BACKGROUND PAPER
DRIVERS AND SCENARIOS OF LAND USE CHANGE IN
IRELAND
Prepared by Teagasc
November 2014
Note: The views expressed in this background paper do not purport to reflect the views of the
Minister or the Department of Agriculture, Food and the Marine
1
TABLE OF CONTENTS
1.
INTRODUCTION ...................................................................................................................................... 3
2.
AGRONOMIC AND ENVIRONMENTAL DRIVERS OF LAND USE ................................................................. 5
CURRENT LAND USE IN IRELAND ................................................................................................................................ 8
AGRONOMIC IMPACT OF ENVIRONMENTAL CHARACTERISTICS........................................................................................ 12
3.
ECONOMIC DRIVERS OF LAND USE ....................................................................................................... 12
LAND MARKETS .................................................................................................................................................... 13
LAND STRUCTURE AND DEMOGRAPHIC DRIVERS OF LAND USE CHANGE .......................................................................... 15
POLICY DRIVERS OF LAND MOBILITY ......................................................................................................................... 16
NON-AGRICULTURAL LAND USE DRIVERS .................................................................................................................. 16
LESSONS LEARNED FROM NEW ZEALAND ................................................................................................................... 19
4.
TECHNOLOGICAL DRIVERS FOR HIGHER RETURNS TO LAND USE .......................................................... 20
TECHNOLOGICAL DRIVERS: ANIMALS ........................................................................................................................ 20
TECHNOLOGICAL DRIVERS: TILLAGE AND GRASSLAND................................................................................................... 20
COLLABORATIVE FARMING AND LAND ACCESS ............................................................................................................ 21
5.
SCENARIO ANALYSIS ............................................................................................................................. 22
SUSTAINABILITY IMPACT OF SCENARIOS ..................................................................................................................... 22
FORESTRY OPTIONS TO REDUCE NET CARBON EMISSIONS............................................................................................. 30
REFERENCES................................................................................................................................................... 32
2
1. Introduction
As a primarily animal based agricultural system in Ireland, agricultural production depends
heavily upon the land base. The objective of this paper is to consider how to maximise the
agricultural return from our land base while maintaining or enhancing our sustainability
credentials by factoring the necessary behavioural, market, technological and policy drivers.
With this objective in mind, we structure the report in four parts
 Agronomic and Environmental Drivers of Land Use
 Economic Drivers of Land Use
 Technological Drivers for Higher Returns to Land Use
 Scenario Analysis
The underlying story in relation to potential is the ongoing differential return to land resulting
in the different returns per hectare across different systems, where the income per hectare in
Dairy is more than double that of most other systems. When subsidies are excluded, this
difference is even greater.
As in the case of the sectors strategy to 2020 in Food Harvest 2020, the dominant policy
driver is the abolition of Milk Quota. Providing markets can be found for increased output, an
expanding Dairy sector in volume terms is likely to continue to be the dominant theme. Prior
to the introduction of Milk Quota in 1984, there were 3 times more Dairy cows than Suckler
cows. As a result of a variety of policy changes, suckler cow numbers increased and dairy
cows decreased so that both were at parity from about 1998, with a subsequent decline in
numbers to the present where there are about 1 million dairy and 1 million suckler cows.
Given the differential income between sectors, and given the abolition of quota, it seems
inevitable that there will be a gradual drift in the relative size of the two industries, involving
land use change. In terms of the Agricultural context we regard land use change not only as
the movement of land between agricultural and non-agricultural uses such as Forestry or
Settlement, but also in land use change between different systems; important given the
different returns. Much of the focus of this report will be on intra-Agricultural land use
changes. However despite income differences, there are many obstacles to substantial land
use change. This paper considers some of these obstacles and the drivers under the four
headings described above.
3
Figure 1.
Land Use Drivers
LAND USE
Agriculture and
Forestry
Forestry
Infrastructure
and Urban
areas
Un-utilisable
area
Use determined by land use
capability and infrastructure demand
Use determined by land use capability
Agriculture
Wood
products
Grassland
Annual Cropping
Ruminant
feeds
(Conc feed
Forage
Whole crop)
Milk, Meat
(Ruminants)
Use determined by:
Land use capability, local markets/infrastructure,
knowledge/tradition and the need for:
 high feed-value transportable animal
feeds
 high value food product substrates
Monogastric
feeds
(Conc Feed)
Meat, poultry
products
(Monogastrics)
Human food
Hort
Malt etc
Land use options and products. Black boxes are land uses, Green are intermediary products
and red are final products.
Figure 1 details the relationship between different land use drivers. Land use such as
Agriculture and Forestry, Urban and Infrastructure and un-utilisable land is determined by
land use capability and infrastructure demand. Agricultural land use in terms of Grassland or
Annual Cropping is determined by land use capability, local markets/infrastructure,
knowledge/tradition and the need for high feed-value transportable animal feeds and high
value food product substrates.
4
2. Agronomic and Environmental Drivers of Land Use
One of the drivers of land use and agricultural or forestry return from this land base are
agronomic or environmental characteristics of the land. The soils, and the dominant
agricultural activities that they support in any area, are influenced by a number of
environmental factors, including:
 Geology or sediments that soils are formed from
 Climate, particularly rainfall and temperature
 Position in the landscape (topography);
The structure of agricultural and forestry production is driven by the interaction between
these environmental characteristics. Tillage land is found in the free-draining soils of the
south-east, with intensive livestock farming on the limestone-rich lowland grasslands of the
south and midlands and the more extensive hill farming and forestry on the acid and peat
soils of the hills, mountains and western seaboard. Resulting from this interplay between
environmental factors, we see the clear North-East South-West dividing line between more
intensive/productive/higher income lands to the South and East and more extensive/lower
income lands to the North and West (Commins and Frawley, 1996).
