Developing a High Nature Value Farming area
indicator
FINAL REPORT
30th of November 2003
Revisions June 2004
Erling Andersen (FSL)
David Baldock (IEEP)
Harriet Bennett (IEEP)
Guy Beaufoy (IDRISI)
Eric Bignal (EFNCP)
Floor Brouwer (WUR)
Berien Elbersen (WUR)
Gerd Eiden (LANDSIS)
Frans Godeschalk (WUR)
Gwyn Jones (EFNCP)
David McCracken (EFNCP)
Wim Nieuwenhuizen (WUR)
Michiel van Eupen (WUR)
Stephan Hennekens (WUR)
George Zervas (EFNCP)
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HNV farming project Final report
Contents
1. INTRODUCTION ................................................................................................................................ 3
Why indicators? ................................................................................................................................ 3
Objective of this project .................................................................................................................... 3
What are High Nature Value farming areas? ................................................................................... 4
Structure of the workprocess and verification .................................................................................. 5
Structure of the report ....................................................................................................................... 7
2. CONCEPTUAL FRAMEWORK - DEFINITION OF HNV FARMLAND .................................... 8
Background ....................................................................................................................................... 8
Defining High Nature Value farmland .............................................................................................. 9
Developing the HNV concepts into a methodology. ........................................................................ 12
3. METHODOLOGY ............................................................................................................................. 14
Introduction to the approaches of the project ................................................................................. 14
3.1 LAND COVER APPROACH ................................................................................................................. 14
Background and objectives of the land cover approach ................................................................. 14
Data sources ................................................................................................................................... 15
Methodology ................................................................................................................................... 15
Limitations of the land cover approach .......................................................................................... 18
Outcome of the land cover approach .............................................................................................. 18
3.2 FARMING SYSTEM APPROACH ......................................................................................................... 19
Background and objectives of the farming system approach .......................................................... 19
Data sources ................................................................................................................................... 20
Structure.......................................................................................................................................... 21
The typology .................................................................................................................................... 21
Limitations in the farming system approach ................................................................................... 25
Outcome of the farming system approach ....................................................................................... 26
3.3 SPECIES APPROACH ......................................................................................................................... 27
Background and objective of species approach .............................................................................. 27
Data sources ................................................................................................................................... 28
Methodology ................................................................................................................................... 29
Selecting bird species judged to be associated with HNV farmland in different regions of Europe
........................................................................................................................................................ 30
Limiting the focus to bird Species of European Conservation concern .......................................... 30
Outcome of the species approach focussing on bird species indicative of different HNV farmland
........................................................................................................................................................ 31
Outcome of the species approach focussing on bird SPECSs ......................................................... 35
Limitations of the species approach ................................................................................................ 37
4. RESULTS ............................................................................................................................................ 39
4.1 SOUTHERN EUROPE ........................................................................................................................ 39
Broad characteristics of HNV farming in the southern countries ................................................... 39
Results of the land cover approach ................................................................................................. 40
Results of the farming systems approach ........................................................................................ 43
Results of the species approach ...................................................................................................... 48
Overall conclusions on the results for the southern countries ........................................................ 48
4.2 WESTERN EUROPE AND SCANDINAVIA ........................................................................................... 50
Broad characteristics of HNV farming in the northern Europe and Scandinavia .......................... 50
Results on land cover approach ...................................................................................................... 51
Results on farming system approach............................................................................................... 54
Results on species approach ........................................................................................................... 59
Overall conclusion on Western Europe and Scandinavia ............................................................... 59
4.3 CENTRAL AND EASTERN EUROPE ................................................................................................... 61
HNV farming in the region.............................................................................................................. 61
Identifying HNV areas .................................................................................................................... 62
The land cover approach ................................................................................................................ 62
The farming systems approach ....................................................................................................... 64
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The species approach ...................................................................................................................... 66
Data considerations ........................................................................................................................ 68
5. CONCLUSIONS AND RECOMMENDATIONS FOR FUTURE WORK ................................... 69
REFERENCES ......................................................................................................................................... 74
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HNV farming project Final report
1. Introduction
Perhaps expressed at its simplest the aim of this project is to obtain an objective
indication of where HNV farmland is predicted to occur in Europe together with an
impression of the likely agricultural characteristics of the farming systems practised in
association with such HNV farmland
Why indicators?
The Concept of High Nature Value (HNV) farmland and farming systems has been
evolving over the last fifteen years in Europe. In the European Union this has been
closely linked to the aim of integrating environmental concerns into Community
policies. The idea that nature values, environmental qualities and even cultural heritage
are linked to or dependent on farming also underlies and supports the concept of a
multifunctional 'European model of farming' which provides benefits other than food.
The 'High Nature Value farming' idea thus ties the preservation of the diversity and
wildlife value of the countryside to the need to safeguard the continuation of farming
in certain areas and the maintenance of specific farming systems associated with the
long term management of these areas.
At a more technical level the issue of High Nature Value areas has been brought into
the discussion on indicators for the integration of environmental concerns into the
Common Agricultural Policy (COM(2000) 20). The European Commission has given
an overall rationale for the development of indicators (COM(2001) 144, p. 3):
to help monitor and assess agri-environmental policies and programmes, and to
provide contextual information for rural development in general;
to identify environmental issues related to European agriculture;
to help target programmes and address agri-environmental issues;
to understand the linkages between agricultural practices and the environment.
Objective of this project
Though the existence of a wide range of predominantly low intensity farming systems
valuable for the rural environment has been recognised for more than a decade, there is
a lack of data on the precise distribution, character and evolution of the farmland and
the farming systems in question.
To remedy this the study has had to provide a framework for compiling compatible
information on HNV farmland across Europe, laying some of the foundations for
longer term improvements in data. Based on this information the primary objective of
the study is to develop and test a High Nature Value farming area indicator or
indicators at EU level and to analyse the possibilities for extending these to all EEA
member countries.
The tasks to be addressed in the project were:
An initial survey of relevant European datasets
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HNV farming project Final report
The conceptual development of a potential HNV farming area indicator
The elaboration of a map of HNV farmland in the EU
An analysis of the possibilities of extending any HNV farmland indicator to all
EEA member countries and Switzerland
The validation of results through consultation with regional experts etc.
An evaluation of the project results and recommendations for future work.
It was understood from the outset that there was no guarantee that an acceptable
indicator could be developed for use at a pan European level. However, it was essential
to investigate a range of different approaches and to explore the options thoroughly.
Indicators
The report and the underlying study are not on HNV farming as such, but on
developing indicators in relation to HNV farming and farmland. Thus, detailed
descriptions of the characteristics of HNV farming systems across Europe cannot be
found here. Detailed information has been gathered, both at the European level and in
individual countries, but only to support the choices made in working up the
approaches for developing indicators taken in the project. The reasoning behind this is
that the indicator(s) need to be developed using Pan-European data to make them
applicable across EU Member States and perhaps beyond. This is a major challenge
because of the limitations of the Pan-European datasets available to effectively capture
the characteristics of HNV farmland. It is important to keep this in mind as it
constrains the scope, methodology and results of this project.
What are High Nature Value farming areas?
HNV farming areas in Europe include a wide range of landscapes and habitats like the
Spanish dehesas, Alpine pastures, the wet heaths and moors of Western Ireland and the
grazed salt marshes of Northern Germany. These at first glance very diverse areas are
in fact all landscapes that have in common the presence of valued habitats and species
and the presence of specific types of farming.
One of the first essential tasks of this project was to define HNV farmland in a way
that links the presence of natural values directly to the farmland. We used the
following working definition,
‘High Nature Value farmland comprises those areas in Europe where agriculture is a
major (usually the dominant) land use and where that agriculture supports or is
associated with either a high species and habitat diversity or the presence of species of
European conservation concern or both’.
The project was undertaken by a core team drawn from six different institutions, with
members based in a range of European countries. In addition, regional specialists were
subcontracted to work on some detailed national profiles and specific questions.
Further experts were involved through a verification process described below. Several
team meetings were held, including a number with EEA staff. A considerate number of
working papers were generated, including national profiles for a range of countries. A
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collection of these papers is available separately from this report, which is the principal
output of the project.
Overall approach
The early stages of the project involved examination of the range of potentially
relevant data sources available at a European level and some national sources as well.
This exercise was complemented by conceptual work, drawing on the literature and
earlier studies of HNV farmland or livestock systems in Europe. Some work at a
national level proved essential, particularly in identifying the characteristics of HNV
farmland in areas which have been studied more closely in order to narrow the range of
variables that might be used to develop an indicator. After an initial analysis it was
decided to pursue three different methods to identifying HNV farmland areas utilising
data on land cover, the character of farming systems and the distribution of wild
species, specifically birds. A fourth approach using bird data to identify a particular
type of HNV farmland was also explored. The scope for compiling these approaches
was also considered.
Structure of the workprocess and verification
The project schema in box 1 below gives an overview of the structure of the
workprocess in the project and the approach taken from defining HNV farmland to the
conclusions and the recommendations. In box 2 on the following page an overview is
given of the verification process pursued in the project. As can be seen, national (or
regional) experts have been involved at different stages of the project, particularly to
ensure that the interpretation of results based on Pan-European datasets does reflect as
far as possible the situation on the ground and the range of conditions in Europe.
Another important part of the verification process was the organisation of 3 parallel
regional workshops held in Montpellier 16th of September 2003. At these workshops
the preliminary results were presented to experts and stakeholders. It should be
mentioned that the work on using the bird species data approach did not follow this
verification process. It was never anticipated that this approach would lead very far
and the more fundamental work based on land cover data and farming system typology
had been given higher priority at that time.
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Box 1: Project schema
What is HNV farmland in Europe?
Three principal types of HNV farmland:
Type 1.
Semi-natural areas
Type 2.
Extensive mosaic landscapes
Type 3.
Areas hosting species of conservation concern
How to identify?
Using pan European data
For types 1 and 2 three methods adopted
in parallel
For type 3
a different method adopted
Land cover approach using CORINE
Mapping wild species of conservation
Farming systems approach
concern
using FADN
using European bird data
Species approach
using European bird data
Conclusion and recommendations
Potential for deploying outputs from different, complementary methods
each with some drawbacks
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Box 2: verification process
Draft selection of HNV land cover classes
Draft typology of HNV farming systems
National reports
Consultations with national
experts
2nd Draft selection of HNV land cover
classes
2nd Draft typology of HNV farming
systems
Workshops at Montpellier
conference
Final selection of HNV land cover classes
Final typology of HNV farming systems
Structure of the report
The main report is divided into four sections and supported by relevant annexes. An
additional set of Working Documents put together during the course of the project is
provided separately. In section 2 of this report we present a range of conceptual
considerations, including the definition of HNV farmland and related terms. As
described above, it was decided to proceed by pursuing three different methodologies
for the identification of indicators, bringing these together in the closing state of the
project. In section 3 these three methodological approaches (land cover, farming
system and bird species-led) are described. In section 4 we critically assess the
predicted distribution and characteristics of HNV farmland utilising the proposed
indicators, focussing on three distinctive regions: Southern Europe, Western
Europe/Scandinavia and Central/Eastern Europe. Finally, in section 5, we draw some
conclusions, consider the potential application and also the limitations of the indicators
and make final recommendations.
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2. Conceptual framework - definition of HNV farmland
Background
The concept of European farmland being of high value for nature in many ways runs
contrary to accepted wisdom about the interaction between farming and the
environment. It is certainly true that, over large parts of north-west Europe, agriculture
has been and continues to be, a major factor in reducing biodiversity. Reflecting this,
the majority of the work on agriculture carried out by environmental NGOs and
government agencies focuses on ameliorating the negative effects of agriculture. Most
of these relate to the high intensity of external inputs, especially fertilisers and
chemicals, the simplification of the landscape, both physically and in terms of land use,
and to pollution of soils and ground water.
During the 1980s and 1990s it began to be recognised that in many places particular
styles of farming were not only less damaging to the environment but were in fact
positively linked to biodiversity. Some might even be essential for maintaining the
current nature conservation value (e.g. Baldock, 1990, Beaufoy
et al 1994, Bignal
et al.
1994, Bignal & McCracken 1996a, 1996b). Very often these "systems" were long
established with modernisation being prevented by physical constraints, location or, in
some places, regional culture.
To differentiate them from the more damaging modernised, intensive systems, they
were termed "Low Intensity Farming Systems". The latter term has recently tended to
be replaced with High Nature Value (HNV) farming systems, although the two are not
strictly interchangeable (see Defining High Nature Value and HNV farmland below).
At a general level it is relatively easy to conceptualise these systems from actual
examples. In the report on "The Nature of Farming" in 1992 there were case studies of
livestock, cereal, permanent crop and mixed systems which were of significance for
nature conservation (Beaufoy
et al 1994).
The biological value of these systems relates to a number of essential factors such as:
They maintain a wide range of vegetation structures and niches (e.g. different semi-
natural habitats, different land use types) on farmland which in turn are essential
for species of other biota. At its simplest a varied habitat mosaic generally
maintains the highest biodiversity (Angelstam, 1992).
Their farming practices (e.g. through grazing and other management factors) create
levels of disturbance, which maintain many vegetation communities which are
highly valued for their nature value.
Farming practices are generally more constrained by location, climate and
topographic factors leading to greater synchronisation with natural features and
processes.
They often farm at a large scale producing conditions favourable for the viability
(sustainability) of plant and animal populations.
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But producing a detailed definition of High Nature Value farming systems is much
more difficult - but nevertheless essential if a Europe-wide classification with
indicators is the objective.
A huge problem is the loose terminology that tends to be used in the literature and
policy debate. For example "HNV farming areas" is ambiguous and implies that the
farming itself is of High Nature Value, "HNV areas" also commonly used makes no
direct reference to agriculture and could imply that both optimal and sub-optimal
farming could occur; whilst naming a set of "HNV farming systems" suggests that
farming at varying levels of appropriateness leads to the nature value and seems to
suggest that all farms within these classes are of High Nature Value, while those
outwith are not. We need to explore these issues further.
Defining High Nature Value farmland
Whilst most previous approaches to classifying farmland have tended to focus on
aspects of agriculture (specifically either low intensity or high intensity), this project
focuses on High Nature Value. The word "value" in HNV refers to conservation value
and necessarily introduces a strong element of subjectivity that would not be there if
we were dealing with more quantitative subjects such as biological diversity or species
richness. It also introduces the question of the relative position and extent of particular
habitats or species - which might be valued differently in different locations.
So, regardless of agricultural activities, our first step was to agree some definitions
relating to what is meant by High Nature Value to provide the foundations for
subsequent analyses and classification. After considerable debate the three broad
categories of farmland set out below and defined in box 3 were agreed on as being
potentially of HNV.
Type 1: Farmland with a high proportion of semi-natural vegetation.
Type 2: Farmland with a mosaic of habitats and/or land uses
Type 3: Farmland supporting rare species or a high proportion of European or World
populations.
Type 1 and Type 2 are based on factors relating essentially to biodiversity although
this is not quantified. Type 3 areas will mostly overlap with Type 1 or Type 2 areas but
not always (for example some highly valued rare bird species such as bustards are
associated with biologically simplified agricultural areas with low vegetation
diversity).
On the one hand we use
land cover surrogate. We believe that for semi-natural areas
we can not necessarily quantify the biodiversity present, but it has inherent value as
well as being associated with a range of species. Large areas of semi-natural land cover
(visible, by definition, from space) also have the potential to support a wide range of
biodiversity at a variety of scales. To complement this we have a land use surrogate.
We do acknowledge that some farms of high biodiversity might not be located by our
methods. We are not convinced that this class accounts for a significant proportion of
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Europe’s HNV farmland. On the other hand we appreciate that it may be locally
significant but, if so, would need to be defined by local criteria.
From this we have established a set of broad definitions that together we feel helps
distinguish most types of
farmland associated with HNV. The definitions are set out as
a dichotomous key in the table below.
Box 3: Definition of types of potentially HNV farmland
Question 1: Is the farmland dominated by semi-natural vegetation?
If yes =
HNV farmland type 1
(e.g. heath, dehesa or
grasslands)
If no, go to question 2
Question 2: Is it dominated either by low intensity agriculture or with a
mosaic of significant density ofsemi-natural and cultivated land and small-
scale features. component parts that provide "ecological infrastructure"
If yes =
HNV farmland type 2
(e.g dry arable areas and
small-scale farms in
mosaic farmland in
southern Europe.
Ecological infra-
structure Small scale
features includes open
water (e.g. on rice
farms), ditches, relict
grassland, field boun-
daries and woodland.
If no, go to question 3
Question 3: Does the area host rare species or support a large proportion of
European or world population of certain species?
If yes =
HNV farmland type 3
(e.g. areas of intensively
managed wet grassland
favoured by migrating
geese)
If no = Not HNV farmland
From this key, it becomes apparent that the team did not define HNV primarily in
terms of legally recognised rare species or Habitats Directive priority habitats. We
believe that a biodiversity-oriented definition is in fact closer to the spirit of the EU's
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HNV farming project Final report
biodiversity strategy, while still being able to encompass narrower policy goals
focussed on rare or threatened species and habitats.
Defining HNV farmland itself is essential, but not simple. We use the following
definition:
High Nature Value farmland comprises those areas in Europe where agriculture is a
major (usually the dominant) land use and where that agriculture supports or is
associated with either a high species and habitat diversity or the presence of species of
European conservation concern or both.
This does not necessarily imply causality between farming practice and the existence
of high nature value on farmland. High species and/or habitat diversity may exist
alongside or despite farming (although for most categories of HNV farmland there
would have been a positive link, at least historically).
We have established a set of criteria that together we feel help to distinguish most
types of HNV farmland. The criteria include factors relating to land cover on the one
hand and land use on the other. Both are only proxies for HNV farmland since they do
not measure biodiversity as such. Lack of adequate data on species distribution and
habitat condition at an appropriate scale prevents a quantitative biodiversity-based
approach. However, we feel confident that the proposed criteria form a reasonable
basis for the delineation of areas where HNV farmland can be expected with high
probability, given sufficient locational details on the one hand and access to data on the
other.
