by the literature and industry opinion. In particular, compaction imposes on-site and offsite costs that can be reduced through management actions. The apparent low adoption rate for
some options may indicate barriers to uptake such as a lack of awareness or confidence amongst
farmers - suggesting behavioural change research already underway for other GHG and diffuse
pollution mitigation options could usefully be extended to include soil compaction issues.
4
List of Acronyms
ATV – All Terrain Vehicle
C–
Carbon
CAP – Common Agricultural Policy
CTF –
Controlled Traffic Farming
CY –
Clay
d–
Depth
D–
Draught Force
FBS –
UK Farm Business Survey
FGM – Farm Gross Margins
GHG – Greenhouse Gas
GM –
Gross Margin
GNSS – Global Navigation Satellite Systems
LGP – Low Ground Pressure
SCL –
Sandy Clay Loam
SL –
Sandy Loam
w–
Soil Moisture Content
WFD – Water Framework Directive
WUE – Water Use Efficiency
ƿ–
Soil Density
5
Introduction
Agricultural soil compaction occurs where, for example, excessive contact pressure from heavy
machinery or repeated livestock trampling, causes vertical and/or horizontal deformation of the soil
structure. This leads to lower porosity and connectivity within the soil, inhibiting root penetration,
water uptake and overall plant development; pest and disease risks can also increase.
These changes can impact directly on both the quantity and quality of crop and grassland yields
achieved, representing a relatively clear negative (i.e. cost) influence on agricultural productivity.
However, productivity losses may also occur less obviously through greater usage of and strain upon
other farm resources. For example, greater energy and labour requirements for impeded cultivation
of compacted soils, greater wear and tear (depreciation) on farm machinery worked harder and/or
more often, and greater use of other inputs (e.g. seeds, fertilisers, sprays) to counteract depressed
yields. Compaction’s influence on water logging can also affect field access, hindering the timeliness
and thus effectiveness of field operations. Examples include delayed sowing, sub-optimal chemical
applications and excessive peak-loading of machinery and labour.
Such effects are felt primarily on-site, by farmers experiencing compaction problems. However,
some other effects may also be experienced off-site as externalities, particularly non-point pollution.
For example, both directly from the soil and indirectly through fossil fuel energy usage. Additionally,
compaction and its management can influence levels of Greenhouse Gas (GHG) emissions as well as
surface water runoff and consequently soil and nutrient losses to watercourses.
Measures to combat soil compaction are thus of interest since they potentially offer agricultural
productivity and environmental gains, although their relative attractiveness need to be established
empirically. That is, they will require adjustments to farming practices and such adjustments may
incur costs as well as conveying benefits. Moreover, since both the incidence and impact of
compaction are likely to vary across different types of soil, weather conditions, enterprises and
farming systems, the balance between different management strategies is likely to vary depending
on local circumstances.
This report presents an attempt to construct illustrative cost-curves for the alleviation and avoidance
of soil compaction specific to a range of soil types and farming operations in England and Wales. The
cost-curves, and the supporting discussion of their creation and assumptions, are intended to guide
the development and implementation of policies by Defra related to soil degradation. Direct costs at
the farm gate and environmental loadings are considered. New technological shifts and trends
towards lower input tillage systems have been incorporated to ensure that the information remains
relevant in coming years.
The sources of information used to populate the cost-curves were hard data reported in peer
reviewed papers, grey data from government and industry reports and direct consultation with
farmers and the agricultural engineering industry. A literature review on the causes, impacts and
mitigation of soil compaction, which is presented in this final report, identified the extent of the
problem and the key parameters needed to provide a robust economic analysis.
Expert judgement was necessary so we brought together a team of soil scientists, agricultural
engineers and economists. We focussed first on operational costs, where the most definitive data
6
are available. This included the costs associated with remediation strategies such as sub-soiling.
Next we considered the costs of avoiding or confining soil compaction through the adoption of new
technologies. The cost-effectiveness of management options through direct impacts at the farm
gate on yields and inputs, and indirectly on nutrient loadings and GHG emissions were incorporated
into indicative cost-curves to assess the value of different approaches.
Objectives
1. To assemble information on the costs of remediating soil compaction, including a
discussion of the knock-on costs from soil structural damage to ecosystem services.
2. To assemble costs of soil compaction avoidance and mitigation through new
technologies and the better timing of field operations/grazing activity.
3. To develop cost curves of avoidance and remediation strategies to soil compaction.
4. To discuss costs and benefits of compaction avoidance or remediation in the
development of policy including effective incentives to the farming community.
5. To consider the implications of future climate scenarios to the implementation of
policies to address the threat, avoidance and remediation of soil compaction.
Review of Hard Data on Soil Compaction – Impacts, Mitigation and
Avoidance
The primary source of hard data is scientific literature published in refereed manuscripts or institute
reports (e.g. Schjønning et al., 2009; Glenket al. 2010; Görlach et al. 2004). We consider the
relevance of the information to current production systems, so for arable some older literature will
be less relevant because of shifts in machinery size and tillage implements. The situation differs with
regard to livestock production as animal numbers and size do not vary over time in the same way.
Our search of the literature has shown that assembling the costs and benefits of soil compaction
mitigation and avoidance approaches presents a great challenge. Economic data on soil compaction
are scarce, despite pleas by Soane and van Ouwerkerk (1995) over 15 years ago for researchers to
begin to assemble this vital information. To some extent the on-site and off-site threats of soil
compaction are appreciated for England and Wales (Bateman et al., 2011; Batey, 2009; Ball et al.
2000) although compared to many other European countries quantitative data are less available
(van den Akker et al., 2003). These factors make it difficult to perform more than an indicative
economic assessment based on existing degradation and mitigation strategies employed in England
and Wales. Nevertheless, some illustrative examples will be possible.
Some information from controlled field experiments exists for the on-site impact of compaction
mitigation strategies on yield, fertiliser inputs and fuel use (e.g. Lipiec et al., 2003; O’Sullivan and
Simota, 1995). We can use these with supplemental industry data on the cost of the equipment for
mitigating soil compaction including sub-soiling and the added draft power required for conventional
surface cultivation. The search of hard data has also identified missing information that needs to be
collected on case-study farms, predicted from semi-quantitative models (e.g. power usage for
subsoiling) or based on expert judgement.
7
We begin with an overview of the potential direct and indirect (e.g. environmental) costs of
compaction. Mitigation strategies are also reviewed. This information provides the framework that
we present to generate the Soil Compaction Mitigation Cost Curves. Although more robust costcurves could be generated with quantitative farm-level analysis, it requires greater modelling
sophistication than enterprise-level analysis. Given the sparse data available, enterprise level
analysis has been adopted. Illustrative curves are presented for winter wheat, potatoes and onions.
Soil Compaction in England and Wales
Recent review articles (Batey, 2009; Greenwood et al., 1997) and government reports (Schjønning et
al., 2009; Dobbie et al., 2011) provide a detailed overview of the causes of soil compaction, the
threat soil compaction poses to farming and the environment and the effectiveness of a range of
mitigation strategies. In arable and grazing systems, compaction occurs if the stress imposed by
traffic causes irreversible damage to soil pores. Damage includes both the compression and
shearing of the soil pore structure, so simple indices such as changes in soil bulk density often
provide a poor indicator of compaction damage (O'Sullivan et al., 1999). As the strength of soil is
heavily dependent on water content, wet soils are far more susceptible to compaction than dry soils.
A general rule of thumb is to prohibit traffic when soils are wetter than field capacity, although this
may not account for conditions in the subsoil.
Land managers appreciate the threat of soil compaction, particularly given trends towards increased
machinery weight, rising fuel costs and adoption of reduced tillage systems in the arable sector. This
was reflected in the survey carried out by the Royal Agricultural Society (RASE, 2012) which revealed
that approaching 20% of farmers in both the arable and livestock sectors recognised soil compaction
as more than of little concern. The predicted likelihood and experience (RASE, 2012) of more erratic
weather conditions may make it more difficult for land managers to time operations to avoid
compaction. Increased production demand on the land resource in coming years, which will be
needed to feed a growing population and driven in the UK by shifts in commodity prices, is a social
driver that may influence compaction and its mitigation. Environmental factors due to climate
change or social factors due to food demands, however, are beyond the scope of our analysis or the
search of hard literature.
Cost benefit analysis of soil compaction and its mitigation
Before it is possible to assess the economic benefits of soil compaction mitigation strategies, the
economic penalty of soil compaction to farm income is required. Various economic on-farm losses
can be considered including yield penalties, fertilizer requirements and land access. Off-site
environmental costs are also important, but much more difficult to ascertain.
If untreated, a compacted soil imposes both higher production costs and lower revenue receipts on
an enterprise. Lower revenues reflect lower yields due to, for example, poorer germination rates
and crop growth but also possibly poorer crop quality. Higher costs reflect additional inputs such as
greater fertiliser use to counter compaction-induced losses plus greater fuel use due to the higher
energy requirements of pulling implements through compacted soil. However, it is important to
note that not all production activities (and thus costs) are affected by compaction
The negative effect is most pronounced on compacted soil where no action is taken to counter the
compaction. Alleviating compaction through, for example, sub-soiling improves the situation but
8
still typically incurs some losses relative to avoiding compaction in the first place. Seeking to avoid
causing compaction through, for example, CTF or the use of low ground pressure tyres limits the
incidence and/or severity of compaction in the first place and tends to offer both superior yields and
lower production costs. For example, wheat yields on a clayey soil under an avoidance strategy such
as Controlled Traffic Farming can be 5% higher than under an alleviated strategy such as sub-soiling
which in turn can be 2.5% higher than under a no-action strategy (see later sections for discussion of
data source). Equally, energy requirements on a compacted soil can be 50% or more than on a noncompacted soil. Figure 1 below (not to scale) illustrates this general pattern.
Lower revenue
Gross Margin
Lower revenue
Gross Margin
Higher costs
Gross Margin
£/ha
Higher costs
Production costs
Production costs
Production costs
Avoided compaction
e.g. CTF
Alleviated compaction
e.g. sub-soiling
Compacted soil
i.e. no management
Figure 1 - Stylised comparison of the effect on gross margin of different compaction management
strategies
Yield Penalty
Yield may decrease in compacted soils because of (1) increased mechanical impedance for roots, (2)
decreased aeration and (3) decreased water storage in soil (da Silva & Kay 1996). Waterlogging is
directly related to compaction (Douglas & Crawford 1998). It has negative impacts on plant
production, often resulting in crop failures in agriculture (Wairiu et al. 1993) and limits access to land
by grazing animals. Although numerous sources of data exist that demonstrate decreased yield
caused by soil compaction, the experimental treatments employed often create a bias that limit the
use of the data for economic cost curves.
Many compaction experiments wheel large parts of fields to induce compacted vs. non-compacted
treatments. Crop responses from regions of higher soil moisture are up to 15% reduction in yields
from wheel traffic. Eriksson et al. (1974) reported estimates that cereal yields in Sweden would be
increased by 6% in the absence of compaction, although research from elsewhere (Koch et al., 2008)
reported no response in wheat yield following sugar beet harvesting and ploughing. Various studies
employ different depths and intensities of cultivation, which have different cost and timeliness
aspects associated with them. Arguably the best data available come from a collaborative project
involving seven countries in northern Europe and North America (Håkansson, 1994). These
experiments wheeled entire plots on one occasion with loads of either 10 Mg on single axles (5 Mg
wheel load) or 16 Mg on tandem axles, with tyre inflation of 250-300 kPa. All fields (both compacted
and controls) were subsequently ploughed to 20-25 cm using lighter machinery, thus limiting the
usefulness of the data for economic cost curves that incorporate reduced tillage systems. Yield data
9
collected from this collaborative project showed large variability due primarily to climatic conditions
either in a growing season or when the compaction stress was applied (Håkansson and Reeder,
1994). These experiments also examined the length of time required for crop yields to recover
following compaction. Compaction of deep subsoil was found to be relatively long term that
continued to influence crop yields even after 10 years of recovery. Shallower compaction to the
plough layer (0-25 cm), however, was short-term with yields recovering to previous levels within 5
years (Figure 2).
Figure 2 – Recovery of crop yield over time following compaction at different levels in the profile.
Paired plots of compacted versus non-compacted treatments were compared at a range of sites
across a number of countries (Håkansson and Reeder, 1994).
Further analysis of crop response to soil compaction in Sweden was conducted by Håkansson (2005).
He used the results of 21 trials in Sweden carried out between 1963 and 1992 representing 259
location years. Wheel loads of around 2 Mg, which are modest by today’s standards, were applied
just before autumn ploughing. However, the intensity of traffic was high (350 Mgkm ha-1) compared
with conventional practice because the traffic was applied uniformly across the whole plot width.
Following the ploughing operation only light vehicles with low ground pressure tyres were used
consistently across all the regional sites, the bulked results of which are shown in Figure 3. These
clearly show that traffic effects were not mediated by the ploughing operation and that yields took
nearly 4 years to restore to the non-treatment level. In parallel with these trials were others
imposing a lower intensity (120 Mgkm ha-1), where the yield losses were about one third of those
from the higher intensity trial, suggesting that the effect was influenced by traffic intensity.
10
Figure 3.Mean crop yield relative to no treatment compaction (100) from a series of 21 long-term
trials in Sweden. A. Mean relative yield in the compacted plots. B. Yields from year 4 to year 8 as a
function of soil clay content. C. Yields following termination of treatment traffic (Year 0 last
treatment) (after Håkansson, 2005)
Figure 4 shows the effect of soil type on the yield of combinable crops subjected to a range of
standard random compaction levels compared with zero traffic. These data were taken from around
25 different research papers quoted by Chamen (2011). Although not definitive, these provide some
indication of distinct yield responses from different soil types.
Figure 4. Reduction in yield of combinable crops grown under random compared with zero traffic on
clays (19), loams (8) and silts (3) (Chamen, 2011). The numbers in brackets are the number of farms
sampled.
Yield reductions for different crops were also reviewed by Håkansson (2005). These were plotted in
terms of degree of compactness, which is based on soil density found in the field versus a density
induced by a large compacting stress applied in the laboratory. A degree of compactness of 100
simulates traffic from very heavy machinery. Håkansson’s (2005) analysis shows a relatively higher
degree of compaction being optimal for cereal crops but a lower level for oilseed rape (Figure 5).
A more recent study in England applied ‘light’ (1 pass) and ‘heavy’ (8 passes) compaction stresses to
soils with different textures and then sowed the fields with wheat (Gregory et al., 2007). The yield
reduction due to ‘heavy’ soil compaction in a sandy loam soil was almost 50%, whereas for a clay soil
the yield was not changed by applying ‘heavy’ compaction stresses (Figure 6). The authors attributed
the results found for the clay soil on the buoyancy effect of pore water.
11
Using any of the data presented thus far to predict yield penalties will be influenced by the
uncertainty of climate, soil type, soil cultivation practice and the crop grown. A more deterministic
prediction of the yield penalty caused by soil compaction could be inferred from other properties.
Further research in England by Whalley et al. (2008) found that the yield of wheat was related to soil
strength, as induced by soil compaction. Pedotransfer equations exist to predict soil strength that
include the influence of soil type and machinery/livestock (Horn and Fleige, 2003). At present these
models still require considerable refinement to provide reasonable predictions of soil strength and
they have not been parameterised for the soils in England and Wales. Expert models of soil
susceptibility to compaction (Jones et al., 2003) could perhaps be adapted as well to make
predictions of yield penalties from soil compaction on a
wide range of soil types. Developing either approach
would require considerable research investment.
Figure 5. Share of trials on different crops
with estimated yield reductions (%)
relative to the maximum yield for an
individual trial with varying degrees of
compactness in the plough layer (after
Håkansson, 2005).
Figure 6. Grain yield following no (grey), light
(large diagonals) and heavy (small diagonals)
compaction on sandy loam, SL, sandy clay loam,
SCL and clay, CY soils (Gregory et al., 2007).
As shown earlier in the study of Håkansson and Reeder (1994), soils have an inherent resilience to
soil compaction, particularly in the topsoil. Given the limitations imposed by the experimental
conditions used to induce compaction in the studies reported thus far (i.e. subsoil compaction, light
and heavy compaction) another approach could be to compare yields between trafficked and nontrafficked soils. Non-trafficked soils are possible through the use of controlled traffic systems, which
will be reviewed in greater detail as a potential mitigation strategy. Table 1 summarises yield data
for a wide range of non-trafficked experiments that have been conducted in paired experiments that
contain trafficked plots.
12
Table 1: Overview of literature comparing crop yield on trafficked versus non-trafficked plots. A
range of soil types, crops and countries are presented.
Crop
Cereals
Barley
Yield
Soil
% of nonInformation
trafficked
Profile: clay,
87-110 loam, sandy
loam, loam
Subsoil: sandy
62-81
loam
Country
Reference
England, NL, Scot.,
Germany
Chamen et al.,
1992b
England
Wheat
85 Profile: clay
England
Spring
barley
86 Profile: clay
England
Wheat
79 Profile: clay
England
Wheat
Barley
Profile: silt
loam
Profile: sandy
100+
clay loam
100
Spring
barley
84 Profile: gley2
Spring osr
80 Profile: gley2
Winter
barley
Wheat
Barley
Oilseed
rape
Wheat
Maize
Soybean
Wheat
Cereals
Cereals &
grain
legumes
Wheat
Wheat
England
Scotland
Pollard & Elliott,
1978
Chamen et al.,
1992a
Chamen et al.,
1994
Chamen &
Longstaff, 1995
Graham et al.,
1986
Campbell et al.,
1986
Scotland
Dickson &
Ritchie, 1996b
74
69 Raised beds:
sands, loams
75
Australia
Hamilton et al.
2003
83
Profile: clay
79
loams
84
USA
Voorhees et al.,
1985
93 Profile: loam
Netherlands
Lamers et al.,
1986
Profile: clay
loam
80 Subsoil: clay
Australia
Radford & Yule,
2003
Profile: Red
Brown earth
Australia
Sedaghatpour et
al., 1995
87 Profile: gley2
69
89
100 Profile: clay
84
Profile: fine
sand
Australia
South Africa
13
Radford et al.,
2000
Bennie & Botha,
1986
Crop
Cereals
Cereals
Oats
Barley &
peas
Wheat
Oilseed
rape
Spring
cereals
Cereals
Yield
Soil
% of nonInformation
trafficked
Profile:
87-95
various
Profile:
77–122
various
71 Profile: clay
77-100 Subsoil: silt
loam
100
Profile: sodic
53
clay
79-84 Profile: clays
88 Profile: clay
Country
Reference
Ukraine
Medvedev et al.,
2002
Poland
Lipiec, 2002
Sweden
McAfee et al.,
1989
USA
Hammel, 1994
Australia
Chan et al., 2006
Sweden
Australia
Håkansson et al.,
1985
Tullberg et al.,
2001
Taking the data from Chamen (2011), the response of different crops to trafficked and non-trafficked
conditions can to some extent be isolated, as indicated in Figure 7. The number of data points is
highly variable but provide an indication of the robustness of the trends.
Crop quality is another factor that will influence the economic return to farmers. Batey (2009)
suggested that soil compaction can have a major impact on crop uniformity, particularly for high
value crops such as salad potatoes, beetroot, leeks and carrots. Given stringent demands for quality
in many high value crops, this will have major implications. The greater potential economic returns
for these crops provide greater incentive to adopt mitigation strategies.
There is very limited information on yield loss associated with poaching. Patto et al (1978) reported
various studies but conclude that there was little quantitative evidence that dry matter yield or
utilised outputs are reduced by grazing. The more recent DEFRA project BD 2304 report provided
little new evidence and actually focussed on environmental impacts such as those on birds, diffuse
pollution and biodiversity other than yield loss.
14
40
Barley (4)
35
Yield increase, %
Oats (5)
30
Peas (1)
25
Sugar beet (1)
Wheat (13)
20
Onions (1)
15
Maize (13)
Potatoes (4)
10
Forage grass (4)
5
0
Figure 7. Yield increase attributed to non-trafficked compared with conventionally trafficked soils
(number of research reports from which data derived) (from Chamen, 2011)
Fertiliser Demand
A decreased spreading of roots in compacted soils can result in less access to nutrients (Miransari et
al. 2009, Wolkowski, 1990). Microbial processes occurring in compacted, waterlogged soils can also
dramatically reduce the amount of nitrogen available to plants (Boone and Veen, 1994). Douglas and
Crawford (1993) demonstrated the combined implications of soil compaction and applied N on crop
production in Scotland. This is also illustrated in Figure 8 which shows that more nitrogen is
required to obtain the same crop yield in compacted than in non-compacted soils.
Wolkowski (1990) found large differences in the uptake of nutrients by crops induced by
compaction. The loss of nitrogen through denitrification tended to increase with reduced tillage and
was exacerbated by compaction that caused anaerobic conditions when soils are moist. Phosphorus
uptake in fertilised soil ranged from 100% in a non-compacted control with a bulk density of 1.4 Mg
m-3 to 62% in a compacted soil with a bulk density of 1.7 Mg m-3. Decreased rooting induced by
compaction caused this drop in uptake. If compaction causes a significant reduction in aeration,
nitrogen availability may decrease because of denitrification while potassium uptake may be
constrained if respiration within the root is reduced.
15
Figure 8.The relationship between the amount of N applied and crop yield under different
compaction regimes. A compacted soil (i.e. 1.55 Mg m-3) may require more N to obtain similar yield
to a non-compacted soil (i.e. 1.30 Mg m-3). From (Soane & van Ouwerkerk 1995).
Cultivation Energy
Energy levels for cultivation differ widely between soil types and with soil moisture content for a
given soil type. Soil related differences are illustrated in the work of Patterson et al. (1980) who
produced data for cereal crop establishment over a number of years from three different soils, the
principal components of which are listed in Table 2 together with energy requirements per unit
volume of soil moved.
Table 2. Soil descriptions and cultivation energy requirements for cereal crop establishment of the
three soils used by Patterson et al. (1980).
Description
Soil series
Parent material
Soil texture
Particle size distribution
Sand
Silt
Clay
Carbonate
Organic
Cultivation energy requirements
Depth of work, mm
Energy, kJ m-3
Site 1
Hanslope
Chalky boulder clay
clay loam
Site 2
Batcombe
Plateau drift
silty loam
Site 3
Wicken
Gault
clay loam
25.0
25.1
45.9
19.1
5.5
12.1
51.4
28.5
3.3
1.8
27.2
21.4
51.4
9.8
3.9
220
117
130
103
110
108
220 145 105 205 130 105
56 75 74 146 108 122
In terms of soil type related compaction effects on these soils, some data can be elicited from
penetration resistance measured by a range of authors (Abu-Hamdeh, 2003; Blackwell et al., 1985;
Braunack et al., 2006; Canarache et al., 1984; Chamen & Audsley, 1983; Chamen et al., 1990;
Chamen et al., 1990; Hansen, 1996; Jorajuria et al., 1997; Pagliai, 2003; Pangnakorn et al., 2003;
Radford & Yule, 2003; Stenitzer & Murer, 2003; Steward & Vyn, 1994; Yavuzcan, 2000; Zhang, 2006).
Figure 9 shows the range of increase in penetration resistance on trafficked compared with non16
trafficked soils based on data from these papers. Considering these in relation to those in Table 2,
although clays have the greatest energy requirement for cultivation, the percentage increase in
strength (penetration resistance) with compaction on these soils appears to be the least. It also
appears that there is no obvious direct relationship between penetration resistance and cultivation
energy requirement.
Lamers et al. (1986) working in the Netherlands on loam and clay soils reported a 25% reduction in
draught in the absence of compaction. Dickson & Campbell (1990) compared conventional and zero
traffic systems over a period of four years on a clay loam in Scotland. They found that for both direct
drilling and ploughing, conventional traffic increased draught forces by 17%. Dickson & Ritchie
(1996a) comparing conventional and zero traffic systems for a rotation of spring barley, spring
oilseed rape and potatoes for five years on a gley soil in Scotland, measured substantial differences
in draught forces and power requirements. Nominal depth of cultivation for all treatments was 25
cm, but for the cereal crops with zero traffic, this was reduced to 20 cm. The conventional system on
average required 92% more draught than zero traffic and 82% and 90% more power for primary and
secondary tillage respectively. Tullberg (2003) concluded that approximately half the total power
output of a conventional tractor used in a random traffic system can be dissipated in the process of
compaction and de-compaction of its own wheel tracks. In contrast, draught differences in dry
conditions were not detectable.
Figure 9. The effect of soil type on the increase in penetration resistance on trafficked compared
with non-trafficked soil
Chamen et al. (1990, 1992a) working on an Evesham series clay soil in England and comparing
conventional and zero traffic reported a 60% reduction in draught and energy for shallow ploughing
(10 cm) and a 20% reduction in draught for conventional ploughing (20 cm), both in the absence of
traffic. Also recorded was an 84% reduction in the energy needed to establish wheat, both as a result
of changing from traffic to no traffic and shallow tillage to no tillage and without loss in yield.
Chamen et al. (1992b) in summarising coordinated projects on the effects of different traffic systems
across northern Europe in the early 1980s reported that zero traffic reduced energy demands within
cereal rotations by 29–87%. Following a longer period without traffic on the Evesham soil, Chamen &
17
Longstaff (1995) reported a 37% reduction in draught when ploughing 20 cm deep. However, they
also reported one instance when the draught requirement for shallow tillage was higher on the nontrafficked compared with the trafficked plots. This was with a tine cultivator and may possibly be
explained by fundamentally different processes in soil failure. On the non-trafficked soil the
implement was working in a moist fine tilth where the tines were causing a stirring action, whereas
on the trafficked soil, the operation was dominated by fracture of aggregates from within the soil
mass. Mouazen (2002) provided a possible explanation for this, albeit in a sandy loam rather than a
clay soil. Cohesion was found to increase in loose soil when the samples underwent contraction due
to shearing forces and conditions in the friable clay may have been similar. Working deeper in the
profile on the same soil, Chamen and Cavalli (1994) reported an 18% reduction in the draught of a
mole plough working at 0.55 m depth on plots non-trafficked for four years compared with
conventionally trafficked plots.
As controlled traffic practitioners, Boydell & Boydell (2003) report savings in power during their soil
cultivation operations and suggest the possibility of downsizing their tractors. Spoor (1997) on a
similar energy theme shows just how much extra pull is needed when hauling trailers across
differently managed land. Compared with conventional practice, he found working from a
permanent traffic lane reduced rolling resistance by between 24% and 30% depending on soil type.
Literature on the specific effect of soil compaction on the wear of soil engaging implements is
scarce. In randomly compacted soils it is generally accepted that “points” behind implement or
tractor wheels wear out more rapidly. This was confirmed by Owsiak (1999) who observed that the
wear of spring tine points was 40–100% higher in sandy loam soil compared with clay soil, and that
wear within a tractor wheel track was 17–40% higher than outside the track. Fielke et al. (1993)
reported 55-73% reduction in wear rate when bulk density had been reduced by a previous pass but
also by 40-50% just due to a change in bulk density from one year to the next. Richardson (1967)
also suggests that wear on a particular implement is subject to the strength of the soil causing
abrasion.