These broad landscape categories were originally defined in the General Soils Map of Ireland
(Gardiner and Radford, 1980). Understanding the environmental factors that are important in
the formation of soils provides an insight into the soil properties. These, in turn, can inform
the understanding of the spatial distribution of agricultural production in terms of soil
capacity, limitations and management and soil suitability for various enterprises.
Fealy and Creamer (2014), utilising the rich spatial data of Teagasc (including the new Soil
information system), detail the spatial pattern of these characteristics. They highlight
particular drivers of agronomic conditions resulting from environmental characteristics such
as soil moisture deficit and grass growth days.
Climate and weather exert significant influence on agricultural production and by extension
the decisions on land use and the spatial distribution of agriculture enterprises in Ireland.
While the impact of major weather events such as drought or floods are generally obvious,
the impact of smaller variations in climatic factors such as temperature, radiation and soils
moisture are harder to see but significant nonetheless.
Ireland has a cool temperate western maritime climate with mild, moist summers and cool to
moderately warm, cloudy summers. The main atmospheric influences are maritime air from
the Atlantic and frequent eastwards passage of depressions. The prevailing winds are
westerly to southwesterly. Mean annual temperatures range from 9.0 deg C in the northeast to
over 10.6 deg c in the southwest. Crop growth is affected by the total amount of heat received
during the growing season. This variable is measured in degree-days which are the total
cumulative degrees by which mean daily temperature exceeds a crop specific threshold. The
number of degree days above 6 deg C ranges from 1,400 in the north to 1,700 in the south.
However even in the south the number of degree days above 10 deg C is only 700 which
inhibits the growth of crops with high temperature requirements. While the influence of
temperature is most directly evident in relation to crop growth it also affects animal
production though direct impact of temperature on animals but also indirectly influencing
fodder production.
5
Figure 2.
Annual average rainfall
Although precipitation facilitates amongst the highest grass and crops yields in the world,
excess precipitation can impact on grassland through the effect arising from excess soil
moisture with reduced productivity and limitations to trafficability and though direct
incidence of liver fluke on cattle and sheep and can result in ripening and harvesting
difficulties and to disease risk for cereal crops arising from excess moisture.
6
Figure 3.
Map grass growing days
Note: Isobars indicate days of grass growth
The configuration of geology, soil and topography in various climate zones across the
country give rise to recognizable landscape types in Ireland. These can be classified into a
number of primary landscape categories , or physiographic divisions, which were originally
delineated by Gardiner and Radford (1980). These five major physiographic divisions are:
 Mountain landscapes support shallow soils (Lithosols) mostly on steep slopes at >
500 m elevation. Wet soils (Groundwater and Surface-water Gleys) and acidic soils
(Podzols) are present where slopes are less steep. Blanket Peat occurs on flat and
gently undulating plateaus.
 Hill landscapes occur at altitudes from 150 to 365 m with soils generally developed
from shale, sandstone or occasionally granite. These soils are mainly acidic in nature,
including Brown Podzolics and Brown Earths, and some Surface-water Gleys.
Drumlin landscapes were formed during the most recent period of glacial advance.
7
Drumlins are oval-shaped hills that stand out as an undulating landscape. They were
formed from glacial deposits, sometimes with a rock core. These deposits vary in
thickness; thin deposits over rock cores tend to have drier soils on the drumlin slopes
such as Luvisols, Brown Earths and Brown Podzolics, whereas drumlins with thick
glacial deposits have wetter soils (Surface-water Gleys). Wet soils (Groundwater
Gleys and Peats) are usually found at the base of the Drumlin where water running
off the slopes accumulates.
 Flat to undulating lowland landscapes in limestone-dominated areas give rise to very
shallow soils (Rendzinas) where limestone bedrock is close to the surface, but deeper
soils (Luvisols and Surface-water Gleys) develop on the limestone-dominated glacial
till that covers much of the limestone bedrock.
 Acidic soil lowland landscapes are underlain by glacial deposits made up of
sandstones and shales, or granite or igneous and metamorphic materials, from
surrounding hill and mountains. These soils tend to be significantly more acidic than
those underlain by limestone. Brown Earths and Brown Podzolics form in coarser till
material and finer material (i.e. in shale areas) gives rise to wetter soils such as
Surface-water and Groundwater Gleys.
 Alluvial and Valley landscapes are found in small areas all over the country often at
the base of the hills/mountains and on the floodplain and terraces of the major river
valleys. The associated soils are mainly Groundwater Gleys, Alluvial Soils and Peat.
Figure 4.
Physiographic Regions of Ireland
Current Land Use in Ireland
8
Green et al. (2014) quantifies the spatial distribution of the nature of the land use resulting
from these environmental and agronomic conditions. They note in particular the challenges in
doing this as a result of the fact that Ireland does not routinely develop maps of land use.
Official estimates utilising LPIS, report that that in 2012, there are 382 kHa of crops and
3635 kHa of Pasture.1 Utilisable agricultural area has been declining at about 24000 hectares
per annum. Utilising CORINE data (See Figure 5), non-arable agricultural areas are the
largest land cover are, accounting for 62.6% of the land cover, with wetlands accounting for
15.2%, followed by forestry and semi-natural areas at 12.9% and Arable at 4.7%.
Figure 5.
Percentage of Level 1 land cover in Ireland for 2012.
Source: CORINE 2012 (unreleased data)
Specifically for forestry, the national forestry inventory estimates that 10.5% of the country is
covered in forestry, while the Teagasc Hedgerow map finds that in 2006, scrub and hedgerow
occupies 6.4% of the country.
There is a clear spatial pattern of Agriculture in Ireland. It is unsurprising that sectors with
higher returns are on the lands with better agronomic potential such as Dairy in the South and
West. Specialist sheep farms are concentrated in upland areas, where the land is less suitable
for larger animals or tillage.