The issue of appropriate agricultural management of HNV farmland, whether
historically or at present, is complicated because it cannot be defined directly from the
presence of HNV farmland. In most cases it is conveniently tackled through the
farming systems approach This approach defines (within the limits of resources and
knowledge currently available to us) those systems that are likely to promote the
maintenance or enhancement of High Nature Value based mainly on past examples and
statistics on contemporary systems. These HNV systems may or may not be visible in
terms of land cover. Identifying and naming a set of systems as such does not imply
that all farms within the class in fact support HNV or that there are no HNV farming
systems outside these classes. However, they can help to understand the management
needs of High Nature Value farmland and support the identification of further potential
HNV areas.
Since we are not able to distinguish by either the land cover or the farming system
approach the precise extent of HNV farmland, and since we believe that some HNV
areas are sub-optimally managed with current farming practices, we are unhappy about
the ambiguities of the term “HNV farming area”. We therefore propose to re-name this
indicator
area of High Nature Value farmland rather than to use the initially defined
High Nature Value farming area. By taking out the term 'farming' the implied positive
link between current farm management and species and habitat richness is eliminated,
yet the critical association between High Nature Value and farmed area (and not other
land uses) is still expressed.
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This new phrase (area of HNV farmland) also contains some difficulties which we
must acknowledge. In particular, we stress that any
areas of HNV farmland which
might be identified by this project are not necessarily homogeneously HNV or
homogeneously well-managed. Conversely, farmland outside of these areas is not
necessarily non-HNV. We are making generalisations only. Similarly,
areas identified
using one approach may differ from those identified by another – neither is necessarily
wrong.
Developing the HNV concepts into a methodology.
The 3 types of HNV farmland pose different problems in terms of their characterisation
and location. To address this we have developed 2 complementary approaches (land
cover and farm system typology) to describing and locating types 1 and 2 which we
feel confident about; and we have explored the potential of a third approach (using bird
species), which although more limited in terms of results does highlight why there is
the need for indirect indicators.
For the identification of Type 1 and Type 2 areas the first approach used was land
cover which, although saying nothing about state relative to the optimum (even
assuming this could be defined), is suited for the identification of
areas, that is the
location. The second is agronomic and economic data derived from farms (e.g. FADN,
IACS, farm census) which, by analysing the pressure from farming practices, gives a
general indication of the presence and character of farming systems that are likely to
manage HNV farmland. The third approach involves using the distribution of birds
associated with HNV farmland to predict the potential occurrence of their breeding
habitats which in turn is used to infer whether the area is of HNV or not.
For the location of Type 3 HNV areas we regard the only feasible way forward to be
the plotting of the actual species distributions. Limitation of species data (e.g. for
invertebrates) means that this is not possible on an European scale other than for
breeding birds. We have explored the possibility of this approach.
In table 1 the expected output from the different methodological approaches are
summarised. Though the table indicates that the different approaches cover different
types of HNV farmland, the validity of the results might differ. This is for example the
case for the land cover approach and for the farming system approach, where the
results for the semi-natural areas (HNV farmland type 1) can be expected to be more
valid than the results for the mosaic landscapes (HNV farmland type 2).
Also the land cover approach is principally about locating areas whilst the farm system
approach is about describing the types of farm. The species approach has not produced
easily interpretable results because there are so many assumptions built into the
methodology. In the presentation of the results references to the different types of
HNV farmland are not made explicitly.
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Table 1: Expected output of the different approaches in relation to the different types of HNV
farmland
HNV farmland type 1
HNV farmland type 2
HNV farmland type 3
Land cover approach
Presence of land cover
Presence of land cover
Not suited
classes related to HNV
classes related to HNV
farming.
farming.
Indicative maps of the
Indicative maps of the
location of HNV
location of HNV
farmland.
farmland.
Farming system
Presence and extent of
Presence and extent of
Not suited
approach
HNV farming systems.
HNV farming systems.
Indicators on the extent
Indicators on the extent
of HNV farmland.
of HNV farmland.
Indicators on the
Indicators on the
pressure from farming
pressure from farming
on HNV farmland.
on HNV farmland.
Species approach
Predicted occurrence of Same as on the LEFT.
Species distribution
the habitats of key
maps show relationship
farmland species in a
to other approaches and
50x50km square
help identify other types
Indicative maps.
of farmland
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3. Methodology
Introduction to the approaches of the project
As outlined above the project has developed three different approaches to developing
indicators of High Nature Value Farming. The
land cover approach aiming to identify
HNV farmland using general land cover data, the
farming system approach aiming to
identify farming systems likely to promote the maintenance or enhancement of nature
value and the species approach aiming to identify selected species supported by or
associated to HNV farmland.
Each of these approaches has different strengths and weaknesses and it has been an
important task of the project to test the different approaches and evaluate the potential
use in an indicator framework.
In this section the methodology of the three different approaches is described in detail.
3.1 land cover approach
Background and objectives of the land cover approach
In the
Nature of Farming (Beaufoy
et al. 1994) typical characteristics of low intensity
farming systems were identified and it was recognised that the types of land cover
present was a potentially important indicator of whether the farming systems being
practised were likely to be low-intensity or not. In particular, it was found that many of
these HNV farming systems were being practised on farmland containing a high
proportion of semi-natural vegetation and that this typically occurred in close
association with areas of natural vegetation (such as woodlands or wetlands) and other
landscape features, or within landscapes containing a large diversity of agricultural
land covers.
The definition of HNV farmland used in this project reflects these land cover
characteristics, with the presence of semi-natural vegetation being considered a
dominant feature of Type 1 HNV farmland and the occurrence of a mosaic of different
low intensity agricultural land uses and other landscape elements being a key feature of
Type 2 HNV farmland. Given the close association of these land cover features with
HNV farmland, it was considered that obtaining an indication of where relevant semi-
natural vegetation types, mosaic farmland and landscape features occur throughout
Europe may therefore suggest where there was also a higher likelihood of HNV
farmland occurring in those areas.
The main objectives of the land cover approach was therefore to:
Assess the range of land cover information available at the European level and
select the most appropriate dataset to work with.
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HNV farming project Final report
Identify relevant land cover types within that dataset considered to be closely
associated with agricultural land.
Identify those agricultural land cover types considered to be closely related to HNV
farmland throughout Europe and plot the location of these cover types on maps.
Make an assessment of whether or not the maps of the chosen land cover types
reflects the likely distribution of HNV farmland on the ground.
Given the concentration of land cover data on semi-natural vegetation types, it was
expected that the land cover approach could potentially be useful to locate both Type 1
and Type 2 HNV Farmland. However, by definition all Type 3 HNV Farmland is not
necessarily associated with particular land cover characteristics and so it was not
expected that the land cover approach would be useful as a means of locating that type
of HNV farmland.
Data sources
At the European level CORINE-Land Cover (LC) was considered to be the best source
of consistent detailed land cover information. One advantage of using CORINE above
other land cover information sources such as PELCOM and the IGBP-DIS Land Cover
information, is that it contains a much larger spatial variety of Land Cover Classes
(LCCs) and also contains a diversity of LCCs which can be regarded as being
potentially closely associated with agricultural land (Table 2). The latter range of LCCs
also offers the potential to distinguish specific LCCs that may have stronger links with
HNV farmland. An additional advantage of CORINE is that the minimum mappable
unit is quite small (corresponding to 25 hectares) and so the potential to provide good
location precision is quite high. The last advantage of CORINE is that it is currently in
the process of being updated. Hence, if this project established that the existing
CORINE data did have a real potential to identify HNV farmland, then the likelihood
of updated data becoming available at some point in the near future would also give
EEA the possibility of making an additional assessment of the potential for the
CORINE land cover approach to be used as a monitoring tool.
Methodology
CORINE contains information on the distribution of a total of 44 Land Cover Classes
(LCCs) and nineteen of these were selected on the basis of being potentially closely
associated with agricultural land (Table 2).
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HNV farming project Final report
Table 2: The 19 Corine Land Cover Classes (LCCs) which were regarded as being potentially
associated with agricultural land
CORINE code
CORINE LCC
2.1.1
non-irrigated arable land
2.1.2
permanently irrigated land
2.1.3
rice fields
2.2.1
vineyards
2.2.2
fruit trees and berry plantation
2.2.3
olive groves
2.3.1
pastures
2.4.1
annual crops associated with permanent crops
2.4.2
complex cultivation patterns
2.4.3
land principally occupied by agriculture with significant natural vegetation
2.4.4
agro-forestry areas
3.2.1
natural grasslands
3.2.2
moors and heath lands
3.2.3
sclerophyllous vegetation
3.2.4
transitional woodland-scrub
3.3.3
sparsely vegetated areas
4.1.1
inland marshes
4.1.2
peat bogs
4.2.1
salt marshes
Prior to attempting to select which of these LCCs may be more indicative of HNV
farmland, it was decided that this selection process would need to be stratified using a
combination of national boundaries and Environmental Zones (see Annex A for
description of Environmental Zones used in this project). This stratification was
considered necessary:
To take into account the fact that there are known inconsistencies in the way
CORINE classes have been interpreted between the different European countries
To reflect the fact that there are differences in the type of HNV farmland that can
occur between different countries and also often within different climatic and
altitude zones.
National experts in each country were provided with the list of CORINE LCCs and,
where relevant, an indication of the extent and location of each environmental zone
within their respective countries. These national experts were then asked to provide for
each Environmental Zone separate lists indicating those LCCs which they judged could
be used to potentially indicate (a) the Minimum potential location of HNV Farmland
with that zone and (b) the Maximum potential location of HNV Farmland within that
zone. The
Minimum selection was to include only the LCCs which are made up
primarily of HNV land, while the
Maximum selection was to include all LCCs that
include
some farmed HNV land. It was assumed that the Maximum selection would
also contain much non-HNV land, whilst the Minimum inevitably would exclude some
known HNV land. The rationale behind the Minimum and Maximum approach was
that it was intended that taken together these may provide some measure of the
extremes within which HNV Farmland was likely to occur.
For some Member States, this initial selection of Minimum and Maximum HNV LCCs
was checked and revised by comparing maps of the selected LCCs with the location of
areas where HNV farmland was known to exist and with national spatial data sources,
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HNV farming project Final report
e.g. inventories of non-improved grasslands, and/or national land cover maps which
can be considered of better quality for indicating where the HNV farming areas are
than CORINE.
Further validation and revision of the selection of LCCs per country and
Environmental Zone occurred during workshop sessions held in Montpellier, France in
September, when delegates from countries throughout Europe were shown draft maps
based on the selected LCCs and their views sought on the selection of LCCs which
would be appropriate for the countries within each of the three European regions
(Northern Europe & Scandinavia; Southern Europe; Central & Eastern Europe)
A final revision of the LCCs selected per country/Environmental Zone occurred when
the national experts were asked to compare their initial selection with those made by
experts within other countries located within the same Environmental Zones. If large
differences between selections occurred within similar Environmental Zones,
corrections were applied in order to achieve greater coherence between countries and
zones, or explanations for the differences were required and registered. An example of
the results of the definite selection is shown in table 3 and the final selection for all
Member States and Environmental Zones is shown in annex B.
Table 3: Example of selection of LCCs in the Alpine South Environmental Zone (for all other
selections see Annex B) X = selected, O = not selected.
MIN
MAX
MIN
MAX
MIN
MAX
Class
Fran-
Fran-
Alpine South
no.
ce
ce
Italy
Italy
Spain
Spain
Non-irrigated arable land
211
0
X
0
X
0
0
Permanently irrigated land
212
0
0
0
0
0
0
Rice fields
213
0
0
0
X
0
0
Vineyards
221
0
0
0
0
0
0
Fruit trees and berry plantation
222
0
X
0
X
0
X
Pastures
231
X
X
X
X
X
X
Annual cops associated with
permanent crops
241
0
0
0
0
0
0
Complex cultivation patterns
242
0
X
0
X
0
X
Land principally occupied by
agriculture
243
0
X
0
X
0
X
Agro-forestry areas
244
0
X
X
X
X
X
Broad-leaved forest
311
0
0
0
0
0
0
Coniferous forest
312
0
0
0
0
0
0
Mixed forest
313
0
0
0
0
0
0
Natural grasslands
321
X
X
X
X
X
X
Moors and heath lands
322
X
X
X
X
X
X
Sclerophyllous vegetation
323
0
0
0
0
0
0
Transitional woodland-scrub
324
0
X
X
X
X
X
Bare rocks
332
0
0
0
0
0
0
Sparsely vegetated areas
333
0
X
0
X
0
X
Burnt areas
334
0
0
0
0
0
0
Inland marshes
411
0
X
0
X
X
X
Peat bogs
412
0
X
0
X
X
X
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HNV farming project Final report
Limitations of the land cover approach
Even though CORINE was the best source of land cover data identified, it is clear that
using CORINE LCCs as a means of potentially locating High Nature Value Farmland
has many limitations:
Some problems are related to the internal logic of CORINE, which is basically to
identify land cover that is relatively uniform. Because the minimal mapping entity
was 25 hectares CORINE classes are either determined by the most dominant land
use or they have been classified as a mixed class. Especially with the mixed
CORINE classes, such as complex cultivation patterns, it is difficult to determine
whether HNV farming areas are contained in this class, especially because most of
the CORINE classes, e.g. “pastures” and “non-irrigated arable land”, do not
distinguish between intensive and extensively managed types.
Some problems relate specifically to the version of CORINE we have worked with.
Firstly, this version of CORINE is several years old and has a large temporal
heterogeneity (1985-1994) which is mainly the consequence of image data
availability and addition financial restrictions. Secondly, the coverages of Finland
and the United Kingdom are the result of translation of classes from independent
national land cover databases. The coverage of Sweden is based on the national
land cover, which was translated into the seven CORINE land cover classes, which
in turn were combined with PELCOM, resulting in the 44 CORINE classes. Also,
some other localities, such as the Greek islands, are not covered by the existing
CORINE version.
It is essential to note that forest LCCs were excluded from the LCC selection
process because CORINE does not distinguish between forest management systems
or give any indication of whether forest are subject to grazing or other forms of
agricultural management. Consequently, if forest LCCs had been included then this
would automatically included a very large amount of forest that has no connection
with any type of farming at all. It is, however, recognised that the decision to
exclude forest LCCs from the selection process also means that there was no
possibility of identifying the location of various types of grazed forest that may be
considered HNV farmland.
Finally, it is essential to remember that land cover information cannot (except in
extremis) indicate anything about the quality of the Nature Value relative to its
potential since it indicates little about management practices. It should therefore be
emphasised that the areas shown in the land-cover derived maps should not be
interpreted as meaning that farming
management in the mapped areas is necessarily
appropriate in relation to the nature values, since in some cases it is clearly not.
Outcome of the land cover approach
The spatial distribution of the final selection of LCCs was mapped for each
country/Environmental Zone and the results combined and presented in the form of:
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HNV farming project Final report
One map showing the distribution on the ground at a 10 x 10 km square level of
those LCCs considered to potentially indicative of the Minimum location of HNV
Farmland and
one map showing the distribution on the ground at a 10 x 10 km square level of
those LCCs considered to potentially indicative of the Maximum location of HNV
Farmland.
These maps are presented in the Results section together with a consideration of their
likely potential usefulness and a consideration of the similarities and dissimilarities
between the outcome from the land cover approach and the outcome from the other
two approaches.
The land cover approach is useful for identifying the potential location of HNV
farmland or at least where there is a higher or lower probability of HNV farmland
occurring. However, it cannot be used to indicate anything about the intensity of the
farming systems or management practices occurring in those areas or even whether the
LCCs mapped are actually under agricultural management at all. The strength of the
land cover approach is its potential to highlight areas where HNV farmland may be
occurring and thereby also provides a means of targeting more accurately any future
validation and ground-truthing exercises. However any potential measurement of the
likely extent of HNV farmland within these areas cannot, for the reasons given above,
be obtained from the land cover approach. Rather this should be best attempted using
the farming system approach and it is in this way that the two approaches have the
potential to complement each other.
3.2 Farming system approach
Background and objectives of the farming system approach
The Nature of Farming study put High Nature Value farming on the agenda and
pointed to the existence of a wide range of low intensity farming systems valuable for
nature. However, the study also revealed a lack of data on the precise distribution,
character and evolution of the farming systems in question.
In this light the overall objective of the farming system approach is to identify those
systems that are likely to promote the maintenance or enhancement of nature value.
However, the brief for this project also specified that the approach should take into
account the need for monitoring. This meant that the availability of data which were
both coherent across the EU and regularly updated became an over-riding factor in
methodology and in the selection of discriminators. The challenge has therefore been
to transform the qualitative knowledge of High Nature Value farming systems on the
ground (mostly based on case-studies providing no predictive capability) into
meaningful, quantitative and monitorable information based on statistical sources
which are universally, regularly and uniformly updated.
It is important to realise the limitations inherent in the farming system approach. The
link between farming practices and the nature values is a complex and seldom direct
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HNV farming project Final report
one. In particular, it is rarely causal in terms of the data gathered in EU-wide data
sources. For example, stocking density is almost never
directly related to HNV
anywhere - the effect is indirect through other species and the structure and
composition of the habitat. This can vary between different environments, so that a
stocking density which may appear generally positive in one place may be highly
negative in another.
This means that identifying and naming a set of farming systems as HNV farming
systems does not imply that all farms within the class in fact support HNV or that there
are no HNV farming systems outside these classes.
However, subject to weaknesses in the data, the strength of the farming systems
approach is that it relates to the management practices of the farms. This means in
principle that the approach can help us to understand the management needs of High
Nature Value farmland and support the identification of further potential HNV areas.
In monitoring terms this means that the farming system approach can be used to give
indications on the pressure from farming in relation to nature values and that it can be
used as a tool for designing and assessing relevant policy initiatives.