Water
Compaction can cause a combined impact of decreased water storage, through the loss of soil
porosity, and decreased root proliferation, through an increase in soil strength (Whitmore et al.,
2010). This has potential implications to how efficiently farming operations use water and the
demands for irrigation. Radford (2001a) compared the water use efficiency (WUE, yield per unit of
evapotranspiration) of maize in a vertisol compacted by either a 6 Mg or 10 Mg axle load. The
greater axle load decreased WUE from 14.3 to 9.7 kg ha-1 compared to the smaller axle load.
Chamen (2011) reviewed numerous articles on the impact of soil compaction on WUE and
infiltration rates. Infiltration increased by 84% to 400% in the absence of wheel compaction, with
increased plant available water also found. In wet conditions, compaction mitigation or avoidance
could decrease the risk of flooding, whereas in dry conditions it could decrease the risk of drought.
Drought is influenced by both the ability of soil to capture water (infiltration rate) and store water in
its pores (plant available water). With subsoil compaction caused by 4 to 5 Mg machinery, hydraulic
conductivity at 0.4-0.5 m depth can decrease by as much as 98% in clays, loams and organic soils.
For a sandy loam soil the subsoil compacts under much smaller loads.
18
Much of the available data, however, was from drier climates. There are some data available for
England and Wales that can provide indicative information for the development of costs curves for
soil compaction mitigation. Processes such as subsoiling to increase infiltration rates, for instance,
could potentially have very large off-site benefits in terms of flood risk reduction. However,
quantification of this is difficult and the literature is largely qualitative and/or anecdotal.
Environmental Costs
Figure
10
illustrates
various
environmental costs associated with soil
compaction. Although a tractor is shown,
the illustration is also appropriate for
grazing systems, and the major drivers
that induce environmental costs are
reviewed below.
Greenhouse Gases
Nitrogen can be lost as N2O emissions,
with this greenhouse gas presenting a
significant environmental cost. There are
Figure 10. A conceptual diagram from Soane & van
Ouwerkerk 1995; and Lipiec et al. 2003 that shows the
numerous papers that report the effect
various implications of soil compaction to the
of soil compaction on nitrous oxide (N2O)
environment. This diagram omits the potential negative emissions (Sitaula et al., 2000; Ball et al.,
implications to crop productivity.
1999a, 1999b, 2008; Vermeulen &
Mosquera, 2009, Hansen et al., 2008).
Poor aeration in compacted soils was identified in all these studies as the underlying cause of
increased emissions. Dobbie and Smith (2003) determined that the key factors affecting N2O
emissions from agricultural soils were water filled pore space, temperature and
NO3—_N content. Milne et al. (2011) using a landscape-scale transect in Eastern England also found
that nitrate and water-filled pore space are the key soil properties for predicting nitrous oxide
emissions, but only at this and not on a field scale. In one study comparing soil normally trafficked
by vehicles to another that was non-trafficked soil, Vermeulen and Mosquera (2009) measured a 2050% decrease in N2O emissions in the absence of traffic suggesting that specific soil management
inputs that have the potential to affect water-filled pore space may have an impact at the field scale.
Soil Biodiveristy
In a review on the impact of soil compaction on biodiversity, Beylich et al. (2010) concluded that,
“due to the high variability of experimental situations and conditions in the evaluated papers,
especially in papers describing field investigations, no general effect of soil compaction (on soil biota
and biological processes) was found”. Moreover, putting an economic value on soil biodiversity
could be highly subjective and not based on a thorough understanding of the function of the
plethora of microbial species living in soil. Soil biodiversity will therefore not be considered in our
analysis.
19
Grazing Systems
Although in the review above, aspects of grazing systems are covered in the costs of soil compaction
to production and the environment, there are aspects of the damage to soil caused by livestock and
mitigation strategies that need to be dealt with separately to agricultural land under crops. There is
a paucity of information on this subject, particularly with regard to the production of cost curves,
and the few notes below are taken largely from Patto et al. (1978). It provides a concise summary of
the problem. The more recent DEFRA project from 2007 ‘Scoping study to assess soil compaction
affecting upland and lowland grassland in England and Wales’ carried out by Cranfield University
offers some remediation measures that have been included in the Solutions section below.
Definition: Poaching is the penetration of the soil surface by the hooves of grazing animals,
causing damage to the sward and deformation of the soil (Patto
et al., 1978) (Fig. 11).
Causes and Susceptibility: Poaching (compaction and plastic
deformation) results from the complex interaction between a
number of factors including:
 The type and number of grazing animals
 The climate, principally the frequency, duration and
intensity of rainfall and evaporation
 The plant cover and grass species
 The soil strength, controlled by texture, structure, pore
space and hydraulic conductivity
 Interactions between these, principally the role of plants
in determining soil strength and soil/climate interactions
in determining soil water content
Fig. 11 Example of poaching,
Damage is primarily restricted to the upper surface layer (0-10
exacerbated by cattle
cm; MAFF, 1970; Scholefield et al., 1985; Greenwood et al.,
running down the slope
1997) and in this respect differs from compaction resulting from
vehicle passes which often extends into the subsoil which is then much more difficult to rectify. This
is an important difference when assessing damage to soil quality and the measures and their costs
required to rectify the damage. In essence, poaching is caused by the co-incidence of an
inappropriate number of animals grazing a sward at a time when the soil is in a condition that
cannot sustain that number.
All soils are susceptible to poaching although Patto et al. (1978) identified the spring and autumn
periods where the probability was highest; these are the periods when the soil is either drying from
or wetting to field capacity and when farmers might be more likely to try and get a few days extra
outdoor grazing.
Incidence
Recent work (Final report DEFRA project BD2304 ‘Scoping study to assess soil compaction affecting
upland and lowland grassland in England and Wales’) has recognised the dearth of information on
the occurrence of soil compaction generally, and in particular, that caused by grazing animals. To
quote: ‘Available data on the severity of soil compaction is extremely scarce’; ‘Surprisingly little is
20
known about the extent and severity of soil compaction and its impacts on the vital functions
(ecosystem services) supported by soil’.
To fill, partially at least, this knowledge gap, there have been two mapping exercises to identify i) the
susceptibility to poaching (Patto et al. 1978) and ii) the risk of poaching (Final report DEFRA project
BD2304, 2007). The earlier study identified three classes: high, variable and low. The classes were
based on the assessed hydraulic conductivity of different soils and average annual rainfall in
different parts of England and Wales. The entire rural land mass was assessed, irrespective of
whether the land use was intensive grazing or not. Approximately half was assessed as having
variable susceptibility with the other two classes making up about a quarter each. There were
marked regional variations between the drier parts of eastern England and the wetter and cooler
areas such as the NW and Wales.
The more recent study benefited from the advent of GIS and database technology and focussed on
those areas where the agricultural land use was more than 40% grassland. It also integrated the
inherent vulnerability of different soils with actual stocking densities to achieve a qualitative risk
assessment of soil compaction. Most grassland areas were assessed as having a moderate or high
risk of poaching with very little in the low class. There were some interesting contrasts with the
earlier study, for example, much of Wales was classified as having a variable susceptibility to
poaching in the 1978 study whereas in 2007, the same area was assessed as having a low
vulnerability. Even with the high stocking rates, the risk was assessed as medium.
A very limited amount of ground truthing was carried out and showed that in broad terms the data
indicate a correlation between vulnerability and actual degradation insofar as low vulnerability soils
were found to have predominantly low levels of actual degradation and, conversely, high
vulnerability soils were linked to the highest proportion of high degradation sites. However the
authors stress caution insofar that the lack of information on the nature and intensity of
management systems and grazing at the actual sites visited is a source of uncertainty that limits the
scope for analysis of the survey results.
Mitigation, Confinement and Avoidance
Soil compaction mitigation strategies incur cost due to the direct costs of, for example, subsoiling,
investment in new equipment, decreasing or altering the timing of traffic of equipment or livestock,
changes in cropping/grazing system and a range of other possible practices. There is a strong
influence of soil type on the incurred costs, but data are sparse or only possible to generate using
empirical models. One example is the fuel use required to subsoil on different soils.
Complete shifts in production approaches may also be employed to alleviate or avoid soil
compaction.
Low ground pressure tyres are now commonplace on arable farms, enabling
machinery access over a wider range of weather conditions. Alleged decreases in topsoil
compaction from low ground pressure tyres, however, may be offset by the greater threat of subsoil
compaction from higher loads and as farmers can access land during wetter conditions. Already,
large shifts towards GPS auto-steered machinery could have very positive implications but the return
on investment for smaller farms is still poor. Decision support tools can also advise livestock farmers
about controlling field access or building mitigation strategies into areas with high intensity traffic.
21
Low Ground Pressure Tyres
Low ground pressure is an avoidance measure aimed at reducing the stresses applied to soils.
As will have been elicited from the research, this measure is only effective for topsoils in the case of
tyres and possibly only for subsoils in the case of tracked vehicles (Ansorge & Godwin, 2007 and
2008).
In the 1980s, Chamen et al. (1990) compared a low ground pressure (LGP) system with conventional
practice and with a “zero” traffic regime. The LGP system employed tyres inflated to around one
third of the pressure of conventional practice (50 kPa to 80 kPa) but after four years there was no
conclusive evidence that the lower pressures had either increased yields or reduced tillage inputs. In
contrast, Graham et al. (1986) recorded a 6-7% increase in wheat yield due to low ground pressure
traffic compared with conventional and zero traffic on a silt loam soil. In more extensive trials some
time later Chamen et al., (1992) using reduced ground pressure systems, also recorded a 3%
increase in yield but the systems were only considered practicable for wheel loads of up to 5 Mg.
Additionally, there was a small increase in shallow tillage (100 mm) draught caused (it was
presumed) by the more extensive area tracked by the low ground pressure system. Dickson and
Ritchie (1998) measured the yields of winter and spring barley, spring oilseed rape and potatoes in
the presence of reduced ground pressure traffic where tyre inflation pressures ranged from 30 kPa
to 120 kPa. Compared with conventional practice with pressures ranging from 80 kPa to 250 kPa,
there was no measurable difference in yields from these crops under the low pressure system.
Pagliai (2003) compared rubber tracks with tyres using modest loads (c. 1 Mg) and concluded that
the tracks tended to confine compaction to the surface layers as did Blunden et al. (1994). Ansorge
and Godwin (2007) working with much higher loads (12 Mg) came to a similar conclusion.
There has also been research and debate on the relationship between ground pressure, wheel or
track load and the attenuation of stresses with depth. Lamandé and Schjønning’s recent research
(2011a) supports that of Söhne (1953) suggesting that stresses in the topsoil rise with contact
pressures whereas those at depth increase with load. For example, they found that the maximum
stress at 0.3 m depth in a silty clay loam (Stagnic Luvisol, FAO, 1988) was related to the mean ground
pressure, while the stress at 0.9 m depth closely correlated with wheel load. Disparities in measured
and predicted stresses according to the Söhne (1953) model were considered to be due to
differences in strength of the frequently tilled topsoil, suggesting soils of this nature may have to be
treated as a two-layer system. In this respect, Lamandé and Schjønning (2011b) measured the
effects of loosening the topsoil to around 200 mm depth by ploughing. This led to a more even stress
distribution at the tyre-soil interface but little attenuation of the peak stresses to 0.3 m depth.
However, the Söhne model tended to underestimate stresses in the subsoil for both the recently
ploughed condition and the soil which had not been cultivated for 18 months. This research does not
stand in isolation; it is supported by the work of Smith & Dickson (1990), Taylor & Burt (1987),
Lamandé et al. (2007) and Arvidsson & Keller (2007) and as such has significant implications in terms
of mitigation measures.
In terms of root crop responses to a low ground pressure system in which maximum tyre inflation
pressures did not exceed 80 kPa (40 kPa in the spring), Vermeulen and Klooster (1992) found that it
provided around a 4% increase and was about half the potential of zero traffic.
22
Vermeulen & Perdok (1994) suggested that a low ground pressure system used with a high
proportion of sugar beet, potatoes and onions, returned only a marginal improvement in farm profit
compared with conventional practice. As this improvement was largely associated with increased
yields, they considered that profitability would be more satisfactory in vegetable production owing
to the higher value of the produce. Eradat Oskoui et al. (1994) determined from a survey that the
cost of tyres was exponentially related to their width and based on yield responses, that farms of
around 200 ha or more were needed to justify their cost. Stranks (2006) provides more information
on the effect of reduced inflation pressure on rolling resistance, rut depth and depth to which
compaction occurs. His studies suggested a significant reduction in rolling resistance and fuel use as
a result of using lower pressure tyres. For a multi-axle machine, fuel cost per hectare could be halved
by increasing tyre size from 700 mm to 800 mm with a reduction in inflation pressure from 220 kPa
to 160 kPa.
The effectiveness and cost of different compaction mitigation measures
Subsoiling
Definition of subsoil
Traditionally the subsoil is often defined as the depth at which there is a transition in soil texture and
frequently colour, denoting both a change in organic matter content as well as the proportions of
different minerals. In a more recent definition Alakukku et al. (2003) suggest this is not so much
defined by a change in texture, rather that it is closely associated with tillage and traffic. In their
paper on prevention strategies for traffic-induced subsoil compaction, Alakukku et al. (2003) divided
the subsoil into two distinct layers, namely:
Pan layer. This is a layer of varying thickness immediately below the annually cultivated layer created
either by implements or wheels, or both. It may or may not be loosened on a regular basis.
Unloosened subsoil. This is the layer that normally remains undisturbed by tillage other than during
drainage operations such as trenching and mole ploughing. Loosening of this layer is often
considered to be undesirable due to its potential to make the soil more vulnerable to further
compaction. In many cases it would also be uneconomic due to the high forces and costs involved.
It may be seen therefore that the deeper the cultivations traditionally carried out, the greater must
be the depth of subsoiling to address a problem with the pan layer, particularly if tractors are driving
in the furrow during ploughing.
Extent and effectiveness of subsoiling as a mitigation measure
According to an ADAS survey (ADAS, 1996) to determine the nature of cultivation practices in
England, nearly 90% of the 868 analysed respondents subsoiled their land with a frequency of
between 1 and 6 years with a trimmed mean of 4 years. Of those that did subsoil, the lowest
percentages were those on loams (72%) and any soil containing chalk (68%). Most subsoiled the
whole field and the majority (76%) at depths of between 310 and 500 mm.
Marks & Soane (1987) assessed crop yield responses to subsoil loosening on a wide range of soils
including sands, loams and silty clay loams but not clays. Soil loosening to 450 mm depth was of a
rigorous nature with virtually complete loosening of the profile to operating depth. Most responses
were confined to spring sown crops and at the 25 sites assessed in this category, six showed a
23
positive response in the range 1.5% to 9.4% but four resulted in a negative response in the range
5.7% to 11.7%. Of the 17 winter crop sites, none provided a positive response while four resulted in
decreased yields (5.8 – 15.1%). Crucially no mention is made of post loosening operations that would
allow estimation of the re-compaction effect prior to crop sowing. Chamen (2011) similarly found no
response from winter wheat on a sandy loam soil despite no further traffic following loosening to
around 350 mm depth. This was also the case on a clay soil except yields were reduced compared
with a long term non-trafficked condition. In terms of soil conditions, responses at both sites were
generally beneficial, with reduced soil strength and increased water infiltration as a result of deep
loosening, but only with no subsequent traffic. On the sandy loam site, just two tractor passes were
sufficient to return the soil to a stronger state than its original condition.
Olesen & Munkholm (2007) assessed the effect of subsoiling on a loamy sand and sandy loam in an
organic farming rotation including a grass-clover mix, wheat, lupin and barley. Other than where
organic manure was added post subsoiling, yield responses were often negative and particularly so
for wheat following a wet winter. The authors suggested that subsoil loosening was not an effective
measure for ameliorating subsoil compaction.
Recognising the lack of effectiveness of these rigorous subsoiling operations, Spoor et al. (2003)
recommended creating fissures or cracks through compacted zones to restore rooting and drainage,
rather than massive disruption, which they considered most inappropriate. Subsoiling should be a
case of “fissuring without loosening” to allow the bearing capacity of the soil to be maintained. It
was also recommended that this operation, which would use conventional but judiciously set
equipment, should be carried out as late as possible in any sequence of field operations. Not only
would this minimise the traffic running over the soil immediately after loosening, it would also allow
the longest period for soil settlement and stabilization, preferably in the presence of a vigorously
rooting crop.
Chamen (2011) demonstrated that subsoiling without further traffic enhanced infiltration on both a
sandy loam and a clay soil, and on the clay, by a factor of 1.7. Allen & Musick (2001) reported a
similar effect on infiltration in irrigated furrows, which was increased by around 28% due to
subsoiling, but this was reduced to no net effect by subsequent traffic. Said (2003) investigating
various tillage tools on sandy loam, sandy clay loam and clay loam soils determined that a subsoiler
increased total porosity and macropores as well as the vertical flow of water in the profile. It would
appear therefore that subsoil loosening can be beneficial but only when extreme care is exercised.
Firstly to avoid preferential flow (and therefore sediment transport) and secondly with subsequent
traffic to avoid recompaction.
Cost of subsoiling
Nix (2010) suggests that the average farmer’s cost for subsoiling is £49 ha-1 while contractor’s
charges average £56.10 ha-1. As will be seen from the above definition, this cost will vary significantly
depending on the depth of operation. Manuwa (2009) determined that tillage draught increased
exponentially with depth according to an equation of the following form:
D = aebd
(1)
where a and b are coefficients of the exponential function. Specific coefficients determined by
Manuwa (2009) for a sandy clay loam soil at 11.5% moisture content in a soil bin were:
24
D = 82.991e0.0091d
(2)
for a 50 mm wide flat plate at a rake angle of 90 degrees travelling at 2.5 m s-1.
Mouazen et al. (2006) further developing their model described in Mouazen et al. (2003) considered
that the draught force (D) on a simple deep loosening tine could be predicted from soil bulk density
(ƿ), moisture content (w) and depth (d). Rearranging their equation in terms of draught force gives
the following relationship:
D = 3.16ƿ3 -21.36w + 73.93d2
(3)
From these data it can be seen that draught forces are dominated by depth of operation and soil
bulk density, with both having an exponential effect on force as they increase. Increase in moisture
content however has the opposite effect but too high a level endangers the effectiveness of tillage
aimed at deep loosening (Spoor & Godwin, 1978).
Auto-drive GNSS farming machinery
In a given year, 95% of an agricultural field can experience at least one wheel pass (Kroulik et al.
2009). Using a one pass cultivation system, such as minimum tillage with auto-steer, the amount
can reduce to 45% and to less than 20% if direct drilling is used.
Use of lighter machines
Using lighter machines has often been proposed as a mitigation measure for soil over-compaction.
However, research is not fully supportive of the effectiveness of using lighter vehicles. Jorajuria et al.
(1997) compared two tractors having an equal contact pressure but one with a mass of 4.2 Mg and
the other just 2.3 Mg. For a given number of passes, the heavier tractor always produced greater
increases in bulk density, but the lighter tractor was capable of causing just as much compaction
with additional passes. Voorhees et al. (1986) drew a similar conclusion about the load on a wheel
and went on to suggest that its damaging effects may not be mediated by decreasing surface
pressures or even over-winter freezing to a depth of 70 cm. Botta et al. (2006) also found that
multiple passes with a lighter tractor (1 Mg maximum wheel load) had serious consequences in
direct drilled topsoil, rendering it unsuitable for seedling emergence. With 10 – 12 passes of this
tractor, compaction effects (increases in penetration resistance and bulk density) reached to 600
mm depth in the same profile.
Present day economics and labour availability are also against using smaller machines, other than
those that might be achieved with robotics that might use very light machines working slowly but
without direct labour constraints..
Organic matter sequestration
There are numerous data to support the premise that adding organic matter to soils helps to protect
them from compaction. Diaz-Zorita & Grosso (2000) for example found that the susceptibility of
soils to compaction was reduced when organic carbon levels were elevated, regardless of soil
textural class in the range loamy sand and loam to silty loam. Kumar et al. (2009) came to a similar
conclusion for both sands and clays suggesting that there is a different level of organic matter in
these soils that could achieve a target maximum bulk density.
25
The effectiveness of different methods of adding organic matter is however either very variable or
unproven. Powlson et al. (2011) for example seem to dispel the widely held assumption that straw
incorporation will improve organic matter levels, at least in terms of timescales of anything less than
ten years. Similarly, Powlson et al. (2012) identified potential increases in nitrous oxide emissions as
a result of reduced tillage. The use of green manures or cover crops to increase soil organic carbon
has similarly not been proven or perhaps well researched, but Cuttle et al. (2003) conclude that
turnover of young organic matter is vital for optimal aggregate stability. Azeez (2009) concludes that
organic farming, which regularly uses green manures, has the potential to increase soil organic
carbon by 28% in Northern Europe and by 20% globally. Although this sequestration is finite, the
author argues that the next 20 years are the critical period when this sequestration will be required.
An added benefit of increased organic matter in soils is the greater availability of nutrients released
through bacterial and other processes. In many cases this has led to a reduction in the use of the
three principal nutrients, N, P & K (Cuttle et al., 2003).
Controlled Traffic
This technique confines all traffic compaction to the least possible area of permanent traffic lanes.
This definition prescribes neither the tillage to be employed nor the area of the traffic lanes, which
are decided by the practitioner and the constraints under which they are operating. However, these
aspects impinge heavily on the economics which will be determined by:



the cost and timescale of conversion to CTF;
the running costs of the CTF system;
the return in terms of sustained crop yields.
Taking the last of these factors first, crop income will depend upon:


yield from the non-trafficked beds;
yield from the cropped traffic lanes.
Work by Chamen & Audsley (1993) considered all these aspects other than the cost and timescale
for conversion to CTF. In their definitive study of a rotation of wheat, barley, beans and oilseed rape
(OSR) using the Silsoe Arable Farm model (Audsley, 1981), detailed account was taken of the rates of
work, timeliness of operations, energy inputs and the transmission efficiencies of the different
machinery involved, including both conventional and gantry tractors. The 6 m tractor-based nonplough CTF system (with extra costs of £57 ha-1 for chemical weed control) was found to be £18 ha-1
less profitable than conventional plough-based practice on medium soil, but £25 ha-1 more
profitable than the same comparison on heavy soil. Gaffney & Wilson (2003) in their comprehensive
desk-top study used a steady state analysis technique to calculate long-term average costs and
returns for four different systems based on a five-year rotation in Australia. They included some of
the implementation costs and considered reductions in field efficiency for the CTF systems as well as
testing yield effects and input savings. Their cautious estimate of the benefit of changing to CTF
based on a 3 m track gauge for all equipment was AU$32 ha-1 (£19 ha-1 at March 2011 prices).
Kingwell & Fuchsbichler (2011) carried out a similar but whole-farm modelling approach to assess
the profitability and role of CTF based on a 2000 ha dryland farm in Western Australia. However,
results are very specific to the regional cropping systems, which contain a high element of pasture to
26
support sheep within what is otherwise a combinable cropping scenario. The model also divides
crop responses to CTF according to soil types, with averages of +5% for sandy soils, +7% for duplex
soils (loams over clays) and +9% for clays. Figure 12 shows that mean values of data collected from
around the world (Chamen, 2011) do not wholly support these averages so some closer analysis will
be needed if they are to be applied to conditions in England and Wales. In their work, Kingwell &
Fuchsbichler (2011) found that CTF increased the profitability on a light soil farm by 53% and by 43%
on a heavy soil farm. Although the greater profitability of CTF for cropping shifted the whole farm
into this rotation, constraining cropping to 1571 ha as for the non-CTF farm only reduced profit by
1.8%. Much of the additional profit with CTF was due to yield improvements and cost savings. To a
large extent the reduction in operating costs was associated with overlap savings brought about by
the adoption of a ±2 cm GNSS compared with physical markers. Casual labour costs were also
reduced by around 17% during harvesting operations because the auto-steer system allowed
cheaper labour to be hired. These results are almost certainly an over-estimate of the increase in
profitability but the authors reduced the advantages of CTF by 50% and still realised an increase in
profitability of 23%. There are also a number of key points that this study did not address. Firstly it
appears that yield benefits were not corrected for the non-cropped traffic lanes which are a feature
of Australian CTF systems. Secondly, although mention was made of reduced draught of implements
due to CTF, this doesn’t seem to have been included in the modelling. Thirdly, overlap savings have
all been attributed to CTF whereas most of these gains are possible with less expensive GNSS
systems that should now be part of best practice. In our analyses, all these factors will be taken into
account.
Figure 12. Percentage reduction in crop yields due to conventional traffic on different soil types (left
columns, combinable crop responses, right column, root crop responses on loam soils)
Interestingly, the authors consider in detail the constraints to CTF adoption because of the relatively
slow uptake of a technology that would appear to deliver such large and tangible benefits. Those
which might apply in England and Wales include the high entry cost and the fact that there are often
long intervals between machinery replacements on farms and the relative complexity of ensuring
proper matching of axle and implement widths. The cost factor is less likely to be an issue in
European conditions because harvester and tractor axle widths are not generally matched (Stewart
27
et al., 1998). The added costs are therefore mostly associated with the auto-steer systems, which
can generally be justified outside of a move to CTF. A further factor is an inability to trial CTF
alongside traditional practice without committing to complete conversion. Without such detailed
comparisons, it is difficult for the farmer to discern whether the modest yield benefits are actually
attributable to CTF (Galambosova et al., 2010). Credible and reliable sources of information on CTF
may also be an impediment as is the complexity of GNSS which suffer from an incompatibility
between providers.
Grazing: Stocking Rates and Timing
Solutions
Catto et al (1978) identified the installation of soil drainage schemes as a possible intervention to
reduce or minimise soil poaching. This reflects the time of the study and remains a potential
mitigation measure, if an unlikely one within today’s economic constraints.