Beef production systems dominate land use in the Border, Midlands and West region, but as
the most common farm type, have a strong presence in every region and land type.
The resulting economic scale is thus highly spatially correlated. Figure 6 describes the
spatial structure of Agriculture by Family Farm Income generated by the Teagasc Simulation
Model of the Irish Local Economy (SMILE). This model combines the 2010 Census of
Agriculture with the 2010 Teagasc National Farm Survey to provide farm income
information at a local scale. Figure 6 describes the pattern of market farming income from
farming (excluding a return to labour or land) per hectare, direct payments per hectare and
their sum family farm incomes per hectare. Market Income from farming reflects the location
1
LPIS is a geographically enabled accounting mechanism for the Single Farm Payment.
9
of dairy and tillage farming in the South and East. The spatial pattern of direct payments is
less clear cut. Combining the two measures, market income drives the overall spatial pattern.
10
Figure 6.
Spatial Pattern of Farm Incomes
(a) Market Family Farm Income per Ha
(b) Direct Payments per Ha
Source Teagasc: SMILE-FARM Model 2010
11
(c) Family Farm Income per Ha
Agronomic Impact of Environmental Characteristics
Given the share of pasture land within Agricultural areas and the importance of ruminant
animals within the agricultural industry in Ireland, an important driver of the return from the
land is the level of grass growth. Teagasc have currently developed a methodology utilising
remote sensing technologies based upon satellite imagery to quantify relative grass growth
cover across the country and over the year. Magnan et al. (2014) have undertaken a simple
statistical analysis utilising a model between the environmental and agronomic characteristics
described above and both grass cover at the start of the year and average grass growth in the
Spring. They find that while agronomic drivers are important, human intervention and grass
management is also very important.
Soil Functions as a driver
Schulte and O’Sullivan (2014) emphasise the importance of differential soil functions as a
driver of land use and land use change. While increasing agricultural productivity is essential
given global food security objectives, the agricultural industry is expected to meet
increasingly stringent environmental objectives. These include targets set in the Nitrates
Directive that sets out a regulatory framework for nutrient management; the Water
Framework Directive that requires that water bodies be of good ecological status; the national
biodiversity plan, through the designation of Natura 2000 sites. This means that there is an
urgent and growing pressure on soils to deliver these multiple functions simultaneously. The
EU Soil Thematic strategy outlines five functions delivered through agriculture:
 Primary productivity
 Water purification
 Carbon storage
 Habitat provision
 Nutrient Cycling
All soils provide all soil functions, but different soils are better at some functions than others.
Soil capacity depend upon land use and soil type. The challenge is to optimise the functions
of soil so that primary productivity achieves balance with the other functions. It is difficult to
increase production and carbon sequestration, water purification and biodiversity and nutrient
cycling, all at the same time in each location. Instead, the aim of Functional Land
Management is to enhance selective functions in specific places or soils to meet demands.
Functional Land Management means that the use of land is managed in such a way that the
total suite of soil functions is maximised, or – put colloquially – that ‘each soil performs
those functions that it is good at’. This does not equate to legislative ‘zoning’ of land use.
Instead, it would see the development of land use policies with the provision of mechanisms
to ensure that actual land management decisions reflect policy.
3. Economic Drivers of Land Use
Agriculture involves the derivation of economic output from the environmental potential of
the land outlined in the previous section. This report considers a number of economic and
social drivers of land use and land use change. Hanrahan and Donnellan (2014) details
macro-economic drivers of develops in Agricultural development and land use change. These
include:
12
 Income growth which will drive demand
 Income and employment growth will have an impact on agricultural factor markets
Economic recovery and associated employment growth may reverse the decline in off-farm
employment observed since the onset of the economic crisis. This will have the effect of
enhancing the household economic sustainability of low margin farming systems. It is likely
also to slow down incentives to land use change. Such a dynamic would represent an obstacle
to the expansion of dairy land use in Ireland.
Land Markets
Land markets in Ireland, discussed in Hanrahan (2014) are characterised by
 Extremely low land sales
 Relatively high land prices
 Moderate levels of leasing, however disproportionally of a short term nature
 Excessive land fragmentation, with farms often comprising multiple parcels
Data from the Census of Agriculture (CoA) and the Farm Structures survey illustrates the
importance of rented land in total Irish agricultural land use. In the 2010 CoA rented in land
accounted for 18% of utilised agricultural area (UAA), 30% of farms rented in some land,
while the average area rented-in in the State in 2010 was 19 hectares. The importance of
rented-in land varied by farm type and by region with rented in land most important on tillage
and dairy farms and least important in terms of share of land used on sheep farms. The
proportion of agricultural land that is rented in is low in comparison with other EU countries
and relatively stable over time.
Official data on Irish agricultural land rents and prices are currently not published by the
CSO or Eurostat. In data from the series developed by Nunan and used by Nunan and
Murphy and Roche and McQuinn (N-R-McQ) that has been extended using the survey of
Irish agricultural land sales by Busteed is presented. The nominal prices (euro per ha) are
deflated to 2013 prices using the CPI (2013=100). In Figure 7 the rental price data from the
extended N-R-McQ dataset is also presented with the data from the Teagasc NFS on average
rents paid used to extend the Nunan-Roche-McQuinn dataset.
13
Figure 7.
Trends in Irish Agricultural Land Prices 1979-2013
Source: Nunan, Roche and McQuinn, Eurostat, CBOI, CSO.
The trends in the data illustrate that the housing bubble and general macroeconomic
imbalances that characterised the first decade of the 21st century in Ireland had,
unsurprisingly, an effect on Irish agricultural land market sale prices and that the collapse of
the property bubble from 2007/2008 forwards led to a large and dramatic downward
correction in Irish agricultural land prices. In contrast Irish agricultural land rents have been
largely stable for the last 30 years.