It may indeed be that the identified HNV systems may not be visible in terms of land
cover at the large scale. They may be present on single farms and still be significant
on the scale at which some species organise their lives. Thus the farming system
approach has the capacity, if carefully tuned and tested, not only to make predictions as
to the
state of HNV, but also to focus down to a much finer scale than the land cover
approach
without losing meaning.
Data sources
As a part of the project the existing data on farming has been reviewed and it was
decided to use the data from the Farm Accountancy Data Network (FADN) for the
farming system approach. There are several reasons for this. Firstly, FADN contains a
broad set of data enabling links to be made to environmental aspects of the sample
holdings. In particular, it contains data on farm area, stocking and input levels - all
important if intensity of use is at all related to HNV.
Secondly, FADN contains data on the level of individual farms enabling the grouping
of farms on the basis of a range of variables. Finally, FADN is updated regularly
enhancing the usefulness for monitoring purposes. It was also an important factor, that
by choosing to work on FADN data, the work could build upon the work on typologies
of grazing livestock systems done in the ELPEN-project.
The use of IACS data was rejected in the initial stages of the work since a) the data is
confidential at farm level, b) there is no consistent EU-wide accessibility of this data,
c) it does not cover all farm types (being related to claims under specific CAP direct
support schemes) and d) the variables available in the data differ between the Member
States. However, it potentially provides a much larger data source than FADN and is at
very least accessible to national policy makers.
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HNV farming project Final report
Structure
To organise the information on HNV farming systems derived from the FADN data a
typology of HNV farming systems has been designed. The typology is based on the
work in the Nature of Farming study, expert knowledge from the different Member
States and on the previous work in the ELPEN project, which also included statistical
analyses.
The typology is divided in three parts: (1) A common level covering EU-15, (2) a
regional level covering Western Europe and Scandinavia and (3) a regional level
covering Southern Europe. The regional-level typologies represent further refinements
of the EU-15 typology, enabling further differentiation between systems than is
possible at the common level.
There are two reasons why we operate with different types at a common level and at a
regional level. Firstly, different discriminating variables and different threshold values
have to be applied in the different regions according to differences in farming systems
and in the environment. Thus working at a regional scale enables more differentiation
than is possible at the common level.
Secondly, working with different levels in some cases makes it possible to by-pass the
limitations in the FADN data-set in relation to the number of farms that needs to be in
the data-set to extract information. Furthermore, establishing a common typology
separately allows for direct cross regional comparisons Thus working at a regional
(this time as opposed to sub-regional) level allows for a degree of meaningful
generalisation which is necessary in order to fulfil the demands of the contract and
which would not otherwise be possible.
Despite the fact that we attempted to optimise the degree of regionalisation used in our
analysis, we recognise that both between farms within one part of that region and
between the various different sub-regions, there are significant variations in the
threshold values of the various indicators of HNV farmland. To illustrate this we have
attempted a maximum/minimum approach corresponding to the approach taken for
land cover. The maximum approach aims to include ”all” HNV farms but in doing so it
is acknowledged that some non-HNV farms will be included. The minimum approach
aims to include only HNV farms, but accepts that some HNV farms will be excluded.
The 'reality' on the ground is therefore somewhere in between the results that can be
captured by the two different approaches..
The typology
The typology distinguishes between 6 types of farming systems (see also figure 1):
HNV cropping systems, low intensity arable systems. Might have livestock, but
this is not the dominant income source.
HNV permanent crop systems, low intensity olives and other permanent crop
systems.
HNV off-farm grazing systems, systems with cattle, sheep or goats grazing outside
the farm for example on common land.
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HNV farming project Final report
HNV permanent grassland systems, cattle, sheep or goat systems where the main
forage resource is grass from permanent or rough grassland.
HNV arable grazing livestock systems, cattle, sheep or goat systems where the
main forage resource is arable crops.
HNV other systems, mainly low intensity pigs or poultry systems
Figure 1: Overview of the different types of HNV farming systems
All farming
Non-HNV
systems
farming
systems
HNV farms
6. HNV ot-
1. HNV
2. HNV
with cattle,
her systems
cropping
permanent
sheep or
(mainly Pigs
systems
crop systems
goats
and poultry)
Dryland
Systems with
3. Off-farm
systems
cattle, sheep
grazing
or goats
systems
Systems
4. Arable
Fallow land
without cattle,
grazing
systems
sheep or goats
livestock
systems
5.
Permanent
grassland
Rough
Only in
systems
grassland
Western
systems
Europe and
Scandinavia
Permanent
Only in
grassland
Southern
systems
Europe
Basically, this divisions is based on the findings in the Nature of Farming study added
the more detailed division of livestock systems developed in the ELPEN project. This
structure also links to the division in EU farming types used in the agricultural
statistics, which again is based on an evaluation of the dominant source of income.
This means that livestock might be present at cropping or permanent crop systems, but
that the non-livestock production is more important economically. In general input use
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HNV farming project Final report
is used to define HNV versus non-HNV. This includes the cost of fertilisers, crop
protection and concentrate feedstuff and not the exact amounts of input as these are not
available in FADN. The exact threshold values are fixed based on expert knowledge
and, for the off-farm grazing systems, the permanent grassland systems and the arable
grazing livestock systems, additional statistical analyses. The off-farm grazing systems
are identified based on the variable grazing days outside utilised agricultural area in
FADN. Ideally this variable identifies systems grazing on common land and systems
practising transhumance. However, it should be noted that the quality of the variable
across EU-15 is not high, and that a lot of farms of this type therefore will not be
correctly represented in the results. It is also worth noting that, although relevant,
information on rough grassland is not used at this level because the data quality is poor
in some countries.
As can be seen in figure 1 these types of farming systems have been divided further.
Permanent grassland systems have in Western Europe and Scandinavia been divided
into systems where the dominant land use is rough grassland and other systems. As
mentioned above the quality of the data does not allow an EU-15 wide use of this
division. In Southern Europe cropping systems have been divided into fallow land
systems and dryland systems and permanent crop systems have been divided into
systems with or without cattle, sheep or goats.
Table 4 gives an overview of the discriminators and threshold values used. As it can be
seen the same HNV system specific discriminators and threshold values have been
applied across EU-15 at the highest level. At this level input cost, share and type of
grassland and grazing outside the farm are used to identify HNV farming systems.
Moving to the regional level the discriminators and threshold values differ between the
Southern Europe region (Greece, Italy, Spain, Portugal and parts of France
(Provence/Alpes/Côte d´Azur, Languedoc-Roussillion, Rhone-Alpes, Auvergne, Midi-
Pyrénées, Corse and Bourgogne)) and the Western Europe and Scandinavia region
(Finland, Sweden, Denmark, Germany, Austria, the Netherlands, Belgium,
Luxembourg, United Kingdom, Ireland and parts of France (Ile de France,
Champagne-Ardennes, Picardie, Haute-Normandie, Centre, Basse-Normandie, Nord-
Pas de Calais, Lorraine, Alsace, Franche-Comté, Pays de la Loire, Bretagne, Poitou-
Charentes, Aquitaine and Limousin)).
For the maximum approach the same types as on the EU-15 level are used for Western
Europe and Scandinavia except for the permanent grassland systems, where a division
has been made between systems where the dominant land use is rough grassland and
the other systems. In Southern Europe information on fallow, irrigation and stocking
density is added to narrow down the number of identified farming systems. For the
minimum approach the same discriminators are used but with tighter threshold values.
Also in the Western Europe and Scandinavia region a distinction is made for
permanent grassland systems between those that use rough grassland for grazing and
the others that do not. An overview of the different HNV farming types and the
definitions at the different levels is shown in the table on the following page.
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HNV farming project Final report
Table 4: Overview of typology
Common Level
Maximum level
Minimum level
EU-15
Western Europe Southern Europe Western Europe Southern Europe
and Scandinavia
and Scandinavia
1. HNV
EU-type 1 and 6
As common level Fallow systems:
Input cost < 40
Fallow systems:
Cropping
and input cost <
>12,5% of UAA
Euro ha
>20,5% of UAA
systems
80 Euro per ha
in fallow
in fallow and
input cost < 40
Euro ha
Dryland systems:
Dryland systems:
Not fallow
Not fallow
systems and <
systems and <
10% of UAA
10% of UAA
irrigated
irrigated and input
cost < 40 Euro ha
2. HNV
EU-type 3 and
No data
Systems with
No data
Systems with
Permanent crops Input cost < 80
GLS: < 10% of
GLS: Input cost
Euro per ha
UAA irrigated
on crop protection
and >= 5 LU GLS
< 10 Euro/ha and
no irrigation and
>= 5 LU GLS
Systems without
Systems without
GLS: < 10% of
GLS: Input cost
UAA irrigated
on crop protection
and < 5 LU GLS
< 10 Euro/ha and
no irrigation and
< 5 LU GLS
3. HNV off-farm EU-type 4, 7.1,8.1 As common level As common level >= 150 grazing
>= 150 grazing
grazing systems
and >= 120
days outside UAA days outside UAA
grazing days
outside UAA
4. HNV
EU-type 4, 7.1,8.1 Rough grassland
Stocking density
Rough grassland
Stocking density
Permanent
and input cost <
systems:
< 0,5 LU/ha
systems:
< 0,2 LU/ha
grassland
150 Euro per ha
Rough grassland
Rough grassland
systems
and >= 55% of
>=66% of UAA
>=66% of UAA
UAA in grass and and stocking
and stocking
<40% of grass in
density < 0,5
density < 0,3
temporary grass
Permanent
Permanent
and not common
grassland
grassland
type 3
systems:
systems:
Rough grassland
Rough grassland
<66% of UAA
<66% of UAA
and stocking
and stocking
density < 1,5
density < 1,0
5. HNV arable
EU-type 4, 7.1,8.1 As common level Input cost < 80
Input cost < 40
Input cost < 40
grazing livestock and input cost <
Euro/ha and ((>=
Euro/ha
Euro/ha and ((>=
systems
150 Euro per ha
12,5 % of UAA in
20 % of UAA in
and not common
fallow) or (<10%
fallow) or (0% of
type 3 or 4
of UAA
UAA irrigated))
irrigated))
6. HNV other
EU-type 5, 7.2,8.2 As common level (>= 12,5 % of
Input cost < 40
Input cost < 40
systems
and input cost <
UAA in fallow) or Euro/ha
Euro/ha and ((>=
80 Euro per ha
(<10% of UAA
20 % of UAA in
irrigated)
fallow) or (no
irrigation))
EU-type = Type of farming used in FADN: (1) Specialist field crops, (3) Specialist permanent Crops ,
(4) Specialist grazing livestock , (5) Specialist granivore, (6) Mixed cropping (7.1) Mixed livestock,
mainly grazing livestock,(7.2)Mixed livestock, mainly granivores, (8.1) Field crops-grazing livestock
combined and (8.2) Various crops and livestock combined. (2) Specialist horticulture has not been
included in the study
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HNV farming project Final report
Limitations in the farming system approach
Given that the aim was to produce a typology of EU-wide application, it is inevitable
that there will be errors of inclusion of non-HNV systems and non-inclusion of HNV
systems in HNV classes and errors of inclusion of HNV systems and non-inclusion of
non-HNV systems in non-HNV classes. These are most likely to occur at or around the
class discriminators. However, our opinion is that most HNV systems will be included
in the suggested HNV types and most non-HNV systems will be in the non-HNV
classes. It is imperative that field testing of our hypothesis is carried out, but
imperfections are likely to remain given the degree of generalisation involved.
Although the FADN database is very extensive, the use of it puts restrictions on the
outcome. The most important limitation is that the sample farms that occur in FADN
might not represent all HNV farming systems very well (or not at all). In total the
FADN represents 52% of the farms and 86% of the Utilised agricultural Area in EU-
15, when compared to the data in the Farm Structural Surveys (see table 5).
Table 5: The number of farms and area of utilised agricultural area (UAA) represented in FADN
and the share of the farms/UAA covered compared to FSS (Farm Structural Survey).
No. of farms
UAA represented Share of FSS-farms Share of FSS-UAA
represented in
in FADN
represented in
represented in
FADN
FADN
FADN
%
%
Belgium
42464
1442890
63
104
Denmark
49934
2595416
79
97
Germany
282429
15282780
53
89
Greece
484566
2993321
59
86
Spain
539907
16551642
45
65
France
387210
25301779
57
89
Ireland
128737
4904409
87
113
Italy
998375
11603783
43
78
Luxembourg
1763
107154
59
85
Netherlands
82512
2102937
76
105
Austria
86220
2139713
41
63
Portugal
301846
3664020
72
96
Finland
52137
1832882
57
84
Sweden
38021
3331265
42
107
United Kingdom
128110
16945535
55
105
EU 15
3604231
110799526
52
86
Source: FADN-CCE-DG Agriculture/A-3; Farm Structural Survey; adaptation LEI.
Though this is not the only reason for the lack of representation of FADN, the
exclusion of economically small farms explains most of the missing farms and
agricultural areas. Comparing the different Member States an average of 36% of the
farms and 11% of the Utilised Agricultural Area are not included in the FADN data
due to the elimination of the small farms. This varies from Ireland, where only 12% of
the farms and 4% of the Utilised Agricultural Area are not included, to Austria, where
58% of the farms and 38% of the utilised agricultural area are not represented. It is
important to stress that economically small and 'non-professional' farms may in fact be
physically large and apparently full-time, particularly in marginal areas where the land
has low productivity but alternative employment is scarce.
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HNV farming project Final report
It is possible not only that small farms represent a different % of HNV farmland to
commercial farms within a given region (all HNV farms might be small farms, to give
an extreme example), but different thresholds might be necessary to differentiate small
farm systems (for example, a small farm might be highly intensive and non-HNV
despite having very low levels of outside inputs, whereas a larger farm might substitute
inputs for labour). These issues require further investigation, but this lies outside the
scope of this current study.
In addition to these problems a comparison with the Farm Structural Survey data also
reveals that mixed livestock farms and beef cattle farms are not very well represented
in FADN, though considerable differences occur between the different Member States.
This problem is of course worse in the cases where specific types of farming systems
with a high probability of being HNV farming systems are not included in FADN. So
the interpretation of the results of this project must always bear in mind this inherent
weakness in the FADN data.
Another important limitation to consider is that the variables in FADN have a strong
economic bias. It is obvious that some of the selected criteria are not the most useful,
e.g. input costs are only a proxy indicator for the pressure from the farming practices,
but no information is available in FADN on the amount (and in some cases on relevant
types) of inputs used.
Furthermore, all data is gathered and presented at the farm level. It is not possible to
discriminate between the intensity in the use of different parts of the farms. Especially
in cases where farms run more than one enterprise, for example dairy cattle and sheep,
it can be difficult to identify potential HNV farming practices. In relation to the results
presented in the following section it is important to stress that the data on agricultural
area managed by potential HNV farming systems includes the entire farmed area of
these farms rather than the actual HNV farmland.
Lastly, a major weakness of FADN is that its major unit of data collection is the
Utilisable Agricultural Area (UAA),
not the area actually occupied by the agricultural
business. Seasonal lets (common in some countries, such as Ireland) or
wintering/summering arrangements, as well as the use of common land and the grazing
of fallows, are excluded from consideration.
Any discriminants which use per hectare measures will produce incorrect and
misleading results for farms with these tenurial arrangements. Worse, these are
more
likely to be HNV in many parts of Europe, since these traditions reflect extreme
seasonal variation in forage resources often associated with semi-natural vegetation.
We have attempted to get round this problem by separating out a group of farms with
high use of land outwith the UAA. However, we recognise that for these the FADN
approach provides no further analytical tools and that this is not a satisfactory outcome.
Outcome of the farming system approach
The output of the farming system approach is maps showing the regional importance of
HNV farming expressed as the share of the UAA managed by the identified HNV
farming systems. Tables have been produced to present the regional distribution of
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HNV farming project Final report
HNV farming and different types of HNV farming systems. Finally, the typology has
been used to present the general characteristics of the different HNV farming systems
and, more specifically, the environmental performance of the systems using selected
agri-environmental indicators.
FADN is useful for identifying HNV farms but not the farmed HNV areas since the
regional level at which FADN data are presented is very coarse. The strength of the
farming system approach is that it provides insight in the farming practices linked to
HNV farmland. This, combined with the characteristics of the FADN data, means that
the farming system approach can be used to monitor short term changes in HNV
farming systems and thus in the pressure on HNV farmland. The farming system
approach will also provide valuable insight into the policy options for keeping the
HNV farming systems in place and for supporting HNV farmland management. The
farming system approach also provides (at best) an alternative 'truth' to that given by
the land cover approach and comparisons between predicted % cover at the regional
scale should prove productive, providing a mechanism for the mutual improvement of
the two methods.
3.3 Species approach
Background and objective of species approach
From what is know about HNV farmland, it is clear that it supports a wider variety of
species than more intensively managed agricultural habitats such as arable or grass
monocultures. The main reason for this is that HNV farmland has a number of essential
characteristics:
It can contain a wide range of types of ecological niches (e.g. different semi-natural
habitats, different land use types, different structures of vegetation) and hence
provides the conditions which allow a large range of species from different biota to
exist there.
The farming practices associated with HNV farmland create medium levels of
disturbance (e.g. through grazing and other management practices such as
ploughing) which maintain more open types of vegetation without letting these
progress fully to its climax stage.
The timing of these farming practices is usually constrained by climatic and
topographic factors on these farms, which means that the farming practices are
more extensive and also more synchronised with natural process and natural
fluctuations in these from year to year.
HNV farmland habitats usually occur at a relatively large enough scale to allow
enough individuals to survive in an areas to maintain viable populations of each
species. The diversity of habitat types and structures on the farmland also mean
that at any one time of the year there is sufficient choice of suitable conditions for
different species.