The more recent work (DEFRA 2007) identified a number of potential mitigation options within a
range of different support schemes available at the time (Table 3). These are listed below:
Table 3. Potential mitigation strategies for soil compaction from grazing systems (DEFRA, 2007)
Scheme Code
Option Type
Ancient trees in intensively
managed grass field
Crop establishment by direct drilling
(non-rotational)
Maintaining high water levels to
protect archaeology
Influence
Restricted access to trees reduces
soil compaction
Reduced impact of machinery use
in wet weather
HLS
HC6
HLS
HD6
HLS
HD8
HLS
HJ3, HJ4 Arable reversion to grassland
Preventing erosion or run-off from
HJ6
intensively managed improved
Seasonal livestock removal on
HJ7
grassland with no input restrictions
EB1-EB3
OB1-OB3
HB12
Hedge management
EE4-EE6
OE4-OE6
Restricted vehicle access along
HE4-HE6 Buffer strips in intensive grasslands boundaries
HLS
HLS
ELS
OELS
HLS
ELS
OELS
HLS
ELS
OELS
HLS
ELS
OELS
HLS
ELS
OELS
HLS
ELS
OELS
HLS
EJ1, EM1
OJ1, OM1
HJ1, HM1
EK1
OK1
HK1
EK2, EK3
OK2, OK3
HK2, HK3
EK5
OK5
Restricted access reduces poaching
Reduced soil compaction, erosion
and run-off
Reduced soil compaction, erosion
and run-off
Restricted livestock access reduces
poaching
Reduced cutting frequency and
therefore vehicle movement along
hedgerow
Soil protection
Reduced soil compaction, erosion
and run-off
Take field corners out of
management
Reduced machinery activity (agrochemical application, cultivation)
Permanent grasslands with (very)
low inputs
Reduced machinery activity (agrochemical application, cultivation)
Mixed stocking
Reduced poaching
28
The DEFRA 2007 report also identified potential remediation measures that could be incorporated
into DEFRA’s Environmental Stewardship scheme. These are, extracted directly from the report:
Match machine operations to the nature and condition of the soil: This is a major management tool
for preventing soil compaction and reducing unnecessary traffic especially on wet soils, for example,
by using umbilical systems to spread slurry in spring (Van den Akker & Schjønning, 2004).
Adjust tyres, inflation pressures and loads: Soil stresses in the subsoil can be decreased by
decreasing tyre inflation pressures, wheel loads and rut depths and by using wider, larger and more
flexible tyres. For sustainable soil management only field traffic with wheel loads lower than the
carrying capacity of the subsoil can be allowed (Van den Akker & Schjønning, 2004)
Loosening of soil: Moderate compaction of surface layers may be eliminated by shallow loosening of
the soil when the soil is dry enough. More severe cases may require ploughing and re-seeding. The
use of slotting to improve grassland soil conditions and yield on shallow soil compaction has been
shown to work well by Davies et al. (1989). However, Douglas et al. (1995) suggest that slotting may
be less effective on grassland where compaction extends throughout the depth of the topsoil.
Guidelines to prevent compaction occurring: It is difficult to generalise about dates for operations
or specific stocking rates, therefore, the best approach to guidance should be similar to “if the
tractor wheel or hoof sinks by more than x cm on average, then stop the operation” – such
guidelines would obviously need a period of development, but the principle of leaving an informed
decision to the operator rather than trying to set a list of general prescriptions is likely to be the best
approach. An example of this is that schemes currently require some operations such as hay making
to be conducted each year for a certain level of grazing. However in a year like 2007 which was
wetter than average, the manager should have the option not to follow the prescription on the basis
of potential damage to soil, without risking a penalty.
Maintenance of good surface drainage: One of the most effective measures to increase soil strength
is by improving drainage. Improving soil drainage will both reduce the risk of compaction and extend
the time frame over which the land can be used as pasture or driven on. This can be as simple as
clearing out ditches or installing subsurface drainage. In heavier clay loam soils shallow moling below
the depth of compaction may be possible. The current HLS guidelines appear to discourage drainage
work, (HK6 stipulates “no new drainage”) but maintenance of good surface drainage infrastructure is
also important in many ways for biodiversity. It should therefore be actively encouraged by the ES
schemes because it is also beneficial in terms of preventing compaction and therefore a win-win
situation. In the RASE study (RASE, 2012) 75% of the 17% respondents identifying drainage problems
had identified crop or livestock management challenges as a result and particularly those in the
North West, North East and East Midlands.
Biodiversity monitoring and responsive management: If an area of a field begins to lose its plant
diversity as a result of heavy trafficking, then a plan should be developed to limit the damage either
by reducing the traffic, or failing that to restrict it to a defined area.
Adaptive management where compaction has occurred: If soil wetness is being managed under an
HLS scheme, it would be necessary to offset the lowered hydraulic conductivity of the soil either
with closer-spaced grips or similar features or via tighter control of water levels in water courses
(particularly relevant to grazing marsh options).
29
Reduce or prevent treading damage: Suggested strategies for reducing or preventing treading
damage include: reducing treading intensity (Drewry, 2003; Drewry & Paton, 2000), excluding
animals (Greenwood et al., 1998; Stephenson & Veigel, 1987), removing animals for several
rotations and using the pasture for silage (Drewry & Paton, 2000), when soils are wet, the numbers
of livestock per unit area or the time spent on the field should be reduced, reducing stocking
densities by either increasing grassland area or reducing livestock numbers (Mulholland & Fullen,
1991). The use of slatted flooring for either indoor or outdoor use can be a means of removing sheep
from fields when soils become vulnerable. These raised flooring systems can accommodate between
0.7 and 0.9 sheep per square metre with a cost of around £45 per head for the flooring materials.
These systems make it easier to manage sheep during lambing and those using the system have
claimed higher stocking rates as a result of less over-winter soil damage and greater pasture
productivity in the spring.
Use of plant species: Plants with desirable rooting characteristics can enhance the structure of soils
(e.g. Macleod et al. (in press))
Use water management to encourage soil shrink-swelling leading to re-structuring: e.g. Spoor,
2000
Remediation of diffuse pollution from compacted grasslands: This can be tackled using 3
approaches: controlling sources, restricting pathways and/or protecting potential receptors.
We had hoped to use data from Defra project BD5001 that is investigating different mitigation
strategies to decrease the impact of compaction on grasslands. However, the first set of reports
from this project were not available as they were awaiting final edits from Defra before being
released.
Overview of Available Hard Data
We found a large amount of evidence on the threat posed by soil compaction and the effectiveness
of mitigation strategies. Climate, soil type and farm typology were large drivers of the threat of soil
compaction to farm gate income through losses in yield or grazing access. Mitigation strategies also
vary considerably in effectiveness depending on the extent and depth of compaction, climate and
soil type. To some extent top soils with adequate levels of organic matter have a natural resilience
to compaction whose repair takes several years, whereas subsoil compaction persists and causes a
long-term yield penalty. Sub-soiling was reviewed to be less effective than perceived by many
farmers other than when used on highly degraded soils or when no further traffic in anticipated
for an extended period. Force of habit is probably responsible for continuation of non-targetted
sub-soiling as a long-standing practice, with farmers unaware of its ineffectiveness and cost.
Environmental costs and benefits (in terms of changes to environmental loadings) of soil compaction
were more difficult to ascertain. No clear evidence of an impact on biodiversity could be found.
Greenhouse gas emissions are likely to increase as a result of soil compaction,
as are nutrient losses and run-off due to poor infiltration and decreased water holding capacity.
30
Industry and Farm Specific Economic Information
Introduction
The aim of the work reported in this section was to elicit as much information as possible from the
industry, (mostly farmers), to determine on-farm strategy and costs associated with soil compaction
mitigation, management or taking no action. To a large extent this involved visiting farms, most of
which were a cross-section of those who have or are converting to controlled traffic farming. These
farmers in particular are aware of soil compaction issues and therefore have a clearer picture than
most about its cost and inconvenience to them. Of these farms, those on the soils identified in Table
1 were targeted but where these were unavailable, contacts were established and visits made to
enable us to fill these gaps. Additionally, observations of farming practice in some regions were used
as an adjunct or alternative to more detailed information.
Table 5 lists the farms visited together with typology information (see also Appendix). Farm types
are based on those listed in Table 4 while “area” is the area of land predominantly under the farm’s
control.
Table 4. Land use and farm typologies targeted in the study
Farm type (and
crop)
Cereals (winter
wheat)
Location
Soil code and
dominant soil type
711r, typical
stagnogley soil
Extensive soil unit
in Eastern England
General
cropping
(potatoes)
Lincolnshire/Norfolk/Cambridgeshire
851a, clayey humic
alluvial gley soil
Cereals (spring
barley)
Hampshire/Yorkshire
Dairy (primarily
grass (75%),
remainder crops
and ley)
Grazing livestock
(Lowland)
(primarily
Cornwall/Devon/Wales
343h, brown
rendzinas over
chalk
Extensive unit in
Southern England,
local occurrences
elsewhere
including east
Yorkshire
541j typical brown
earths
Extensive in SW
England and Wales
541j typical brown
earths
Extensive in SW
Lincolnshire/ Norfolk
Cornwall/Devon/Wales
31
Main soil features
Sandy clay loam or clay
loam surface horizon,
subsoil becomes more
clayey with depth.
Poorly drained.
Silty clay topsoil, silty clay
or clay subsoil
Although classified as a
groundwater gley, the
water table is highly
managed through
pumping and ditchers and
drainage is classified as
well drained
Silty clay loam calcareous
topsoil (20cm) overlying
bedded chalk at 40 cms
Well drained
Clay loam topsoil
overlying clay loam
subsoil. Well drained
Clay loam topsoil
overlying clay loam
subsoil. Well drained
permanent grass
(85%))
Horticulture –
Onions
England and Wales
Farm identified – soil type and
coverage to be determined.
Compaction mitigation
Mitigation has the meaning of both alleviation and lessening. On the cross section of farms we
visited, alleviation generally consisted of deeper than normal tillage, sometimes with specialist
machines such as subsoilers, but also with conventional cultivators used at a greater depth.
Table 5. Farms visited together with enterprise type, location and soil features
Farm ID
Ll
Bd1
Ox1
Bd2
Gw
Ox2
Hu
Ha1
Ha2
Nf1
Su
So
Nf2
Ng
Farm type
Area, ha
Cereals WW
1085
General
950
cropping
Cereals WW
3300
Cereals WW
1175
Grazing/livestock
245
Cereals WW
500
General
850
cropping
Cereals WW
900
Cereals WW
1200
Cereals WW
240
Cereals WW
Grazing/livestock
Cereals WW
Cereals WW
760
1400
Location
Lincolnshire
Bedfordshire
Soil code
711r
541(A)
Main soil features
As in Table 7
Ditto
Oxfordshire
Bedfordshire
Gwynedd
Oxfordshire
Huntingdonshire
541j/616c
Ditto
Ditto
Ditto
Ditto
Ditto
Hampshire
Hampshire
Norfolk
Suffolk
Somerset
343h
343h
711r
711r
813e
851a
Ditto
Ditto
Ditto
Ditto
Stoneless mostly reddish
clayey affected by
groundwater. Flat land,
risk of flooding
Norfolk
711r
As in Table 7
Nottinghamshire 813b/572f Ditto
In terms of mitigation meaning “lessening” we learned of subtle measures as well as those more
commonly used. The latter included the lowering of pressures under vehicles through the use of
rubber tracks or by using specialist low ground pressure or high quality tyres. Rubber tracks were
stated by one farming company not to have the anticipated mitigation benefits and it is now looking
at other means. A subtle strategy was associated with livestock and involved removing animals from
the land at the onset of cooler and wetter conditions. Although this is commonly practised with
cattle, farmers are now finding benefits from bringing sheep onto open or covered yards at the
farmstead (http://www.stackyard.com/news/2008/03/jennifer/02_bateson.html). This change has
resulted in more grass in the spring for both grazing and silage, reflected also in quicker lamb growth
and a small increase in flock size. Winter feeding is easier with less machinery impact on the land.
Equally, lambing can be better managed and is less time consuming.
Increasing soil organic matter was another effective compaction alleviation measure brought about
by longer term grass leys (5 years plus). In these conditions, compaction by cattle was much less
noticeable, as were the tracks of machinery. However, where barley had been introduced for just
32
one year and grass was in the early stages of re-establishment, there was much greater evidence of
compaction.
Lessening of compaction has also resulted from the introduction of new technology in the form of
“all terrain vehicles” (ATVs). In the past, farmers often used tractors to inspect their livestock, with
consequential damage. The ATV is much lighter with relatively low pressure tyres thus reducing the
potential for damage.
A further subtle strategy lies in timing and better and more flexible equipment. Timing is all about
good management that has every machine and material in place for all operations on the farm well
ahead of when they are required. Having machines that perform as and when required relies on
good and timely maintenance as well as attention to detail. Good management releases more time
for field operations which can then be carried out in more favourable conditions.
All the farms visited undertook some compaction mitigation measures. These are outlined in Table 6
together with an indication of their cost or cost base and potential return on investment. Particularly
important in these calculations is the proportion of land on which these measures are taken. This
was not always easy to ascertain mostly because the proportion varied from year to year in response
to prevailing conditions.
One compaction mitigation measure which is perhaps overlooked is mouldboard ploughing.
Ploughing is undertaken for a variety of reasons one of which is to relieve compaction in the topsoil,
but only a proportion of the cost can be attributed to this and the return on this proportion of the
investment might be the generally higher level of yield achieved by plough-based systems (Patterson
et al., 1980). Contractor’s charges for ploughing range from £49 - £55 ha-1 and farmer’s costs from
£54 - £70 ha-1 (Nix, 2010) so an approximate 6% increase in yield of wheat for example, would be
needed to justify ploughing on a compaction mitigation basis.
33
Table 6. Compaction mitigation measures undertaken on the farms visited and estimated costs and returns (see also Appendix Table 1A)
Aspect
Machinery
Livestock
Action
Subsoiling
Cost
£56 ha-1 (Nix, 2010)
Subsoiling tramlines
£6 ha-1 based on 24 m tramlines
Deeper cultivations
Low ground pressure
tyres
D = 3.16ƿ3 -21.36w + 73.93d2 (see Milestone 3 report)
[Use Vermeulen & Perdok, 1994 guideline pressures to
estimate cost – 1.6-2.4 bar compared with 0.8 bar]
Rubber tracks
45% extra cost compared with wheeled tractor (Nix, 2010)
ATV in place of
tractor
Winter housing
£8000
Extended grass leys
Management Machinery
maintenance
Materials stocking
Maintain status quo
Building or yard infrastructure, manure disposal, drainage
installation
Cash crop foregone
Return on investment
Improved timeliness, reduced loss of soil and nutrients,
possible yield improvement
Improved ease and effectiveness of ploughing, no yield loss
in tramlines
Yield improvement, reduced loss of soil and nutrients
Determine typical LGP versus conventional system cost
versus 6% yield increase for spring crops (Vermeulen &
Perdok, 1994).
Less tracked area, greater pulling power, improved field
access
Improved labour efficiency, less loss of yield
Extra labour over winter
Improved productivity and stocking rate, potentially
improved nutrient uptake
Difference in cash crop foregone and extra concentrate
bought in
Improved timeliness and productivity
Interest on capital invested
Loss of yield, poor field access, loss of soil and nutrients
Improved timeliness and productivity
No investment but yield foregone
34
Costs and returns for mitigation measures
The farm visits and investigations have provided a reasonable overview of the measures many
farmers take to combat the effects of soil compaction and some costs were elicited from these visits.
However, as was recognised in the project proposal, there is a great deal of uncertainty as to their
national application. For this reason, the costs and indeed the returns will be assessed in more detail
based on the measures identified in Table 6.
Subsoiling
First, although no farms visited could place a monetary return against the cost of subsoiling,
anecdotal evidence, particularly from headlands, was that areas of water logging had been reduced
as a result of subsoiling and there was less visual evidence of poor crop growth. This is perhaps
where practice and research data diverge in that subsoiling trials will almost certainly not have been
placed on the equivalent of field headlands. Some credence must therefore be placed on grower
reports of poor winter and spring crop performance on these areas even though research failed to
identify any consistent yield improvement as a result of subsoiling. The practice of subsoiling is
firmly entrenched in the arable sector but the depth of operation has lessened compared with the
ADAS survey of 1996 (ADAS, 1996). Now, claimed depths of operation rarely exceed 350 mm,
whereas in the mid 1990s the range was between 310 mm and 500 mm. In addition, subsoiling has
become more targeted, with concentration on tramlines and field headlands. Also of particular
relevance is the practice of one pass subsoiling and sowing of oilseed rape. In effect, this is a deep
loosening operation which is not immediately compromised by machinery compaction because the
only subsequent wheeling in the crop is in the tramlines. Chan et al. (2006) report an 18% increase in
yield of oilseed rape with this technique compared with sowing traditionally without loosening.
Improved timeliness due to subsoiling
The benefit of improved timeliness due to subsoiling is unlikely to apply every year or on every soil
but in a wet season, could be the difference between getting a crop established or not. In general,
the benefit can be measured in terms of crop yield from sowing more crop at the optimum time.
This was found to be the case by Dickson and Ritchie (1996) when they compared the performance
of different traffic systems. They found an advantage of 3-4 days but only for secondary cultivations,
particularly those carried out in the spring, and only for the zero compared with reduced pressure
and conventional traffic.
Predicting actual returns will be based on soil type, crop and weather. The effect of sowing dates on
the yield of different crops is contained in the data associated with the Silsoe Arable Farm Model
(Audsley, 1981), examples of which are listed in Table 7. Spink et al. (2000) identified a 6% reduction
in wheat yield for crop sown between the 8th and 21st October rather than earlier, which is line with
the data from Audsley (1981).
35
Table 7. Timeliness yield penalties for different crops sown during different time periods (taken from
Audsley, 1981)
Time period
Yield loss for planting and harvesting in the given time periods, %
Wheat
Oilseed rape
Spring barley
Potatoes
Sowing
1–14 Jan
15–28 Jan
29 Jan–11 Feb
12–25 Feb
26 Feb–11 Mar
12–25 Mar
26 Mar–8 Apr
9–22 Apr
23 Apr–6 May
16–19 July
30 Jul–12 Aug
13–26 Aug
27 Aug–9 Sept
10–23 Sept
24 Sept–7 Oct
8–21 Oct
22 Oct–4 Nov
5–18 Nov
19 Nov–2 Dec
3–16 Dec
17–31 Dec
Harvest
Sowing
Harvest
Sowing
Harvest
2
0
1
3
7
12
18
2
0
5
9
11
13
15
16
0
2
4
6
1
0
0
1
2
Sowing
Harvest
5
0
5
15
Sugar beet
Sowing
Harvest
0
1
5
11
0
10
20
30
0
2
4
0
0
5
10
5
2
0
0
4
8
12
As Audsley (1981) points out however, it can be more profitable to incur large timeliness penalties if
less labour is required or the crop is highly profitable, even if harvested late. Such farm-scale detail is
outside the scope of this project, but the yield data do provide a basis upon which delayed sowing
(the most likely soil structure effect) can be estimated. Of these, spring sown crops are the most
likely to be impacted and a two week delay for spring barley is a reduction of 1%, while that for
potatoes is 5%. As mentioned earlier, delays will only happen occasionally, but weather data could
provide an estimation of their frequency. Figure 13 shows that spring periods of extreme wetness
are relatively rare.
36
Figure 13. The ten wettest months in Bedfordshire since 2000 shown in mm total rainfall.
(Source: Clifton Weather, http://www.cliftonweather.co.uk/index.html)
Those spring months when rainfall was 30% or more above the ten year average in a relatively dry
area are more common, as shown in Table 8. This will have an impact on the timing of the cultivation
for and sowing of spring crops.
Table 8. Spring months in Bedfordshire when rainfall was 30% above the 10 average
Year
Month
Monthly 10 year 30% above
average, mm
average, mm
2000 April
34
95
2001 February
41
73
March
32
64
April
34
61
2008 March
32
73
These data are similar from arable areas further west in the country and suggest that on a national
scale, improved timeliness due to subsoiling will be confined to extreme events but these events are
becoming more common.
Loss of soil and nutrients
There are rather few data to support the premise that subsoiling reduces run-off and erosion,
principally because rapid re-compaction of the soil has occurred due to subsequent traffic. Putting a
monetary value on subsoiling is therefore difficult and can only be estimated. Certainly the effects
are transient and only likely to last for the first 12 months after loosening and only likely to be of any
measurable benefit on soils with a propensity for erosion, such as the South Downs. On soils of this
nature, Evans (2002) isolated different crops in terms of percentage occurrence of erosion and
volumes of eroded soil, as indicated in Table 9.
Table 9. Erosion occurrence under different crops as a proportion of total erosion and volume of soil
eroded.
Crop
Occurrence, % Mean volume of soil eroded, m3 ha-1
Winter cereals
42.8
1.85
Spring cereals
11.5
1.75
Oilseed rape
1.5
1.92
37
Evans (personal communication, Feb. 2012) also makes the observation that infiltration effects are
not significant if soils are already saturated. Evans (2005) found in the 1980s that about half the
erosion was in autumn sown crops and occurred when soils were saturated. In a later study Evans
(2011) further refined this to around three-quarters of the erosion and runoff being when soils were
saturated, meaning that around 25% occurred at other times. Frequency of saturation and duration
are closely linked to drainage efficiency which is influenced by soil structure as well as many other
factors. In this respect although subsoiling may improve hydraulic conductivity (Chamen, 2011), this
may encourage transport of chemicals directly into the field drains. The ideal may therefore be an
undisturbed soil profile with many interconnected but tortuous paths to the field drains. Such a
profile might be anticipated with a non-compacted, little cultivated condition but quantification of
differences in losses between these conditions and most traditional practice cannot be estimated
without closely targeted research.
Tramlines
Tramline subsoiling is normally carried out to avoid the risk of yield loss because the new tramlines
will not be in the same place. A conservative estimate of losses in these strips would be 10% and the
most common tramline spacing is 24 m. With each track having a width of around 0.4 m, this
equates to 3.3% of the field and the net cost would be around £3 ha-1 and yield benefit just 0.3%.
Loosening tramlines may also be a precursor to ploughing. This eases the problem of excessive
draught and plough stability created as the machine passes through these highly compacted strips at
an angle. There may be some benefit in terms of seedbed conditions, but probably not measurable
in terms of final crop yield.
Headlands
To estimate the return on investment in subsoiling headlands, there must be an assumption of
avoidance of yield depression, and an estimate of 5% would not seem unreasonable. Headlands
however take up a varying proportion of fields depending on their extent and field sizes. Figure 14
shows the relationship between field size and headland area, assuming different headland widths
based on the size of equipment likely to be associated with different field sizes. These data relate to
irregular fields that have headlands on all four sides, whereas rectangular or square fields tend to
have headlands only at each end. From the “worst case” data shown in Figure 14, we can calculate
the net field response to headland subsoiling. With field sizes from 2 ha to 100 ha, assuming 5% yield
depression avoidance, net responses only range from 0.4% for the largest fields to 1.6% for the
smallest. If 10% avoidance is assumed on the headland, these figures rise to 0.7% and 3.1%
respectively. Data from Graves et al. (personal communication, 2012) suggest a more modest
average of 5.4% headland area exposed to compaction based on a 12 ha average field size. This
would indicate a further reduction in the effectiveness of subsoiling as a mitigation measure.
38
Figure 14. Headland area as percentage of field size assuming 12 m and 24 m headlands on all four
sides.
Reduced cost of subsequent cultivations
Subsoiling not only loosens deeper in the profile but also reduces the strength of topsoil layers. This
was clearly demonstrated by Chamen (2011) and is an accepted outcome of subsoiling. What is less
clear is the effect of subsoiling on the draught requirement of subsequent operations, for example
ploughing or non-inversion tillage. A key requirement is to relate implement draught to penetration
resistance. Lapen et al. (2002) measured plough draught in relation to soil conditions on a clay loam,
the results of which are shown in Figure 15. The clearest correlation seems to be between plough
draught and penetration resistance in the 0 – 0.15 m depth layer, as might be expected with a
consistent plough operating depth of 0.12 m. However, Figure 16 shows that these particular data
when more closely analysed exhibit little or no correlation and cannot therefore form any basis upon
which draught predictions can be made.
An additional and opposing factor is the increase in rolling resistance that occurs on loosened soil.
This could counteract any benefit from the looser conditions in terms of draught but is unlikely to
also counter a reduction in depth of operation due to the magnitude of saving in this respect.
39
Figure 15. Map of plough draught and soil variables with the plough working at 0.12 m deep on a
clay loam soil (after Lapen et al., 2002)
Figure 16. Plot of plough draught working at 0.12 m depth against average penetration resistance in
the 0–0.15 m depth profile. (After Lapen et al., 2002)
Summary of subsoiling return on investment
1. Yield depression avoidance.
a. Tramlines. 0.3% yield benefit across the farm
40
b. Headland remediation. 0.5% to 1.6% yield benefit for fields from 2 -20 ha and 0.5%
to 0.4% for fields of 20 – 100 ha and applying to 50% of the farmed area.
2. Timeliness.
a. Only likely to have a significant impact on spring sown crops.
i. Cereals 1% net improvement in yield
ii. Potatoes, 5% yield improvement
3. Soil hydraulic properties
a. Reduction in soil and nutrient losses. Unable to quantify
4. Reduced cost of subsequent cultivations
a. Faster ploughing. No definitive data
b. Shallower overall tillage. See next section which provides a conservative estimate for
this situation
Deeper cultivations
The assumption here is that farmers cultivate to around 250 mm depth to take out seedbed
compaction rather than a maximum of 100 mm, which indicates that they have no concern of
compaction. The cost of this in terms of implement draught can be calculated from the equation
identified by Mouazen & Ramon ( 2002). This requires the key soil parameters of bulk density (ƿ) and
moisture content at the time of cultivation (w).
D = 1.6734ƿ3 -21.36w + 73.93d2
Taking soil parameters from Chamen (2011), the effect on draught of these two different depths of
operation on a sandy loam and on a clay soil are shown in Table 10. These show that there is likely to
be an increase of 90% on the sandy loam when the depth of operation increases from 0.1m to
0.25 m and a 120% increase on the clay soil.
Table 10. Change in predicted draught force with depth on a sandy loam soil.
Soil texture
Depth of
work, m
Bulk
density, Mg
m-3
Moisture
content, g g-1
Draught,
kN/m
Sandy loam
0.1
0.25
0.35
1.4
1.5
1.6
0.15
0.16
0.17
2.1
11.9
12.3
Draught
increase
compared with
0.1 m, %
229
486
These data are supported by a simple cost calculator that suggests more than double the cost when
the depth of operation is increased from around 0.1 m to 0.25 m. Similarly, carefully monitored costs
from a benchmarked farm (Ward, personal communication, 2011) suggested an increase of £13/ha,
namely from £12/ha to £25/ha with this same level of depth increase. These data are further
supported by those of Patterson et al. (1980) who compared the draught of ploughing at around 220
mm compared with 110 mm depth on three different soils over a period of six years. Energy
requirements were consistently doubled on a clay loam, a silty loam and a silty clay loam soil with
this increase in depth of operation.
A return on the investment in deeper cultivations is difficult to quantify. Research (Chamen, 2011,
Patterson et al., 1980) showed no consistent evidence of a yield benefit from deeper cultivations
and the main anecdotal evidence from farms is a reduction in the amount of surface water. In many
41
cases this comparison is between farms that plough with much secondary cultivation, compared
with those that expend 75kW/m width in cultivation passes that require only a cultivator drill and
rolls to establish the crop. Field access and therefore timeliness is likely to be the main return on
investment. This could be exacerbated by differences in crop growth due to water-logged conditions
following sowing, but again are difficult to quantify.