There are no data collected on the term structure of Irish agricultural rental contracts.
Anecdotal evidence suggests that the majority of Irish land rental agreements are conacre
rental agreements and in this respect Ireland is an outlier in a European context where longer
term rental agreements are more prevalent.
This type of land market is a barrier to land use change through acquisition, both as a result
of low levels of land sales and relatedly the high price relative to the agricultural income
available on many farms.
While leasing land remains an option to access land or expand the land base, the extensive
use of conacre or short term leasing reduces the incentives to improve land and make it more
productive or to make land use changes that involve long term investments in facilities such
as milking parlours, roadways and water supplies that are required for dairy expansion.
Land fragmentation limits the use of land and technology more effectively, and also limits the
establishment of dairy farms, which require land close or contiguous with milking parlours as
animals must go to the milking parlour twice per day.
14
Land Structure and Demographic Drivers of Land Use Change
Geoghegan and O’Donoghue (2014) consider the impact that land structure and socioeconomic characteristics have on potential conversion to dairy farming. While much of the
dairy expansion anticipated over the period to 2020 will occur on existing dairy farms,
replacing existing beef cattle herds on these herds and through increased yield and intensity,
larger and higher stocked cattle farms are the farms more likely to convert to dairy in the
medium term.
However they find (see Figure 8) that only relatively few cattle farms have characteristics
that are associated with the possibility of converting to dairy; on good and moderate soil
quality.
The majority of agricultural land in Ireland is used for the purposes of cattle farming.
However, since public policy targets envisage an expansion of dairy production, it is likely
that there will be a necessary increase in the amount of land with dairy. There is already a
pre-existing share of land on dairy farms that is either spare dairy platform or is being used
for non-dairy purposes. According to NFS data, land on dairy farms currently being used for
other purposes corresponds to 11.9% of all agricultural land (44.4% of land on dairy farms),
while spare dairy platform corresponds to 2.9% of all land (11% of land on dairy farms).
Of the alternative farming systems, cattle managing systems are the most complementary for
moving into dairy. Nearly half of the land on farms with good or medium soils is used for
cattle farming. However, of these, 24% have farms with less than 25 hectares and would thus
require consolidation before moving into dairy. Of the remainder, 55% of cattle farms on
good or medium soils have stocking rates of less than 1.4 livestock units per hectare (LU/ha)
and are larger than 25 hectares. The stocking rate is low largely due to either age (31% aged
65+) or due to other work commitments (33% with an off-farm job). Those most likely
therefore to consider moving into dairy are those with stocking rates of 1.4 LU/ha or higher
and a farm of at least 25 hectares, which amount to 21% of cattle farmland in the
good/medium soil range and to 10% of all farmland with these soils. Of the farmers with the
necessary land and stocking rate, 25% have off-farm employment. Age is also likely to be an
issue with 19% over 65 in 2011, and only 29% 50 years of age or younger.
15
Figure 8.
Land Structure in Cattle Farms (in hectares), 2011
Policy Drivers of Land Mobility
Many policy initiatives have been enacted to encourage land mobility in Irish agriculture, but
access to land continues to be a problem. These initiatives include mechanisms such as
incentivised land leasing, the removal of barriers associated with farm partnerships and farm
consolidation restructuring relief. However challenges remain to increase the extent of land
mobility. Due to the tiny amount of land put on the market each year, as well as the
prohibitive expense, purchasing land is not an option open to most farmers. In 2011, only
17.6% of land was accessed by farmers through renting according to the National Farm
Survey (NFS), which remains far below the European average. There have been recent efforts
made to improve incentivise long-term land rental agreements (5 years or greater) through tax
relief on long-term rental income. Consideration should continue to be given to the interplay
between land mobility incentives arising from both the tax system and the direct payments
system. The definition of an “ active farmer” is one such example where the taxation system
and direct payments system could be aligned.
Non-Agricultural Land Use Drivers
Non-Agricultural land use in recent years has had very significant impacts on national land
use. Meredith and O’Donoghue (2014) analyses changes in agricultural land use and the land
area allocated to housing over the period 1991 to 2011. It explains the increase in utilisable
agricultural area identified above, arising from a change in methodology and mainly
occurring in the North and West on more marginal land.
16
It notes the increase in housing by 366,000 in rural areas as result of population growth
between 1991 and 2011 (Figure 9). Reflecting the concentration of urban areas in better
farming areas, most of the increase in housing occurred on better soils.
Figure 9.
Changes in Agricultural Area
Drawing upon the CSO’s population forecast, there will be an expected half a million more
people in Ireland in the period to 2026. The largest population growth rates are expected in
areas of best soil in the South and West, which could see a significant area lost from farm
land.
The CSO in its recent regional population projections has forecasted an increase in the
national population by 10% to 2011 (See Table 3), with the population expected to surpass 5
million people. Although this is about a third of the population growth that occurred between
1991, the expected growth is likely to be concentrated in areas in the South and East with
better land.
Over time, Ireland has converged to European norms in terms of the number of persons per
household. Given the ageing population, this is likely to continue to 2026. If the number of
persons per household reached 2.5 per household in 2026, then Ireland would require in the
region of 340 thousand new houses (including apartments) by 2026, with approximately 150
thousand in rural areas. On the basis of the analysis above, including ancillary services and
infrastructure, this may require in the region of 180 thousand hectares of additional land,
17
much from the better farming areas, which for example is greater than the entire likely
forestry planting area in that period.
18
Table 1.