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HNV farming project Final report
The Land Cover approach based on Corine (section 3.1 above) largely involves a
specific focus on semi-natural vegetation and/or complexes of agricultural habitats
identifiable via the Corine classification. As such, the Corine approach would be
expected to be potentially useful in identifying HNV Type 1 and Type 2 Farmland and
the resulting outputs from Corine would also be expected to include some Type 3
Farmland where the species concerned have a particular association with semi-natural
habitats. However, by its very nature not all Type 3 Farmland is associated with semi-
natural vegetation and hence it would be expected that areas of Type 3 farmland would
not be readily identifiable with the land cover approach.
Making a selection of the species and habitat types that are typical of, and most
indicative for HNV farming systems requires expert knowledge on typical farmland
biodiversity in different European regions. The relationships between HNV farmland
and biodiversity are very broad-ranging and can be considered in terms of many
different groups of biota such as vegetation, birds, mammals, insects and reptiles. The
selection is further complicated because one particular species may be potentially
indicative of HNV farmland in one region but the same species may have no link to
farmland in other European regions. The range of expert knowledge needed to make an
appropriate selection of indicative species for the whole of Europe is therefore
considerable.
The objectives of the species approach were to:
Investigate whether it was possible to identify areas of HNV Farmland by
concentrating on the distribution of species known to occur in association with it.
Compare the results with the land cover approach and assess whether or not the
species approach provided similar results with regard to the potential distribution of
Type 1 and Type 2 HNV Farmland.
Assess whether the species approach was of additional value in helping to identify
potential Type 3 HNV Farmland not achievable through the land cover approach.
Data sources
Ideally the types of groups and species to use in such an approach would be vegetation
communities or species strongly associated with extensive farmland or particular fauna
(such as butterflies or other invertebrates) with intimate links with the vegetation
structure on HNV farmland, since the distribution of those species or groups of species
would then be expected to reflect closely the location of their required habitats on the
ground. For example, knowledge about the ecological requirements of butterflies has
been well documented and some information on butterflies distribution has also
become available recently (Swaay, C. van, and Warren, M. S. (1999), Red Data Book
of European butterflies (Rhopalocera) (Council of Europe Publishing, Strasbourg,
Nature and Environment Series No. 99) and Swaay, C van and Warren, Prime
Butterfly areas in Europe (2003)). However, distribution information is only available
for a selection of countries and regions and at a variety of different scales (e.g. in the
Netherlands there are population data available at 1*1 km square level; for Belgium the
same applies for 5*5 km square; for the UK and Ireland at 10*10 km square; and for
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HNV farming project Final report
the whole of Europe at a 50*50 km square level. However, the quality of the data and
consistency of the data collection exercise (especially at the latter scale) is unclear at
the moment and time and the availability of resources meant that this was not possible
within the scope of this project.
The potential for using distribution data based on indicative plant species was also
considered during the early stages of the project. However, there is no currently
available consistent European-wide database on indicative plant species and
communities for extensively managed farm land and semi-natural vegetation. For some
countries, information is available at a national level of distribution patterns of
individual plant species. Another difficulty is that in the present sources the vegetation
species distribution information is often provided without its ecological context,
making it very time-consuming to select the “characteristic species” and link them to
the right HNV farming habitats. At present a European-wide spatially explicit
vegetation distribution database is being built in the SYMBIOSIS project. For each
plant species the aim is to present country-based distribution patterns. SYMBIOSIS
aims to link national flora data to a hierarchical overview of European vegetation
types. In this way vegetation information will, it is intended, be presented for each
vegetation unit including descriptions, species composition, structure and dynamics,
ecology, geographic distribution. The results of this project have however not yet been
finalised and the data from SYMBIOSIS was therefore unavailable for use within this
HNV project.
At present the most up-to-date species distribution information at European level is for
birds via such sources as
The EBCC Atlas of European Breeding Birds (Hagemeijer &
Blair 1997) and the
Atlas of the Birds of the Western Palearctic (Harrison 1982)
Additional data sources covering parts of Europe are ornithological reference works
such as
Birds of the Western Palearctic (Cramp
et al. 1997-1994),
Handbuch der
Vögel Mitteleuropas (Glutz von Blotzheim
et al. 1966-1997),
Handbook of the Birds of
the World (del Hoyo
et al. 1992-2003) and
Europese Vogels. Alle vogels van Europa,
Noord-Afrika en het Midden-Oosten (Mullarny
et al. 1999). The breadth of information
available on birds and the potential greater level of consistency of data collection
across Europe mean that birds were taken as the group of choice used for testing the
species approach within this project.
Methodology
Two approaches were taken with the available bird distribution data:
The first one is based on a selection of breeding bird species judged to be indicative
of different types of farmland habitat within different regions of Europe.
The second one is based on a selection of bird species of conservation concern in
Europe (SPECs) which were considered to be potentially associated with farmland.
The approaches are described in detailed below.
For both approaches the selection of bird species could then be used to map presence-
absence data (based on EBCC's Bird Atlas of Europe) across Europe on a 50*50 km
grid.
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HNV farming project Final report
Approach 1: Selecting breeding bird species judged to be associated with HNV
farmland in different regions of Europe
Experts at the European Birds Census Council (EBCC) were asked to select bird
species representative of the following 10 types of potential HNV farmland (based on a
slight expansion of the habitat classes used by Tucker & Heath 1994) in different
regions of Europe:
Arable and improved grasslands
Mediterranean Shrub
Montane grassland
Moorland
Pastoral woodland
Rice cultivation
Sand dunes and saltmarshes
Dry grassland (steppic)
Wet grasslands
Agricultural complexes
Annex C provides an exact description of the selection procedure. In summary this
involved: Making a list of breeding birds recorded within each of nine environmental
zones of Europe, using literature surveys to assess the habitat requirements of the bird
species within each zone and subsequently for each zone obtaining 10 separate lists of
bird species considered to be linked to each of the 10 HNV farmland habitats given
above. This assessment of link with each HNV habitat was based both on recorded
occurrence in each habitat and on an assessment of whether each habitat was of
primary, secondary or tertiary importance to the respective bird species in that
environmental zone. An attempt was made to ensure that the list of bird species
associated with each HNV habitat within each environmental zone only contained bird
species considered to be good discriminators of that habitat within that zone. Annex D
shows the final list of bird species selected by environmental zone and each of the
above 10 HNV farmland habitats
Approach 2: Limiting the focus to bird Species of European Conservation concern
Tucker & Heath (1994) conducted an assessment of the conservation status of all
Europe's birds and provided a list of Species of European Conservation Concern
(SPECs). Four categories of Species of European Conservation Concern were
identified according to their global and European status, and the proportion of their
total of their world population occurring in Europe (Table 6). Species are considered
to have an Unfavourable Conservation Status if their European Threat Status is
Localised, Declining, Rare, Vulnerable, Endangered or Insufficiently known according
to criteria summarised in Table 7 (see Tucker & Heath, 1994 for full details). The
SPEC designation has become accepted as highlighting bird species of especially high
conservation concern.
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HNV farming project Final report
A total of 102 species were chosen by the project partners for inclusion in the analyses
(Annex F). This list included all Category 1-3 species which were considered to be
potentially associated with farmland throughout Europe
Table 6: Categories of Species of European Conservation Concern (SPEC), from Tucker (1997)
Category 1
Species of global conservation concern because they are classed as Globally
Threatened, Conservation Dependent or Data Deficient in Collar
et al. (1994).
Category 2
Species whose global populations are concentrated in Europe (i.e. more than
50% of their global population or range in Europe) and which have an
Unfavourable Conservation Status in Europe.
Category 3
Species whose global populations are not concentrated in Europe, but which
have an Unfavourable Conservation Status in Europe.
Category 4
Species whose global populations are concentrated in Europe (i.e. species with
more than 50% of their global population or range in Europe) but which have
a Favourable Conservation Status in Europe.
Table 7: Summary of European Threat Status categories. Adapted from Tucker (1997)
European population size
Size of Decline
< 250 pairs
< 2,500 pairs
< 10,000 pairs
> 10,000 pairs***
Large*
ENDANGERED
ENDANGERED
ENDANGERED
VULNERABLE
Moderate**
ENDANGERED
ENDANGERED
VULNERABLE
DECLINING
None
ENDANGERED
VULNERABLE
RARE
SECURE
* Declined in size or range by at least 20% in at least 66% of the population, or by at least 50% in at
least 25% of the population between 1970 and 1990
** Declined in size or range by at least 20% in 33%-65% of the population, or by at least 50% in 12-
24% of the population between 1970 and 1990
*** In addition, species that have more than 10,000 pairs in Europe are categorised as Localised if more
than 90% of the population occurs in 10 sites or fewer
Outcome of the species approach focussing on breeding bird species indicative of
different HNV farmland
Map 1 shows the number of the 10 agricultural habitats where one or more of the
indicative species are present. In other words, the map shows how many of the 10
HNV farmland habitat types that are predicted to occur within each square (see also
Annex E). There are two important points to be taken into account in the interpretation
of the map:
The predicted occurrence of any HNV habitat type within any one square is based
simply on the occurrence of one or more of those bird species taken to be
associated with that habitat in that part of Europe. As some of the species allocated
to each habitat type are quite broad-ranging in habitat requirements, then this has
the potential to lead to an over-representation of HNV farmland in some areas of
the maps. For example, it is highly likely that many of the very dark green dots on
the map in Spain do not actually contain montane grassland but instead do contain
bird species (such as red-billed chough and twite) which were taken as indicative of
that habitats but which in these instances are also breeding in other habitats.
The 10 chosen habitat types are not all of equal weighting in terms of likely size of
each habitat when occurring on the ground. Hence the apparent under-
representation of HNV habitat types in northern Europe is likely to be reflecting the
fact that type of HNV farmland which occurs in northern Europe generally occurs
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HNV farming project Final report
in larger blocks and so wherever it occurs there is less chance of other habitats also
occurring since there is less 'room' for them to 'fit' in the square. The potential
value of some areas on the map (especially northern and mountain areas) are
therefore likely to be misrepresented by any consideration of diversity of these 10
habitats occurring.
Map 1: The number of the 10 agricultural habitats where one or more of the indicative species are
present.
Given these qualifications, it may be best to try and view the map in terms of the red
and orange categories being taken together as predicting a low potential diversity of
HNV farmland habitats, the yellow and grey cells taken together as predicting a
medium potential diversity of HNV farmland habitats and the two green categories as
predicting a high potential diversity of HNV farmland. However, a difficulty arises
because there is no separate category for predicted zero occurrence of these 10
farmland habitats and so other than where data is lacking, the impression is given that
one or other of these 10 agricultural habitats occur all over Europe. In addition, the
inclusion of some very broad habitat categories which can also be extremely variable
in terms of the Nature Value associated with them (such as
Arable and Improved
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HNV farming project Final report
Grassland and
Agricultural Complexes) has the effect of swamping the overall
appearance of the map.
Leaving aside these qualifications for a moment, the map suggests that the diversity in
HNV farmland habitats generally increases towards the south of Europe. This does
suggest some similarity with the results from the land cover approach, with higher
diversity of HNV farmland occurring in central parts of Spain, southeast and south-
central parts of France, Central and northern parts of Greece, large parts of Bulgaria
and Romania, northwestern Scotland and mountain ranges throughout Europe.
However, this map only gives a limited picture as it does not take into account the type
of habitat present nor does it provide any indication of the quality of the farmland in
relation to the birds requirements. It is therefore very difficult to provide any real
interpretation of this combined map.
To try and address this problem, a second map was produced (see Map 2) to take into
account that the 10 agricultural habitats do not all occur across Europe and that each
can differ in terms of the extent of the number of species supported in different parts of
Europe. The process used to produce this map was as follows:
1. For each of the seven environmental zones, an assessment was made of which of
the10 agricultural habitats occurred within each zone (see Annex D).
2. For each environmental zone, each of the agricultural habitats which occurred
within that zone were first considered separately. Hence for each agricultural
habitat, the presence of indicative species within the 50*50 km grid occurring
within that zone was recorded as being either high, medium or low (based on the
overall standard deviation of the data)..
3. An overall total score (with a value of 3 for high, 2 for medium and 1 for low) was
assigned to each grid-cell within each environmental zone by adding together the
values for each agricultural habitat associated with that cell.
4. The potential maximum score which any one grid cell could have achieved was
calculated by assuming a maximum score of 3 for every agricultural habitat
indicative of that zone which occurred within that grid cell, i.e. this potential
maxium score was equal to (3 x the number of agricultural habitats present)
5. A map was then produced showing the proportion of the potential maximum score
which was actually achieved by each grid cell.
Map 2 shows the results obtained and suggests that northern parts of Europe generally
come out better than most southern and eastern parts. In order to provide an
explanation for why this shoudl be so, Map 2 has to be viewed in association with the
individual farmland habitat maps contained in Annex F.
Taking this approach, it then becomes evident, for example, that the high scores
achieved for the Baltic States can be especially related to a high occurrence of
farmland birds associated with agricultural habitat categories (e.g. Arable land,
Agricultural complexes, Dry grassland and Dunes and saltmarshes) more indicative of
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HNV farming project Final report
Type 2 HNV farmland. Similarly, the high score achieved in many parts of Hungary
appears to be related to particularly high scores for birds in Agricultural complexes
together with relatively high scores for most other agricultural habitats. Conversely,
parts of Western Europe and Scandinavia score well in Map 2 because of relatively
high scores in agricultural habitats most strongly related to Type 3 HNV farmland
(such as arable land and wet grasslands) in this environmental zone.
Map 2: Map showing the presence of indicative species relative to a potential maximum score. The
potential maximum score takes into account that not all agricultural habitats are present in all
environmental zones. See text for further explanation.
However, it is also evident that the map suggests scores for some parts of Europe
which are lower than would be expected from knowledge of what is happening on the
ground. For example, the central and western parts of France appear to score high on
the map because of high scores for Agricultural complexes, Dry grassland and Pastoral
woodland in this area. However, it is strange that these areas of France score higher for
the latter category than areas of Spain and Portugal where montado and dehesa pastoal
woodlands are key components of the agricultural landscapes. Clearly, the selection of
bird species taken as representative of this agricultural habitat has to be reassessed and
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HNV farming project Final report
improved.Similarly, the low scores for parts of Eastern Europe may be related in some
part to the quality of the data avaialble from these areas, but further work would be
required to assess this.
In conclusion, the potential value of any species occurrence approach will depend very
strongly on the type of species chosen and the scale at which information on those
species is available. For this project it was only possible to obtain distribution data for
breeding birds at a 50*50 km level for Europe. The selection of the indicative species
was done by EBCC, but had to be done within a limited time span. Consequently, the
data in the draft list of key bird species has limitations. In particular, the selection for
certain HNV farmland habitat categories are very broad and include bird species which
are not necessarily very good discriminators of any one habitat. In addition, the HNV
farmland habitat categories which were selected are also rather broad. For example, the
category dry grassland does not distinguish between the different types of steppe (e.g.
grass or arable) and the different bird communities associated with them. The selection
of both bird species and habitat categories should therefore be seen very much as a first
selection, which can be further improved by involving more regional expert knowledge
in a later stage and by using better and more detailed data.
Outcome of the species approach focussing on bird SPECSs
The distribution of the 102 SPECS in Annex F was plotted on 50*50 km grid level for
the whole of Europe using breeding bird data available at that scale. The resulting map
(Map 3) was presented as the total number of each of these species occurring in each
50*50 km square. It was anticipated that SPEC hotspots would be identified which
would allow a comparison with the maps produced via the land cover approach (with
regard to Type 1 and Type 2 HNV Farmland) and in particular serve to identify
potential Type 3 HNV Farmland which was less associated with semi-natural
vegetation.
Given that the bird species selected were all considered to have some association with
agricultural land across Europe, then at the very basic level the resulting map can be
regarded as potentially providing a broad indication of where agricultural land occurs
in Europe. Even though agriculture is the dominant land use across Europe, it is,
however, surprising that the map indicates that one or more of these species (and hence
by implication some form of agricultural land) have been recorded in every single 50 x
50 km square for which data is available across Europe. Even though some of the
species selected can be quite widespread in the regions where they occur, it was not
expected that so many would be so widespread over Europe as to mean that a hit on at
least one species would be recorded in every square. This result is additionally
surprising given (a) that the majority of the selected species have quite specific
requirements for breeding habitat and so would have been expected to be more
localised in their distribution and (b) that despite the large grid under consideration, it
would have been anticipated that there would have been much more cells which were
unfavourable to all of these species (e.g. through containing complete forest cover).
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HNV farming project Final report
Map 3: The number present of the 102 species of European conservation concern associated with
farmland
Leaving these initial qualifications aside, the map could be read as implying that there
are areas of Europe which are potentially 'hotter' or 'colder' for HNV farmland in terms
of the occurrence of high or low numbers of the selected species. However, there is no
consistent pattern across Europe, especially when the known distribution of HNV
farmland in some areas is taken into account. For example, overall the map gives the
impression that the potentially 'hotter' areas are located in the south and east of Europe
while the potentially 'colder' areas are located in the north. The latter may in part be a
reflection of the fact that the overall species list was dominated by species more
indicative of southern or lowland agricultural habitats.
In either event, it would appear that the apparent 'cold' nature of the north (especially
Ireland, Scotland and Scandinavia) is simply a side-effect of the species selection and
that consequently it is not valid to try and draw any conclusions one way or the other
about these areas. After removing the north and north-west from further consideration,
it may then be tempting to regard any increasing number of records of selected bird
species per grid cell over the remainder of Europe as reflecting the increased
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HNV farming project Final report
possibility of the occurrence of HNV farmland within the cells with higher number of
species. However, again there is no consistent pattern in the map and many
inconsistencies with known Type 1, 2 and 3 HNV Farmland distributions (e.g. the fact
that most of Italy and much of France are shown as containing high numbers of the
these species would suggest that no direct link with HNV farmland can be drawn).
At best, the cells with the highest (26 and above) counts on the map can potentially be
regarded as indicating where HNV farmland may occur either in the form of a large
extent of individual HNV farmland habitats or where the 50*50 km cells contain quite
a mosaic of such habitats. It is only with this approach to interpreting the map that
anything potentially 'sensible' appears to emerge from the spatial distribution on the
map. However, this would be a rather sweeping conclusion to draw from the map and
should not be drawn before cross-checking this with the distribution of sub-sets of
species specifically indicative of specific habitats.