Summary of deeper cultivation effects
1. £13/ha additional cost
2. Tentative 2% increase in yield for both winter and spring sown combinable crops
Low ground pressure tyres
To determine the cost of operating a commercial1 reduced pressure system compared with the
original equipment fitted to the machinery, the base specification of a number of tractors was
compared with the best available tyres for that configuration. These differences are shown in Table
11 and indicate a modest increase in cost across the power range of 2.6%-3.6% of the tractor price.
Return on this investment is likely to be realised in a number of ways, not all of which reduce
compaction. The first thing to note is that the greater contact area of these tyres reduce rutting. By
implication, reduced rutting means lower pressures in the soil but also spread over a wider area and
particularly width. Where shallow tillage is employed, this extra width (20-25%) can result in a
marginal increase in tillage energy rather than the reverse (Chamen et al., 1990). When the soil is
moist lower pressure tyres can improve field access but may increase the risk of compaction. Most
of the tyres listed in Table 11 allow inflation pressures as low as 0.8 bar (Vermeulen & Perdock,
1994; Michelin Tyre plc, 2010) with a load of around 5 Mg but with the largest tractor these
pressures had risen to 1.0 and 1.4 bar for the rear and front wheels respectively showing that
Table 11. - Additional cost of wheels and/or tyres to equip new tractors which allow inflation
pressures of around 0.8 bar when in the field and on the road.
Axle
Nominal engine Standard tyre
Optional
Additional cost
power, kW
size
lower
Tyres, £
% of base tractor
pressure tyre
price
size
Front
420/85R30
600/65R30
980
155
Rear
20.8R42
710/70R38
2032
2.6
Front
540/65R34
600/70R30
1636
195
Rear
650/85R38
800/70R38
3703
3.6
Front
600/70R30
600/70R30
1988
270
Rear
650/85R38
800/70R38
3553
3.0
pressures are already being compromised to achieve transmission of this power. Similarly, on
combine harvesters loads are such that even with 1050/50R32 tyres, the pressure required to
support 10 Mg is around 2 bar and many harvesters have wheel loads in excess of this. Similarly with
twin-axle grain trailers, there is not enough physical room to fit tyres that will reduce pressures
below around 1.6 bar. From this analysis, low ground pressure systems that maintain pressures of
around 1 bar are only possible across all operations on farms operating with smaller machinery. In
1
Commercial In this context means a system that complies with all road legislation and tyre manufacturer’s
recommendations for loads and speeds. (Michelin Tyre plc)
42
wheel load terms this relates to around 2.5 Mg for haulage trailers and around 7 Mg for harvesters.
In the case of grain harvesters, this would make them around 4 m wide in their road mode. Another
option is rubber track systems. These don’t universally reduce topsoil compaction but can be relied
upon to protect subsoils (Ansorge & Godwin, 2007 & 2008; Chamen, 2011). Retro-fitting tracks on
tractors may cost £40,000 while original equipment on a 265 kW tracked tractor for example carries
a list price premium of around 25% compared with the equivalent wheeled tractor of around 425
kW. In monetary terms, this is around £50,000 at 2011 prices. The price differential for combine
harvesters is less because the tracks do not need to provide high tractive loads and the additional
cost generally equates to around 10-15% of the purchase price of the machine.
Translating these additional capital costs into a cost per hectare has been estimated from an average
annual use for tractors, which according to Nix (2010) is 500 hours. Estimating an average work rate
for all operations is difficult, but if the main crop establishment operations are assessed, an average
of 0.75 ha h-1 would not seem unreasonable. For the tracked tractor, a 10% increase in work rate has
been assumed to allow for differences in slip when operating. Depreciation for tractors of this size is
based on 10 years useful life with 30% of their initial value being retained at the end of this period,
during which annual repair costs have been 4% of the initial price (Nix, 2010).
Table 12 provides an overview of these data and the estimated additional cost per hectare for a low
ground pressure option. In reality, if the farmer wishes to run a rubber tracked tractor as part of this
strategy, then a wheeled, albeit smaller tractor, is likely to be needed alongside it. Thus, the
additional operating costs are likely to be in the region of £21 ha-1 for the tracked tractor
combination and £3.58 ha-1 (£1.22 + £2.36) for a complete wheeled tractor system. In terms of
return on investment, this will revolve primarily around additional yield. Research data suggest that
this could be around 3% across different crops and soils. With average yields of around 8 Mg ha-1
and wheat price of £120 Mg-1, this equates to a return of £29 ha-1 and net benefit of £8 ha-1 for the
tracked system and around £25 ha-1 for the wheel-based system. However, these yield and
machinery load data relate to around 20 years ago with loads that did not exceed 5 Mg. Today many
vehicles impose double that load with unknown effects on subsoils.
Table 12. Additional costs per hectare for operating with low ground pressure equipment compared
with standard machines, assuming 500 hours annual use over 375 ha, ten years life, 30% resale
value, 4% of initial price repair costs and 5% interest on capital.
Tractors
155 kW
195 kW
270 kW
425 kW
265 kW rubber track
List price, £
Standar LGP
d
113,793 116,640
146,601 152,153
186,032 191,573
169,000
220,000
Extra cost per annum
Depreciation Repairs,
,£
£
200
114
389
222
388
221
3570
2040
Summary of low ground pressure effects
Assuming maximum wheel loads of around 5 Mg:
1. Yield improvement approximately 3% across a range of crops
2. Additional costs ranging from around £4 ha-1 to £21 ha-1.
43
Interest,
£
142
278
277
2550
Additional
cost, £/ha
1.22
2.37
2.36
19.80
Controlled traffic
There are a great deal of data from research and practice in different parts of the world that report
significant benefits of conversion to controlled traffic farming, a system that confines all field traffic
to the least possible area of permanent traffic lanes. These include yield increases alongside lower
production costs and benefits to the environment. There is nothing controversial about minimising
the area extent of machinery compaction; the crucial questions are; is it practical, sustainable and
cost effective?
Operating costs and returns
Presently there are 25 farms in the UK that have adopted this technique or are on the road to
adoption, these representing an area of around 12,000 ha. Most have been in the system for no
more than two years, so data are still limited. Detailed information from one of these farms was
used to calculate farm gross margins (FGM). These are the sum of the crop gross margins less
rotational losses, timeliness losses for drilling and harvesting, labour, and machinery costs including
fuel and repairs. This is equivalent to profit before deduction of fixed costs such as rent, office etc.
Results suggest machinery cost savings of £178/ha and an overall reduction in costs of £43/ha.
Similarly, this farm increased its profit margin by £75/ha (8%) without allowing for any potential crop
yield increase. If predicted net field yield responses are included in this wheat/oilseed rape rotation,
farm profit increased by 17% compared with traditional practice, representing an additional £87/ha
due to increased crop yields.
On a similar sized farm, initial calculations suggest a £12/ha lowering in machinery costs when it was
converted to controlled traffic. These and the previous data are supported by an anecdotal report of
cost savings of £100/ha with a 2000 ha farming operation.
Assessing on-farm yield responses to controlled traffic has not proved possible because all farms
have converted all their fields, meaning that no rigorous comparisons with conventional
management are possible. Predictions must therefore be based on research results which are best
calculated from the data shown in Figure 17. In practice an 8% increase in the yield of wheat on the
non-trafficked beds will resolve into a 4% increase when a yield reduction in the cropped permanent
traffic lanes has been accounted for. Figure 18 provides a possible scenario based on an 8% yield
increase in the non-trafficked beds and different levels of yield reduction in the cropped permanent
traffic lanes.
44
Figure 17. Percent increase in crop yield of different crops grown on non-trafficked compared with
randomly trafficked soil (Chamen, 2011).
Figure 18. Predicted net field yield of wheat for different trafficked areas within a controlled traffic
system. Prediction based on chemical application tramlines at 24 m and different levels of yield
reduction in the cropped traffic lanes compared with conventional practice.
Consequential benefits
Timeliness benefits are likely to be similar to those identified due to sub-soiling but in this case are
derived from fewer inputs and extended field access due to firm traffic lanes and improved drainage
on the non-trafficked beds. The return on more efficient utilisation of fertiliser is accounted for on
the profit level in terms of yield but there will also be an environmental benefit “for the greater
good” in terms of reduced diffuse pollution and greenhouse gas emissions.
45
Summary of controlled traffic returns on investment
1. Net yield increases in the range 5 – 15 % depending upon crops, other than grass, included
in Figure 17.
2. Lowering of production costs in the range £10 - £40/ha, including no need for deeper
cultivations costing around £25/ha
3. Consequential benefits resulting in improved timeliness valued at;
a. 1% yield increase for spring barley
b. 5% yield increase for potatoes
Satellite guidance and auto-steer
With traditional production systems the overlap between machinery passes in the field is governed
by the skill and concentration of the driver. With tillage equipment, overlaps average 10%, meaning
that 10% more of the land is run on than actually necessary. With drilling this percentage is lower
because physical markers are used to provide guidance to the driver, but overlaps still range from 14% (Kroulik et al., 2009). High-level guidance and auto-steer systems cut these overlaps to well
under 1% for all operations.
The outcome of a 10% reduction in trafficked area (improvement in efficiency) in terms of fuel
saving is around £0.7/ha but in compaction terms is difficult to quantify. This is because it is a
different 10% for every tillage pass so a net reduction of just 5% might be more applicable; the
return on this would be further fuel saving due to the smaller area extent of compaction. Chamen
(2011) identified different draught savings according to depth of operation, suggesting an average
saving of around 30% at 150 mm depth of operation in non-trafficked compared with trafficked soil.
As the draught component of any tillage operation contributes about 75% to the fuel being used, the
net saving in fuel per hectare for this depth of work would be 30% x 5% x 75% = c. 1%. An operation
of this nature carried out at 8 km/h uses around 18 litre/ha of diesel2, which at today’s price of
£0.65/litre equates to £11.50/ha. A 1% saving on this is just £0.11/ha.
Summary of recommendations for compaction mitigation and
management
Mitigation
1. There is a good case for avoiding immediate trafficking following subsoiling and the benefits
of this are demonstrated where oilseed rape sowing is combined with deeper cultivation.
2. An improvement in some soil hydraulic properties by subsoiling can be maintained despite
immediate trafficking but these are unlikely to remain for more than one season.
3. Maintaining areas without traffic can give measurable benefits for at least four years.
Subsoiling has been shown to avoid yield losses where extremes of compaction have been
alleviated, such as on headlands, but there is little research evidence to suggest yield improvement
where subsoiling is used in less extreme conditions. To some extent, this is considered to be due to
subsequent rapid re-compaction from random trafficking.
Management
1. Plough “on the land” with tracked vehicles followed by lighter vehicles on tracks or tyres, the
latter having inflation pressures of around 0.8 bar. Similarly harvesters should be equipped
2
Ward Cultivation Solutions (http://www.wcs-farming.co.uk/)
46
2.
3.
4.
5.
6.
7.
8.
with good quality tracks or tyres at the lowest pressure possible conducive with practical
limitations. On land ploughing can be facilitated more easily with RTK auto-steer.
Avoid running on newly loosened soil. If this is unavoidable leave as long as possible and use
low pressures (c. 0.8 bar) and light vehicles.
Consider sowing crops in combination with deep loosening rather than deep loosening
followed by further cultivation and/or sowing.
Consider adopting a controlled traffic farming system to confine all wheels or tracks to the
least possible area of permanent traffic lanes. This is also facilitated by RTK auto-steer.
Manage intermediate cropped traffic lanes to minimise crop yield losses.
Consider auto-steer systems as a means of cutting down on the extra compaction caused by
overlaps.
Consider stock removal from vulnerable soils over-winter. This has the added advantage of
easier management and potentially higher stocking rate due to better grass recovery.
Only re-seed leys when a downturn in production efficiency can be clearly identified. Forage
production is significantly curtailed by trafficking, both from immediate physical damage and
due to compaction. Low ground pressure and/or controlled traffic should be considered.
When re-seeding, minimise tillage to reduce organic matter oxidation and consider
alternatives to tillage.
Maximise organic matter content of soils by all available means taking account of nitrate
loadings and any heavy metals which might be present in imported materials.
47
Development of Economic Cost Curves
Measures to combat soil compaction are of interest since they potentially offer agricultural
productivity and environmental gains, although their relative attractiveness need to be established
empirically. That is, they will require adjustments to farming practices and such adjustments may
incur costs as well as conveying benefits. Moreover, since both the incidence and impact of
compaction are likely to vary across different types of soil, weather conditions, enterprises and
farming systems, the balance between different management strategies is likely to vary depending
on local circumstances.
Such management strategies may, with some overlaps, be viewed as falling into three categories
(Table 13, also Figure 1 earlier). First, compaction could simply be accepted as an inevitable (or
unacknowledged) consequence of agricultural activities with no attempt made to address problems
associated with it. Costs would thus relate mainly to on-site yield reductions and additional input
usage, plus off-site environmental damage.
Second, once encountered, attempts could be made to alleviate compaction. For example, the use
of sub-soiling to mechanically and quickly reduce compaction or the use of alternative rotational
practices to restore soil structure more gradually. Equally, the effects of compaction could be
countered through adjustments to other aspects of farming practices within a given system. For
example, increasing the use of fertilisers and irrigation to maintain yields, or the use of buffer strips
to contain surface runoff. Alleviation costs would thus relate to the additional effort (training,
labour, energy) and materials (machinery, chemicals) required, to be weighed against the benefits of
avoiding some yield losses and some environmental damage.
Third, awareness of compaction effects could prompt attempts to avoid or mitigate compaction
occurring in the first place rather than adapting to its presence. This could involve the temporary (or
permanent) cessation of agriculture on susceptible soils through the postponement (or
abandonment) of particular livestock grazing and of cropping activities in favour of fallowing the
land, diverting it to another enterprise or delaying the start of the enterprise (e.g. later turning-out
of livestock or later planting). Although the costs of such land use change in terms of agricultural
production foregone in the current year could be high, higher yields and lower environmental
damage might be achieved in subsequent years. More generally, a flexible approach to the timing of
activities and indeed the choice of agricultural land use - taking account of soil conditions – might be
cost effective. Equally, alternative technological solutions could be deployed. For example, low
pressure tyres, minimum tillage, zero grazing and controlled traffic farming (CTF) may all offer routes
to managing compaction more effectively. However, in all instances, the investment and
operational costs of altering farming systems need to be weighed against likely yield gains and
reduced environmental damage.
48
Table 13: Possible compaction management strategies and example options
Strategy
Example Options
Description
Comments
Endure compaction Depressed yields (and thus
under conventional lower farm revenue) and
management.
higher environmental damage.
No action
Alleviation
Sub-soiling,
ploughing.
Avoidance
Low pressure tyres
CTF
deeper Attempt to reduce
degree
of
compaction and/or
counteract negative
impacts
through
discrete
management
actions.
Reduction in yield losses and
environmental damage likely,
but magnitude and duration of
reduction may be limited
whilst management actions
incur
costs.
Sub-soiling
without subsequent traffic
management frequently futile
in terms of crop yields.
Attempt to avoid
compaction and thus
avoid
negative
impacts
through
management
flexibility
and/or
wider changes to
farming systems.
Reduction in yield losses and
environmental damage likely,
but time profile of costs and
benefits arising from systemwide changes may be uneven.
Consideration of the costs and benefits of different strategies and of specific management options
may be envisaged at different levels of economic aggregation. Initially, a focus at the enterpriselevel (e.g. winter wheat, potatoes, onions) may be appropriate since a pre-requisite for any further
analysis is a sound technical understanding of how the type, intensity and ordering of particular
management operations interact with compaction to affect yields, operational costs and
environmental loadings. Enterprise-level analysis can be conducted relatively easily through partial
budgeting and gross-margin analysis, drawing on standard farm management data supplemented by
experimental and survey data to characterise farm operations. Given that the efficacy and duration
of alleviation and avoidance measures are likely to vary over time, care needs to be taken to
consider the time profile both of costs incurred (e.g. initial capital investment) and benefits achieved
(e.g. rising, stable or declining yields), entailing the use of techniques such as financial discount rates
or pay-back periods.
However, an increase in the relative profitability of a given enterprise may lead to that enterprise
expanding at the expense of another. Similarly, rotational patterns may be affected by the degree of
compaction and its management. Hence a farm-level (e.g. cereals, general cropping, dairying) focus
may extend analysis of costs and benefits by allowing for substitution possibilities and interdependencies between enterprises and their resource allocations. Similarly, assessment of
49
environmental loadings may be more accurate if account is taken of adjustments to whole farming
systems rather than enterprises in isolation. Quantitative farm-level analysis requires greater
modelling sophistication than enterprise-level analysis, typically involving parameterisation of interlinkages between different resources, operations and enterprises over time (e.g. a season or a
rotation) plus an optimisation algorithm to maximise an objective function (e.g. farm profitability) by
choosing between different enterprises and resource allocations.
Finally, at the sectoral or national-level, aggregate changes to resource allocations across competing
enterprises (and farm types) will have market effects in terms of the relative prices of inputs and
outputs. For example, an expansion in the production of wheat for milling may lower its price yet
raise the price of feed wheat – and such changes may have feedback effects on resource allocations.
Quantitative assessment of such inter-linkages and possible feedback effects requires a market-level
focus, typically through either a partial or (preferably) general equilibrium model that simulates
market dynamics and production responses. Unsurprisingly, market-level analysis requires
considerable volumes of data (plus a number of simplifying assumptions) to capture the complexity
of market operations. For example, the demand for different commodities and the scope for
substitution between different supplies of a given commodity (e.g. domestic and international) and
between different commodities (e.g. different animal feedstuffs). A market-level analysis would also
require information on the current distribution (both structurally by farm type and spatially by soil
type) of compaction and farm practices plus the likely distribution and uptake of alternative
compaction strategies.
Unfortunately, notwithstanding clear evidence (see earlier sections of this report) on the existence
of compaction problems, basic information on the incidence and effects of soil compaction plus on
the distribution of current compaction management is insufficient to support formal market-level
analysis. Similarly, in the absence of information on how a wide range of enterprises are each
affected by compaction and how their inter-relationships might be altered by alternative
compaction management, the scope for quantitative farm-level modelling and thus estimation of
uptake rates is somewhat limited. Hence the enterprise-level is an appropriate starting-point for any
quantitative analysis.
Recap of cost categories
Soil compaction inhibits plant growth, leading to lower crop yields. Compaction also exacerbates
nutrient losses, including nitrogen leached into water and emitted as N20 to air. In addition,
compacted soils are harder to pull tillage implements through meaning that cultivation operations
consume greater quantities of fuel than would otherwise be required.
All of these effects impact on farm productivity and financial returns. For example, lower yields
equate to lower revenues whilst nutrient losses and increased fuel usage impose higher costs. At
the same time, nutrient losses and higher fuel usage also impose off-farm environmental costs in
terms of water pollution and green house gas emissions.
Management responses to soil compaction offer the possibility of partially or wholly mitigating these
negative effects, either through alleviating compaction once it has occurred or avoiding causing
compaction in the first place. However, such management options themselves incur costs that need
to be considered alongside any reductions in negative impacts arising from compaction.
50
Attempting to quantify the cost-effectiveness of different management options in addressing the
various negative impacts of compaction requires several specific pieces of information regarding the
effects of both compaction and the efficacy of management options in addressing these effects.
Moreover, it is desirable to differentiate effects and management efficacy across different
circumstances.
Unfortunately, notwithstanding general consensus in the literature and amongst experts regarding
the nature of compaction effects and their mitigation, detailed data sufficient to differentiate across
different soil types or weather conditions, or indeed across different farming systems and
managerial abilities, remain scarce. Consequently, attempting to estimate cost-effectiveness, even
for purely illustrative purposes, requires deploying a number of assumptions. The following sections
outline briefly the main assumptions used and the sensitivity of final results to variation in the
assumptions. Although cost curves are presented for potatoes and onions, only the winter wheat
example is presented in detail here since the same process was followed for each, and the same
issue arise for each.
A winter wheat example
Wheat is the dominant cereal crop in England and Wales, accounting for around 1.8m ha of the 2.5m
ha under cereals (AHDB HGCA planting survey 2011)3. Within this, autumn sown “winter” wheat is
most common since it achieves higher yields than spring sown varieties. Yields vary slightly between
years, locations (i.e. soil types), position within a crop rotation and whether the grain is intended for
milling or animal feed purposes. The extent of wheat production means that a variety of soils are
covered, both heavy and light.
Although the operational practicalities of winter wheat production will vary across different farms,
locations and years. A stylised plan is shown in Table 14:
Table 14 – Typical winter wheat field operations over the year for rigourous non-inversion tillage.
Month
Operation
October
November
March
April
Cultivation and drilling
Weed and aphid control
Fertiliser top-dressing
Fertiliser top-dressing
Weed control
May
Weed and disease control
June
Disease control
August
Harvesting
Seed rates are typically around 175 kg/ha and nitrogen applications around 200 kg/ha. Machinery
used can vary greatly, partly depending on soil type, but tractor power of 0.75 kW/ha to 1.4kW/ha
(Nix, 2010: p191) implies typical tractor power requirements of around 75kW to 140kW.4
3
http://www.hgca.com/document.aspx?fn=load&media_id=7077&publicationId=100
Estimated on basis that average cereal area on cereal farms is c.140ha (inferred from Defra’S census on-line
tables) and wheat accounts for 70% of this. Nix (2011, p191) reports average power of 107kw for current
tractor sales.
4
51
This list suggests a relatively large number of field operations and the potential risk of significant
compaction. However, quantifying this and estimating the impact of alternative management
responses necessarily invokes a number of assumptions and some uncertainty.
Baseline yields, compaction penalties & mitigation effects
Reflecting differences in site conditions and management, yields of winter wheat vary spatially
across farms and also over time. However, site conditions and management regimes are seldom
recorded routinely alongside reported yields, meaning that parameterising yield variation to soil
type is not easy.
For the purposes of this exercise, baseline yields for winter wheat on different soil types have been
taken from a parallel Defra project on the costs of soil degradation. Specifically, yields per hectare
of 10.2t, 9.0t, 7.7t and 8.0t have been assumed for, respectively, clay, silt, sand and peat soils (pers.
comm., Anil Graves, Cranfield University, 2012). These are assumed to be achieved under a
conventional farming system using typical levels of inputs as outlined in, for example, Nix (2011).
Variation in management practices and input intensity across different soils has not been
considered.
Against these assumed baseline yields, compaction – if not addressed – is assumed to impose a per
hectare yield penalty of 2.5% on clay and 2.0% on other soil types. This is based on a conservative
interpretation of the literature and findings from the farm visits, and allows for higher pro rata
penalties on compacted areas within a field but lower pro rata losses on uncompacted areas.
The baseline yields and yield penalties give per hectare output losses below the baseline of 0.26t,
0.18t, 0.15t and 0.16t respectively on clay, silt, sand and peat. Both baseline yields and percentage
yield penalties might be expected to vary with, for example, weather conditions so Table 15 shows
how such variation could alter output losses. Higher baseline yields and/or higher percentage
penalties imply higher physical output losses.
Table 15 - Physical yield loss under different baseline yields and different percentage penalties5.
Crudely, clay soils will lie to the right of the Table, silts and peat in the middle, and sands to the left –
although local conditions and variable weather will also play a role.
Yield penalty
(% of
baseline)
7.0
7.5
8.0
8.5
9.0
9.5
10.0
1.0
0.07
0.08
0.08
0.09
0.09
0.10
0.10
2.5
0.18
0.19
0.20
0.21
0.23
0.24
0.25
5.0
0.35
0.38
0.40
0.43
0.45
0.48
0.50
Baseline yield (t/ha)
5
This Table and other Tables in this section show the effect of varying one or two baseline parameter values
whilst holding all others constant.
52
7.5
0.53
0.56
0.60
0.64
0.68
0.71
0.75
10
0.70
0.75
0.80
0.85
0.90
0.95
1.00
Note: Defra statistics show a rising trend for wheat yields over time, but with year-on-year variation.
http://archive.defra.gov.uk/evidence/statistics/foodfarm/enviro/observatory/indicators/b/b11_data.htm
Farm Business Survey data also show year-on-year variation, but also geographical variation between c.7t/ha
and c.10t/ha http://www.farmbusinesssurvey.co.uk/databuilder/
In turn, the value of a given physical output loss will also depend on the prevailing market price for
wheat. Here, a value of £118/t has been assumed – but Table 16 shows how different combinations
of physical output loss and market prices affect the value of lost output. Higher yield penalties
and/or higher prices imply greater lost output value. Prices can vary considerably, as described in
the footnote on Table 16. As a globally-traded commodity, market prices for wheat can fluctuate
from year-to-year. For example, prices spiked notably in 2008 having been considerably lower in
earlier years. However, prices received by farmers will also be influenced by other factors including
the quality and volume of grain produced and marketing arrangements such as spot selling, forward
contracting and storage.
Table 16 - Revenue loss (£/ha) for given physical yield loss and output price values (or equivalently
the revenue gain for overcoming the yield penalty)
Yield penalty
(t/ha)
Output price (£/t)
60
90
120
150
180
210
0.10
6
9
12
15
18
21
0.25
15
22.5
30
37.5
45
52.5
0.50
30
45
60
75
90
105
0.75
45
67.5
90
112.5
135
157.5
1.00
60
90
120
150
180
210
Note: Defra statistics show that wheat prices have varied by more than +/-100% around the current price of
£120/t over the period 1984 to 2008, http://www.defra.gov.uk/statistics/foodfarm/farmgate/agripriceindex/
.The efficacy of management responses in terms of mitigating yield (and thus output) losses may be
expected to vary across different management options, but also with respect to site conditions and
managerial ability. However, in the absence of detailed data on such variation, efficacy has simply
been assumed to be 100% for most options, meaning that the entire yield penalty is negated and the
baseline yield is achieved. Only sub-soiling was assumed to be less than 100% effective at 84% on
clay and 80% on other soils. Again, these assumptions are based on interpretations of the literature
and findings from field visits. Lower efficacy due to, for example, technical weaknesses with
mitigation options or poor implementation would lead to less of the yield penalty being negated.
Tables 17 & 18 show how different efficacy rates could affect physical and financial outcomes.
53
Separately, the literature and findings from the farm visits suggest that some management options
offer yield gains in excess of simply negating the yield penalty attributed to compaction. That is,
some options achieve yields above the baseline by going further than alleviation measures in limiting
compaction. Specifically, both low ground pressure tyres and tracks are assumed to achieve yields
3% above the baseline and CTF is assumed to achieve yields 5% above the baseline. Such additional
productivity gains are also partially attributable to broader efficiency improvements that go beyond
simply addressing compaction and are important since they affect the relative cost-effectiveness of
options. Maintaining low ground pressure with tyres is feasible for loads of up to around 7 Mg, with
modest additional costs, but above this, tracks must be resorted to, with tracked tractor equivalents
costing around 25% more than their wheeled counterparts. Tracks for harvesters on the other hand,
which do not need to deliver high levels of traction, have a cost differential of between +10-15%.