CSO Population 1991-2011 and Projections to 2026 by Region
1991
1996 2011 2026
% Increase (1991-2011)
Border
403
407
516
531
27.9
Dublin
1021.5 1058 1,262 1,448
23.5
Mid-East
329.1
347
534
639
62.2
Midland
254.9
206
284
307
11.3
Mid-West
310.7
317
378
403
21.6
South-East
383.2
392
499
542
30.3
South-West
532.3
547
662
719
24.4
West
291.1
352
441
455
51.4
State
3526
3626 4,575 5,044
29.8
Number of Households
1127 1678 2018(e)
Persons per household
3.22 2.73
2.50(e)
Source: CSO Census of Population and Population Projections
(e) – Estimated by Authors
% Increase (2011-2026)
3.0
14.8
19.7
8.2
6.6
8.6
8.5
3.3
10.3
Lessons learned from New Zealand
Given the focus on grass based animal systems, there is much discussion about learning
lessons from New Zealand in relation to their dairy expansion over the past 3 decades.
Thorne et al. (2014) undertook a comparison between Ireland and New Zealand in relation to
lessons that can be drawn in relation to how land use change may differ in a post quota
environment.
In terms of countries which have an extreme export orientation, NZ does appear to relatively
low total costs of production. In addition, NZ has exhibited one of the fastest paces of
productivity growth internationally in recent times.
While climatic conditions and ensuing successful grass-based dairy farming are common to
both countries, there are dissimilarities in relation to the degree of industry liberalisation. Part
of this relates to the policy environment. While milk quota abolition will make the market
environment more similar, Dairy farming in Ireland will continue to operate within the
confines of the CAP and the associated conditions, such as GAEC, Greening etc. that is
associated with the CAP. Also in New Zealand the rapid expansion in dairy production
following deregulation happened in the absence of much of the restrictions of Environmental
Policy that will apply in Ireland post quota.
As a much bigger country with larger distances between urban and rural areas, there are
fewer non-agri-food employment opportunities in New Zealand than in Ireland. The land
market in New Zealand also is much more fluid than in Ireland, where less than 1% of the
land is traded in any year. Ireland is much more reliant on rented land, which reduces
incentives to invest in facilities required for dairy expansion. There have also been
differences in the way debt is provided for land acquisition. On the taxation side, zero level
capital gains tax and the agri deposit type scheme which operates to handle income volatility
are two very important differences in taxation policy, which facilitate agricultural expansion.
19
A tradition of succession planning, through lower order share-milking to 50:50 share-milking
partnerships, facilitated the asset accumulation of young farmers and an exit strategy for
those ready for retirement, which is not replicated in Ireland to the same extent.
NZ has a long history of competing at world market price levels and has mechanisms in place
to deal with volatility such as income smoothing tools which are not evident in Ireland, which
has built up a business/commercial ethic which is not fully mirrored in Ireland which still
bears a lot of hallmarks of family farming type operations.
4. Technological Drivers for Higher Returns to Land Use
Increasing the return from land depends upon a number of factors
 Improved technical efficiency through the use of better technologies
 Sustainable intensification, where land is more intensively farmed within
environmental limits
 Land use change from lower value to higher value systems
 Finding markets for increased output
Different technological and practice adoption pathways will result in different outcomes in
terms both Agricultural output and the required land use to achieve specific goals in specific
sectors. So better technology and practice adoption can achieve a given dairy outcome,
requiring less land and/or at a lower intensification level.
Technological Drivers: Animals
French et al. (2014) detail that farm level intensity and technological adoption were lower
than economic optimum levels during the quota period due to an inability to expand on farm.
The study details how milk production per cow grew at 2.8% in the pre-quota period, but
only by 1.2% in the post quota period. An improvement in the growth rate of milk yield is
expected post quota, particularly given the advances in genomic selection. The study outlines
target growth rates in a variety of on-farm practices in dairy farms. These include
 Milk characteristics
 Calving intervals and dates
 Genetic improvement
 Stocking Rate
 Labour Efficiency
 Environmental efficiency
 Net Margin
Technological Drivers: Tillage and Grassland
Spink and O’Donovan (2014) outline potential sources of production and efficiency gains for
grassland and crops. In relation to grassland, targeted improvements were outlined for
 Higher grass utilisation.
 Earlier calving.
 Higher Nitrogen usage on farms.
 Land improvement/ adaption.
 Higher reseeding levels.
20





Soil fertility improvements .
Higher usage of clover within swards.
Better use of varieties using Pasture Profit Index.
Better use of grassland technology
Increase usage of clover in grass swards, based on achievement of higher DM output
and animal performance
 Move areas for silage harvesting to out farms on dairy farms.
 Better focus on grass nutritive value across the grazing season.
 More focus on prediction of grass growth.
Areas of genetic improvement has been identified in relation to the following traits:
 Nitrogen use efficiency (NUE) in ryegrass
 Cold tolerance in ryegrass
 Waterlogging stress in ryegrass
In terms of tillage, most of the potential for expansion lies in continued yield improvements.
As specialist tillage farms have a high technology uptake, the biggest potential yield gains
can occur through tillage enterprises on mixed farms increasing technology adoption.
Given stagnation in farm yields in most tillage crops in recent years whilst genetic
improvement has continued there is pent up yield potential to be exploited through improved
management, it is estimated that yields could increase by between 1.5% and 2.5% per hectare
per year over the coming decade.
In terms of management there is room for improvement in:
 Improved timing and targeting of fungicide inputs.
 Increased movement from spring to winter feed barley to result.
 Development of agronomic approaches for oilseed rape and beans suited to Irish
conditions.
 Increased production of break crops to meet greening rules.
 Development of low cost reliable establishment systems that can cope with variable
soil conditions.
Genetically, there is room for improvement in
 Yield potential.
 Nitrogen use efficiency (NUE).
 Disease resistance.
 Waterlogging stress in barley.