Similarly, it might be tempting to suggest that some indication of the location of Type
3 farmland can be obtained from the location of the cells containing 26+ SPECS which
fall outwith the areas identified by the land cover approach. However, as indicated
above, the map shows many inconsistencies with known distribution of Type 3
farmland and hence it would be wrong to assume that that those cells where nothing is
known of their content are reflecting Type 3 occurrence on the ground.
All that can therefore be said about the approach with any certainty is that the map
either reflects a simple reality on the ground (in that agriculture and associated bird
species is all pervasive throughout Europe) or more likely suggests that the use of only
one list of SPECS covering the whole of Europe is far too broad an approach to take.
Time did not allow for any iterative process in considering the pros and cons of
including or excluding different bird species within the list. If this approach was to be
investigated further it may be more appropriate to utilise sub-sets of the SPEC list with
regard to species specifically potentially more closely associated with Type 3 HNV
farmland within different areas of Europe However, it may also be that 50*50 km is in
any event far too broad scale at which to try and locate concentrations of Type 3
farmland.
Limitations of the species approach
The EBCC European breeding bird atlas only provides information on
presence/absence rather than abundance or even breeding success. Both the latter
factors will be important determinants of what the mapped information is reflecting on
the ground. Mapping attempts based on groups of species should therefore always be
interpreted with care.
In addition, mapping of biodiversity value can only be done where there is relatively
good population distribution data available for different species groups. This of course
does not diminish the value of the exercise done in this study. It is true that the
biological reality is that a wide range of biotic and abiotic factors affect species
distributions. As such it is sometimes possible to find good correlations between
species and types of farmland and it would be potentially possible to then use these
species as "indicators" but for birds it should be mentioned that there are many other
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HNV farming project Final report
over-riding influencing factors (e.g. degree of hunting, proximity of the sea, territorial
behaviour).
If this approach is to be taken further in the future with birds then it would be
better to consider the spatial occurrence of different bird and other species
assemblages and not only include all farmland-associated (bird) species in the list
of species considered but also obtain information on these species at the smallest
spatial scale possible (e.g. in Britain bird data is available (at a high cost) at 10 km
square level and in the Netherlands at 1 and 5 km square). Similarly, it may be
feasible to obtain an indication of potential HNV areas by combining the
distributions of different groups of biota, e.g. French regional atlas data on the
distribution of birds and butterflies. The value of all these approaches do,
however, depend on there being consistent survey/reporting effort across the
countries under consideration. For example, in the UK, The Netherlands, Belgium
there are many recording schemes, which contain data on the species distribution
of different biological groups at a 10-km and 5-km square level respectively.
However, it should always be remembered that in general recording/reporting
effort will never be equal across all areas of any one country let alone Europe as a
whole.
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HNV farming project Final report
4. Results
4.1 Southern Europe
Broad characteristics of HNV farming in the southern countries
HNV 1: Semi-natural grazing land covers extensive areas of the southern countries. A
considerable proportion of this is grassland, ranging from dry grassland on lowland
plains to hay meadows and alpine pasture in mountain regions. In addition, a particular
characteristic of the Mediterranean regions is the presence of various forms of
scrubland and woodland that are used for extensive grazing and browsing by sheep,
goats, cattle and pigs and that cover large areas in some regions, especially in the
uplands. Where these different forms of semi-natural vegetation exist in a mosaic, the
land cover is of particular natural value.
Although stock may be sedentary and fenced on semi-natural vegetation, they are more
commonly shepherded, especially in the case of sheep, goats and pigs. Cattle are more
often free-ranging, whether on high mountain pastures or dry grasslands in the
lowlands. Stocking densities on HNV1 land tend to be extremely low (often well
below 0.2 LU/ha). Some types of vegetation are grazed or browsed only occasionally
(by shepherded flocks) and/or seasonally (under various forms of local or long-distance
transhumance). Extensive grazings are often publicly owned land or some form of
common land, with many different systems of allocation, depending on the country and
region.
HNV 2: these systems are widespread and diverse in southern countries. Some of the
main types are:
- Low-intensity arable systems, that often include a proportion of fallow land on long
rotations. These systems may consist of small parcels with semi-natural or tree-
lined field margins (e.g. Tras-os-Montes in Portugal), or large-scale, pseudo-
steppic landscapes (e.g. on Spanish table lands).
- Mosaics of arable and permanent crops: typically olives and vines, with almonds,
figs and other tree crops more localised.
- Grassland landscapes that exist in a mosaic with scrub, forest and sometimes with
arable and permanent crops (e.g. chestnuts, fruit trees). These are typically in more
northern and/or upland regions.
Distinguishing HNV 2 systems from non-HNV is extremely complicated. Many mixed
farming systems are of landscape and cultural value, but some are intensive in their use
of inputs and land. Information on the natural values of mixed systems is sparse. Often
they are valued for a generally high level of biodiversity, rather than for the specific
species and habitats of conservation concern that tend to be associated with HNV 1 and
HNV 3 systems.
HNV 3: Probably the most characteristic of these systems in the Mediterranean is
extensive arable cultivation that supports valued bird communities. A typical example
is provided by the Great Bustard populations in Spain and Portugal. Although they
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HNV farming project Final report
generally are associated with low-intensity fallow systems in pseudo-steppic
landscapes (HNV 2), some populations co-exist with more intensified forms of arable
cropping, especially where alfalfa is present and used as a feeding area. Also in
category HNV 3 may be rice fields in all the Mediterranean countries, that can support
valuable bird populations even when quite intensive in terms of input use.
Results of the land cover approach
The areas shown in the
Minimum approach (map 4) are made up almost exclusively of
semi-natural vegetation (pastures, natural grasslands, moors, scrub, agro-forestry,
marshes, etc.). These areas tend to coincide with upland and mountain regions in each
of the countries, plus some other regions, such as the
dehesa/montado systems in the
west of the Iberian Peninsula. The map thus provides a useful illustration of the
distribution of semi-natural vegetation types that generally are HNV and, in some
categories (e.g. pastures, grasslands, agro-forestry), are under livestock farming by
definition.
However, some other categories (e.g. moors, scrub, marshes) may be used for grazing,
but may equally well have no farming use at present. The only grazing may be from
wild herbivores. CORINE does not distinguish these vegetation types according to use.
Thus, whereas the Minimum approach illustrates quite well the minimum HNV area, a
considerable proportion of this area may not be farmland.
Perhaps the clearest example of this problem is the forest categories. Native
broadleaved forest in particular is often used for grazing in some Mediterranean
regions (mainly by goats, cattle and pigs), but there are also extensive areas that are not
used in this way, although historically they probably were. Because of this problem,
and because CORINE does not distinguish native from exotic broadleaves reason,
forests were excluded from the land cover exercise. However, as a result, certain HNV
grazed forests are excluded from the Minimum map.
Another significant caveat is that the Minimum map includes all types of permanent
grassland (under the Pastures category), regardless of the farming system. In some
areas, this grassland may be under quite intensive management, with heavy fertilisation
and grazing pressure. Lower precipitation in the Mediterranean regions means that
these types of pasture are less widespread than in Lusitanian and Atlantic regions
(intensification in the Mediterranean generally requires irrigation, which presumably
would take them into the Permanent Irrigation category). Even so, they may be present
in certain areas, such as Catalunya (Mediterranean North). In wetter regions, such as
northern Spain, there are more intensified pastures, especially in the lowlands.
The only categories included in the Minimum approach that are
not semi-natural
vegetation are in the Mediterranean regions: olive groves in Portugal and Italy, and
Complex Cultivation Patterns and Land Principally Occupied by Agriculture in the
Mountain regions of most countries. Natural and socio-economic limitations in the
Mediterranean Mountain region have tended to prevent the intensification of small-
scale mixed systems. The category Land Principally Occupied by Agriculture is
difficult to interpret, but seems more likely to be HNV in mountain regions than in
lowlands.
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HNV farming project Final report
Map 4: Potential type 1 and type 2 HNV farmland according to the minimum CORINE selection
for Southern Europe
Map 5: Potential type 1 and type 2 HNV farmland according to the minimum CORINE selection
for Southern Europe
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HNV farming project Final report
Finally, it should be emphasised that the Minimum map excludes some very significant
areas of HNV farmland. Notable examples are low-intensity arable systems harbouring
highly valued bird communities and permanent crops, such as olives in parts of Greece
and Spain, that are of high biodiversity. The fact that arable and permanent crop
systems vary enormously in intensity and in natural values means that they cannot be
included in the Minimum approach, except in certain cases as mentioned above.
The
Maximum map for the Mediterranean regions include almost all farmland that it is
not under permanent irrigation (Map 5). As a result, very large areas of land are
included, especially outside the main river valleys and coastal areas. Forests are also
excluded for the reasons explained above.
For some regions, for example in the interior of Portugal or the LFA in Greece, the
picture provided by the Maximum map may be considered acceptable as an
approximate, if slightly exaggerated, distribution of HNV farmland. Here, the
widespread presence of traditional, low-intensity farming (livestock systems, arable,
olives, etc.) means that the rural landscape is generally HNV, except where irrigation
and intensive forest plantations dominate.
However, for some other Mediterranean regions the Maximum picture includes an
excessive amount of farmland that is not HNV, even in the absence of irrigation.
Examples include the intensively managed olive groves that dominate parts of southern
Spain, modern fruit plantations, dairy and beef fattening farms in Greek non-LFAs, and
the more intensive arable systems that are found on better soils in all countries.
Table 10: Share of the total area of CORINE LCCs potentially associated with agriculture
according to minimum and maximum selections
Proportion of agricultural LCCs total which is
Total area (ha) of those predicted to be under LCCs associated with HNV
LCCs associated with
farmland:
agriculture
Maximum
Minimum
EU 15
143655448
73.0
26.6
Southern Europe
88854223
91.5
37.0
Southern France
13966940
86.2
25.4
Greece
9120318
90.7
53.0
Italy
20212728
94.8
29.5
Portugal
5970951
94.3
37.9
Spain
39583286
91.5
41
Source: Corine Land Cover
Table 11: Share of the total area of CORINE LCCs potentially associated with agriculture
according to minimum and maximum selections in 3 altitude classes
Maximum
Minimum
0-300
300-600
600+
0-300
300-600
600+
EU 15
47.9
24.2
27.8
34.9
26.0
39.1
Southern Europe
33.2
25.5
41.3
18.4
25.8
55.8
Southern France
37.7
27.3
35.0
11.7
15.9
72.4
Greece
38.5
25.9
35.6
21.4
29.4
49.1
Italy
53.3
23.8
22.9
26.9
27.0
46.1
Portugal
57.9
23.2
18.8
50.5
25.7
23.8
Spain
33.2
25.5
41.3
11.3
26.5
62.1
Source: Corine Land Cover
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HNV farming project Final report
Conclusions on the land cover approach
The Minimum map captures quite well the distribution of HNV 1 systems, but with the
problem that unfarmed HNV land is also included, as well as some intensified systems
(e.g. Pastures, Olive groves) in certain areas. The very significant HNV 2 systems are
mostly excluded, except where Complex Cultivation Patterns have been included
(principally in the quite restricted Mediterranean Mountain region). HNV 3 systems
are excluded almost entirely.
The Maximum map includes practically all non-irrigated farmland. While this is a
reasonable reflection of HNV land in certain regions with predominantly traditional
farming, for most regions the Maximum map includes large areas of non-HNV
cropping systems.
Both maps are hampered by certain problems with CORINE. For example, quite large
parts of Greece (such as the Aegean islands) are not covered by the current database.
Results of the farming systems approach
Given the limitations of the FADN-based approach, the maps should only be regarded
as giving a general impression of which regions are the most significant in terms of
HNV farmland (see map 6). In some cases, the picture provided by the maps appears to
coincide with expert judgement and with the CORINE maps. However, there are also
cases of regions where the results certainly would be questioned by those with expert
knowledge.
Some regions show up consistently under the three typologies as having >25% of UAA
under HNV systems, including: Alentejo in Portugal, the Spanish regions of
Extremadura, Andalucía, Castilla la Mancha, Madrid and Aragón, and Lazio, Molise
and Basilicata in Italy. Regions such as Sicily, Sardinia, Castilla y León and the
northern half of Portugal are also prominent, although with lower percentages under
the Minimum typology.
Most other regions, notably in Greece, north-east and south-east Italy, northern and
eastern Spain and France, are shown as having a considerably lower proportion of
UAA under HNV systems. In some cases, such as the Po Valley in Italy or La Rioja in
Spain, this result is as might be expected, considering the dominant types of
agricultural land use. However, other cases are more surprising. Thus, even under the
Maximum typology, most of the mainland regions in Greece are shown as having only
5-15% UAA under HNV systems. Galicia and Asturias in Spain appear to have only 0-
5%, despite having quite large areas of land under extensive, mountain livestock
systems. Under the Minimum typology, numerous regions are shown as having 0-5%
UAA under HNV systems, including Cantabria and Navarra in Spain, and most of
Mediterranean France. Clearly in some of these cases, the Minimum typology is
excluding considerable areas of HNV farming, especially grazing systems.
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HNV farming project Final report
Map 6: Share of Utilised Agricultural Area managed by HNV farming systems
Source: FADN-CCE-DG Agriculture/A-3; adaptation LEI.
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HNV farming project Final report
Table 12: Share of Utilised Agricultural Area managed by HNV farming systems
UAA managed by HNV farms
%
Total UAA Common typology
Maximum
Minimum
ha
EU15
118000235
34,6
27,9
13,5
Southern
46792384
51,3
38,7
17,9
Southern France
3110182
34,0
9,0
1,4
Greece
8430851
16,7
13,8
8,8
Italy
12477379
41,1
32,6
12,1
Portugal
3762069
75,4
56,7
35,3
Spain
19011904
66,4
56,3
27,0
Source: FADN-CCE-DG Agriculture/A-3; adaptation LEI.
UAA = Utilised agricultural area
Table 13: Share of the farms identified as HNV farming systems
Farms identified as HNV farming systems
%
Total farms Common typology
Maximum
Minimum
No.
EU 15
3815172
25,1
18,9
8,1
Mediterranean
2653794
27,2
19,7
8,4
Southern France
147009
25,4
6,3
1,0
Greece
511622
15,0
12,5
9,1
Italy
1058531
25,9
22,8
7,9
Portugal
317771
48,2
22,1
9,5
Spain
618862
29,3
22,1
9,9
Source: FADN-CCE-DG Agriculture/A-3; adaptation LEI.
The profile of HNV farming systems selected by the typology is summarised in Table
14 to 16. Of the total number of farms analysed, 8.4% qualify as HNV following the
Minimum typology. Of these, 38% of farms are HNV arable systems, and a further
24% are permanent crop systems. Only 23% of the HNV farms are grazing livestock
systems.
In terms of land area, HNV systems are more prominent, with 17.9% of the total UAA.
As with farm numbers, arable systems represent the largest proportion (47%) of the
UAA under HNV systems. Grazing systems represent 29% of the UAA under HNV
systems. The average UAA of HNV farms varies from <12ha for permanent crop
systems to >240ha for permanent grassland systems.
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HNV farming project Final report
Table 14: General profile of HNV farming systems in Southern Europe (data from minimum
approach)
Farms
UAA
Share of
Share of
Average
Share
Average
all HNV
UAA on
UAA
farmers economic
farms
HNV
over 55
size
farms
years
no.
ha
%
%
ha
%
ESU
All systems (HNV and
2653794 46792384
-
-
17,6
36,2
14,6
Non-HNV)
All HNV farms
222581
8367740
100,0
100,0
37,6
33,8
11,1
Low-input cropping
84496
3887214
38,0
46,5
46,0
38,4
13,7
systems
- of these fallow systems
17650
966588
7,9
11,6
54,8
60,2
11,0
- of these dryland
66846
2920626
30,0
34,9
43,7
32,6
14,5
systems
Low-input permanent
53528
634393
24,0
7,6
11,9
33,6
7,3
crop systems
- of these with cattle
2585
80351
1,2
1,0
31,1
10,4
12,5
sheep or goats
- of these without cattle
50944
554042
22,9
6,6
10,9
34,8
7,1
sheep or goats
Off-farm grazing
43873
709267
19,7
8,5
16,2
24,6
10,6
livestock systems
Low-input permanent
7126
1729593
3,2
20,7
242,7
16,4
12,0
grassland systems
Low-input arable grazing
18399
999835
8,3
11,9
54,3
45,8
11,7
livestock systems
Low-input other systems
15158
407438
6,8
4,9
26,9
29,3
9,6
Source: FADN-CCE-DG Agriculture/A-3; adaptation LEI. UAA = Utilised agricultural area, ESU =
European size unit
Table 15: Environmental profile I of HNV farming systems in Southern Europe (data from
minimum approach)
Share of
Share of
Share of
Share of
UAA in
UAA in
UAA in
UAA
permanent
rough
fallow
irrigated
grassland
grassland
%
%
%
%
All systems (HNV and Non-HNV)
14,1
8,2
4,5
11,3
All HNV farms
12,8
18,6
12,3
1,5
Low-input cropping systems
3,6
5,1
11,4
1,3
- of these fallow systems
1,2
0,3
40,1
5,1
- of these dryland systems
4,4
6,7
1,9
0,0
Low-input permanent crop systems
3,1
6,1
9,4
0,0
- of these with cattle sheep or goats
2,1
40,3
6,8
0,0
- of these without cattle sheep or goats
3,3
1,1
9,7
0,0
Off-farm grazing livestock systems
47,6
2,9
1,0
6,1
Low-input permanent grassland systems
24,5
71,5
0,0
0,3
Low-input arable grazing livestock systems
8,2
3,7
38,7
2,0
Low-input other systems
17,4
7,0
33,4
1,3
Source: FADN-CCE-DG Agriculture/A-3; adaptation LEI.