Variation across soils, other than in the baseline yields, has not been considered, but Table 16 shows
how different yield gains (i.e. yield penalties avoided) lead to different changes in the value of
output gained, whilst Table 17 extends this to show how different base conditions and mitigation
efficacy could affect other losses too. Environmental loadings associated with different levels of
mitigation efficiency are shown in Table 18.
K saving
P saving
N saving
Diesel
saving
Yield gain
Table 17 - Example physical and financial penalties avoided on different soil types under different
assumed levels of mitigation efficacy.
Efficacy
25%
50%
75%
100%
25%
50%
75%
100%
25%
50%
75%
100%
25%
50%
75%
100%
25%
50%
75%
100%
Clay
65
130
195
260
4.08
8.15
12.23
16.30
3.89
7.77
11.66
15.54
1.05
2.10
3.15
4.20
0.95
1.89
2.84
3.78
Physical units (kg/ha)
Sand
Silt
45
38
90
75
135
113
180
150
2.63
1.18
5.25
2.35
7.88
3.53
10.50
4.70
2.14
0.39
4.27
0.78
6.41
1.17
8.55
1.55
0.58
0.11
1.16
0.21
1.73
0.32
2.31
0.42
0.52
0.09
1.04
0.19
1.56
0.28
2.08
0.38
54
Peat
40
80
120
160
1.18
2.35
3.53
4.70
3.89
7.77
11.66
15.54
1.05
2.10
3.15
4.20
0.95
1.89
2.84
3.78
Clay
7.67
15.34
23.01
30.68
2.85
5.71
8.56
11.41
2.41
4.82
7.23
9.63
0.71
1.43
2.14
2.86
0.51
1.02
1.53
2.04
Financial value (£/ha)
Sand
Silt
5.31
4.43
10.62
8.85
15.93
13.28
21.24
17.70
1.84
0.82
3.68
1.65
5.51
2.47
7.35
3.29
1.32
0.24
2.65
0.48
3.97
0.72
5.30
0.96
0.39
0.07
0.79
0.14
1.18
0.21
1.57
0.29
0.28
0.05
0.56
0.10
0.84
0.15
1.12
0.20
Peat
4.72
9.44
14.16
18.88
0.82
1.65
2.47
3.29
2.41
4.82
7.23
9.63
0.71
1.43
2.14
2.86
0.51
1.02
1.53
2.04
CO2e from
diesel
CO2e from
N20
Nitrogen
Leached
Table 18 - Example reductions in environmental loadings (kg/ha) on different soil types under
different assumed levels of mitigation efficacy.
Efficacy
25%
50%
75%
100%
25%
50%
75%
100%
25%
50%
75%
100%
Clay
1.32
2.64
3.96
5.28
48.17
96.35
144.52
192.70
11.00
22.01
33.01
44.01
Sand
0.73
1.45
2.18
2.91
26.50
52.99
79.49
105.98
7.09
14.18
21.26
28.35
Silt
0.13
0.26
0.40
0.53
4.82
9.63
14.45
19.27
3.17
6.35
9.52
12.69
Peat
1.32
2.64
3.96
5.28
48.17
96.35
144.52
192.70
3.17
6.35
9.52
12.69
The net cost of a management option is calculated as the value of any yield gains and reduced input
(i.e. nutrients and fuel) usage less any additional expenditure incurred by the management option.
In some cases (e.g. sub-soiling, deeper ploughing, stubble cultivating) additional expenditure was
based on Nix (2011) but adjusted for different soils on the basis of estimated differences in diesel
usage (see below).
Diesel usage
UK farming systems are highly dependent on fossil fuels, and diesel usage for field operations
represents a significant on-farm cost whilst GHG emissions from diesel usage6 also represent a
significant off-farm cost. Diesel usage for any given field operation is likely to vary with a number of
factors including soil type and soil conditions, but also size and age of tractor plus operator skill. For
example, larger and/or poorly maintained machinery tends to be less fuel efficient whilst style (e.g.
depth, speed) and accuracy (e.g. degree of overlap between passes) of driver operation can also
influence fuel consumption.
Accounting for such variation is impossible without detailed farm-level information, but indicative
figures in Nix (2011) suggest that a 120HP tractor consumes around 18l of diesel per hour whilst an
180HP tractor consumes around 25l per hour. Nix (2011) also gives indicative figures for how long
particular field operations should take. For a conventional wheat system, field operations likely to
be affected by compaction (e.g. ploughing) are expected to take around 1.4 hours (pers. comm., Anil
Graves, Cranfield University, 2012). Diesel is costed at £0.70 per litre (current price, March 2012)
and is assumed to generate 2.7 kg CO2e per litre consumed on-farm.7
6
A Life Cycle Analysis (LCA) perspective would also encompass the GHG emissions associated with the
production and transportation of diesel prior to its use on-farm, but a narrower on-farm perspective is
adopted here.
7
A Life Cycle Analysis (LCA) perspective would also encompass the GHG emissions associated with the
production and transportation of diesel prior to its use on-farm, but a narrower on-farm perspective is
adopted here. Values of 2.6 to 2.8 are generally cited in carbon calculations, although (again) there is likely to
55
Given that clay soils dominate wheat production (pers. comm., Anil Graves, Cranfield University,
2012) it is assumed here that the Nix-based figures will relate to clays. However, different soils
impose different draught requirements and operations on clay will have higher fuel consumption
than on silt or sand. Although variation in power requirements will also be affected by other
factors, it assumed here that the relative fuel consumption figures are 1 for clay, 0.8 for silt and 0.6
for sand and peat. These differentials are based on limited information gleaned from the literature8
but give some plausible variation in fuel consumption across heavy and light soils. This variation in
fuel consumption was also used to adjust Nix (2011) cost figures to reflect soil type differences for
some mitigation options.
Compaction will increase the power and thus fuel required to pull implements through the soil. As
with overall fuel usage, estimating the additional consumption attributable to compaction is
hindered by the number of possible confounding factors and a lack of data. Nevertheless, additional
fuel usage is assumed here to be +87% on clays, +60% on silt and +29% on sand and peat (pers.
comm., Anil Graves, Cranfield University, 2012). If it is assumed that the estimated fuel usage
figures above include the effects of compaction, this implies that mitigating compaction could lower
fuel usage relative to those figures.
The assumed effectiveness of mitigation options in terms of overcoming yield penalties attributable
to compaction were specified above as 100% for most options. However, the effectiveness in terms
of lowering fuel usage will not necessarily be the same for a number of reasons. First, even if soil
density is reduced through the mitigation action, other problems may arise that require further
action and fuel usage. For example, sub-soiling may bring clods to the surface requiring additional
subsequent tillage activities such as heavy “pressing” and thus further diesel usage. Second,
mitigation activities themselves may require additional diesel that partially or wholly offsets any
savings from easier subsequent tillage operations. For example, sub-soiling is a discrete additional
activity and, deeper ploughing requires more energy than standard depth ploughing.
On this basis, and in the absence of reliable data, it is assumed here that only CTF offers a net saving
on diesel usage and that all other options are neutral in this regard. . That is, all other options
neither increase nor decrease diesel usage.9 In terms of diesel use for low compared with
conventional pressure systems there are counter arguments. On the one hand shallow compaction
(most important in terms of tillage energy) is increased slightly due to wider tyres impacting a larger
area. In the example costs shown in Table 11, tyre widths on average increase by 17%, while rolling
resistance is reduced by only about 10% due to the lower pressure (Stranks, 2006). Where track
systems are involved in traction operations, a 10% reduction in slip is almost countered by higher
transmission losses (Zoz et al., 1999). The fuel use has therefore not been changed for low pressure
systems compared with conventional practice. By contrast, on the basis of evidence in the literature
be some variation across different vintages, conditions and sizes of tractor. For example, see
http://www.carbontrust.co.uk/cut-carbon-reduce-costs/calculate/carbon-footprinting/pages/conversionfactors.aspx or http://archive.defra.gov.uk/environment/business/reporting/pdf/envrpgas-annexes.pdf
8
For example, http://unctc.unctad.org/data/e83iia4b.pdf and
http://ec.europa.eu/energy/renewables/transparency_platform/doc/article_19_2/19_2_denmark_en.pdf
9
For some options, such as sub-soiling or deeper ploughing, it is possible to use the same approach as outlined
above to estimate discrete additional diesel usage arising from the mitigation option. However, since this is
not possible for all options and the effect on subsequent activities’ diesel usage is difficult to specify, it is
simpler to assume no net change.
56
and from farm visits, CTF is assumed to eliminate the additional diesel usage attributable to
compaction. In fact, by reducing the number of field operations undertaken and achieving more
efficient use of machinery, CTF probably offers fuel savings in excess of this but such further savings
are not included in this analysis. Tables 19 & 20 show how the various fuel usage assumptions
interact. To show how relaxing this assumption could affect results, Tables 19 & 20 show how the
various fuel usage assumptions interact - confiming the earlier observation that GHG emissions are
dominated by N2O.
57
Uncompacted
Compacted
Table 19 - : Variation in diesel usage (litres) under different assumed hourly consumption rates and
work rates, with and without compaction
1.0
Clay
1.5
2.0
1.0
Hours per ha
Silt
1.5
15
15.0
22.5
30.0
12.0
18.0
20
20.0
30.0
40.0
16.0
25
25.0
37.5
50.0
30
30.0
45.0
15
8.0
20
Litres
per
hour
1.0
Sand or Peat
1.5
2.0
24.0
9.0
13.5
18.0
24.0
32.0
12.0
18.0
24.0
20.0
30.0
40.0
15.0
22.5
30.0
60.0
24.0
36.0
48.0
18.0
27.0
36.0
14.1
23.3
6.4
11.3
18.6
4.8
8.4
14.0
10.7
18.8
31.0
8.6
15.0
24.8
6.4
11.3
18.6
25
13.4
23.4
38.8
10.7
18.8
31.0
8.0
14.1
23.3
30
16.0
28.1
46.5
12.8
22.5
37.2
9.6
16.9
27.9
2.0
Table 20 - Variation in CO2 emissions (kg/ha) from diesel usage under different assumed hourly
consumption rates and work rates, with and without compaction
Uncompacted
Compacted
Litres
per
hour
1.0
Clay
1.5
2.0
1.0
Hours per ha
Silt
1.5
2.0
1.0
Sand or Peat
1.5
2.0
15
40.5
60.8
81.0
32.4
48.6
64.8
24.3
36.5
48.6
20
54.0
81.0
108.0
43.2
64.8
86.4
32.4
48.6
64.8
25
67.5
101.3
135.0
54.0
81.0
108.0
40.5
60.8
81.0
30
81.0
121.5
162.0
64.8
97.2
129.6
48.6
72.9
97.2
15
21.7
38.0
62.8
17.3
30.4
50.2
13.0
22.8
37.7
20
28.9
50.6
83.7
23.1
40.5
67.0
17.3
30.4
50.2
25
36.1
63.3
104.7
28.9
50.6
83.7
21.7
38.0
62.8
30
43.3
75.9
125.6
34.7
60.8
100.5
26.0
45.6
75.3
58
Nutrient losses
Compaction exacerbates nutrient losses through, for example, inhibiting uptake by the crop and
facilitating leaching and denitrification. Such nutrient losses impose off-farm environmental costs in
the form of water pollution and GHG emissions but also impose on-farm productivity costs in terms
of the value of lost nutrients. Lost nutrients are valued at cost to the farmer of £0.62/kg N, £0.68/kg
P and £0.52/kg K (Nix, 2011).
Mitigating compaction therefore offers the possibility of both improving on-farm productivity and
reducing environmental loadings. However, nutrient losses are highly variable over time and across
sites due to, for example, weather conditions, the nature of nutrient applications (e.g. timing,
intensity and form) and management practices. For the purposes of this exercise, nutrient losses
attributable to compaction have been assumed to be 20% on clays, 11% on silt, 2% on sand and 20%
on peat (pers. comm., Anil Graves, Cranfield University, 2012). For the assumed baseline nutrient
application rates, this equates to per hectare losses of N of 15.54 kg on clays and peat, 8.55 kg on silt
and 1.55kg on sand. Of the total N losses, 34% is assumed to be leached and 4% emitted as N 20
(pers. comm., Anil Graves, Cranfield University, 2012). N2O GHG emissions are multiplied by 310 to
convert to CO2e. 10 Significantly, the relative GWP weighting of N2O means that it dominates
estimates of CO2e arising from compaction and mitigation here – implying that improved estimation
of fuel usage estimates would be of less analytical GHG emission value than improved estimates of
nutrient losses.
Table 21 - Illustrative variation of leached N (kg/ha) under different assumed N applications rates,
rates of N loss from compacted soil and compacted area within a field.
Nutrient
loss rate
2%
2%
2%
5%
5%
5%
10%
10%
10%
20%
20%
20%
50%
50%
50%
Compacted
area
37%
42%
47%
37%
42%
47%
37%
42%
47%
37%
42%
47%
37%
42%
47%
150
0.38
0.43
0.48
0.94
1.07
1.20
1.89
2.14
2.40
3.77
4.28
4.79
9.44
10.71
11.99
N application rate (kg/ha)
175
200
225
0.44
0.50
0.57
0.50
0.57
0.64
0.56
0.64
0.72
1.10
1.26
1.42
1.25
1.43
1.61
1.40
1.60
1.80
2.20
2.52
2.83
2.50
2.86
3.21
2.80
3.20
3.60
4.40
5.03
5.66
5.00
5.71
6.43
5.59
6.39
7.19
11.01
12.58
14.15
12.50
14.28
16.07
13.98
15.98
17.98
10
250
0.63
0.71
0.80
1.57
1.79
2.00
3.15
3.57
4.00
6.29
7.14
7.99
15.73
17.85
19.98
As with diesel usage, an LCA perspective would also account for the GHG emissions generated in the
production and transportation of nitrogen prior to application on farm, but a narrower on-farm perspective is
adopted here.
59
Table 22 - Illustrative variation of CO2e (kg/ha) of N20 emitted under different assumed N
applications rates, rates of N loss from compacted soil and compacted area within a field.
N application rate (kg/ha)
Nutrient Compacted
loss rate
area
150
175
200
225
250
2%
37%
13.76
16.06
18.35
20.65
22.94
2%
42%
15.62
18.23
20.83
23.44
26.04
2%
47%
17.48
20.40
23.31
26.23
29.14
5%
37%
34.41
40.15
45.88
51.62
57.35
5%
42%
39.06
45.57
52.08
58.59
65.10
5%
47%
43.71
51.00
58.28
65.57
72.85
10%
37%
68.82
80.29
91.76
103.23
114.70
10%
42%
78.12
91.14
104.16
117.18
130.20
10%
47%
87.42
101.99
116.56
131.13
145.70
20%
37%
137.64
160.58
183.52
206.46
229.40
20%
42%
156.24
182.28
208.32
234.36
260.40
20%
47%
174.84
203.98
233.12
262.26
291.40
50%
37%
344.10
401.45
458.80
516.15
573.50
50%
42%
390.60
455.70
520.80
585.90
651.00
50%
47%
437.10
509.95
582.80
655.65
728.50
The effectiveness of mitigation options in terms of reducing nutrient losses is likely to depend on a
number of factors. For example, whether mitigation activities alone overcome water-logging
problems and whether other changes are made to the nature of nutrient applications. However, for
simplicity, the effectiveness assumed in relation to overcoming yield penalties attributable to
compaction is also assumed to relate to nutrient losses. Hence, with the exception of sub-soiling, all
options are assumed to eliminate the estimated nutrient losses. However, unlike for yields, no
allowance is made for further possible productivity gains that may arise. That is, nutrient savings are
capped at the estimated nutrient losses attributable to compaction. Tables 21 &22 present some
variation around these assumptions.
Illustrative Cost curves
Using the assumptions outline above, illustrative cost curves were constructed first for winter wheat
as an enterprise for which relatively good data are available. These curves were then modified
slightly to consider potatoes and onions as other crops affected by compaction. Although the
precise figures presented may be subject to considerable uncertainty, the broad patterns revealed
are informative.
Wheat
For wheat, the changes in gross margin achieved under different management options are shown in
Table 23. Although sub-soiling and ploughing are assumed optimistically to counter any yield loss
attributable to compaction, they incur additional operational costs that outweigh the gain in yield
revenue and savings in nutrient losses achieved. Hence they have a negative impact on enterprise
gross margin. The ineffectiveness of non-targetted subsoiling does not appear to be appreciated by
farmers, as evident from its widespread use. Assuming a lower (and more realistic) level of efficacy,
60
the effect on gross margins would be even worse. By contrast, by limiting additional operational
costs and only addressing areas of concern rather than entire fields, targeted sub-soiling has a
positive effect on gross margin – apart from on sand where the effect is more or less neutral.
Assuming a lower level of efficacy would weaken this result, but the option would still rank higher
than non-targeted sub-soiling or ploughing.
However, avoidance options of using low ground pressure tyres, tracked vehicles or Controlled
Traffic Farming (CTF) all deliver superior gross margin gains. This is essentially due to achieving
higher yields and thus higher revenues – although savings on nutrients and (for CTF) diesel also play
a role. The performance gap widens if alleviation options are assumed to be less than 100%
effective. In all cases, the “best” results relate to clayey soils since these are characterised by worse
compaction problems. Avoidance options outdo alleviation options by virtue of having lower option
costs, higher ouput gains and for CTF only further fuel savings.
Table 23 - Changes (£/ha) in wheat output, inputs and gross margin under alternative options
Type
Management option
£/ha change
Alleviation
Sub-soiling (general)
Alleviation
Alleviation
Avoidance
Avoidance
Avoidance
Sub-soiling (targeted)
Plough
Low ground pressure tyres
Tracked tractors
CTF
Option cost
Clay
£56.10
Silt
£51.90
Sand
£47.70
Peat
£47.70
Input saving
£12.49
£6.87
£1.25
£12.49
Output gain
£30.09
£21.24
£18.17
£18.88
GM change
Option cost
-£13.52
£23.56
-£23.79
£21.80
-£28.28
£20.03
-£16.33
£20.03
Input saving
£12.49
£6.87
£1.25
£12.49
Output gain
£30.09
£21.24
£18.17
£18.88
GM change
Option cost
£19.02
£54.90
£6.31
£46.50
-£0.61
£38.10
£11.34
£38.10
Input saving
£12.49
£6.87
£1.25
£12.49
Output gain
£30.09
£21.24
£18.17
£18.88
GM change
Option cost
-£12.32
£3.58
-£18.39
£3.58
-£18.68
£3.58
-£6.73
£3.58
Input saving
£12.49
£6.87
£1.25
£12.49
Output gain
£66.20
£53.10
£45.43
£47.20
GM change
Option cost
£75.11
£21.00
£56.39
£21.00
£43.10
£21.00
£56.11
£21.00
Input saving
£12.49
£6.87
£1.25
£12.49
Output gain
£66.20
£53.10
£45.43
£47.20
GM change
£57.69
£38.97
£25.68
£38.69
Option cost
Input saving
£0.00
£23.90
£0.00
£14.22
£0.00
£4.54
£0.00
£15.78
Output gain
£90.27
£74.34
£63.60
£66.08
GM change
£114.17
£88.56
£68.14
£81.86
Note: Assuming 100% alleviation of yield penalties and nutrient losses, with further yield gains under
avoidance options plus fuel savings under only CTF. Hence differences in GM changes are driven mainly by
relative changes to output values and the respective option costs.
61
Table 24 and Figure 19 show how changes in gross margin translate into the cost per kg of nitrogen
not leached. That is, reducing compaction leads to less leaching of nitrogen but the cost of achieving
this reduction depends on how the management option causing it has also affected enterprise
profitability. All options reduce the level of leaching but since they have different effects on gross
margin, the cost per kg not leached does vary.
Specifically, general sub-soiling and ploughing incur costs per kg not leached whilst all other options
(except targeted sub-soiling on sand) combine lower leaching with higher profitability – meaning
that they offer win-win possibilities for farmers and for the environment. Lower efficacy
assumptions weaken these results, but the avoidance options still dominate. The results for sand
are influenced strongly by the low level of leaching attributable to compaction, which produces
extreme results per kg.
Table 24 - Cost per kg N leaching avoided from compaction mitigation under winter wheat
Management option
Sub-soiling (general)
Sub-soiling (targeted)
Plough
Low ground pressure tyres
Tracked tractors
CTF
Clay
£3
-£4
£2
-£14
-£11
-£22
62
£/kg N not leached
Silt
Sand
£8
£54
-£2
£1
£6
£35
-£19
-£82
-£13
-£49
-£30
-£129
Peat
£3
-£2
£1
-£11
-£7
-£15
Cost per kg leaching avoided
£100.00
£50.00
Clay
£0.00
Silt
Sand
-£50.00
Peat
-£100.00
-£150.00
Figure 19: Cost per kg N leaching avoided from compaction mitigation under winter wheat
Table 25 and Figure 20 show how changes in gross margin translate into the cost per kg of CO2e not
emitted. Emissions are reduced by lowering net diesel use and by reducing N2O emissions. Although
the volume of the latter is relatively small, its high GWP weighting means that it dominates the GHG
emissions here. Again, results on sand fluctuate between extremes due to the relatively low level of
emissions involved.
Not all options reduce GHG emissions, notably sub-soiling and ploughing on sand and ploughing on
silt. This reflects lower levels of emissions to start with meaning that savings are relatively modest
whilst the extra diesel used by additional field operations more than offsets these. Again, N2O
dominates estimates of CO2e arising from compaction and mitigation. On other soils, general subsoiling and ploughing do reduce overall emissions, but their impact on enterprise gross margin
means that there is a cost per t. By contrast, low ground pressure tyres, tracked vehicles and CTF all
have strongly negative costs per t. Hence, again, there is scope for win-win options for farm
profitability and environmental quality.
Table 25 - Cost per t CO2e not emitted from compaction mitigation under winter wheat
Management option
Sub-soiling (general)
Sub-soiling (targeted)
Plough
Low ground pressure tyres
Tracked tractors
CTF
£/t CO2e not emitted
Clay
Silt
Sand
£121
£578
-£120
-£80
£401
-£390
-£532
-£2,237
-£299
-£368
-£1,333
-£482
-£659
-£2,132
63
Peat
£113
-£66
£70
-£291
-£201
-£399
Cost per t CO2e avoided
£1,000.00
£500.00
£0.00
Clay
-£500.00
Silt
Sand
-£1,000.00
Peat
-£1,500.00
-£2,000.00
-£2,500.00
Figure 20: Cost per t CO2e avoided from compaction mitigation under winter wheat
Using estimates of wheat areas on each soil type (pers. comm., Anil Graves, Cranfield University,
2012), the GHG emission figures can be aggregated crudely to the national level. Table 26 below
shows this.
Table 26 - Total GHG reductions from compaction mitigation under winter wheat
Management option
Sub-soiling (general)
Sub-soiling (targeted)
Plough
Low ground pressure tyres
Tracked tractors
CTF
Clay
145.3
206.4
39.9
250.6
250.6
307.8
kt CO2e not emitted
Silt
Sand
10.3
0
19.6
0
0
0
26.4
5.9
26.4
5.9
33.5
9.7
Peat
3.6
4.3
2.4
4.8
4.8
5.1
The potential savings is greatest on clays due to their dominance of the wheat area but also greater
susceptibility to compaction. Conversely, the potential savings are least on sand due to its low area.
Importantly, since each management option is addressing the same compaction problem, total
savings cannot be summed down a column. That is, unlike mitigation cost curves produced
elsewhere where different sources of GHG emissions are being tackled by different mitigation
options, the options considered here are not additive in nature – once compaction on a given parcel
of land has been addressed, the same savings cannot be achieved again by another means.
Potatoes
For potatoes, the changes in gross margin achieved under different management options are shown
in Table 27. With the exception of deep inversion tillage, all management options achieve improved
gross margins – essentially because then yields and yield gains are higher than for wheat. In the
case of sub-soiling, additional operational costs are more than outweighed by the gain in revenue
and savings in nutrient losses achieved. In the case of deep inversion tillage, no yield gains are
64
assumed and only a modest saving on fuel usage. However, avoidance options still outperform
alleviation options. Assuming a lower level of efficacy would weaken this result, but the options
would still rank higher than sub-soiling or deep non-inversion.
In all cases, the “best” results relate to peat soils since these are characterised by the highest
baseline yields and thus greatest changes in yield revenues.
Table 27 - Changes (£/ha) in potato output, inputs and gross margin under alternative options
Type
Management option
£/ha change
Alleviation
Sub-soiling (general)
Alleviation
Alleviation
Avoidance
Avoidance
Avoidance
Sub-soiling (targeted)
Deep non-inversion
Low ground pressure tyres
Tracked tractors
CTF
Option cost
Clay
£56.10
Silt
£51.90
Sand
£47.70
Peat
£47.70
Input saving
£16.23
£8.93
£1.62
£16.23
Output gain
£1,102.50
£1,012.50
£922.50
£1,170.00
GM change
£1,062.63
£969.53
£876.42
£1,138.53
Option cost
£23.56
£21.80
£20.03
£20.03
Input saving
£16.23
£8.93
£1.62
£16.23
Output gain
£1,102.50
£1,012.50
£922.50
£1,170.00
GM change
£1,095.17
£999.63
£904.09
£1,166.20
Option cost
£33.30
£30.50
£27.70
£27.70
Input saving
£2.94
£1.89
£0.98
£0.84
Output gain
£0.00
£0.00
£0.00
£0.00
GM change
-£30.36
-£28.61
-£26.72
-£26.86
Option cost
£3.58
£3.58
£3.58
£3.58
Input saving
£16.23
£8.93
£1.62
£16.23
Output gain
£1,323.00
£1,215.00
£1,107.00
£1,404.00
GM change
£1,335.65
£1,220.35
£1,105.04
£1,416.65
Option cost
£21.00
£21.00
£21.00
£21.00
Input saving
£16.23
£8.93
£1.62
£16.23
Output gain
£1,323.00
£1,215.00
£1,107.00
£1,404.00
GM change
£1,318.23
£1,202.93
£1,087.62
£1,399.23
Option cost
Input saving
£0.00
£75.03
£0.00
£46.73
£0.00
£21.22
£0.00
£33.03
Output gain
£1,470.00
£1,350.00
£1,230.00
£1,560.00
£1,545.03
£1,396.73 £1,251.22 £1,593.03
GM change
Note: Assuming 100% alleviation of yield penalties and nutrient losses, with further yield gains under
avoidance options plus fuel savings under only CTF. Hence differences in GM changes are driven mainly by
relative changes to output values and the respective option costs.
Table 28 and Figure 21 show how changes in gross margin translate into the cost per kg of nitrogen
not leached. That is, reducing compaction leads to less leaching of nitrogen but the cost of achieving
this reduction depends on how the management option causing it has also affected enterprise
profitability. All options apart from deep inversion tillage reduce the level of leaching but since they
have different effects on gross margin, the cost per kg not leached does vary.