Collaborative Farming and Land Access
In addition to technological and farm management practice innovation to improve land use
efficiency and productivity, there are opportunities to achieve gains via organisational
innovations. Collaborative farming, described in Curran and Phelan (2014) can contribute to
increasing the productivity of Irish farmland by bringing together factors of production such
as land, labour, capital and enterprise, improving management ability and a means of
achieving greater scale in a socially sustainable way.
21
Collaborative farming can produce improved outcomes at farm level, resulting in a more
productive use of the land base, while allowing farmers to maintain control of their own land.
Collaborative arrangements such as registered farm partnerships, contract rearing and share
farming demand that the landowner is as a minimum an active participant in a management
sense.
Collaborative farming takes a more inclusive approach that encompasses more than just
taking over the land. It is a business arrangement that is to the benefit of all the parties
involved. It includes the land and labour (skillset) that is available through all the
participating farmers to the arrangement. When land and labour are taken together, they can
lead onto a more balanced lifestyle for all involved. This is a core value of good
collaborative farming.
5. Scenario Analysis
Given the variety of drivers for land use change, Donnellan and Hanrahan (2014) consider,
scenarios of potential change within the Agricultural sector. They utilise Teagasc’s FAPRI
model to generate a reference run to 2025 and consider the economic implications of two
alternative possible scenarios.
The reference scenario anticipates that Beef and Dairy will remain the dominant systems, but
that dairy cow numbers will expand to return to the number that existed prior to the
introduction of milk quota in 1984, by 2025. With stagnant returns in the beef sector, it is
anticipated that Suckler and Other cow numbers will gradually decline over time, declining
by about 13% to 2025 from 2014 levels
The reference scenario assumes that while the national stocking rate is likely to increase only
slightly, it is anticipated that the intensity of dairy farms will increase. Land may transfer to
dairy production from other enterprises, principally beef production given its low
profitability, but given that the rate of land sales in Ireland is as low as ¼ of a percent per
annum, this process is likely to be slow, barring a radical increase in liquidity in the Irish land
market. Developments in other sectors will not be very dramatic. The area allocated to tillage
crops is not expected to grow. The number of sheep is expected to decline due to low levels
of profitability. Production of pig and poultry meat is expected to grow but not dramatically.
In order to test the robustness of the projection, two alternative scenarios are considered
(albeit not modelled); a Low scenario that sees a lower increase in dairy and lower decrease
in Beef and conversely a High scenario, with the opposite trends.
They find that as the time horizon extends towards and beyond 2025 competitive tensions
between dairy and beef production should begin to become more pronounced. While in the
short term dairy expansion will take place largely within the existing land base of current
dairy farms, this expansion potential will be become exhausted at some point in the medium
term. The difference in the profitability between dairy farming and much of the existing beef
production will create an economic incentive for the conversion of land use.
Sustainability Impact of Scenarios
22
Different development pathways are also likely to have different environmental implications.
Schulte et al. (2014) considers the environmental implications of alternative growth
pathways. They find that the 2025 growth scenario will result in small increases in animal
numbers and fertilizer usage. These projected increases are much smaller than those
frequently assumed in the public discussions surrounding the potential environmental impact
of Food Harvest 2020.
The study considers the implications of the alternative scenarios under different
environmental dimensions:
 Water Quality
 Greenhouse Gas Emissions
 Biodiversity
The main issues requiring consideration and mitigation in the context of water quality are:
 Pressures: a potential local concentration of livestock leading to increased organic N
and P and fertiliser N loadings, with associated localised increases in farm N
surpluses;
 Pathways: an increase in surface-subsurface-stream connectivity through maintenance
and upgrading of drainage networks;
 Receptors: the requirement to further reduce impacts on water quality in high-status
sites.
The study notes that there opportunities to improve nutrient use efficiency; improvements
that would improve both a farmers bottom line and reduce impact on environment.
While FH2020 calls for growth in Irish agriculture, this may pose challenges in an
environmental context. In 2012 agriculture was responsible for almost 32 percent of
Ireland’s total GHG emissions (EPA 2014). In this context Ireland is unusual, since typically
in developed economies agricultural emissions would represent a much smaller share of the
national total.
Figure 10.
2010
Proportion of GHG emissions from agriculture in EU Member States in
23
Source: European Environment Agency Data Viewer
At a global level it seems inevitable that agricultural greenhouse gas (GHG) emissions will
increase in the coming decade. Decoupling food production from associated GHG emissions
globally is much talked about by policy makers, and indeed the dual challenge of maintaining
food security while mitigating emissions has been acknowledged under the 2030 Climate and
Energy Policy Framework (EU 2014). Achieving this decoupling will be challenging in the
short term. Such decoupling would require that while food production grows, aggregate
agricultural GHG emissions are contained or even reduced and /or carbon sequestration
enhanced by increased forestry and optimal pasture management. The challenge of
decoupling food production from GHG emissions will be influenced by a number of drivers.
Implications of projected agricultural activity levels for GHG emissions
The changes in agricultural activity levels projected for the period to 2030 have implications
for the evolution of emissions of GHG from the Irish agricultural sector. As noted earlier,
growth in the volume of agricultural output will always lead to growth in the volume of GHG
emissions in the absence of an, as yet unobserved, productivity change that delivers
additional output without the use of additional physical resources. However, offsetting some
of these emissions via an optimal land-use policy may contribute to further reducing
Agricultural emissions intensity. In summary, by 2030 the number of dairy cows will have
increased while the aggregate inventory of cattle is expected to have decreased marginally
when compared with the FH2020 reference period. The number of beef cows is projected to
decline significantly, while the level of tillage activities will be largely stable over the
projection period to 2030.