UAA = Utilised agricultural area
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HNV farming project Final report
Table 16: Environmental profile II of HNV farming systems in Southern Europe (data from
minimum approach)
Stocking
Grazing
Nitrogen
Fertiliser
Crop
Grazing
density
pressure
surplus
cost protection
days
cost
outside
UAA
LU/ha
GLS/ha
Kg/ha
Euro/ha
Euro/ha
no.
All systems (HNV and Non-HNV)
0,5
1,5
30,8
70,6
57,4
26,8
All HNV farms
0,3
0,7
14,1
15,6
2,8
190,6
Low-input cropping systems
0,1
0,7
9,2
19,6
3,1
5,3
- of these fallow systems
0,0
1,4
4,5
19,3
3,3
0,2
- of these dryland systems
0,1
0,6
10,7
19,7
3,1
6,0
Low-input permanent crop
0,1
0,5
-4,8
24,2
3,7
55,5
systems
- of these with cattle sheep or
0,3
0,6
-29,6
14,6
2,7
57,8
goats
- of these without cattle sheep or
0,0
0,4
2,6
25,6
3,9
50,6
goats
Off-farm grazing livestock
1,4
2,7
79,9
32,7
9,8
363,0
systems
Low-input permanent grassland
0,1
0,1
10,0
2,5
0,2
0,4
systems
Low-input arable grazing livestock
0,4
2,3
2,1
8,7
0,7
0,4
systems
Low-input other systems
0,6
1,4
1,7
6,2
2,1
29,6
Source: FADN-CCE-DG Agriculture/A-3; adaptation LEI.
UAA = Utilised agricultural area, LU. Stocking density is calculated on all types of livestock on entire
UUA. Grazing pressure is calculated for cattle, sheep and goats in grassland only. Grazing days outside
UAA is calculated as the average days per LU spend grazing of the farm – for example on common
land.
Overall, the typologies seem to have captured a higher proportion of cropping systems
than of grassland systems. This is reflected to some extent in the maps, where regions
with extensive areas of low-input arable land show up as having a high proportion of
HNV farmland (notably in the drier regions of Spain and Portugal, or Basilicata in
Italy). On the other hand, regions where HNV farming is mostly characterised by
extensive livestock grazing, but which have little extensive arable cropping, are less
prominent in the maps (Asturias in Spain, the Alpine regions in Italy).
Clearly there are weaknesses in the database that are causing some of these
unsatisfactory results. In Greece, for example, the FADN data excludes farms of less
than 2 ESU. These farms represent 40% of all Greek farms, or 20% of the total Greek
UAA. Another difficulty is that publicly owned areas (mainly used for grazing) are not
included in the UAA of the respective farms. These areas make up almost 80% of the
rough grasslands in Greece. The database thus indicates high stocking densities,
calculated for the small areas of privately owned land.
It is possible that a modified database, with greater homogeneity between countries and
with a correction of the factors referred to above, could lead to results more in tune
with those from the land cover approach, and coinciding with expert knowledge of the
Mediterranean regions.
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HNV farming project Final report
Results of the species approach
The maps based on bird data produce some surprising results, when viewed from the
perspective of the Mediterranean regions. For example, the map for arable and
improved grassland species shows greater richness across most of northern France than
in the arable steppes of Iberia. The same is true for species associated with agricultural
complexes. The map for pastoral woodland shows low richness in the regions of
dehesas and montados in south-west Iberia, but much higher values in most of
Germany. These results suggest that the chosen suites of species do not reflect well the
birds associated with Mediterranean land uses.
As a tool for enriching the land cover and farm typology approaches, the data used for
the species approach seems to be inappropriate, as the suites of species are not
sufficiently tailored to particular systems and regions, such as arable land that harbours
important steppeland bird communities.
Overall conclusions on the results for the southern countries
The species approach appears to have significant weaknesses in its present form and
will not be commented on further.
The land cover and farm typology approaches give variable results. Some regions show
up strongly through both methods, notably western Spain, and in particular
Extremadura. This is probably a significant result and is supported by the fact that
Important Bird Areas in Extremadura cover over 70% of the land area, considerably
higher than for other regions of the EU15. The combined approaches seem to confirm
that this region is exceptional for its large proportion of farmland under HNV systems.
Some other regions show up strongly on the CORINE Minimum map, but much less
strongly on the FADN map. Southern Greece and Galicia are perhaps the clearest
examples. This may be explained by problems with FADN data in these regions,
especially in relation to extensive common grazings.
Table 17 and 18 comparing the results of the land cover and the farming systems
approach indicates that the land cover approach in general estimates the agricultural
area and the HNV farmland to be larger than the calculated by FADN. This is not
necessarily wrong as the two approaches have different purposes and logics that can
explain this. However, it indicates that the land cover approach is the best suited for
mapping HNV farmland, but that the extent cannot be analysed this way. It also points
to some problematic regions where the comparisons show skewed results. This is for
example the case in Southern France.
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HNV farming project Final report
Table 17: Comparison of agricultural area according to the farming system approach and the land
cover approach.
FADN UAA
Agricultural land cover
FADN in percentage of
ha
classes in CORINE
CORINE
ha
%
EU15
118000235
143655448
82
Southern
46792384
88854223
53
Southern France
3110182
13966940
22
Greece
8430851
9120318
92
Italy
12477379
20212728
62
Portugal
3762069
5970951
63
Spain
19011904
39583286
48
Source: FADN-CCE-DG Agriculture/A-3; adaptation LEI and CORINE land cover.
Table 18: Comparison of the area included in the different approaches. Farming system approach,
common typology is set as 100
FADN common
FADN max
FADN min
CORINE max
CORINE min
typology
Ha = 100
%
%
%
%
EU15
40828081
81
39
257
94
Southern
24004492
75
35
339
137
Southern France
1057461
26
4
1139
335
Greece
1407952
83
53
588
343
Italy
5128202
79
29
374
116
Portugal
2836600
75
47
198
80
Spain
12623904
85
41
287
129
Source: FADN-CCE-DG Agriculture/A-3; adaptation LEI and CORINE land cover.
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HNV farming project Final report
4.2 Western Europe and Scandinavia
Broad characteristics of HNV farming in the northern Europe and Scandinavia
Type 1 and type 2 HNV farming systems surviving in northern Europe and
Scandinavia are associated mainly with grazing livestock systems rearing sheep and/or
cattle on farmland dominated by semi-natural vegetation. Areas containing a high
proportion of HNV farmland generally contain a patchwork of habitats such as natural
pastures (including alpine grassland, heath, moorland, saltmarsh, marshland, bog,
wood-pasture) and woodland and scrub (some of which is grazed) as well as
agriculturally managed land of pasture and crops.
Most farms are geographically discrete and their management practices create
important and complex links between the semi-natural habitats and the annual farming
cycle. Although the long-distance transhumance systems common in southern Europe
are not a major feature in northern Europe the use of pastures held and managed in
common or other off-farm grazing is often an important feature of livestock systems,
particularly in the more remote and isolated parts of the region.
Type 1 HNV Farmland: By definition these farms contain pastures composed of a high
proportion of semi-natural vegetation which is used for grazing, but they also in many
cases involve on-farm finishing of the animals. Hay and silage cropping from meadows
is also a practice common across this region. If crops are grown, this is generally only
a small proportion of the total UAA but a large proportion of these crops is used for
feeding livestock on the farm. Some examples include:
Grazing of cattle in the marshlands of north-western France, where the grazing and
associated mowing practices serve to maintain a range of open grassland habitats
within the marshes.
Low intensity raising of sheep in the Uplands of UK.
Type 2 HNV Farmland: Such systems can involve a combination of both arable and
semi-natural vegetation in the landscape. However, they are also found in association
with relatively large areas of permanent crops (such as old orchards) or low-lying
wetter areas formerly given over to hay meadows. More natural habitats (such as
woodlands, wetlands) are also generally interspersed through such areas. Examples
include:
Small scale farming in mixed agricultural/forestry landscapes in Scandinavia
Type 3 HNV Farmland: Across this region, Type 3 HNV Farmland is generally more
closely associated with the geographical location and ecological requirements of the
rare species involved rather than the characteristics of the farms per se. In some cases
this may be associated with remnant habitats, but in others it reflects edaphic
conditions rather than the farm management - the large concentrations of wintering
Arctic geese found on the wet farmland are examples. Other examples are:
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HNV farming project Final report
Areas in Denmark and the Netherlands where the proximity to the coast and
relative fertility of the pastures means that these often intensively managed pastures
hold internationally important populations of breeding waders and especially
wintering wildfowl.
Areas such as the Breckland and east Anglia in south-east England where birdlife
such as stone curlew and wintering geese are attracted to the intensively managed
arable land.
Results on land cover approach
The results of the selection of Corine Land Cover Classes (LCCs) are shown in the
form of two maps and tables, indicating the results from the Minimum and Maximum
approaches.
Overall the results suggest that in northwestern Europe HNV farmland is less
widespread than in southern and eastern Europe. This can be seen from Table 19 which
indicates the predicted area of those CORINE LCCs taken as being indicative of HNV
farmland expressed as a proportion of the total area of those LCCs regarded as being
potentially associated with agriculture in each region/country. Separate figures are
given for the proportions for both the minimum and maximum approaches. It can be
seen that there is a clear difference between Scandinavia and the rest of Europe, and
also between the different countries within western Europe. From these figures,
Ireland, Austria and the UK would be assumed to have more HNV farmland than
Germany, The Netherlands, Belgium, Denmark and Northern France. This is similar to
the result from the farming systems approach.
Table 19: Share of the total area of CORINE LCCs potentially associated with agriculture
according to minimum and maximum selections
Proportion of agricultural LCCs total
Total area (ha) of those
which is predicted to be under LCCs
LCCs associated with
associated with HNV farmland:
agriculture
Maximum
Minimum
EU 15
143655448
73.0
26.6
Western Europe & Scandinavia
111070378
58.3
18.3
Austria
4053038
99.2
29.0
Belgium
1833489
62.7
1.6
Denmark
3366542
46
4.5
Finland
8815056
65.1
49.1
Northern France
23525602
63.3
2.0
Germany
22017339
35.2
1.7
Ireland
6223053
94.7
24.7
Luxembourg
146079
76.7
0.4
Netherlands
2682897
78.6
3.1
Sweden
18436315
64.4
33.7
United Kingdom
19970968
51.7
30.0
Source: Corine Land Cover
From Table 20 it becomes clear that in Northern Europe and Scandinavia a much
larger proportion of CORINE LCCs associated with HNV farming are situated in
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HNV farming project Final report
lowland areas than in Southern Europe. This is not so much of a surprise as it was
already indicated in the former sections of this report that typical of HNV farming
systems is that they are often constraint by climatic and topographic factors which
more often occur in mountainous areas than in lowland areas, where farming activities
have already taken the opportunities to optimise agricultural activities to the most
optimal situation the local physical environment allows.
Table 20: Share of CORINE farm land classes potentially of HNV according to minimum and
maximum selections in 3 altitude classes
Maximum
Minimum
0-300
300-600
600+
0-300
300-600
600+
EU 15
47.9
24.2
27.8
34.9
26.0
39.1
Western Europe & Scandinavia
66.5
22.6
10.9
61.7
26.3
12.0
Austria
20.0
33.9
46.1
1.2
5.5
93.3
Belgium
77.5
21.7
0.8
67.7
20.5
11.8
Denmark
100.0
0
0
100.0
0
0
Finland
80.2
19.6
0.2
94.8
5.2
0.0
Northern France
85.1
12.2
2.7
53.5
23.9
22.6
Germany
50.1
35.7
14.2
45.1
21.4
33.5
Ireland
94.2
5.6
0.2
82.1
17.1
0.8
Luxembourg
31.1
68.9
0.0
8.4
91.6
0.0
Netherlands
100.0
0.0
0.0
100.0
0.0
0.0
Sweden
38.0
35.5
26.5
58.7
32.0
9.3
United Kingdom
69.2
25.8
5.0
48.1
43.3
8.6
Source: Corine Land Cover
As in southern and eastern European situations, the results show that in Northern
Europe and Scandinavian CORINE LCCs included in the
Minimum approach (see map
7) are made up almost exclusively of semi-natural vegetation (pastures, natural
grasslands, moors and heath, woodland-scrub vegetation and marshes, peat bogs and
coastal dunes and marshes). The countries where there is the smallest proportion of
agricultural CORINE LCCs associated with HNV farmland are also the ones where
land is practically flat. Most of the CORINE LCCs associated with HNV farmland are
found in the countries with considerable proportions of land above 300 meters. The
map thus provides a useful illustration of the distribution of semi-natural vegetation
types that are taken as being generally indicative of HNV.
The CORINE LCCs that are mostly associated with HNV farmland are the Natural
grassland, Moorland, Inland marshes and Peat bogs classes which can more often be
associated with extensive grazing practices than with some arable land use. However,
several of these CORINE LCCs may still be used for grazing, but are often managed
by Nature Conservation organisations. So strictly they may not be used for farming
anymore although grazing is still practised. This situation is most often the case in
western European countries such as The Netherlands, Belgium, Germany and
Denmark. In most parts of Scotland, Ireland, Northern England grazing as part of
agricultural practices is still very commonly practised on moors and heathlands. Thus,
the Minimum approach shows reasonably well where HNV farmland is potentially
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HNV farming project Final report
Map 7: Potential type 1 and type 2 HNV farmland according to the minimum CORINE selection
in Western Europe and Scandinavia
Map 8: Potential type 1 and type 2 HNV farmland according to the maximum CORINE selection
in Western Europe and Scandinavia
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HNV farming project Final report
concentrated, but it should be remembered that CORINE does not provide any
indication of how intensively an area may be farmed or even whether it is farmed at all.
By definition, the
Maximum map for Northern Europe and Scandinavian region
includes CORINE LCCs that are only very partly considered to be indicative of HNV
farmland (see map 8). Consequently, the map from the maximum approach is
swamped by the occurrence of a greater extent of the potentially more intensively
managed LCCs. This approach therefore markedly over-represents the location of land
likely to be under HNV farmland.
Overall conclusions on the land cover approach
The Minimum map captures quite well the likely location of Type 1 and Type 2 HNV
Farmland but with the problem that many of the CORINE LCCs used to produce this
map will not always be farmed. The Maximum map includes a very considerable
amount of farmland that is not HNV.
Results on farming system approach
In Western Europe and Scandinavia 35%, 28% and 14% of the agricultural area is
managed by HNV farms according to the different approaches (Table 21). In general
United Kingdom, Ireland, Sweden and to some degree also Austria are the Member
States with the highest score. In the other end the Netherlands, Denmark and Belgium
can be found. For the region the difference between the common typology and the
maximum approach is small, reflecting that high stocking grazing livestock farms are
not included in large numbers in the common typology. In contrast the maximum and
minimum approaches yield very different results, as only half of the agricultural area
from the maximum approach is included in the minimum approach. This is mainly due
to a relatively large reduction in the area for systems with arable crops. For the
dominant system, the permanent grassland system, about one third of the farmed area
is not included in the minimum approach area. Compared to the general picture
national differences can be found. It is worth noting that the reduction in the area
managed by HNV farms from the common typology to the minimum approach is
relatively smaller for three of the Member states with the largest share of their
agricultural area being managed by HNV farms: United Kingdom, Ireland and Sweden.
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HNV farming project Final report
Table 21: Share of Utilised Agricultural Area managed by HNV farming systems
UAA managed by HNV farms
%
Total UAA
Common
Maximum
Minimum
ha
typology
EU15
118000235
34,6
27,9
13,5
Western Europe and
71207850
23,6
20,8
10,7
Scandinavia
Austria
2161498
31,3
26,9
9,4
Belgium
1447840
6,7
3,3
0,6
Denmark
2785253
5,6
5,4
1,3
Finland
2064233
15,1
15,0
5,4
Northern France
18208392
10,6
10,0
2,8
Germany
16207393
13,9
12,7
4,6
Ireland
4912614
48,1
40,6
23,4
Luxembourg (LU)
127179
15,9
10,6
2,1
Netherlands
2152182
2,3
0,0
0,0
Sweden
3454276
38,1
38,1
19,7
United Kingdom
17686990
43,3
36,7
23,4
Source: FADN-CCE-DG Agriculture/A-3; adaptation LEI.
Table 22: Share of the farms identified as HNV farming systems
Farms identified as HNV farming systems
%
Total farms
Common
Maximum
Minimum
No.
typology
EU 15
3815172
25,1
18,9
8,1
Western Europe /
1161377
20,2
17,2
7,4
Scandinavia
Austria
86220
34,0
27,5
8,7
Belgium
41842
4,7
2,4
0,5
Denmark
49970
8,5
7,9
2,0
Finland
55570
14,3
14,0
5,9
Northern France
261456
11,6
10,8
3,5
Germany
279632
13,9
11,6
5,3
Ireland
129350
52,6
44,3
24,9
Luxembourg (LU)
1943
18,1
13,4
1,7
Netherlands
81150
2,5
0,0
0,0
Sweden
40070
33,6
33,6
15,4
United Kingdom
134174
28,3
22,2
8,8
Source: FADN-CCE-DG Agriculture/A-3; adaptation LEI.
In map 9 the Member State information is detailed on HARM1 regions. As it can be
seen the maps pinpoint Scotland as the most important region concerning HNV
farming. For some regions the maps indicates relatively stable interregional
differences. This is for example the case for United Kingdom and Ireland. In other
cases differences can be found in the patterns between the different maps. Only two of
the maps for France indicate that the southwestern regions are more important for
HNV than the northeastern regions. The maps also indicate that southern Germany and
Austria and some of the northeastern regions of Germany have a relatively high
importance for HNV farming. The data for Scandinavia give some problems. The
relative picture of the Finish regions is best represented on the common typology map,
because of lack of data from FADN. In Sweden the southern part of the country and
the region around Stockholm to the east should be distinguished from the other
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HNV farming project Final report
southern Sweden region, which is not the case on two of the maps, partly due to the
mapping classes.