As with wheat, there are win-win possibilities for farmers and for the environment. Lower efficacy
assumptions weaken these results, but the avoidance options still rank higher. The results for sand
65
are influenced strongly by the low level of leaching attributable to compaction, which produces
extreme results per kg.
Table 28 - Cost per kg N leaching avoided from compaction mitigation under potatoes
Management option
Sub-soiling (general)
Sub-soiling (targeted)
Deep non-inversion
Low ground pressure tyres
Tracked tractors
CTF
£/kg N not leached
Clay
Silt
Sand
-£207
-£343 -£1,705
-£213
-£354 -£1,759
Peat
-£221
-£227
-£260
-£256
-£301
-£276
-£272
-£310
66
-£432
-£425
-£494
-£2,150
-£2,116
-£2,434
Cost per kg leaching avoided
£0
-£500
Clay
-£1,000
Silt
-£1,500
Sand
-£2,000
Peat
-£2,500
-£3,000
Figure 21 - Cost per kg N leaching avoided from compaction mitigation under potatoes
Table 29 and Figure 22 show how changes in gross margin translate into the cost per kg of CO2e not
emitted. Emissions are reduced by lowering net diesel use and by reducing N2O emissions. Although
the volume of the latter is relatively small, its high GWP weighting means that it dominates the GHG
emissions here. Again, results on sand fluctuate between extremes due to the relatively low level of
emissions involved.
Not all options reduce GHG emissions, notably sub-soiling on sand and deep inversion tillage on all
soils (due to assuming no effect on yields and therefore N20 emissions). This reflects lower levels of
emissions to start with meaning that savings are relatively modest whilst the extra diesel used by
additional field operations more than offsets these. However, emission reductions are achieved on
all other soils and on sand by other options. Indeed all costs are strongly negative. Hence, again,
there is scope for win-win options for farm profitability and environmental quality.
Table 29 - Cost per t CO2e not emitted from compaction mitigation under potatoes
Management option
Sub-soiling (general)
Sub-soiling (targeted)
Deep non-inversion
Low ground pressure tyres
Tracked tractors
CTF
Clay
£/t CO2e not emitted
Silt
Sand
Peat
-£9,979
-£25,302
-£8,197
-£7,136
-£13,170
-£6,980
-£7,124
-£11,834
-£58,939
-£7,556
-£7,031
-£11,665
-£58,010
-£7,463
-£3,729
-£5,611
-£13,262
-£6,314
67
Cost per t CO2e avoided
£0
-£10,000
-£20,000
Clay
-£30,000
Silt
-£40,000
Sand
Peat
-£50,000
-£60,000
-£70,000
Figure 22 - Cost per t CO2e avoided from compaction mitigation under potatoes
Using estimates of potato areas on each soil type (pers. comm., Anil Graves, Cranfield University,
2012), the GHG emission figures can be aggregated crudely to the national level. Table 30 below
shows this.
Table 30 - Total GHG reductions from compaction mitigation under potatoes
Management option
Sub-soiling (general)
Sub-soiling (targeted)
Deep inversion tillage
Low ground pressure tyres
Tracked tractors
CTF
Clay
5.5
8.0
0.0
9.7
9.7
21.5
kt CO2e not emitted
Silt
Sand
1.2
0.0
2.4
0.0
0.0
0.0
3.3
0.8
3.3
0.8
7.9
3.8
Peat
0.8
1.0
0.0
1.1
1.1
1.4
As with wheat, the potential savings is greatest on clays due to their dominance of the potato area
but also greater susceptibility to compaction – but the totals are less than for wheat since wheat
occupies a much greater area. Again it is important to note that since each management option is
addressing the same compaction problem, total savings cannot be summed down a column. That is,
unlike mitigation cost curves produced elsewhere where different sources of GHG emissions are
being tackled by different mitigation options, the options considered here are not additive in nature
– once compaction on a given parcel of land has been addressed, the same savings cannot be
achieved again by another means.
Onions
For onions, the changes in gross margin achieved under different management options are shown in
Table 31. Although not as impressive as for potatoes, all management options (apart from deep
68
inversion tillage) achieve improved gross margins – essentially because the yields and yield gains are
higher than for wheat. In the case of sub-soiling, additional operational costs are more than
outweighed by the gain in revenue and savings in nutrient losses achieved. In the case of deep
inversion tillage, no yield effect is assumed and only a modest reduction in diesel usage. However,
avoidance options still outperform alleviation options. Assuming a lower level of efficacy would
weaken this result, but the options would still rank higher than sub-soiling or deep non-inversion.
In all cases, the “best” results relate to peat soils since these are characterised by the highest
baseline yields and thus greatest changes in yield revenues.
Table 31 - Changes (£/ha) in onion output, inputs and gross margin under alternative options
Type
Management option
£/ha change
Alleviation
Sub-soiling (general)
Alleviation
Alleviation
Avoidance
Avoidance
Avoidance
Sub-soiling (targeted)
Deep non-inversion
Low ground pressure tyres
Tracked tractors
CTF
Option cost
Clay
£56.10
Silt
£51.90
Sand
£47.70
Peat
£47.70
Input saving
£16.23
£8.93
£1.62
£16.23
Output gain
£600.00
£600.00
£600.00
£720.00
GM change
£560.13
£557.03
£553.92
£688.53
Option cost
£23.56
£21.80
£20.03
£20.03
Input saving
£16.23
£8.93
£1.62
£16.23
Output gain
£600.00
£600.00
£600.00
£720.00
GM change
£592.67
£587.13
£581.59
£716.20
Option cost
£33.30
£30.50
£27.70
£27.70
Input saving
£1.30
£0.77
£0.63
£0.35
Output gain
£0.00
£0.00
£0.00
£0.00
GM change
-£32.01
-£29.73
-£27.07
-£27.35
Option cost
£3.58
£3.58
£3.58
£3.58
Input saving
£16.23
£8.93
£1.62
£16.23
Output gain
£720.00
£720.00
£720.00
£864.00
GM change
£732.65
£725.35
£718.04
£876.65
Option cost
£21.00
£21.00
£21.00
£21.00
Input saving
£16.23
£8.93
£1.62
£16.23
Output gain
£720.00
£720.00
£720.00
£864.00
GM change
£715.23
£707.93
£700.62
£859.23
Option cost
Input saving
£0.00
£42.13
£0.00
£24.33
£0.00
£14.22
£0.00
£23.23
Output gain
£800.00
£800.00
£800.00
£960.00
£842.13
£824.33
£814.22
£983.23
GM change
Note: Assuming 100% alleviation of yield penalties and nutrient losses, with further yield gains under
avoidance options plus fuel savings under only CTF. Hence differences in GM changes are driven mainly by
relative changes to output values and the respective option costs.
Table 32 and Figure 22 show how changes in gross margin translate into the cost per kg of nitrogen
not leached. That is, reducing compaction leads to less leaching of nitrogen but the cost of achieving
this reduction depends on how the management option causing it has also affected enterprise
profitability. All options apart from deep inversion tillage reduce the level of leaching but since they
have different effects on gross margin, the cost per kg not leached does vary – but all are negative,
69
meaning that they offer win-win possibilities for farmers and for the environment. Lower efficacy
assumptions weaken these results, but the avoidance options still dominate. The results for sand
are influenced strongly by the low level of leaching attributable to compaction, which produces
extreme results per kg.
Table 32 - Cost per kg N leaching avoided from compaction mitigation under onions
Management option
Sub-soiling (general)
Sub-soiling (targeted)
Deep non-inversion
Low ground pressure tyres
Tracked tractors
CTF
£/kg N not leached
Clay
Silt
Sand
-£109
-£197 -£1,078
-£115
-£208 -£1,131
Peat
-£134
-£139
-£143
-£139
-£164
-£171
-£167
-£191
70
-£257
-£250
-£292
-£1,397
-£1,363
-£1,584
Cost per kg leaching avoided
£0
-£200
-£400
-£600
Clay
-£800
Silt
-£1,000
Sand
-£1,200
Peat
-£1,400
-£1,600
-£1,800
Figure 23: Cost per kg N leaching avoided from compaction mitigation under onions
Table 33 and Figure 23 show how changes in gross margin translate into the cost per kg of CO2e not
emitted. Emissions are reduced by lowering net diesel use and by reducing N2O emissions. Although
the volume of the latter is relatively small, its high GWP weighting means that it dominates the GHG
emissions here. Again, results on sand fluctuate between extremes due to the relatively low level of
emissions involved.
Not all options reduce GHG emissions, notably sub-soiling and deep non-inversion on all soils. For
sand, this reflects lower levels of emissions to start with meaning that savings are relatively modest
whilst the extra diesel used by additional field operations more than offsets these. For deep noninversion tillage it reflects the assumed absence of any yield gains and thus any reduction in nutrient
losses, including N2O emissions. However, emission reductions are achieved on all other soils and on
sand by other options. Indeed all costs are strongly negative.11 Hence, again, there is scope for winwin options for farm profitability and environmental quality.
Table 33 - Cost per t CO2e not emitted from compaction mitigation under onions
Management option
Sub-soiling (general)
Sub-soiling (targeted)
Deep non-inversion
Low ground pressure tyres
Tracked tractors
CTF
£/t CO2e not emitted
Clay
Silt
Sand
Peat
-£5,260
-£14,537
-£4,957
-£3,862
-£7,735
-£4,287
-£3,908
-£7,034
-£38,298
-£4,676
-£3,815
-£6,865
-£37,369
-£4,583
-£2,930
-£5,072
-£12,090
-£4,584
11
The magnitude of cost savings per unit of emission avoided is affected by both the volume of emissions
saved and the gain in Gross Margin, leading to some very high per unit values when the volumes are relatively
low. Interpretation of results may be easier if it is accepted that environmental loadings can be reduced at no
net cost to farm profitability and the significance of different options is judged in terms of their potential
impact on aggregate emission savings.
71
Cost per t CO2e avoided
£0
-£5,000
-£10,000
-£15,000
Clay
-£20,000
Silt
-£25,000
Sand
-£30,000
Peat
-£35,000
-£40,000
-£45,000
Figure 24 - Cost per t CO2e avoided from compaction mitigation under onions
Using estimates of onion areas on each soil type (pers. comm., Anil Graves, Cranfield University,
2012), the GHG emission figures can be aggregated crudely to the national level. Table 34 below
shows this.
Table 34 - Total GHG reductions from compaction mitigation under onions
Management option
Sub-soiling (general)
Sub-soiling (targeted)
Deep inversion tillage
Low ground pressure tyres
Tracked tractors
CTF
Clay
1.9
2.7
0.0
3.3
3.3
5.0
kt CO2e not emitted
Silt
Sand
0.3
0.0
0.6
0.0
0.0
0.0
0.8
0.2
0.8
0.2
1.2
0.8
Peat
0.1
0.1
0.0
0.1
0.1
0.2
As with wheat, the potential savings is greatest on clays due to their dominance of the onion area
but also greater susceptibility to compaction – but the totals are less than for wheat since wheat
occupies a much greater area. Again it is important to note that since each management option is
addressing the same compaction problem, total savings cannot be summed down a column. That is,
unlike mitigation cost curves produced elsewhere where different sources of GHG emissions are
being tackled by different mitigation options, the options considered here are not additive in nature
– once compaction on a given parcel of land has been addressed, the same savings cannot be
achieved again by another means
72
Discussion
Despite a general consensus in the literature and amongst experts regarding the qualitative nature
of compaction effects and mitigation options, detailed data sufficient to differentiate across
different soil types or weather conditions, or indeed across different farming systems and
managerial abilities, remain scarce. Consequently, attempting to estimate cost-effectiveness, even
for purely illustrative purposes, requires deploying a number of assumptions.
Hence, inter alia, it is necessary to specify the negative effects of compaction in terms of lower crop
yields, higher fuel usage and nutrient losses. Equally, to determine the cost-effectiveness of
different management responses to compaction, it is necessary to specify the efficacy of
management in counteracting each of the negative effects. Assumed values for such parameters
are subject to considerable uncertainty given acknowledged variation in site conditions both
spatially and over time. Such uncertainties are amplified by variation in market prices for inputs and
outputs.
Nevertheless, it is possible to draw some general conclusions about the cost-effectiveness of
mitigation options. First, the higher the yield, fuel and nutrient losses attributable to compaction,
the greater the likelihood that any given mitigation option will be cost-effective, even more so if
prevailing input and output prices are high. Second, the greater the efficacy of any given option at
countering negative effects, the greater the likelihood of it being cost-effective - again more so if the
negative effects imposed significant costs. Third, due to additional operational costs, alleviating
compaction tends to be more costly than avoiding it in the first place. Hence options such as low
ground pressure tyres or CTF are likely to be more cost-effective than options such as untargeted
sub-soiling. Indeed, options such as CTF appear to deliver significant productivity gains at negative
net on-farm cost – in which case adoption would simultaneously improve farm profitability and
reduce environmental loadings.
The validity of these general conclusions and the applicability of them to specific farm-situations
could be tested by further empirical research.
If options such as CTF do indeed offer win-win
situations, apparently low uptake rates may indicate barriers to adoption such as a lack of awareness
or confidence amongst farmers - suggesting behavioural change research already underway for
other GHG mitigation options could usefully be extended to include soil compaction issues.
Soil compaction and climate change
Agriculture is both a contributor to climate change and subject to the impacts of climate change.
Soil compaction on farms also displays this dual relationship with climate change.
First, compaction risks and thus the need for management adaptations to address on-farm
productivity may be affected by changing climatic conditions. In particular, although the type and
condition of a soil affects the potential for compaction, all soils are more prone to compaction if
wet. Specifically, compaction risks are highest when soil water content is at or above field
capacity. Conversely, soils are more resistant to compaction under drier conditions.
Consequently compaction risks and impacts identified in this report may increase or decrease
depending on shifts in expected rainfall patterns. Although subject to some uncertainty, climate
73
change projections12 suggest that mean winter rainfall will probably be higher than currently
whilst mean summer rainfall will be lower. This may suggest higher compaction risks in Spring
and Autumn when planting operations are most likely, but lower compaction risks during
harvesting periods. Given that compaction often occurs with the first few passes of heavy
machinery, reduced summer risks are unlikely to offset higher winter risks.
However,
compaction risks will remain highly context-specific in terms of local soil types, weather
conditions and management systems.
Second, through impacts both on fuel consumption and on nutrient losses, soil compaction
contributes to GHG emissions from agriculture. Precise quantification of this contribution is
difficult, but it is unlikely to be trivial (pers. comm., Anil Graves, Cranfield University, 2012).
Moreover, given challenging targets for reducing GHG emissions, all GHG sources are subject to
scrutiny.
On the basis of the findings presented in this report, mitigation of GHG emissions attributable to
soil compaction is both technically feasible and economically cost-effective. That is, with some
exceptions, most management options deliver reductions in GHG emissions – mainly through
reducing N2O losses from the soil rather than fuel savings, although avoiding compaction on
large areas has the potential to reduce both. The precise estimates of cost-effectiveness are
subject to considerable uncertainty and are sensitive to underlying assumptions, but the
estimated aggregate GHG emission savings of up to around 350kt CO 2e from winter wheat
production equate to around 0.7% of total agricultural emissions, 13 implying perhaps 1-2%
across all arable enterprises.
Moreover, unlike many other agricultural GHG mitigation options (Moran et al., 2008), the
private net cost to farmers of adopting management that reduces emissions is negative. That is,
there are win-win possibilities for simultaneously improving farm profits and reducing GHG
emissions. If such management options are not being adopted, if compaction remains
unaddressed, then options for policy support may need to be reviewed.
Policy support for mitigating soil compaction
The effects of soil compaction feed into several policy areas, including enhancing agricultural
efficiency, reducing diffuse water pollution and combating climate change. Although this project
explored technical and cost-effectiveness aspects of mitigation rather than policy measures, some
general observations can be made.
A wide range of policy mechanisms are available, but may be characterised broadly as incentivising,
obliging or urging land managers to alter their activities – as carrots, sticks and sermons
(Bemelmans-Videc et al., 2007). More detailed classifications break these down further into, for
example: grants and subsidies or tax breaks; prescriptive and proscriptive regulatory controls,
licenses and permits; and information provision, training and capacity building (Gunningham &
12
13
For example, see http://ukclimateprojections.defra.gov.uk/content/view/1311/499/
See http://www.defra.gov.uk/publications/files/pb13622-ghg-emission-projections.pdf
74
Grabosky, 1998; Goulder & Parry, 2008). Each has advantages and disadvantages, although in
practice some combination of individual policy measures is typically used.
In cases where win-win opportunities for improving farm profitability and environmental quality are
not being adopted, lack of adoption may reflect constraints on land managers’ behaviour arising
from a lack of awareness or incorrect information and/or social considerations such as household or
peer group approval on changing farming practices and systems. As such, further incentives in the
form of grants and subsidies are unlikely to be effective at encouraging adoption since they do not
address the root cause of the lack of uptake. Equally, regulatory controls may be resisted and –
whilst possibly effective – may incur significant costs for land managers and administrative bodies
((Pannell, 2008; Barnes et al, 2009). Hence attention is directed increasingly towards facilitating
behaviour change14 through supporting land managers by providing information and building (social)
capacity. For example through, publicity campaigns, simple indicators of risk & success, provision of
advice or training, demonstration projects and forums for discussion (Pannel & Vanclay, 2011). Such
approaches may be merited in the case of soil compaction given the range of ecosystem functions
impacted.
However, support for encouraging the spread of best practice in mitigating soil compaction cannot
operate in a policy vacuum.
That is, agriculture is already subject to considerable policy
interventions. For example, perhaps most notably, through the Common Agricultural Policy (CAP)
but also via regulatory measures such as the Water Framework Directive (WFD).
Reforms to the CAP are currently out to consultation, but soil compaction issues could potentially be
addressed through both Pillar I and Pillar II measures. For example, through inclusion in crosscompliance or GAEC, or via RDR measures aimed at improving competitiveness or agri-environment
measures. Equally, existing aspects of the WFD could perhaps be used to emphasise soil compaction
issues. For example, by emphasising the contribution of compaction to diffuse pollution. However,
the appropriateness of such approaches may be questionable if the barriers to uptake of mitigation
options are a lack of awareness and/or social: a greater emphasis on extension-type activities may
be required.
14
See also http://archive.defra.gov.uk/sustainable/government/documents/change-behaviour-model.pdf
75
References
1. Abadi Ghadim, A., Kingwell, R. and Pannell, D. 1991. An economic evaluation of deep tillage to
reduce soil compaction on crop-livestock farms in Western Australia Agricultural Systems,
Volume 37, Issue 3, 1991, Pages 291-307
2. ADAS. 1996. Farmland Cultivation Practices: Survey Report. ADAS Market Research Team on
behalf of MAFF Environmental Protection Division. 44 pp.
3. Alakuku, L., Weibkopf, P., Chamen, W.C.T, Tijink, F.G, van der Linden, J.P., Pires, S.,
Sommer, C., and Spoor, G. 2003. Prevention strategies for field traffic-induced
subsoil compaction: A review. Part 1. Machine/soil interactions, Soil and Tillage
Res., 73,145 - 160.
4. Allen, R.R. & Musick, J.T. (2001). Deep ripping and blocked furrow effects on lower 1/3 furrow
irrigation infiltration. Applied Engineering in Agriculture, 17: 41-48.
5. Andersen, E., Elbersen, B., Godeshalk, F., Verhoog, D., 2007. Farm management indicators and
farm typologies as a basis for assessments in changing policy environment. Journal of
Environmental Management 82, 353-362.
6. Ansorge, D. and Godwin, R.J. 2007. The effect of tyres and a rubber track at high axle loads on
soil compaction, Part 1: Single axle-studies. Biosystems Engineering, 98: 115-126.
7. Ansorge, D. and Godwin, R.J. 2008. The effect of tyres and a rubber track at high axle loads on
soil compaction, Part 2: Multi-axle machine studies. Biosystems Engineering, 99: 338-347.
8. Arndt, W. and C.W. Rose. 1966. Traffic Compaction of Soil and Tillage Requirements.
Journal of Agricultural Engineering Research 11:170-187.
9. Arvidsson, J. and Keller, T. 2007. Soil stress as affect by wheel load and tyre inflation pressure.
Soil & Tillage Research, 96: 284–291.
10. Audsley, E. 1981. An arable farm model to evaluate the commercial viability of new machines
or techniques. Journal of Agricultural Engineering Research, 11: 182-187.
11. Azeez, G. (2009). Soil carbon and organic farming. A review of the evidence on the relationship
between agriculture and soil carbon sequestration, and how organic farming can contribute to
climate change mitigations and adaptation. Soil Association, South Plaza, Marlborough Street,
Bristol BS1 3NX.
12. Ball, B.C., Horgon, G.W. and Parker, J.P. 2000. Short-rang spatial variation of nitrous oxide
fluxes in relation to compaction and straw residues. European Journal of Soil Science, 51: 607616.
13. Ball, B.C., Parker, J.P. and Scott, A. 1999a. Soil and residue management effects on cropping
conditions and nitrous oxide fluxes under controlled traffic in Scotland. 2. Nitrous oxide, soil N
status and weather. Soil and Tillage Research, 52 (3-4): 191-201.
14. Ball, B.C., Scott, A. and Parker, J.P. 1999b. Field N2O, CO2 and CH4 fluxes in relation to tillage,
compaction and soil quality in Scotland. Soil and Tillage Research, 53, (1): 29-39.
15. Ball, B.C., Crichton, I. and Horgan, G.W. 2008. Dynamics of upward and downward N2O and
CO2 fluxes in ploughed or no-tilled soils in relation to water-filled pore space, compaction and
crop presence. Soil & Tillage Research, 101: 20-30.
16. Barnes, A.P., Willock, J. Hall, C. and Toma, L. (2009). Farmer perspectives and practices
regarding water pollution control programmes in Scotland. Agricultural Water Management,
96, pp. 1715-1722
17. Bateman, I., Mace, G., Fezzi, C., Atkinson, G. and Turner, K.. 2011. Economic Analysis for
Ecosystem Service Assessments. Environmental and Resource Economics 48:177-218.
76
18. Batey,T. 2009. Soil compaction and soil management - a review. Soil Use and Management
25:335-345.
19. Bathgate, A. and Pannell, D. 2002. Economics of deep-rooted perennials in Western Australia.
Agricultural Water Management 53, 117–132
20. Bemelmans-Videc, M-L., Rist, R.C. & Vedung, E. (Eds, 2007) Carrots, Sticks & Sermons. Policy
Instruments and Their Evaluation. Transaction Publishers, London.
21. Bennie, A.T.P. and Botha, F.J.P. 1986. Effect of deep tillage and controlled traffic on root
growth, water use efficiency and yield of irrigated maize and wheat. Soil & Tillage Research, 7
(1/2): 85–95.
22. Bergtold, J. S., Raper, R. L. and Schwab, E. B. 2009. The Economic Benefit of Improving the
Proximity of Tillage and Planting Operations in Cotton Production with Automatic Steering.
Applied Engineering in Agriculture 25 (2):133-143.
23. Bergtold, J.S., Raper, R.L. and Schwab, E.B.. 2009. The Economic Benefit of Improving the
Proximity of Tillage and Planting Operations in Cotton Production with Automatic Steering.
Applied Engineering in Agriculture 25:133-143.
24. Beylich, A., Oberholzer, H-R., Schrader, S., Höper, H., Wilke, B-M. 2010. Evaluation of soil
compaction effects on soil biota and soil biological processes in soils. Soil & Tillage Research,
109: 133-143.
25. Bochtis, D.D., Sørensen , C.G., Busato, P., Hameed, I.A., Rodias, E., Green, O., Papadakis, G.
2010. Tramline establishment in controlled traffic farming based on operational machinery
cost, Biosystems Engineering 107: 221-231
26. Boone, F.R. and Veen, B.W. 1994. Mechanisms of crop responses to soil compaction. In B.D.
Soane & C. van Ouwerkerk, eds. Soil compaction in crop production pp. 237–264. Amsterdam,
Elsevier Science B.V. 662 pp.
27. Botta, G.F., Jorajuria, D., Rosatto, H., Ferrero, C. (2006). Light tractor traffic frequency on soil
compaction in the Rolling Pampa region of Argentina. Soil & Tillage Research, 86: 9-14.
28. Boydell, B. and Boydell, C. 2003. A decade of directions: trials and tribulations of precision
agriculture and controlled traffic at ‘Marinya’. Keynote address. Proceedings of the
International Soil Tillage Research Organisation 16th Triennial conference, Brisbane, 13–18
July, pp 196–207.
29. Campbell, D.J., Dickson, J.W., Ball, B.C. and Hunter, R. 1986. Controlled seedbed traffic after
ploughing or direct drilling under winter barley in Scotland, 1980–1984. Soil & Tillage
Research, 8: 3–28.
30. Catto, G. 1976. Optimal production from a blesbok herd.Journal of Environmental
Management 4:105–121.
31. Chamen, W.C.T. 2011. The effects of low and controlled traffic systems on soil physical
properties, yields and the profitability of cereal crops on a range of soil types. PhD thesis,
School of Applied Sciences, Cranfield University, Bedfordshire, UK.Unpublished. 290 pp.
32. Chamen, W.C.T. and Audsley, E. 1993. A study of the comparative economics of conventional
and zero traffic systems for arable crops. Soil & Tillage Research, 25: 369–390.
33. Chamen, W.C.T. and Cavalli, R. 1994. The effect of soil compaction on mole plough draught.
Soil & Tillage Research, 32: 303–311.
34. Chamen, W.C.T. and Longstaff, D.J. 1995. Traffic and tillage effects on soil conditions and crop
growth on a swelling clay soil. Soil Use & Management, 11: 168–176.
35. Chamen, W.C.T., Watts, C.W., Leede, P.R. and Longstaff, D.J. 1992a. Assessment of a wide
span vehicle (gantry), and soil and crop responses to its use in a zero traffic regime. Soil &
Tillage Research, 24: 359–380.
36. Chamen, W.C.T., Vermeulen, G.D., Campbell, D.J., Sommer, C. 1992b. Reduction of trafficinduced soil compaction: a synthesis. Soil & Tillage Research, 24: 303–318.
77
37. Chamen, W.C.T., Chittey, E.T., Leede, P.R., Goss, M.J. and Howse, K.R. 1990. The effect of tyre
soil contact pressure and zero traffic on soil and crop responses when growing winter wheat.
Journal of Agricultural Engineering Research, 47: 1–21.
38. Chan, K.Y., Oates, A., Swan, A.D., Hayes, R.C., Dear, B.S. and Peoples, M.B. (2006). Agronomic
consequences of tractor wheel compaction on a clay soil. Soil & Tillage Research, 89, 13-21.
39. Cuttle, S.P., Macleod, C.J.A., Chadwick, D.R., Scholefield, D., Haygarth, P.M., Newell-Price, P.,
Harris, D., Shepherd, M.A., 2006. An inventory of methods to control diffuse water pollution
from agriculture(DWPA). User Manual. Prepared as part of Defra project ES0203, UK.