The intensity of grassland synthetic nitrogen use is illustrated in Figure 11. A downward
trend in nitrogen use per hectare is evident in the period 2000 to 2012. Some of the decline
can be explained by more efficient usage of slurry, but the rising price of nitrogen may have
also been a factor in the decline in its use.
24
Figure 11.
Intensity of Nitrogen Usage on grassland in Ireland
Source: FAPRI-Ireland (2013)
Nitrogen use reached a low in 2011 and 2012. However, nitrogen use rose again in 2013,
most likely as a reaction to the experience of the fodder crisis. It is difficult to be sure what
the required amount of nitrogen is at the current level of production intensity, given the extent
of the variation in nitrogen use in the last three years. In turn this makes it more challenging
to project future levels of nitrogen use.
Over the projection period there is an intensification of some agricultural production (most
notably dairy production) which is projected to result in increased usage of inputs. This is
particularly noticeable in the case of projections of synthetic nitrogen use, principally due to
the increase in milk production which is projected to occur. Milk production has a synthetic
nitrogen requirement per hectare that is typically three times that of beef systems. In the
aggregate, fertiliser usage rises over time reflecting the increasing intensity of production and
the increasing share of milk production in overall bovine agriculture.
Activity projections (animal numbers, waste volumes, synthetic nitrogen use) can be used to
estimate the GHG emissions from the agriculture sector in the same manner that historical
GHG emissions are estimated in the national GHG inventory report. The projected GHG
emissions to 2030, along with historical emissions since 1990 are shown in Figure 12.
25
Figure 12.
GHG Emissions from Irish Agriculture 1990-2030
Source: FAPRI-Ireland (2013)
The net effect of projected developments in levels of agricultural activity and input usage is
to leave agricultural GHG emissions in 2030, at 19.7 mt CO2 eq. Over the projection period,
aggregate agricultural GHG emissions exhibit an increase relative to the 2005 level by over 5
percent.
At the EU Member State (MS) level existing GHG reduction targets, as set out in the EU
ESD place an overall cap on the level of GHG emissions and do not make allowance for the
impact of upward drivers. Policy therefore requires that the reduction in GHG emissions
achieved via the downward drivers should outweigh the growth in GHG emissions resulting
from the upward drivers. However, in the context of the next ten or fifteen years, given the
expect growth in food production and anticipated developments in GHG mitigation
technologies, containing agricultural emissions may be an unrealistic aspiration in an Irish
context.
In terms of biodiversity, critical conservation, relating primarily to 14% of the land area of
Ireland designated as Natura 2000 sites, is unlikely to be significantly impacted by potential
changes in land-use patterns to achieve the production targets of Food Harvest 2020/2025.
However, the biodiversity associated with the remaining 86% of the land area is more likely
to be impacted by changes in land-use patterns such as expansion or intensification.2
The ecological value of agri-ecosystems can be viewed as a gradient (Figure 13) ranging
from sites that are considered to have high ecological value (e.g. Natura 2000 sites that host a
2
In relation to hedgerows, the majority of them are designated as landscape features under GAEC (Cross
Compliance) and hence they are afforded some protection (generally, landscape features cannot be removed,
under certain circumstance they can). However landscape features are only one of a n umber semi-natural
habitats, the majority of which are more likely to be impacted by changes in land-use patterns such as expansion
or intensification.
26
range of habitats and species of conservation concern) through to agri-ecosystems that are
considered to have relatively low ecological value (e.g. improved agriculture and forestry
hosting a low abundance and diversity of species) (Finn & Ó hUallacháin, 2010).
Figure 13.
Gradient in ecological value associated with agri-ecosystems
Natura 2000 (SAC+SPA+NHA)
Eligible habitats not designated for Natura 2000
Habitats containing rare or threatened species
High Nature Value Farmland
Common farm habitats
Semi-improved grassland
Improved agriculture/forestry
This study identifies three generic pathways, through which the Food Harvest 2025 targets
can be achieved (Figure 14):
 ‘intensification’,
 ‘expansion’ and
 ‘resource efficiency’.
Figure 14.
Visual representation of the three pathways towards Food Harvest 2020:
Intensification, Expansion and Resource Efficiency
27
Sources: Schulte et al., 2014
The intensification pathway may be associated with negative impacts on water quality, and
potentially biodiversity, if intensification takes place on land of high nature value. By
contrast, the expansion pathway is unlikely to impact significantly on water quality (unless
associated with significant drainage works). This pathway however, is likely to impact on
greenhouse gas emission targets and biodiversity. Finally, the resource efficiency pathway
will few, if any, impacts on the environment, but this pathway is likely to be associated with
significant costs, if pursued in isolation.
The pathway analysis suggests that a sustainable increase in agricultural production requires a
mosaic of solutions, i.e. a targeted mosaic of the three scenarios above. Obviously, the
‘efficiency’ scenario is preferable from an environmental perspective, but this scenario on its
own is unlikely to deliver on the Irish 2020 agricultural growth targets, because of the
diminishing economic returns, and ultimately higher costs. As a result, it is likely some form
of both ‘expansion’ and ‘intensification’ will be required, both at national scale and indeed
global scale. Here, we introduce the concept of ‘Functional Land Management’, where these
scenarios are managed with a view to achieve the growth targets, while minimising impacts
on the environment.
The risks associated with each of these pathways is context specific, i.e. specific to the
existing farm systems (infrastructure and management), soil types, hydrology, and
landscapes.
As a practical example, consider in Table 4 the drivers of changes in gross margin amongst
dairy farmers over a similar length period as 2014-2025 in the past, 1997-2008. We note that
farmers in the four highest quintiles of gross margin achieved income growth by increasing
their yield annum, by increasing the area they farmed with dairy, but interestingly reducing
their intensity. The bottom quintile had the lowest growth rate, with the lowest yield increase,
but increased stocking rate. While intensity growth was driven by increasing yield combined
with overall limits driven by milk quota, the environmental implications of the top farms
resulted in fewer cows producing more milk and thus reducing the environmental foot print.