Map 9: Share of Utilised Agricultural Area managed by HNV farming systems
Source: FADN-CCE-DG Agriculture/A-3; adaptation LEI.
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HNV farming project Final report
Table 23 confirms the importance of grazing livestock in relation to HNV farming in
Western Europe and Scandinavia, though 15% of the HNV farms and 9% of the HNV
managed UUA fall into the category of cropping systems. 83% of the agricultural area
of HNV farms are permanent grassland systems, half of which is managed by farms
where rough grassland is the major land use. However, it is worth noting that the rough
grassland farms only account for 4% of the HNV farms, whereas other permanent
grassland farms account for two thirds. Off-farm grazing systems are not very
abundant in Western Europe and Scandinavia, though their importance for HNV can be
high. They account for 3% of the agricultural area managed by HNV farms, but the
area used for grazing outside the farms is not recorded in the statistics and might be
substantial. Also low-input other systems only make up a very small proportion of the
HNV farms and the agricultural area managed by HNV farms with 1,4 and 0,3%
respectively).
Table 23: General profile of HNV farming systems in Western Europe and Scandinavia (Data
from minimum approach)
Farms
UAA
Share of
Share of
Average
Share
Average
HNV farms
UAA on
UAA
farmers
economic
HNV farms
over 55
size
No.
ha
%
%
ha
years
ESU
%
All systems (HNV
1161377 71207850
-
-
61,3
26,2
58,8
and Non-HNV)
All HNV farms
86522
7594649
100
100
87,8
35,9
18,2
Low-input cropping
12987
668151
15,0
8,8
51,4
17,9
23,5
systems
Off-farm grazing
3020
245749
3,5
3,2
81,4
39,6
32,9
livestock systems
Low-input
61160
6275104
70,7
82,6
102,6
43,4
15,2
permanent grassland
systems
- of these rough
3334
3161971
3,9
41,6
948,4
49,4
27,8
grassland systems
- of these permanent
57826
3113133
66,8
41,0
53,8
43,1
14,4
grassland systems
Low-input arable
8151
380432
9,4
5,0
46,7
10,2
23,6
grazing livestock
systems
Low-input other
1205
25212
1,4
0,3
20,9
13,4
45,1
systems
Source: FADN-CCE-DG Agriculture/A-3; adaptation LEI.
UAA = Utilised agricultural area, ESU = European size unit
From tables 23 and 24 a general description of HNV farming systems and the different
types of HNV farming systems in Western Europe and Scandinavia can be given. In
average
HNV farms are larger in area than the average farm in the region. This is
however not the case for the economic size of the farms, where the average farm is
more than 3 times larger than the average HNV farm. It is also worth noting that HNV
farmers are older than the average farmer is. 36% of the HNV farmers are older than
55, whereas this is only the case for 26% of all farmers. Also for the environmental
profile the HNV farms, as expected, differ from the other farms. HNV farms have
more grassland, especially rough grassland accounting for almost half of the
agricultural area on HNV farms, but for less than 10% on an all farms. The use of
inputs is markedly lower on HNV farms: The use of fertilisers, measured in Euro, are
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HNV farming project Final report
only 15% of the average for all farms and crop protection less than 4% of the average.
Combined with a total stocking density half the size of average farms, the low fertiliser
use means that the nitrogen surplus is only 30 kilo per ha compared with 76 kilo on
average for all farms. Finally, the potential pressure on the grassland from grazing is
with 0,5 cattle, sheep or goats more than 3 times lower than on the average farm.
Table 24: Environmental profile of HNV farming systems in Western Europe and Scandinavia
(Data from minimum approach)
Share of
Share of Stocking
Grazing Nitrogen Fertiliser
Crop
Grazing
UAA in
UAA in
density pressure
surplus
cost protection
days
permanen
rough
cost
outside
t grassland
UAA
grassland
%
LU/ha
GLS/ha
kg/ha
Euro/ha
Euro/ha
No.
%
All systems (HNV
27,3
8,7
1,1
1,6
76,2
85,4
69,4
5,7
and Non-HNV)
All HNV farms
36,2
47,3
0,5
0,5
30,2
13,2
2,5
27,4
Low-input
18,0
0,8
0,2
0,4
37,6
10,3
4,5
0,0
cropping systems
Off-farm grazing
52,8
34,3
1,5
1,6
76,4
37,7
9,5
196,2
livestock systems
Low-input
38,0
55,7
0,4
0,4
24,6
13,1
2,0
5,9
permanent
grassland systems
- of these rough
3,0
96,1
0,1
0,1
3,6
2,4
0,2
17,8
grassland systems
- of these
73,5
14,7
0,7
0,7
46,0
23,9
3,9
3,5
permanent
grassland systems
Low-input arable
26,8
0,2
0,7
1,3
53,7
6,1
2,4
0,0
grazing livestock
systems
Low-input other
67,4
14,5
13,8
1,2
447,9
10,0
4,1
0,8
systems
Source: FADN-CCE-DG Agriculture/A-3; adaptation LEI.
UAA = Utilised agricultural area, LU = Livestock units, GLS = LU of cattle, sheep or goats. See also
notes to table 15.
Information on the specific HNV farming systems can also be derived from the tables.
As an example the most interesting feature of the
rough grassland farms is of course
that 96% of the agricultural area on these farms is rough grassland. As mentioned
before relatively few farms are of this type, but with an average size of 1.000 ha they
are 15 times as big as the average farm. In economic terms, however, they are only half
the size of an average farm. It is also worth noting that almost half of the rough
grassland farmers are older than 55, indicating that succession can become an issue in
relation to these systems. Apart from having the huge rough grassland areas the
environmental in general is positive. On average 2.400 Euro is spent on fertilisers and
200 Euro is spent on crop protection. Combined with a stocking density of 0,1 it means
that the nitrate surplus is only 3 kilo per ha.
Conclusions on the farming system approach
The results from the farming system approach in Western Europe and Scandinavia
provide a good insight in HNV farming in the region. The systems that have been
identified are surely
more HNV than the systems that are considered to be non-HNV.
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HNV farming project Final report
But, as the results from the three different approaches indicate it is hard to draw an
exact line between HNV and Non-HNV. Also the overall pattern regarding the spatial
distribution of HNV farming is believed to be reflected in the tables and maps.
However, at the HARM1 level data problems occur because the number of sample
farms in FADN is to small, when a detailed typology like the HNV typology is applied.
The results also show that valuable information on the characteristics of the different
farming systems can be calculated. Distinct profiles of the different HNV systems can
be analysed for monitoring or policy purposes.
Results on species approach
The maps based on both the approaches using bird data produce some surprising
results for northern Europe and Scandinavia. For example, although large parts of
northern Scotland are shown, as would be expected, as having over 60% of the species
deemed to be associated with this habitat type, this figure drops to less than 30% in the
Republic of Ireland even though moorland is characteristic feature of much farmland,
especially in the west of the country. In addition, most of Britain is shown as having
over 50% of the bird species being indicative of dry grassland (steppic) habitat, thereby
incorrectly suggesting that much of Britain is on a par with the heartland of this type of
habitat in central Spain. Finally, with the exception of bird species associated with
pastoral woodlands and those associated with arable and improved grasslands, then
most of Scandinavia is shown as being misleadingly low in bird species associated
with the other habitat types. Overall, the results suggest that the chosen suites of
species do not consistently reflect the bird species associated with HNV farmland in
northern Europe. The current maps produced from the bird species approaches appear
to be at worst inappropriate and at best unreliable in terms of adding any additional
value to the results from the land cover and farming systems approaches.
Overall conclusion on Western Europe and Scandinavia
The different approaches show different strengths and weaknesses in relation to the
results on Western Europe and Scandinavia. Though some regions still need further
work and verification the maps based on the land cover approach give a fair
representation of the location of HNV farmland. However, the maps stemming from
this approach cannot be used to analyse the extent of HNV farmland. This is indicated
in table 25 and 26 comparing the agricultural land cover classes selected from
CORINE and the UUA in the FADN and the results of the different approaches. Not
surprisingly, the tables show that the agricultural area as estimated from CORINE is
too large compared with FADN. Also for the results on identified HNV farmland the
figures from CORINE overestimated the area. The main reason is that CORINE
operates with heterogeneous areas and therefore includes non-HNV farmland and non-
agricultural areas. However, this does not limit the use of the approach for making
indicative maps of the location of HNV farmland. The farming system approach is
therefore the best approach for analysing the extent of the HNV farmland.
Furthermore, the farming systems approach can be used to analyse the characteristics
of HNV farming at a regional level. The species approach needs to be elaborated
further to be useful.
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HNV farming project Final report
Table 25: Comparison of agricultural area according to the farming system approach and the land
cover approach.
FADN UUA
Agricultural land cover
FADN in percentage of
ha
classes CORINE
CORINE
ha
%
EU15
118000235
143655448
82
Western Europe and
71207850
111070378
64
Scandinavia
Austria
2161498
4053038
53
Belgium
1447840
1833489
79
Denmark
2785253
3366542
83
Finland
2064233
8815056
23
Northern France
18208392
23525602
77
Germany
16207393
22017339
74
Ireland
4912614
6223053
79
Luxembourg
127179
146079
87
Netherlands
2152182
2682897
80
Sweden
3454276
18436315
19
United Kingdom
17686990
19970968
89
Source: FADN-CCE-DG Agriculture/A-3; adaptation LEI and CORINE land cover.
Table 26: Comparison of the area included in the different approaches. Farming system approach,
common typology is set as 100
FADN common
FADN
FADN
CORINE
CORINE
typology
maximum
minimum
maximum
minimum
approach
approach
approach
approach
ha=100
%
%
%
%
EU15
40828081
81
39
257
94
Western Europe
16805053
88
45
385
121
and Scandinavia
Austria
676549
86
30
594
174
Belgium
97005
49
9
1185
30
Denmark
155974
96
23
993
97
Finland
311699
99
36
1841
1389
Northern France
1930090
94
26
772
24
Germany
2252828
91
33
344
17
Ireland
2362967
84
49
249
65
Luxembourg
20221
67
13
554
3
Netherlands
49500
0
0
4260
168
Sweden
1316079
100
52
902
472
United Kingdom
7658467
85
54
135
78
Source: FADN-CCE-DG Agriculture/A-3; adaptation LEI and CORINE land cover.
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HNV farming project Final report
4.3 Central and Eastern Europe
Although there is no definitive survey, there is widespread agreement that there are
extensive areas of high nature value farmland in Central and Eastern Europe (CEE, see
Baldock et al 1994, 2000 & 2002, Redman 2001). Several other EEA countries,
including Norway and Switzerland also have a significant endowment of such
farmland. In CEE large areas have retained a significant habitat value, despite a period
of intensive agricultural production methods and the large land improvement schemes
which took place during the communist era. In most countries, sizeable areas persisted
on the margin of intensification or remained under relatively traditional management,
whether in the more mountainous regions or in small scale production systems on
lower land. Since 1990 farmland habitats have benefited in several regions as a result
of the collapse of the agricultural economy. The use of pesticides and fertilisers has
fallen significantly, major intensive livestock units have been closed, and sizeable
areas have been left fallow. However, abandonment and the withdrawal of historic
management have become a threat to the nature value of some farmland areas, both on
grassland and some traditional arable areas.
Many species and habitats of conservation concern are found on farmland in CEECs
and the wildlife dependent on agricultural habitats generally exceeds the biodiversity
value of farmland in most EU countries in similar bioregions. Many farmland bird
species in rapid decline within the EU have very important populations in the region
(e.g. the White stork
Ciconia ciconia, Corncrake
Crex crex and
Whinchat
Saxicola
rubetra). In addition, many grassland and less intensive arable areas have high
botanical values and there are rare or threatened mammals dependent on farmed
habitats.
HNV farming in the region
Extensive livestock production is widespread throughout the region. HNV livestock
systems typically consist of very small herds, or individual animals, owned by semi-
subsistence farmers, which are tethered or herded. Herding mostly takes place on
common or fallow land or arable stubbles and is often governed by informal
arrangements. The seasonal movement of livestock (transhumance) also remains a key
part of some livestock systems, especially in mountainous regions such as the
Romanian and Bulgarian Carpathians and Polish Tatras. Larger scale livestock
production varies greatly in its character but a proportion is associated with HNV
farmland. Some farms that remain from the collectivised period maintain large herds of
cows, sheep and horses which are grazed at low stocking densities on low-input
grasslands. However, livestock numbers have fallen sharply in the region since the
early 1990’s and sizeable areas appear undergrazed.
The extensive, and often semi-natural, grassland associated with extensive livestock
grazing varies across the region due to climatic and abiotic conditions and variations in
management styles. Semi-natural and extensively grazed grasslands range from the dry
steppe or ’puszta’ in Hungary, to the wet grasslands on the Baltic coast. Both provide a
key habitat for migrating birds such as cranes, raptors, geese and waders, as well as
specialist flora.
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HNV farming project Final report
Low input arable systems are also common in the region. They are typically mosaic
habitats consisting of small areas of varied crops with few, if any, fertiliser or pesticide
inputs. These areas are typically also rich in natural features, often containing hedges,
small woodland areas, small wetlands etc.
Permanent crops, in particular low input fruit orchards are often also HNV farmland.
Such orchards typically contain mature trees in a mosaic with arable cultivation. In the
’tanyas’ system in Hungary vineyards are found in a mosaic of crops.
The major changes that have swept agriculture in the region since the early 1990a have
created new landscapes with a rapidity and on a scale unfamiliar in the EU. Further
changes lie ahead with accession to the EU taking place from May 2004. There is
concern that significant intensification could occur in some regions, together with an
increase in input use, while under-management and abandonment takes place
elsewhere.
For this reason it would be particularly desirable to be able to identify HNV farming
areas in CEE in the near future in order to assist in policy making. For example, rural
development plans and specific measures, including agri-environment schemes, are
being drawn up at the time of writing in 2003 and may be further revised before 2003.
An ability to target these on areas vulnerable to further adverse change in the coming
years would be particularly timely.
Identifying HNV areas
The primary focus of this study was the development of an indicator or indicators for
HNV farming in the current EU but the potential for extending this to all EEA
countries and also Switzerland was also to be considered. To this end, consideration
was given to:
The potential application of the land cover approach to identifying HNV
farmland outside the EU.
The potential application of the farm systems approach.
The possible application of the species approach.
The availability of relevant agricultural land cover and environmental data in
the countries concerned.
In addition, a number of experts from CEE were involved in the study, particularly
commenting on the potential value and applicability of the approach in their countries.
The results of this investigation are summarised briefly below.
The land cover approach
Several national experts from CEE countries were asked to follow part of the
procedure adopted in EU countries under the land cover approach. They selected land
cover classes that they judged could be used to indicate both the minimum potential
locations of HNV farmland within their country and also the maximum potential
location of such farmland (see section 3.1 for a fuller explanation). This exercise was
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HNV farming project Final report
Map 10: Potential type 1 and type 2 HNV farmland according to minimum CORINE selection in
eastern Europe
Map 11: Potential type 1 and type 2 HNV farmland according to maximum CORINE selection in
eastern Europe
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HNV farming project Final report
carried out in Bulgaria, the Czech Republic, Hungary, Lithuania and Romania1,
although the results can only be shown in a map form for countries which are currently
covered by the CORINE database (Bulgaria, Czech Republic and Romania – see map
10 and 11). The initial results have not yet been peer-reviewed, but at first glance they
do not appear to suggest any obvious problems over and above those associated with
applying this approach in the EU, for example the treatment of woodland. On this basis
the land cover approach appears suitable for use in CEECs, as most will be in the
updated CORINE database that will be available from mid 2004. Some early results
from three countries are shown in the table below.
Table 27: Share of total farmland where HNV farmland potentially could be located – minimum
and maximum approach
Country
Total agricultural area
Maximum
Minimum
(x 1,000 Ha)*
Bulgaria
7,040
89.6%
27.2%
Czech Republic
4,924
22.6%
2.2%
Romania
15,090
87.5%
31.0%
Source: CORINE land cover
The farming systems approach
Using the farming system approach described in section 3.2 to identify areas of HNV
farmland has particular problems outside the EU, where the database does not exist.
There are further limitations in the CEE context. Most significantly the majority of
HNV farms in the region are likely to be below the minimum threshold for inclusion in
FADN, which is governed by rules and procedures agreed in the EU, so excluded from
the database. A detailed description of the implementation of the FADN system in EU
Accession Countries is provided in box 4.
Other limitations with the FADN approach in the CEE in particular should also be
noted. For instance, farm inputs in the region are typically very low at present and it
would be difficult to set an appropriate threshold for input costs. It should be noted that
some areas, such as orchards, are farmed almost without inputs. It would be beneficial
if the thresholds chosen for EU conditions could be differentiated to take into account
the differences between input costs in arable areas, grasslands and permanent crops. In
addition, the land tenancy and grazing arrangements are often informal, so calculating
stocking densities could be very difficult when stock is herded over a large area, and in
particular where transhumance is carried out.
In the next decade input use and expenditure could increase significantly in large areas
of CEE, although this would not be anticipated in other EEA countries. Any indicators
based on input use or expenditure per hectare would require regular review.
1 Other non-EU countries covered include Cyprus, Switzerland and Turkey.
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HNV farming project Final report
Box 4: FADN implementation in EU Accession Countries
EU Accession Countries are required to implement the EU’s FADN system fully after
accession in May 2004, although progress towards meeting this target is varied. All ten of
the first wave of Accession Countries became observers in the FADN committee in April
2003. Many began to implement FADN with sample sizes of ten per cent of the agricultural
area in 2002. Five countries (Czech Republic, Hungary, Lithuania, Latvia and Estonia) have
already put in place a system for the collection, control and preparation of accountancy data
to be transmitted securely by their national administration to the FADN database (RICA-1).
Poland also expects to have reached this stage by the end of 2003. The second and third
stages of FADN administration (RICA-2, a database and analysis system, and RICA-3, an
information system for reporting and dissemination) will be completed by all new Member
States immediately after accession (FADN Committee, 2003).