40. Cuttle, S., Shepherd, M., Goodlass, G. (2003). A review of leguminous fertility-building crops,
with particular reference to nitrogen fixation and utilisastion. Part of Defra Project OF0316
“The development of improved guidance on the use of fertility-building crops in organic
farming.
41. Da Silva, A. P. and Kay, B. D. 1996. The sensitivity of shoot growth of corn to the least limiting
water range of soils. Plant and Soil, 184:323-329.
42. Davies, A., Adams, W.A., Wilman, D. 1989. Soil compaction in permanent pasture and its
amelioration by slitting. J. Agr. Sci. 113: 189-197
43. Defra. 2007. Scoping study to assess soil compaction affecting upland and lowland grassland in
England and Wales - BD2304. Cranfield University. 24 pp.
44. Diaz-Zorita, M. & Grosso, G.A. (2000). Effect of soil texture, organic carbon and water
retention on the compactibility of soils from the Argentinian pampas. Soil and Tillage
Research, 54: 121–126.
45. Dickson, J.W. and Campbell, D.J. 1990. Soil and crop responses to zero- and conventionaltraffic systems for winter barley in Scotland, 1982–1986. Soil and Tillage Research, 18: 1–26.
46. Dickson, J.W. and Ritchie, R.M. 1996. Zero and reduced ground pressure traffic systems in an
arable rotation 2. Soil and crop responses. Soil and Tillage Research, 38 (1-2): 89-113.
47. Dobbie, K.E., Bruneau, P.M.C and Towers, W. (eds) 2011. The State of Scotland’s Soil. Natural
Scotland, www.sepa.org.uk/land/land_publications.aspx
48. Dobbie, K.E. and Smith, K.A. 2003. Nitrous oxided emission factors for agricultural soils in
Great Britain: the impact of soil water-filled pore space and other controlling variables. Global
Change Biology, 9:204-218.
49. Douglas, J.T. and Crawford, C.E., 1993. The response of a ryegrass sward to wheel traffic and
applied nitrogen. Grass and Forage Sci. 48, pp. 91–100
50. Douglas J.T., Crawford C.E. and Campbell D.J. 1995. Traffic systems and soil aerator effects on
grassland for silage production. Journal of Agricultural Engineering Research, 60, 261–270.
51. Drewry, J.J. and Paton, R.J. 2000. Effects of cattle treading and natural amelioration on soil
physical properties and pasture under dairy farming in Southland, New Zealand. New Zealand
Journal of Agricultural Research, 43: 377-386
52. Drewry J.J. 2003. Dairy grazing strategies to minimise soil pugging and compaction in
Waikato. Proceedings of New Zealand Grassland Association, 65: 99-103
53. Eradat Oskoui, K., Campbell, D.J., Soane, B.D., McGregor, M.J. 1994. Economics of modifying
conventional vehicles and running gear to minimize soil compaction. In: B.D. Soane, C. van
Ouwerkerk, eds, Soil Compaction in Crop Production. Elsevier Science Publishers, B.V.,
Amsterdam: 539-567.
78
54. Eriksson, J., Håkansson, I. and Danfors, B. 1974. The effect of soil compaction on soil structure
and crop yields. Bull. 354, Swedish Inst. Agric. Engl, English translation by J. Kristian AASE,
USDA, Agricultural Res. Service, Sidney, Mas., 101 pp.
55. Evans, R. 2011. Reconnaissance surveys to assess sources of diffuse pollution in rural
catchments in East Anglia, eastern England – implications for policy. World and Environmental
Journal. Available online 3 August 2011.
56. Evans, R. 2005. Monitoring water erosion in lowland England and Wales – a personal view of
its history and outcomes. Catena, 64:142-161.
57. Evans, R. 2002. An alternative way to assess water erosion of cultivated land – field-based
measurements and analysis of some results. Applied Geography, 22: 187–208.
58. FAO (Food and Agriculture Organization). 1988. FAO/UNESCO Soil Map of the World
1:5,000,000: Revised Legend, with corrections. World Resources Report 60, FAO, Rome.
59. Farrell, T. 2008. An economic evaluation of conservation farming practices for the Central
West of NSW. 52nd Annual Conference of the AARES, Canberra.
60. Fezzi, C., Rigbay, D., Bateman, I.J., Hadley, D., Posen, P., 2008. Estimating the economic
impacts of nutrient leaching reduction policies. Agricultural Economics 39, 197-205.
61. Fielke, J.M., Riley, T.W., Slattery, M.G., Fitzpatrick, R.W. 1993. Comparison of tillage forces and
wear rates of pressed and cast cultivator shares. Soil & Tillage Research, 25: 317-328.
62. Franzluebbers, A.J. 2007. Integrated crop-livestock systems in the southeastern USA.
Agronomy Journal 99:361-372.
63. Gaffney, J. and Wilson, A. 2003. The economics of zero tillage and controlled traffic farming for
Western Downs farms. Proceedings of the International Soil Tillage Research Organisation
16th Triennial conference, Brisbane, 13–18 July, pp 458–464.
64. Galambosova, J., Rataj, V., and Vasek, M.. 2010. Effects of Controlled Traffic Farming. Trends in
Agricultural Engineering 2010 158-162.
65. Ghadim, A. A., Kingwell, R. and Pannell D. 1991. An Economic-Evaluation of Deep Tillage to
Reduce Soil Compaction on Crop - Livestock Farms in western-Australia. Agricultural Systems
37 (3):291-307.
66. Ghadim, A.A., Kingwell, R., and Pannell, D.. 1991. An Economic-Evaluation of Deep Tillage to
Reduce Soil Compaction on Crop - Livestock Farms in Western-Australia. Agricultural Systems
37:291-307.
67. Glenk, K., McVittie, A., Towers, W., Watson, C. and Black H.I.J. 2010. Socio-economic data on
Scottish soils – collection and development. Scottish Environment Protection Agency
Commissioned Report. [online] www.sepa.org.uk/land/idoc.ashx?docid=ebebd86e-4af1-4a48b2e4-952c534fce8e&version=-1 (checked 4 November 2010).
68. Görlach, B. , Landgrebe-Trinkunaite, R. and Interwies, E. 2004. Assessing the Economic
Impacts of Soil Degradation. Final Report Volume I: Literature Review Final Version, December
2004. Report by EcoLogic to the European Commission. Study Contract,
ENV.B.1/ETU/2003/0024
69. Goulder, L.H. & Parry, I.W.H. (2008) Instrument Choice in Environmental Policy, Review of
Environmental Economics and Policy, 2/2, 152–174
70. Graham, J.P., Blackwell, P.S., Armstrong, J.V., Christian, D.G., Howse, K.R., Dawson, C.J. and
Butler, A.R. 1986. Compaction of a silt loam by wheeled agricultural vehicles II. Effects on
growth and yield of direct drilled wheat. Soil & Tillage Research, 7: 189–203.
71. Greenwood, K.L., MacLeod, D.A. and Hutchinson, K.J.. 1997. Long-term stocking rate effects on
soil physical properties. Australian Journal of Experimental Agriculture 37:413-419.
72. Greenwood, K.L., MacLeod, D.A., Scott, J.M. and Hutchinson, K.J. 1998. Changes to soil
physical properties after grazing exclusion. Soil Use and Management, 14: 19-24
79
73. Gregory, A.S., Watts, C.W., Whalley, W.R., Kuan, H.L., Griffiths, B.S., Hallett, P.D. and
Whitmore, A.P. 2007. Physical resilience of soil to field compaction and the interactions with
plant growth and microbial community structure. European Journal of Soil Science 58:12211232.
74. Gunningham, N. & Grabosky, P. (1998) Smart Regulation. Designing Environmental Policy.
Oxford Socio-Legal Studies, Oxford University Press, Oxford
75. Håkansson, I. 1994. Subsoil Compaction Caused by Heavy Vehicles - A Long-Term Threat to Soil
Productivity. Soil & Tillage Research 29:105-110.
76. Håkansson, I. 2005. Machinery-induced compaction of arable soils – incidence, consequences
and countermeasures.Swedish University of Agricultural Sciences, Division of Soil
Management. Report no. 109, 153 pp.
77. Håkansson,I. and Reeder, R.C.. 1994. Subsoil Compaction by Vehicles with High Axle Load
Extent, Persistence and Crop Response. Soil & Tillage Research 29:277-304.
78. Hammel, J.E. 1994. Effect of high-axle load traffic on subsoil physical properties and crop yields
in the Pacific Northwest USA. Soil Tillage Research, 29: 159-203.
79. Hamilton, G., Bakker, D., Houlbrooke, D, Hetherington, R. and Spann, C. 2003. Permanent
raised beds prevent waterlogging and increase the productivity of dryland farming areas in
Western Australia. Proceedings of the International Soil Tillage Research Organisation 16th
Triennial conference, Brisbane, 13–18 July, pp 524–530.
80. Hansen, S., Bleken, M., Sitaula, B.K. 2008. Effect of soil compaction and fertilization practise on
N2O emission and CH4 oxidation. In: Proceedings from the International conference Organic
Agriculture and climate change, Enita of Clermont, France, April 17-18th, 2008. 6 pp.
81. Horn,R., and Fleige, H.. 2003. A method for assessing the impact of load on mechanical
stability and on physical properties of soils. Soil & Tillage Research 73:89-99.
82. Jones, R.J.A., Spoor, G., and Thomasson, A.J.. 2003. Vulnerability of subsoils in Europe to
compaction: a preliminary analysis. Soil & Tillage Research 73:131-143.
83. Jorajuria, D., Draghi, L., Aragon, A. (1997). The effect of vehicle weight on the distribution
of compaction with depth and the yield of Lolium/Trifolium grassland. Soil and Tillage
Research, 41 (1-2): 1-12.
84. Olesen, J.E., and Munkholm, L.J. 2007. Subsoil loosening in a crop rotation for organic farming
eliminated plough pan with mixed effects on crop yield. Soil & Tillage Research, 94:376-385.
85. Kingwell, R. and Fuchsbichler, A. 2011. The whole-farm benefits of controlled traffic farming:
An Australian appraisal. Agricultural Systems, 104: 513-521.
86. Koch, H-J., Heuer, H., Tomanová, O. and Märländer, B. 2008. Cumulative effect of annually
repeated passes of heavy agricultural machinery on soil structural properties and sugar beet
yield under two tillage systems. Soil & Tillage Research, 101: 69-77.
87. Kroulík, M.; Kumhála, F. H la, J.; Honzík, I. (2009). The evaluation of agricultural machines
field trafficking intensity for different soil tillage technologies. Soil & Tillage Research, 105:
171-175. Kuhlman, T., Reinhard, S. and Gaaff, A.2010. Estimating the costs and benefits of soil
conservation in Europe. Land Use Policy 27 (1):22-32.
88. Kuhlman,T., Reinhard, S.and Gaaff, A.. 2010. Estimating the costs and benefits of soil
conservation in Europe. Land Use Policy 27:22-32.
89. Kumar, D., Bansal, M.L., Phogat, V.K. (2009). Compactability in relation to texture and organic
matter content on alluvial soils. Indian Journal of Agricultural Research, 43 (3): 180-186.
90. Lamandé M. and Schjønning, P. 2011a. Transmission of vertical stress in a real soil profile. Part
II: Effect of tyre size, inflation pressure and wheel load. Soil and Tillage Research, 114: 71-77.
80
91. Lamandé M. and Schjønning, P. 2011b. Transmission of vertical stress in a real soil profile. Part
I: Site description, evaluation of the Söhne model, and the effect of topsoil tillage. Soil and
Tillage Research, 114: 57-70.
92. Lamandé, M., Schjønning, P. and Tøgersen, F.A. 2007. Mechanical behavior of an undisturbed
soil subjected to loadings: effects of load and contact area. Soil & Tillage Research, 97: 91–106.
93. Lamers, J.G., Perdok, U.D., Lumkes, L.M. and Klooster, J.J. 1986. Controlled traffic farming
systems in the Netherlands. Soil & Tillage Research, 8: 65–76.
94. Lapen, D.R., Hayhoe, H.N., Topp, G.C., McLaughlin, N.B. and Gregorich, E.G. 2002. Precision
Agriculture, 3:237-257.
95. Lipiec, J., Arvidsson, J. and Murer, E. 2003. Review of modelling crop growth, movement of
water and chemicals in relation to topsoil and subsoil compaction. Soil & Tillage Research, 73:
15-29.
96. Lipiec, J. 2002. Impact of soil compaction on crop productivity – Polish experience. In
Proceedings of the 3rd workshop, INCO COPERNICUS Concerted Action “Experiences with the
impact of subsoil compaction on soil nutrients, crop growth and environment, and ways to
prevent subsoil compaction. A. Canarache, E. Dimitru & R. Enache, eds. Research Institute for
Soil Sciences and Agrochemistry, Bucharest, Romania, pp.229–233.
97. MAFF. 1970. Modern farming and the soil. Report of the Agricultural Advisory Council on soil
structure and soil fertility. London.
98. Manuwa, S.I. 2009. Performance evaluation of tillage tines operating under different depths in
a sandy clay loam soil. Soil & Tillage Research, 103: 399-405.
99. Marks, M.J. andand Soane, G.C. 1987.Crop and soil response to subsoil loosening, deep
incorporation of phosphorous and potassium fertiliser and subsequent soil management on a
range of soil types. Part 1: Response of arable crops. Soil Use and Management, 3: 115-123.
100. McAfee, M., Lindström, J. and Johansson, W. (1989). Effects of pre-sowing compaction on
soil physical properties, soil atmosphere and growth of oats on a clay soil. Journal of Soil
Science, 40: 707–717.
101. Medvedev, V.V., Laktionova, T.N. and Lyndina, T.E. 2002. Estimation of agricultural crop
losses in the Ukraine through soil overcompaction. In Proceedings of the 3rd workshop, INCO
COPERNICUS Concerted Action “Experiences with the impact of subsoil compaction on soil
nutrients, crop growth and environment, and ways to prevent subsoil compaction. A.
Canarache, E. Dimitru & R. Enache, eds. Research Institute for Soil Sciences and
Agrochemistry, Bucharest, Romania, pp. 213–223
102. Michelin. (2010). Agricultural tyre range and technical data. Michelin Tyre plc, Campbell
Road, Stoke on Trent, ST4 4EY.
103. Milne, A.E., Haskard, K.A., Webster, C.P., Truan, I.A., Goulding, K.W.T. and Lark, R.M. 2011.
European Journal of Soil Science, 62:467-478.
104. Miransari, M; Bahrami, HA; Rejali, F Malakouti, MJ. 2009. Effects of soil compaction and
arbuscular mycorrhiza on corn (Zea mays L.) nutrient uptake. Soil & Tillage Research.
103(2):282-290.
105. Moran, D., MacLeod, M., Wall, E., Eory, V., Pajot, G., Matthews, R., McVittie, A., Barnes, A.,
Rees, B., Moxey, A., Williams, A., Smith, P., 2008. UK Marginal Abatement Cost Curves for the
Agriculture and Land Use, Land-Use Change and Forestry Sectors out to 2022, with Qualitative
Analysis of Options to 2050. Final Report to the Committee on Climate Change. SAC.
81
106. Mouazen, A.B., Ramon, H. 2006. Development of on-line measurement system of bulk
density based on on-line measured draught, depth and soil moisture content. Soil & Tillage
Research, 86: 218-229.
107. Mouazen, A.B., Ramon, H. and De Baerdemaeker, J. 2003. Modelling compaction from online measurement of soil properties and sensor draught.Precision Agriculture, 4: 203-212.
108. Mouazen, A.M. 2002. Mechanical behaviour of the upper layers of a sandy loam soil under
shear loading. Journal of Terramechanics, 39: 115-126.
109. Mouazen, A.B. & Ramon, H. (2002). A numerical-statistical hybrid modelling scheme for
evaluation of draught requirements of a subsoiler cutting a sandy loam soil, as affected by
moisture content, bulk density and depth. Soil & Tillage Research, 63: 155-165.
110. Mulholland, B. and Fullen, M.A. 1991. Cattle trampling and soil compaction on loamy sand.
Soil Use and Management, 7: 189-193
111. Nix, J. 2010.Farm management pocketbook. Forty first edition.The Pocketbook, 2
Nottingham Street, Melton Mowbray, Leicestershire, LE13 1NW.
112. O'Sullivan, M.F., Robertson, E.A.G. and Henshall, J.K.. 1999. Shear effects on gas transport in
soil. Soil & Tillage Research 50:73-83.
113. O'Sullivan, M.F., and C.Simota. 1995. Modeling the environmental impacts of soil
compaction: a review. Soil and Tillage Res. 35: 69-84.
114. Owsiak, Z. 1999. Wear of spring tine cultivator points in sandy loam and light clay soils in
southern Poland. Soil and Till Res. 50: 333–340.
115. Pagliai, M., Marsili, A., Servadio, P., Vingozzi, N. and Pellegrini, S. 2003. Changes in some
physical properties of a clay soil in Central Italy following the passage of rubber tracked and
wheeled tractors of medium power. Soil & Tillage Research, 73: 119–129
116. Pannell, D. & Vanclay, F. (2011) Changing Land Management: Adoption of New Practices by
Rural Landholders. CSIRO Publishing.
117. Pannell, D. (2008) Public benefits, private benefits and policy mechanism choice for land-use
change for environmental benefits, Land Economics, 84/2, 225-40
118. Patterson, D.E., Chamen, W.C.T. & Richardson, C.D. 1980. Long-term experiments with
tillage systems to improve the economy of cultivations for cereals. Journal of Agricultural
Engineering Research, 25: 1-35.
119. Patto, P.M., Clement, C.R. and Forbes, T. J. 1978. Permanent Grassland. 2 Grassland
poaching in England and Wales. Joint Permanent Pasture Group Grassland Research Institute,
Hurley, Bucks.
120. Pollard, F. and Elliott, J.B. 1978. The effect of soil compaction and method of fertilizer
placement on the growth of barley using a concrete track technique. Journal of Agricultural
Engineering Research, 23: 203–216.
121. Powlson, D.S., Whitmore, A.P., Goulding, W.T. (2011). Soil carbon sequestration to mitigate
climate change: a critical re-examination to identify the true and the false. European Journal
of Soil Science, 62: 42-55.
122. Radford, B.J., Yule, D.F., McGarry, D. and Playford, C. 2001. Crop responses to applied soil
compaction and to compaction repair treatments. Soil and Tillage Research, 61 (3-4): 157-166.
123. Richardson, R.C.D. 1967. The wear of metals by hard abrasives. Wear, 10 (4): 291–309.
124. Said, H.M. (2003). Effect of tillage implements on the state of compaction in different soils.
Egyptian Journal of Soil Science, 43: 91-107.
125. Royal Agricultural Society of England. (2012). Water and Soils Survey, 2012. Royal
Agricultural Society of England, Stoneleigh Park, Warwickshire CV8 2LZ and England Marketing
(www.englandmarketing.co.uk)
82
126. Schjønning, P., Heckrath, G. and Christensen, B.T. 2009. Threats to soil quality in Denmark: A
review of existing knowledge in the context of the EU Soil Thematic Strategy. DJF Report Plant
Science No. 143, The Faculty of Agricultural Sciences, Aarhus University,
http://web.agrsci.dk/djfpublikation/index.asp?action=search&type=DJF%20rapport%20Markb
rug
127. Scholefield, D., Patto, P.M. and Hall, D.M. 1985. Laboratory research on the compressibility
of four topsoils from grassland. Soil and Tillage Research 6: 1-16.
128. Sedaghatpour, S., Ellis, T., Hignett, C. and Bellotti, B. (1995). Six years of controlled traffic
cropping research on a red brown earth at Roseworthy in South Australia. Proceedings of the
National Controlled Traffic Conference, Rockhampton, Queensland, 13–14 September, pp. 69–
75.
129. Sitaula, B.K., Hansen, S., Sitaula, J.I.B. and Bakken, L.R. (2000). Effects of soil compaction on
N2O emission in agricultural soil. Chemosphere - Global Change Science, 2 (3-4): 367-371.
130. Smith, D.L.O. and Dickson, J.W. 1990. Contributions of vehicle weight and ground pressure
to soil compaction. Journal of Agricultural Engineering Research, 46: 13–29.
131. Soane, B. D. and van Ouwerkerk, C.. 1995. Implications of soil compaction in crop production
for the quality of the environment. Soil and Tillage Res. 35: 5-22.
132. Söhne, W. 1953. Druckverteilung im Boden und Bodenformung unter Schlepper-eiffen.
[Pressure distribution in the soil and soil deformation under tractor tyres]. Grundlagen der
Landtechnik 5: 49–63.
133. Spoor, G., 2000. Compaction characteristics of swelling clay subsoils. In: Horn, R.,
Van den Akker, J.J.H. and Arvidsson, J. (Eds). Subsoil Compaction, distribution, processes and
consequences. Advances in Geoecology 32. Catena Verlag GMBH, Reiskirchen, Germany, pp.
427-434.
134. Spoor, G. 1997. Benefits from traffic control. Landwards, 52 (1): 2–5.
135. Spoor, G. and Godwin, R.J. 1978. An experimental investigation into the deep loosening of
soil by rigid tines.Journal of Agricultural Engineering Research 23: 243–258.
136. Spoor, G., Tijink, F.G.J. and Weisskopf, P. 2003. Subsoil compaction: risk, avoidance,
identification and alleviation. Soil & Tillage Research, 73: 175-182.
137. Stephenson, G.R. and Veigel, A. 1987. Recovery of compacted soil on pastures used for
winter cattle feeding. Journal of Range Management, 40: 46-48
138. Stewart, L.E.D., Copland, T.A., Dickson, J.W. and Douglas, J.T.. 1998. Economic evaluation of
traffic systems for arable and grass crops on an imperfectly drained soil in Scotland. Journal of
Sustainable Agriculture 12:41-56.
139. Strahan, R., Hoffman, A. 2009. Estimating the Economic Implications for Broad Acre Cropping
Farms in the Fitzroy Basin Catchments of Adoption of best Management Practices.
https://www.grainsbmp.com.au/images/documents/Economic%20report%202009.pdf
140. Stranks, S. 2006. The effects of tyre systems on the depth and severity of compaction. MScThesis in Agricultural and Environmental Engineering, Cranfield University, Silsoe, UK (2006)
Confidential.
141. Taylor, J.H. 1992. Reduction of traffic-induced soil compaction.Soil & Tillage Research, 24:
301-302.
142. Taylor, J.H. and Burt, E.C. 1987.Total axle load effects on soil compaction. Journal of
Terramechanics. 24: 179–186.
143. Tullberg, J. 2010. Tillage, traffic and sustainability—A challenge for ISTRO Soil & Tillage
Research 111: 26–32
83
144. Tullberg, J., Yule, D.F. and McGarry, D. 2003. ‘On track’ to sustainable cropping systems in
Australia. Proceedings of the International Soil Tillage Research Organisation 16th Triennial
conference, Brisbane, 13–18 July, pp. 1271–1285.
145. Tullberg, J.N. 2000. Traffic effects on tillage draught. J. Agric. Eng. Res. 75: 375–382
146. Tullberg, J.N., Ziebarth, P.J. and Li, Y. 2001. Tillage and traffic effects on runoff. Australian
Journal of Soil Research, 39: 249–257.
147. Van den Akker, J.J.H., Arvidsson, J. and Horn, R. 2003. Introduction to the special issue on
experiences with the impact and prevention of subsoil compaction in the European Union.Soil
& Tillage Research, 73: 1-8.
148. Van den Akker, J.J.H. and Schjønning, P., 2004. Subsoil compaction and ways to prevent it.
Chapter 10 in: Schjønning, P., Elmholt, S. and Christensen, B.T. (eds.). Managing Soil
Quality: Challenges in modern agriculture. CAB International, Wallingford, Oxon, UK, pp
163-184.
149. Vermeulen, G.D. and Mosquera, J. 2009. Soil, crop and emission responses to seasonalcontrolled traffic in organic vegetable farming on loam soil. Soil & Tillage Research, 102, 126134.
150. Vermeulen, G.D. and Klooster, J.J. 1992. The potential of a low ground pressure traffic
system to reduce soil compaction on a clayey loam soil. Soil & Tillage Research, 24: 337-358.
151. Vermeulen, G.D. and Perdok, U.D. 1994. Benefits of low ground pressure tyre equipment. In:
B.D. Soane, C. van Ouwerkerk, eds, Soil Compaction in Crop Production. Elsevier Science
Publishers, B.V., Amsterdam: 447-478.
152. Voorhees, W.B., Nelson, W.W., Randall, G.W. (1986). Extent and persistence of subsoil
compaction caused by heavy axle loads. Soil Science Society of America Journal, 50: 428–
433.
153. Voorhees, W.B., Evans, S.D. and Warnes, D.D. 1985. Effect of preplant wheel traffic on soil
compaction, water use and growth of spring wheat. Soil Science Society of America Journal,
49: 215–220.
154. Wairiu, M., Mullins, C.E. and Campbell, C.D. 1993. Soil physical factors affecting the growth
of sycamore (Acer-pseudoplatanus l) in a silvopastoral system on a stony upland soil in
northeast Scotland. Agroforestry Systems, 24: 295-306.
155. Whalley,W., Watts, C.W., Gregory, A.S., Mooney, S.J., Clark, L.J.and Whitmore, A.P.. 2008.
The effect of soil strength on the yield of wheat. Plant and Soil 306:237-247.
156. Whitmore, A.P., Whalley, R.W., Bird, N.R.A., Watts, C.W., Gregory, A.S. 2010. Estimating soil
strength in the rooting zone of wheat. Plant and Soil, 339: 363-375.
157. Wolkowski, R.P. 1990. Relationship between wheel-traffic-induced soil compaction, nutrient
availability and crop growth: a review. Journal of Production Agriculture, 3 (4):460–469.
158. Zoz, F.M., Reed, R.J., Lon, R. (1999). Power delivery efficiency: A valid measure of belt/tire
tractor performance? ASAE Paper No. 99-1034.
84
APPENDIX
Appendix A1: Selection of Soil Types and Farm Typology
We adapted stylized farm typology descriptions (Cuttle et al., 2006) by incorporating the variability
of real-world farms (Andersen et al., 2007; Fezzi et al., 2008) as captured by, for example, the Farm
Practices Survey or the UK Farm Business Survey (FBS)15. Our selection focuses on enterprise types
since the data are easier to compile for soil compaction mitigation. To provide reliable cost-curves
related to soil compaction mitigation, a subset of farm typologies and soil types for England and
Wales were selected (Table A1). These met the following criteria:
1. Good coverage of agricultural land including geographic spread.
2. Major crop and grazing systems. Addition of potatoes as a root crop because of the unique
soil cultivation and harvesting operations.
3. Inclusion of major soil types with a wide range of soil textures.
4. Availability of economic data, including overlap with economic analysis on farm done
specifically for this project.