Thus farm level growth has been driven by a combination of land expansion and yield growth
– the resource efficiency scenario. Those farms at the top of the distribution have
demonstrated very significant yield growth, demonstrating strong potential for the resource
efficiency scenario.
Table 2.
Annualised Growth Rate in Components of Gross Margin 1997-2008
1
0.005
0.016
2
0.024
0.018
Gross Margin per Hectare Quintile
3
4
0.030
0.037
0.015
0.019
Gross Margin
Yield
(Lt
per
Livestock Unit)
Intensity (Livestock 0.006
-0.010
-0.006
Unit per Hectare
Area (Hectare)
0.018
0.027
0.030
Source: Teagasc National Farm Survey
Note: Quintiles of Milk produced, ranked by Gross Margin per Hectare
28
5
0.032
0.025
-0.007
-0.012
0.030
0.020
In Table 3 we summarise the scientific evidence to date on known impacts of each of these
pathways on the five indicators of sustainability, corresponding to each of the five soil
functions introduced above.
Table 3.
Projected primary impacts of three contrasting pathways of
increased agricultural production on five aspects of sustainability. ‘+’ and ‘-‘
indicate positive and negative effects, respectively, and ‘o’ indicates no effect.
Scenario
Economic
Water
sustainability quality
Greenhouse
Biodiversi
gas emission ty
intensitya
Nutrient
recycling
Intensification
+
–
o
o/–
o
Expansion
+
o
–
–
+
Resource
efficiency
+–
+
+
o
o
a. Emission intensity is defined as the greenhouse gas emissions per unit of agricultural produce, using
life cycle analysis.
The intensification pathway may be associated with negative impacts on water quality, and
potentially biodiversity, if intensification takes place on land of high nature value. By
contrast, the expansion pathway is unlikely to impact significantly on water quality (unless
associated with significant drainage works). This pathway however, is likely to impact on
greenhouse gas emission targets and biodiversity. Finally, the resource efficiency pathway
will few, if any, impacts on the environment, but this pathway is likely to be associated with
significant costs, if pursued in isolation.
‘Functional Land Management’ means that the use of soils is managed in such a way that the
total suite of soil functions is optimised to achieve maximum economic productivity which
does not undermine other environmental functions, or – put colloquially – that ‘each soil
performs those functions that it is good at’, in line with contemporary thinking.
At this point, it is important to consider that implementation of Functional Land Management
does not equate to legislative ‘zoning’ of land use. Rather than legislating for particular land
management practices, an alternative would see the development of land use policies with the
provision of incentivisation mechanisms to ensure that actual land management decisions
reflect agreed policy priorities.
There are two mechanisms through which such a bottom-up approach could be readily
incentivised. First, the process of developing and continuously updating River Basin District
29
Management Plans can in principle provide an essential tool to facilitate this bottom-up
approach. These plans are – by definition – context-specific in terms of soil and water
resources, and are developed with stakeholder consultation as a core-ingredient of the
process. There is scope to further strengthen this process by deeper engagement with and
from the agricultural stakeholders, including farmers, advisors, local authorities and
agricultural state actors. Secondly, specifically where context-specific measures may be
required for the protection of ‘high status’ sites (as provided for in the draft GLAS scheme),
these can be incentivised by specific targeting of agri-environmental schemes towards
measures and sites where maximum (positive) impact is likely to be achieved, in line with the
review and recommendations by Finn et al. (2009).
As Ireland uses its strong environmental credentials to market its food exports via the Origin
Green programme, it is essential that as the Agricultural sector expands, it is essential both to
monitor continued good practice in terms of these sustainability credentials, but also
important to provide early warning systems to the sector to be able to mitigate potential risks
to these status. It is important to utilise representative, detailed farm level data to identify
these issues.
Forestry Options to Reduce Net Carbon Emissions
Farrelly and Ní Fhlatharta (2014) highlights the potential contribution of forestry in reducing
net carbon emissions for agriculture is highly dependent on further expansion of the forest
estate and getting an ‘early start’. Current Government forest policy is to increase forest
cover to 18% of the land area by 2046, requiring an annual planting programme of 16,000 ha
per annum. The expansion of the forest estate depends on land use change to forestry; much
of this is currently in agricultural use. An analysis of suitable land resources for forestry in
Ireland carried out for COFORD land availability working group, indicates that
approximately 54% of the land area 3,75 Million hectares of land are most likely to have
potential for afforestation (Farrelly and Gallagher, 2013). This excludes areas biophysically
and biologically unsuitable for forestry and areas subject to national and EU designations.
These lands could be considered more suitable for targeted agricultural production associated
with Food Harvest 2020 targets and may be less readily available for forestry expansion. An
area of 1.3 Million hectares of land with more difficult soils and subject to a more limited
range of agricultural enterprises may have more potential for forestry expansion given
historical planting rates. These lands have been shown to have high production rates and may
have significant sequestration potential if planted with appropriate species, this could offer
significant potential to reduce net carbon emissions. The conversion of land to forestry will
continue to depend on farmers availing of grant aid and annual premium payments, which
may prove to be attractive to landowners depending on farming enterprise, land quality and
individual social circumstances. Some farmers hoping to expand agricultural production may
see forestry planting as a mechanism to reduce GHG emissions and may opt to plant more
marginal parts of farms.
Other forestry measures that could assist in reducing net carbon emissions include the use of
forest management options which may increase forest carbon sequestration capacity in the
new and existing resource.
30
Figure 15.
Area of land (3.75 million hectares) most likely to have potential for
afforestation (Farrelly and Gallagher, 2013)
Note: Green: Higher potential for afforestation
31
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