The implementationCertain aspects of the of data gathering required under FADN differs
between current Member States. The exact way in which FADN will operate in the new
CEE Member States is not yet clear. The data is likely to be subject to specific limitations in
relation to its potential use for indicating high nature value farmland due to the varying
sample size in each country, the threshold set for ‘commercial’ farms (and potential
exclusion of many small farms likely to be of high nature value) and informal grazing
outside the official UAA of a farm (which will distort official grazing densities).
In Lithuania, for instance, there are 200-250,000 farms covering more than one hectare. Of
these, it is expected that only 45-55,000 farms exceed 2 ESU, which is the size threshold for
inclusion in FADN, although these commercial farms cover 85-95 per cent of UAA. The
types of farm most likely to be excluded are mixed cropping, mixed grazing livestock and
field crops with grazing livestock combined (FADN farm types 60, 71 and 81).
Table # A summary of planned FADN implementation in ten Accession Countries
Number of farms
Number of regions for
Threshold for
Country
in sample
FADN purposes
‘commercial’ farms
(in ESU)
Cyprus
500
*
1
1 or 2
*
Czech Republic
1,000
*
1
1 or 2
*
Estonia
500
*
1
1 or 2
*
Hungary
1,900
7
2
Latvia
500
*
1
1 or 2
*
Lithuania
1,300
1
2
Malta
500
*
1
1 or 2
*
Poland
12,000
*
4 regions with 16 sub-regions
1 or 2
*
Slovakia
600
*
1
1 or 2
*
Slovenia
500
*
1
1 or 2
*
* This is approximate information, based on what was discussed during technical meetings at DG Agri during 2003.
The total number of holdings in Hungary is 960-970,000 but only nine per cent of farms are
above the 2 ESU threshold (90-92,000 based on data from 2000). The majority of those that
are below the ESU threshold are considered by be semi-subsistence farms, often with a mix
of arable and livestock production.
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HNV farming project Final report
The species approach
The data needed to implement this approach, bird species of conservation concern for
example, has not been examined in detail but there is good information for a number of
species. In principle, this approach appears equally applicable outside and within the
EU with the comparability of the data being the main concern. However, there are
broader questions about how it is best developed and what it shows (see section 3.3)
This approach would be expected to highlight the sizeable areas of HNV farmland in
the area since there are large populations of many species of conservation concern.
Table 28: Examples of relevant data sources in non-EU EEA member countries
Data type
Farm data
Natural values
Country
FADN
Other
CORINE
Other
Bulgaria
Due in 2006
The Ministry of
Already
Environmental data is available from the
Agriculture and Forestry
available
Ministry of Environment and Waters and its
and its related structures,
related structures, including the Executive
including the Institutes
Environmental Agency.
of the former
A grassland inventory is in preparation.
Agricultural Academy
(Soil Institute, High
Mountain Agriculture
Institute, Executive Soil
Agency, etc.) can supply
farm data.
Cyprus
Due in 2004
Due in
mid 2004
Czech Rep
Due in 2004
The Czech Statistical
Already
The Agency for Nature Conservation and
Office annually records land
available
Landscape Protection (AOPK) runs the
that is no longer farmed.
NATURA 2000 mapping project and is
building up new information on flora and
fauna, which, it is hoped, will ultimately take
the form of repeat surveys, allowing a time
series to be established.
Time series of farming related wildlife
populations are maintained and published at
the Ministry of Agriculture
(www.mze.cz).
The Agency for Nature Conservation and
Landscape Protection of the Czech Republic
is preparing to publish a book that will
inventory the habitats found in the Czech
Republic, but as yet there is not enough data
on the area they are covering and it is not
expected that this work will be complete until
NATURA 2000 is fully implemented. This
inventory should be more detailed than the
CORINE habitats database managed by
AOPK.
Estonia
Due in 2004
The Statistical Office of Already
Grassland inventory by Estonian Fund for
Estonia (SOE) collects data
available
Nature 2002. A GIS database is available at 1:
on the abandonment of
10,000.
arable land. This
The National Environmental Monitoring
information is published in
Programme (NEMP) is currently the most
the yearbook series
comprehensives data source for biodiversity and
Agriculture. Data is
landscape issues.
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HNV farming project Final report
available for at least the last
five years. The last edition
is from 2001. Data on
abandoned natural
grasslands is inadequate, but
when the Agricultural
Census 2001 is published
more data is likely to be
available.
Hungary
Due in 2004
Due in
Grassland inventory by Authority for Nature
mid 2004
Conservation 2002.
Environmentally Sensitive Areas map, by a
variety of institutions.
Biodiversity monitoring data available from
the Authority for Nature Conservation.
Iceland
No plans for
?
inclusion
Latvia
Due in 2004
Data on nutrient loads is Already
Grassland inventory is in preparation.
available from the Latvian
available
The Latvian State Environment Inspectorate
Environment Agency (LEA)
(SEI) manages a database on protected plant
and is updated annually.
species. The database was created in 1990 and
updated in 1995.
The LEA collects and processes data on the
overall status of flora and fauna. This data is
updated annually and is available for public
access on the LEA website.
Lithuania
Due in 2004
See annex G for details.
Already
See annex G for details.
available
Malta
Due in 2004
Already
available
Norway
No plans for
?
inclusion
Romania
Due in 2006
Already
Grassland inventory in preparation.
available
Slovakia
Due in 2004
Due in
Grassland database available from Seffer
mid 2004
et al 2002.
The State Nature Conservancy office is
creating a comprehensive information system
with the Central database that will collect and
analyse data on biodiversity in Slovakia.
The Slovak Environmental Agency
(www.sazp.sk/index_en.html) also provides
environmental data.
Slovenia
Due in 2004
Has national register of
Due in
There is a programme ‘National
agricultural holdings,
mid 2004
Environmental Monitoring of Slovenia’, but
cadastre of actual
consists of randomly selected research studies
agricultural land use, central
rather than regular monitoring.
animal register and location
Inventory of Most Important Natural
of LFAs.
Heritage in eastern and central Slovenia has been
published; for western Slovenia it is in
preparation.
The Anton Melik Geographical Institute
(www.zrc-sazu.si/gi/landscapes.htm) has data on
landscape features and geology.
A grassland inventory is in preparation.
Switzerland
No plans for
Due in
inclusion
mid 2004
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HNV farming project Final report
Data considerations
There is a limited range of relevant data on agricultural and environmental data
available at the Pan European or EFTA scale, FAO farm statistics being one of the
most important exceptions. CORINE will be available for an increasing number of
countries from 2004 onwards, including for Switzerland. In the enlarged EU the
agricultural statistics required of Member States will be collected over a larger area and
FADN will eventually become available for Bulgaria and Romania as well as the EU
25. However, it will have major weaknesses as a tool for identifying potential HNV
farmland, as described above.
National statistics on a range of relevant topics are collected by government agencies,
academic institutions, NGOs and others. A selection of the type of information
collected by different sources, some as time series data, is given in table 28. Some
countries have particularly relevant information. See annex G for a detailed description
of relevant data available in Lithuania. The data available in Hungary, for example,
goes beyond that available in many current EU Member States in complexity,
resolution and coverage. A great deal of information on soil, altitude, farm and
environmental characteristics is published in map form. Data can be overlaid in order
to identify potential environmentally sensitive areas, for instance (see Map 12).
N
High priority
Medium priority
Low priority
Map 12: Environmentally Sensitive Areas in Hungary (after Bartram et al 1998)
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HNV farming project Final report
5. Conclusions and recommendations for future work
Conclusions
In the project a simple definition of HNV farmland and a dichotomous key for
identifying three different types of HNV farmland land has been established. We
believe that these definitions are relatively robust and contribute to further work on
HNV farmland by providing a basis for other approaches (more detailed and regionally
based) to the broad characterisation of HNV farmland for others interests.
The different approaches that have been used for identifying, localising and
characterising HNV farmland at a European scale and utilising European data are as
follows:
Firstly, a land cover approach was developed to identify and analyse land cover classes
indicating HNV farmland. Secondly, a farming system approach was developed to
identify and analyse farming systems likely to manage HNV farmland. Thirdly, a bird
species approach was developed to identify habitats linked to HNV farmland. Finally,
because rare species associated with European farmland would not be located by these
approaches, we explored the value of using European species distribution data using
birds, because of the availability of data for species of European Conservation concern.
The output of the land cover approach was a prediction of the distribution of HNV
farmland. Though some inconsistencies still occur on the maps, they do, in our opinion,
give a fair picture of the potential location of HNV farmland in Europe at a broad scale.
However, the maps cannot be used for analysing the extent of the HNV farmland and
the possibilities for using the approach to monitor any changes in the extent of HNV
farmland are very small. This is due to both to the limitations stemming from to the
rationale behind the accessible Pan-European data (CORINE) and to the updating
frequency of the data. As the new version of CORINE becomes available and the
number of participating countries increases, the land cover approach will become more
useful at a European scale.
There are limited data sources available for applying a farm systems approach at a
European scale. FADN seems the best available in the EU. The farming system
approach yielded maps of the regional distribution of potential HNV farming systems
and profiles presenting the main characteristics of these systems. The approach was
developed through several stages but needs considerable further refinement and general
level validation before it could be used as a strong predictive tool. Though problems of
representativity in the underlying data source (FADN) have been identified, the results
of the farming systems approach will give a fair indication of the distribution and
characteristics of HNV farming systems once the variables and thresholds proposed
have been further testified. For the different systems the data can be used to give a
general assessment of the environmental performance regarding for example stocking
densities, input use etc. indicating the pressure (positive as well as negative) from these
systems in relation to HNV farmland. Due to the yearly update of the underlying data
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HNV farming project Final report
the potential for using the approach for monitoring short term changes in HNV farming
is much greater than for the land cover approach.
The output of the bird species approach to predicting the occurrence of habitats
associated with HNV farmland was disappointing. Pan-European data have been
identified and tested but the methods necessitate many assumptions and value
judgements making it difficult to produce results that can be interpreted with any
confidence at this stage.
The species approach might be improved by applying it at a local scale and not
restricting it to bird species. Invertebrates are probably more suited for this approach if
adequate data are available. Despite these difficulties, a species based approach is
needed to complement the others, particularly in the definition of Type 3 HNV
farmland.
To sum up the different approaches have different strengths and weakness. The Land
Cover approach gives the most precise and most detailed picture of where there are
higher probabilities of finding HNV farmland in Europe. The map showing the
maximum extent of HNV farmland and the map showing the minimum extent of HNV
farmland both include valuable information and should be seen as complementary.
However, we would regard the map of the minimum extent of HNV farmland as
showing the core areas of HNV farmland in Europe. The maps have the potential to be
updated in the future with newer data. This might give a visible impression of changes,
but it cannot be used to analyse and monitor changes until the presumed link with land
cover on the map and the actual occurrence of HNV farmland on the ground has been
validated.
The extent of HNV farmland can at present best be monitored using the farming system
approach. This approach cannot provide exact figures on the development in the extent
of HNV farmland, but reliable indications of certain trends of relevance to nature value
are achievable. Furthermore, the farming system approach can provide information on
the characteristics of different types of HNV farming systems and changes in relevant
management practices. The output of the species approach so far can be used for
qualitative assessments of the results from the other approaches, but should be seen as
the first step in using species to develop HNV farmland indicators. Further work is
required.
The fundamental differences in the three approaches make it difficult to combine them
into a single indicator or map. At this stage, the ‘minimum’ land cover approach would
be regarded as the most indicative single map, subject to the caveats set out above.
Potential Policy Applications
The maintenance of HNV farmland and farms has been referred to as an objective in a
number of EU policy documents and now appears explicitly in the Rural Development
Regulation and both Agenda 2000 and the Mid-Term Review of the CAP. In some cases
it may be an objective in its own right, in others it may be a means of pursuing related
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objectives, such as the conservation of biodiversity or the continuation of genuinely
multi-functional agriculture at a time of significant economic pressures. Up to now it
has been difficult to characterise this farmland or identify either its extent or location
within Europe, other than in the broadest terms. This has greatly restricted the utility of
the concept other than as a signpost to an important issue. Further information at both
the European and national level is required to allow the concept to play a greater role in
different aspects of policy development and implementation.
Ideally this information should be authoritative, unambiguous, consistent, up to date and
expressible in different forms (e.g. in both maps and statistical presentations).
This level of data quality is difficult to achieve in practice, and policy decisions
frequently have to be made on the basis of less good data. Provided that the precise
character and main weaknesses of data sources are understood they can be used to
inform policy in a measured way. In the sphere of agricultural policy the number of
consistent and comprehensive data sources at European level is rather few, so expert
judgement often has to be deployed. There is considerable scope to inform policy
decisions with data of the kind presented in this report, even though the key indicators
are subject to significant caveats and data shortcomings discussed in earlier chapters.
However, we are still some distance from having a single authoritative data base that
could be used for targeting policy very precisely. If the outputs achieved so far could be
validated on the ground it would strongly support the idea of further developing the
approach - both in a more refined form in the EU and, subject to greater limitations
(especially regarding FADN) in a wider Europe.
In the interim, a range of possible applications can be considered:
In the preparation of impact assessments for new policy proposals, for example in
the agricultural, regional and nature conservation spheres. Information on the extent
and distribution of potential HNV farmland and the key agricultural characteristics
of farming systems apparently associated with it may be relevant to several types of
question. Which Member States, regions and farming sectors would be most
affected by measures aimed explicitly at HNV agriculture? Which areas are
potentially sensitive to large-scale development projects (infrastructure, dams,
irrigation, commercial forests etc). Is the impact of new policy measures aimed at
grazing livestock, fallow land or other relevant aspects of agriculture predictable?
In the evaluation of current policies. How far have these affected the principal areas
of HNV farmland or relevant aspects of agriculture? How does policy targeting at
EU or national level correspond to areas likely to have a substantial endowment of
HNV farmland? The information presented in this report could be useful in
assessing progress in integrating agricultural and nature conservation measures or
evaluating the accuracy of reports on related topics.
There is some scope for targeting policies on the basis of the land cover and farming
systems approaches but with due regard to the various data limitations caveats and
other potential deficiencies identified in the report. At this stage the land cover
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HNV farming project Final report
approach is most relevant for this purpose, where the requirement is for a
characterisation of the areas where most HNV farmland is concentrated.
Recommendations on future work
The essential first next step is to validate the outcomes from both the land cover and
farming systems approaches on the ground. In addition to ensuring that both these
approaches are reflecting reality on the ground, this validation process should also
include an assessment of the likely sensitivity to change of the variables used within
each approach.
There is a need for additional information/understanding of the characteristics of many
likely-HNV systems, especially in CEEC, and particularly with regard to knowing
whether or not they will be identified by any of the approaches used in the report.
Further work is therefore needed in the form of sample studies to get more detailed
information on the HNV farming systems including detailed information on
management practices important in relation to the HNV issue and appropriate thresholds
for grazing densities, inputs etc. Gathering data on the characteristics of HNV farmland
in new Member States should be given high priority, since these farming systems are
likely to be subject to powerful policy drivers after accession to the EU by many of
these countries in 2004. Other Central and Eastern European countries are also a
priority. Case studies to determine appropriate methods of identifying HNV farmland
(through the current methodology, therefore requiring some work on appropriate
thresholds and data sources, and exploring alternative methodologies that may be more
appropriate to the region) should be undertaken. Further work should also be done with
national experts to ensure appropriate selections of CORINE habitats and investigate
how the results from the various approaches relate to their perception of the situation on
the ground.
In relation to the land cover approach advantage should be taken of the more consistent
data of the new version of CORINE currently being processed. Additionally, (national)
spatial data sources can be used to further improve the Corine LCC selections based on
smaller mapping entities and/or aimed at identifying semi-natural vegetation types,
mosaic farmland and landscape features. These additional spatial data sources could be
inventories of non-improved grasslands, and/or national land cover maps which can be
considered of better quality for indicating where the HNV farming areas are than
CORINE.
In relation to the farming systems approach four tasks needs attention in the future.
Firstly, we recommend that the possibility for using the farming system approach to
monitor changes over time is explored for example by analysing trends in the
development in HNV farming systems in the last fifteen years. Secondly, we
recommend that both the pros and cons of a unified typology and further regionalisation
are explored further. There is for example a need for more detailed considerations as to
whether or not there are any consistent stocking density levels of HNV which are
'common' across all/parts of Europe - especially with regard to underlying
'state/condition' of the HNV farmland. Thirdly, the possibilities for enhancing the
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HNV farming project Final report
strategy and content of the FADN sampling in relation to agri-environmental issues in
general and more specifically to HNV farming issues should be explored. This also
includes consideration on the problems caused by the large size of the sampling regions
and the fact that the number of sample farms within these in FADN is too small or do
not target HNV relevant farming systems. Finally, the new FADN data from the
accession countries should be analysed as soon as they become available.
Case studies of means of enriching or validating the FADN approach for example using
IACS data also would be valuable. Also, neglecting the statistical significance, LUCAS
data may provide some ancillary information that may give insight into issues such as
the diversity of different land cover types, the crop diversity, or the presence of linear
landscape elements (hedges, grass margins etc.).
In relation to the species approach there is a need to develop this further, for example in
relation to the habitat/species data interlinkages, the possibilities of using non-bird
species, the potential for more localised mapping etc. A concentration on species of
conservation concern is particularly needed to identify Type 3 farmland.
In relation to combining the different approaches at EU level, further work is needed to
combine the information on HNV farming systems to specific land cover classes. It is
obvious that HNV Cropping systems do not link to natural grassland and that the HNV
rough grassland systems do not link to the mosaic type land cover classes. If these links
could be quantified satisfactorily, information on the HNV farming systems could be
added as attributes to the land cover based map of HNV farmland. This might also be a
feasible approach for presenting combined information at levels below the HARM1
regions, which is currently only possible for the CORINE based land cover information
and the species information. This and other means of strengthening the complementarily
of the approach need further research.
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