Major drivers that can be assessed based on this subset include (i) influence of soil texture and
drainage, (ii) cropping/grazing practice and (iii) mitigation practices. Given the poor availability of
economic data on soil compaction and scope of this project, we opted for a smaller number of farm
typologies than other economic studies (e.g. DP-ALL - WQ0106). However, we feel that our
approach provides reliable data on which to formulate policy with less risk of uncertainty due to the
adoption of biophysical models and optimisation routines to estimate costs.
Table A1: Land use – Soil Typologies
Farm type (and
crop)
Cereals (winter
wheat)
Location
Soil code and
dominant soil type
711r, typical
stagnogley soil
Extensive soil unit in
Eastern England
General
cropping
(potatoes)
Lincolnshire/Norfolk/Cambridgeshire 851a, clayey humic
alluvial gley soil
Lincolnshire/ Norfolk
15
Main soil features
Sandy clay loam or
clay loam surface
horizon, subsoil
becomes more
clayey with depth.
Poorly drained.
Silty clay topsoil,
silty clay or clay
subsoil
Although classified
as a groundwater
gley, the water
table is highly
managed through
pumping and
ditchers and
Farm Business Survey (FBS) data is subject to confidentially restrictions and can be used once permission is
obtained from Defra.
85
Cereals (spring
barley)
Hampshire/Yorkshire
Dairy (primarily
grass (75%),
remainder
crops and ley)
Grazing
livestock
(Lowland)
(primarily
permanent
grass (85%))
Horticulture –
Onions
Cornwall/Devon/Wales
343h, brown
rendzinas over
chalk
Extensive unit in
Southern England,
local occurrences
elsewhere including
east Yorkshire
541j typical brown
earths
Extensive in SW
England and Wales
541j typical brown
earths
Extensive in SW
England and Wales
Cornwall/Devon/Wales
Norfolk
541a brown earths.
drainage is
classified as well
drained
Silty clay loam
calcareous topsoil
(20cm) overlying
bedded chalk at 40
cms
Well drained
Clay loam topsoil
overlying clay loam
subsoil. Well
drained
Clay loam topsoil
overlying clay loam
subsoil. Well
drained
Well-drained coarse
loamy and sandy
soils over sand or
sandstone
Table A1 has been compiled based on an assessment of the overlap between different farming
systems, crop types and soils. Where possible, map units and soil types that are spatially extensive
have been selected on the premise that the results of the cost curves will be relevant and applicable
more widely. We have found realistic scenarios of soil type versus cropping practices for which it is
possible to generate case studies from direct interaction with land managers.
This proved straightforward with winter cereals and grazing livestock (lowland). Spring barley is a
less widely grown crop but DEFRA statistics at county level and information from the 1: 250 000
scale soil bulletins indicate a reasonable match between this map unit and areas where spring barley
is a more extensively grown crop.
Potatoes account for only 2.6% of all cropped land in England, so matching with extensive soil types
is more problematic. Here therefore DEFRA statistics guided us to areas where they are grown more
extensively and the relevant soil bulletin provided some detail on soil types.
Horticulture posed the same problem but data can be obtained directly from producers using
different technologies to manage or remediate the effects of soil compaction.
86
Appendix A2: Mitigation measures taken on individual farms and their estimated costs and returns
Farm
ID
Ll
Mitigation measure
Estimated cost
Estimated return
Controlled traffic
% area to
which applied
100
-£12/ha
Subsoiling
Deep cultivations
Deep cultivations
80
20
50%
£56/ha
£38/ha
£38/ha
Bd2
Subsoiling
Converting to CTF
50
100
£52/ha
£0
Gw
Livestock housing overwinter
Longer maintenance of
leys
Subsoiling
Subsoiling
Controlled traffic
90
100
Slatted yards
Cash crop yield
foregone
1
40
100
£56/ha
£56/ha
£-15/ha
Subsoiling tramlines and
some headlands
Deep cultivations
Subsoiling
Medium depth cults
Subsoiling
Subsoiling
Loosening below plough
sole
Subsoiling
Controlled traffic
100
£3/ha
Yield improvement and
lower operating costs
Maintenance of yield
Maintenance of yield
Maintenance of yield and
improved drainage
10% yield increase in OSR
6% yield increase, ?%
reduction in costs
Higher stocking rate,
quicker finishing of lambs
Less poaching and better
grass yields
Avoidance of wet areas
Maintenance of yield
Reduced inputs, increased
yields
0.3% yield benefit
Bd1
75
25
25
15
10
20
15
£38/ha
£56/ha
£30/ha
£56/ha
£56/ha
£4/ha
£56/ha
Maintenance of yield
Maintenance of yield
Maintenance of yield
Maintenance of yield
Maintenance of yield
Maintenance of yield
Maintenance of yield
100
£-43/ha
£75/ha
Ox1
Ox2
Hu
Ha1
Ha2
Nf1
Su
So
Nf2
Ng
87
Appendix A3: Summary of general agricultural data sources.
Data collected routinely under, for instance, the June Agricultural Census, the Farm Structure Survey,
the Survey of Farm Production Methods, the Survey of Farming Practices, the Survey of Fertiliser
Practice, the Pesticide Usage Survey and the Farm Business Survey, all provide useful contextual
information. However, most of them deal individually with only one dimension of interest (e.g. land
cover rather than management; specific management activities but not their spatial distribution) and
differences in their spatial and structural coverage and reporting hinder combining them other than
in an ad hoc manner.
In particular, although some management information is provided, the level of detail is typically
insufficient to identify how management practices vary spatially & temporally (i.e. by environmental
conditions) and structurally (i.e. by farm size and type.) That is, neither the local (contextual)
situation of farms nor the timing and intensity of all management operations are recorded in detail.
Consequently specification of, for example, the power and type of machinery used, the sequence
and timing of field operations or within-season responsiveness to changes often has to be taken
from industry sources, experimental data and expert opinion - with aggregate patterns then
inferred crudely from these in conjunction with the official data sources noted above.
Data Source
Description
Comment
Agricultural census
Physical land cover and
livestock numbers, by
geographical area but also
by farm size and type.
Sometimes machinery too.
No management
information. Vague
geo-referencing,
although interpolation to
grid-squares has been
performed and
overlaying with
biophysical data could
generate approximate
cover x soil x weather
combinations.
EU Farm structure survey.
http://www.defra.gov.uk/statistics/foodfa
rm/enviro/observatory/crosscompliance/eu-farm-structure-survey/
Data on labour usage and
age/gender/skill profile.
Not really relevant.
Farm Practices Survey
http://www.defra.gov.uk/statistics/foodfa
rm/enviro/farmpractice/
Data on (general)
cultivation techniques and
rotational practices.
Not by crop or farm
type, nor spatial
distribution.
EU Survey of production methods
Data on tillage methods,
soil conservation, manure
storage and treatment and
irrigation. Possibly
machinery.
Evolving from structure
survey and will include
geo-referencing.
Survey of fertiliser practice
http://www.defra.gov.uk/statistics/files/d
efra-stats-foodfarm-environ-
Fertiliser application rates
by crop and farm type.
Good information on
averages, including
timings. Some
http://www.defra.gov.uk/statistics/foodfa
rm/landuselivestock/junesurvey/junesurve
yresults/
88
information on variation.
Not linked to soil type.
fertiliserpractice-2010.pdf
Pesticide usage survey
http://fera.defra.gov.uk/plants/pesticideU
sage/fullReports.cfm
Detailed information on
total and average chemical
usage, by crop type.
Not by farm type.
Limited spatial
information.
Farm Business Survey (inc. occasional
Special Studies)
http://www.farmbusinesssurvey.co.uk/ind
ex.html
Detailed financial
performance data for
individual (but
anonymised) or average
farms by type & size.
Little physical data i.e.
on yields, input
quantities or biophysical
conditions. Vague georeferencing.
Nix Farm Management Pocketbook
Stylised management and
performance data.
Based on industry
sources/expert opinion.
Averages with some
performance variation.
No geo-referencing.
89
Appendix A4: Excel extracts for winter wheat, as an example – see spreadsheets for more detail16
Winter wheat assumptions
Prices, input levels and emission factors
Price £/t 118
Diesel £/l 0.7
N £/kg
0.62
P £/kg
0.68
K £/kg
0.54
Diesel l/havariable
N kg/ha 185
P kg/ha 50
K kg/ha 45
CO2e/l
CO2e/kg
2.7 (NB. Not on an LCA basis)
310 (NB. Not on an LCA basis)
Baseline outputs & diesel usage
Base yield (t/ha)
Clay
10.2
Silt
9
Sand
7.7
Peat
8
Comment
App F Table E4
Compacted area proportion
0.42
0.42
0.42
0.42
App H Table 5a
0.26
2.5%
£30.09
£11.41
16.3
1
£9.63
15.54
5.28
0.62
0.18
2.0%
£21.24
£7.35
10.5
0.8
£5.30
8.55
2.91
0.34
0.15
2.0%
£18.17
£3.29
4.7
0.6
£0.96
1.55
0.53
0.06
0.16
2.0%
£18.88
£3.29
4.7
0.6
£9.63
15.54
5.28
0.62
£2.86
4.20
£2.04
3.78
£1.57
2.31
£1.12
2.08
£0.29
0.42
£0.20
0.38
£2.86
4.20
£2.04
3.78
Yield penalty (t/ha)
Yield penalty % per ha
Yield penalty (£/ha)
Extra diesel use (£/ha)
Extra diesel use (l/ha)
Relative power requirements
N loss (£/ha)
N loss (kg/ha)
of which leached
of which as N 20
P loss (£/ha)
P loss (kg/ha)
K loss (£/ha)
K loss (kg/ha)
#1
#2
#3
Table A4.1
16
Own estimates (Tim Chamen)
Own estimates (Tim Chamen)
@ assumed output price
See note #1
See note #2
See note #3
Inferred as 34% of N lost, using App H Table 8
Inferred as 4% of N lost, using App H Table 8
See note #3
See note #3
Diesel use for field operations affected by compaction is assumed to be around 35l/ha on clay, 28l/ha on silt (=0.8 of clay) and 21l/ha on sand or peat (=0.6 of clay).
For an uncompacted soil, the equivalent figures are 18.7l, 17.5l & 16.3l respectively. The differences give extra diesel usage attributable to compaction.
Relative power requirements are taken as clay =1, silt = 0.8, sand and peat = 0.6. These can be used to estimat differences in fuel usage,
but then also for variation in operational costs across soil types i.e. difference in fuel usage * unit fuel price.
Nutrient losses will vary with from of application, other management actions, soil type and weather. However, Appendix H Table 9 suggests that losses attributable
to compaction are (as a % of total applications) 20% on clay, 11%, 2% on sand and 20% on peat.
Comments citing (e.g.) App F Table E4 refer to as-yet-unpublished Defra report on soil degradation (pers. comm., Anil Graves, Cranfield University, 2012)
90
Table A4.2
Sub-soiling (general)
Nix (£/ha) £56.10
#1
Diesel use
Efficacy
Yield
Diesel
Nutrient
30
1
0
1
Clay
Base yield (t/ha)
10.2
Compaction yield penalty t/ha
0.26
Compaction yield penalty % per ha
2.5%
Compaction penalty avoided % ha
2.5%
relative to penalty 100.0%
Additional Yield gain t/ha
0.00
Overall output value gain £/ha
£30.09
Additional diesel usage (#1)
30.0
Cost £/ha (inc. Diesel)
£56.10
Subsequent diesel reduction l/ha
0.00
Subsequent diesel reduction £/ha
£0.00
N loss avoided £/ha
£9.63
N loss avoided kg/ha
15.54
of which not leached
5.28
0.62
of which not as N 20
Silt
9
0.18
2.0%
2.0%
100.0%
0.00
£21.24
24.0
£51.90
0.00
£0.00
£5.30
8.55
2.91
0.34
Sand
7.7
0.15
2.0%
2.0%
100.0%
0.00
£18.17
18.0
£47.70
0.00
£0.00
£0.96
1.55
0.53
0.06
Peat
8
0.16
2.0%
2.0%
100.0%
0.00
£18.88
18.0
£47.70
0.00
£0.00
£9.63
15.54
5.28
0.62
Comment
From baseline tab
From baseline tab
From baseline tab
P loss avoided £/ha
P loss avoided kg/ha
K loss avoided £/ha
K loss avoided kg/ha
Net impact on CO2e emissions (kg/ha)
Net impact on CO2e emissions (kg/t)
Impact on gross margin
£1.57
2.31
£1.12
2.08
-41.18
-4.58
-£23.79
£0.29
0.42
£0.20
0.38
29.33
3.81
-£28.28
£2.86
4.20
£2.04
3.78
-144.10
-18.01
-£16.33
Assuming same % avoidance as for yield penalty, capped by baseline
Assuming same % avoidance as for yield penalty, capped by baseline
Assuming same % avoidance as for yield penalty, capped by baseline
Assuming same % avoidance as for yield penalty, capped by baseline
£2.86
4.20
£2.04
3.78
-111.70
-10.95
-£13.52
Own estimate (Tim Chamen)
Needed for GHG calculations
Adjusted for diesel usage difference
Assuming same % avoidance as for yield penalty, capped by baseline
Assuming same % avoidance as for yield penalty, capped by baseline
Assuming same % avoidance as for yield penalty, capped by baseline
Assuming same % avoidance as for yield penalty, capped by baseline
Additional diesel. Sub-soiling is a discrete additional field operation that requires additional fuel. Although the cost of this is subsumed within the contractor's charge, the extra
fuel usage is needed for GHG emission estimates. Estimated as 30l (for an hour of a 200hp tractor) on clay, adjusted for diesel usage relativities (see baseline tab)
91
Table A4.3
Sub-soiling (targetted, 42% of general)
Nix (£/ha) £23.56
Diesel
Clay
10.2
0.26
2.5%
2.5%
100.0%
0.00
£30.09
12.6
£23.56
0.00
£0.00
£9.63
15.54
5.28
0.62
of which not as N 20
Base yield (t/ha)
Compaction yield penalty t/ha
Compaction yield penalty % per ha
Compaction penalty avoided % ha
relative to penalty
Additional Yield gain t/ha
Overall output value gain £/ha
Additional diesel usage (#1)
Cost £/ha (inc. Diesel)
Subsequent diesel reduction l/ha
Subsequent diesel reduction £/ha
N loss avoided £/ha
N loss avoided kg/ha
of which not leached
P loss avoided £/ha
P loss avoided kg/ha
K loss avoided £/ha
K loss avoided kg/ha
Net impact on CO2e emissions (kg/ha)
Net impact on CO2e emissions (kg/t)
Impact on gross margin
#1
£2.86
4.20
£2.04
3.78
-158.68
-15.56
£19.02
Efficacy
Yield
Diesel
Nutrient
12.6
1
0
1
Silt
9
0.18
2.0%
2.0%
100.0%
0.00
£21.24
10.1
£21.80
0.00
£0.00
£5.30
8.55
2.91
0.34
Sand
7.7
0.15
2.0%
2.0%
100.0%
0.00
£18.17
7.6
£20.03
0.00
£0.00
£0.96
1.55
0.53
0.06
Peat
8
0.16
2.0%
2.0%
100.0%
0.00
£18.88
7.6
£20.03
0.00
£0.00
£9.63
15.54
5.28
0.62
Comment
From baseline tab
From baseline tab
From baseline tab
£1.57
2.31
£1.12
2.08
-78.77
-8.75
£6.31
£0.29
0.42
£0.20
0.38
1.14
0.15
-£0.61
£2.86
4.20
£2.04
3.78
-172.28
-21.54
£11.34
Assuming same % avoidance as for yield penalty, capped by baseline
Assuming same % avoidance as for yield penalty, capped by baseline
Assuming same % avoidance as for yield penalty, capped by baseline
Assuming same % avoidance as for yield penalty, capped by baseline
Own estimate (Tim Chamen)
Needed for GHG calculations
Adjusted for diesel usage difference
Assuming same % avoidance as for yield penalty, capped by baseline
Assuming same % avoidance as for yield penalty, capped by baseline
Assuming same % avoidance as for yield penalty, capped by baseline
Assuming same % avoidance as for yield penalty, capped by baseline
Additional diesel. Sub-soiling is a discrete additional field operation that requires additional fuel. Although the cost of this is subsumed within the contractor's charge, the extra
fuel usage is needed for GHG emission estimates. Estimated as 30l (for an hour of a 200hp tractor) for clay, adjusted for diesel usage relativities (see baseline tab)
92
Table A4.4
Plough
#1 £54.90
Diesel
Clay
10.2
0.26
2.5%
2.5%
100.0%
0.00
£30.09
60.0
£54.90
0.00
£0.00
£9.63
15.54
5.28
0.62
of which not as N 20
Base yield (t/ha)
Compaction yield penalty t/ha
Compaction yield penalty % per ha
Compaction penalty avoided % ha
relative to penalty
Additional Yield gain t/ha
Overall output value gain £/ha
Additional diesel usage (#1)
Cost £/ha (inc. Diesel)
Subsequent diesel reduction l/ha
Subsequent diesel reduction £/ha
N loss avoided £/ha
N loss avoided kg/ha
of which not leached
P loss avoided £/ha
P loss avoided kg/ha
K loss avoided £/ha
K loss avoided kg/ha
Net impact on CO2e emissions (kg/ha)
Net impact on CO2e emissions (kg/t)
Impact on gross margin
#1
£2.86
4.20
£2.04
3.78
-30.70
-3.01
-£12.32
Efficacy
Yield
Diesel
Nutrient
60
1
0
1
Silt
9
0.18
2.0%
2.0%
100.0%
0.00
£21.24
48.0
£46.50
0.00
£0.00
£5.30
8.55
2.91
0.34
Sand
7.7
0.15
2.0%
2.0%
100.0%
0.00
£18.17
36.0
£38.10
0.00
£0.00
£0.96
1.55
0.53
0.06
Peat
8
0.16
2.0%
2.0%
100.0%
0.00
£18.88
36.0
£38.10
0.00
£0.00
£9.63
15.54
5.28
0.62
Comment
From baseline tab
From baseline tab
From baseline tab
£1.57
2.31
£1.12
2.08
23.62
2.62
-£18.39
£0.29
0.42
£0.20
0.38
77.93
10.12
-£18.68
£2.86
4.20
£2.04
3.78
-95.50
-11.94
-£6.73
Assuming same % avoidance as for yield penalty, capped by baseline
Assuming same % avoidance as for yield penalty, capped by baseline
Assuming same % avoidance as for yield penalty, capped by baseline
Assuming same % avoidance as for yield penalty, capped by baseline
Own estimate (Tim Chamen)
Needed for GHG calculations
Adjusted for diesel usage difference
Assuming same % avoidance as for yield penalty, capped by baseline
Assuming same % avoidance as for yield penalty, capped by baseline
Assuming same % avoidance as for yield penalty, capped by baseline
Assuming same % avoidance as for yield penalty, capped by baseline
Estimate from Tim Chamen, relative to cost of normal ploughing. Diesel usage assumption as per sub-soiling.
93
Table A4.5
Low ground pressure tyres
Efficacy
Yield
Diesel
Nutrient
#1 £3.58
Clay
10.2
0.26
2.5%
2.5%
100.0%
0.31
£66.20
0.0
£3.58
0.00
£0.00
£9.63
15.54
5.28
0.62
of which not as N 20
Base yield (t/ha)
Compaction yield penalty t/ha
Compaction yield penalty % per ha
Compaction penalty avoided % ha
relative to penalty
Additional Yield gain t/ha
Overall output value gain £/ha
Additional diesel usage
Cost £/ha (excl. Diesel) #1
Subsequent diesel reduction l/ha
Subsequent diesel reduction £/ha
N loss avoided £/ha
N loss avoided kg/ha
of which not leached
P loss avoided £/ha
P loss avoided kg/ha
K loss avoided £/ha
K loss avoided kg/ha
Net impact on CO2e emissions (kg/ha)
Net impact on CO2e emissions (kg/t)
Impact on gross margin
#1
£2.86
4.20
£2.04
3.78
-192.70
-18.34
£75.11
1
0
1
Silt
9
0.18
2.0%
2.0%
100.0%
0.27
£53.10
0.0
£3.58
0.00
£0.00
£5.30
8.55
2.91
0.34
Sand
7.7
0.15
2.0%
2.0%
100.0%
0.23
£45.43
0.0
£3.58
0.00
£0.00
£0.96
1.55
0.53
0.06
Peat
8
0.16
2.0%
2.0%
100.0%
0.24
£47.20
0.0
£3.58
0.00
£0.00
£9.63
15.54
5.28
0.62
Comment
From baseline tab
From baseline tab
From baseline tab
£1.57
2.31
£1.12
2.08
-105.98
-11.43
£56.39
£0.29
0.42
£0.20
0.38
-19.27
-2.43
£43.10
£2.86
4.20
£2.04
3.78
-192.70
-23.39
£56.11
Assuming same % avoidance as for yield penalty, capped by baseline
Assuming same % avoidance as for yield penalty, capped by baseline
Assuming same % avoidance as for yield penalty, capped by baseline
Assuming same % avoidance as for yield penalty, capped by baseline
Own estimate (Tim Chamen)
Needed for GHG calculations
Not Adjusted using diesal usage relativities (see baseline tab)
Assuming same % avoidance as for yield penalty, capped by baseline
Assuming same % avoidance as for yield penalty, capped by baseline
Assuming same % avoidance as for yield penalty, capped by baseline
Assuming same % avoidance as for yield penalty, capped by baseline
Estimate from Tim Chamen, on basis of capital cost and assumed annual usage
Diesel used is assumed to cancel out diesel savings elsewhere, so not net change.
94
Table A4.6
Tracked tractors
Efficacy
Yield
Diesel
Nutrient
#1 £21.00
Clay
10.2
0.26
2.5%
2.5%
100.0%
0.31
£66.20
0.0
£21.00
0.00
£0.00
£9.63
15.54
5.28
0.62
of which not as N 20
Base yield (t/ha)
Compaction yield penalty t/ha
Compaction yield penalty % per ha
Compaction penalty avoided % ha
relative to penalty
Additional Yield gain t/ha
Overall output value gain £/ha
Additional diesel usage
Cost £/ha (excl. Diesel) #1
Subsequent diesel reduction l/ha
Subsequent diesel reduction £/ha
N loss avoided £/ha
N loss avoided kg/ha
of which not leached
P loss avoided £/ha
P loss avoided kg/ha
K loss avoided £/ha
K loss avoided kg/ha
Net impact on CO2e emissions (kg/ha)
Net impact on CO2e emissions (kg/t)
Impact on gross margin
#1
£2.86
4.20
£2.04
3.78
-192.70
-18.34
£57.69
1
0
1
Silt
9
0.18
2.0%
2.0%
100.0%
0.27
£53.10
0.0
£21.00
0.00
£0.00
£5.30
8.55
2.91
0.34
Sand
7.7
0.15
2.0%
2.0%
100.0%
0.23
£45.43
0.0
£21.00
0.00
£0.00
£0.96
1.55
0.53
0.06
Peat
8
0.16
2.0%
2.0%
100.0%
0.24
£47.20
0.0
£21.00
0.00
£0.00
£9.63
15.54
5.28
0.62
Comment
From baseline tab
From baseline tab
From baseline tab
Own estimate (Tim Chamen)
£1.57
2.31
£1.12
2.08
-105.98
-11.43
£38.97
£0.29
0.42
£0.20
0.38
-19.27
-2.43
£25.68
£2.86
4.20
£2.04
3.78
-192.70
-23.39
£38.69
Assuming same % avoidance as for yield penalty, capped by baseline
Assuming same % avoidance as for yield penalty, capped by baseline
Assuming same % avoidance as for yield penalty, capped by baseline
Assuming same % avoidance as for yield penalty, capped by baseline
Own estimate (Tim Chamen)
Needed for GHG calculations
Not Adjusted using diesal usage relativities (see baseline tab)
Assuming same % avoidance as for yield penalty, capped by baseline
Assuming same % avoidance as for yield penalty, capped by baseline
Assuming same % avoidance as for yield penalty, capped by baseline
Assuming same % avoidance as for yield penalty, capped by baseline
Estimate from Tim Chamen, on basis of capital cost and assumed annual usage
Diesel used is assumed to cancel out diesel savings elsewhere, so not net change.
95
Table A4.7
CTF
Efficacy
Yield
Diesel
Nutrient
#1 £0.00
Clay
10.2
0.26
2.5%
2.5%
100.0%
0.51
£90.27
0.0
£0.00
16.30
£11.41
£9.63
15.54
5.28
0.62
of which not as N 20
Base yield (t/ha)
Compaction yield penalty t/ha
Compaction yield penalty % per ha
Compaction penalty avoided % ha
relative to penalty
Additional Yield gain t/ha
Overall output value gain £/ha
Additional diesel usage
Cost £/ha (inc. Diesel) #1
Subsequent diesel reduction l/ha
Subsequent diesel reduction £/ha
N loss avoided £/ha
N loss avoided kg/ha
of which not leached
P loss avoided £/ha
P loss avoided kg/ha
K loss avoided £/ha
K loss avoided kg/ha
Net impact on CO2e emissions (kg/ha)
Net impact on CO2e emissions (kg/t)
Impact on gross margin
#1
£2.86
4.20
£2.04
3.78
-236.71
-22.10
£114.17
1
1
1
Silt
9
0.18
2.0%
2.0%
100.0%
0.45
£74.34
0.0
£0.00
10.50
£7.35
£5.30
8.55
2.91
0.34
Sand
7.7
0.15
2.0%
2.0%
100.0%
0.39
£63.60
0.0
£0.00
4.70
£3.29
£0.96
1.55
0.53
0.06
Peat
8
0.16
2.0%
2.0%
100.0%
0.40
£66.08
0.0
£0.00
4.70
£3.29
£9.63
15.54
5.28
0.62
Comment
From baseline tab
From baseline tab
From baseline tab
Own estimate (Tim Chamen)
£1.57
2.31
£1.12
2.08
-134.33
-14.22
£88.56
£0.29
0.42
£0.20
0.38
-31.96
-3.95
£68.14
£2.86
4.20
£2.04
3.78
-205.39
-24.45
£81.86
Assuming same % avoidance as for yield penalty, capped by baseline
Assuming same % avoidance as for yield penalty, capped by baseline
Assuming same % avoidance as for yield penalty, capped by baseline
Assuming same % avoidance as for yield penalty, capped by baseline
Own estimate (Tim Chamen)
Needed for GHG calculations
Not Adjusted using diesal usage relativities (see baseline tab)
Assuming same % avoidance as for yield penalty, capped by baseline
Assuming same % avoidance as for yield penalty, capped by baseline
Assuming same % avoidance as for yield penalty, capped by baseline
Assuming same % avoidance as for yield penalty, capped by baseline
Estimate from Tim Chamen, on basis that capital cost is no different to that for conventional equipment if replaced under normal replacment cycle
96