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A systematic evaluation of Scotland's Natural Capital Asset Index

Authors:

Abstract

In 2011 Scotland became, “The first country in the world to publish a detailed attempt to measure annual changes in its natural capital, based on an evaluation of ecosystem service potential” . The Natural Capital Asset Index (NCAI) was developed as a measure of relative change in the extent and condition of each of seven ecosystems (Broad Habitats) weighted across ecosystem services2, and standardised to 100 in the year 2000. A single aggregate value for Scotland is derived by weighting across Broad Habitats. The motivation for developing the NCAI was two-fold. Firstly, as a measure which could easily communicate the overall change in Scotland's natural assets and highlight the factors which are driving change, and so inform action. Secondly, as a measure of the sustainability of Scotland’s economic development, this could potentially be used alongside GDP to reflect the nation’s overall wealth. The methodology adopted to construct the NCAI was informed by the early thinking about Experimental Ecosystem Accounting instigated by the UN Committee of Experts on Environmental-Economic Accounting (UNCEEA 2013). The NCAI is based on a range of pre-existing indicators/measures of ecosystems and the flow of services, available from government, government agencies, NGOs, etc. However, the robustness of the indicators and weighting system used to combine across ecosystem services, within and between ecosystems, has not been evaluated systematically before now.
Scottish Natural Heritage
Commissioned Report No. 751
A systematic evaluation of Scotland’s
Natural Capital Asset Index
COMMISSIONED REPORT
Commissioned Report No. 751
A systematic evaluation of Scotland’s Natural
Capital Asset Index
For further information on this report please contact:
Paul Watkinson
Scottish Natural Heritage
Great Glen House
INVERNESS
IV3 8NW
Telephone: 01463 725276
E-mail: paul.watkinson@snh.gov.uk
This report should be quoted as:
Albon, S., Balana, B., Brooker, R. & Eastwood, A. 2014. A systematic evaluation of
Scotland’s Natural Capital Asset Index. Scottish Natural Heritage Commissioned Report No.
751.
This report, or any part of it, should not be reproduced without the permission of Scottish Natural Heritage. This
permission will not be withheld unreasonably. The views expressed by the author(s) of this report should not be
taken as the views and policies of Scottish Natural Heritage.
© Scottish Natural Heritage 2014.
i
A systematic evaluation of Scotland’s Natural Capital
Asset Index
Commissioned Report No.: 751
Project no: 14872
Contractor: The James Hutton Institute
Year of publication: 2014
Keywords
Natural capital; ecosystem services; environmental quality indicators.
Background
In 2011 Scotland became, “The first country in the world to publish a detailed attempt to
measure annual changes in its natural capital1, based on an evaluation of ecosystem service
potential” (SNH 2012a). The Natural Capital Asset Index (NCAI) was developed as a
measure of relative change in the extent and condition of each of seven ecosystems (Broad
Habitats) weighted across ecosystem services2, and standardised to 100 in the year 2000. A
single aggregate value for Scotland is derived by weighting across Broad Habitats.
The motivation for developing the NCAI was two-fold. Firstly, as a measure which could
easily communicate the overall change in Scotland's natural assets and highlight the factors
which are driving change, and so inform action. Secondly, as a measure of the sustainability
of Scotland’s economic development, this could potentially be used alongside GDP to reflect
the nation’s overall wealth. The methodology adopted to construct the NCAI was informed by
the early thinking about Experimental Ecosystem Accounting instigated by the UN
Committee of Experts on Environmental-Economic Accounting (UNCEEA 2013). The NCAI
is based on a range of pre-existing indicators/measures of ecosystems and the flow of
services, available from government, government agencies, NGOs, etc. However, the
robustness of the indicators and weighting system used to combine across ecosystem
services, within and between ecosystems, has not been evaluated systematically before
now.
Main findings
Although the proportion of indicators assessed as ‘green’ (fit-for-purpose) was low (< 30%
for all Broad Habitats), there were a large number viewed as ‘amber’ (possibly fit-for-
purpose). Typically concerns in the ‘amber’ class were around the extent to which
changes in the indicator reflected changes in the asset (cause-effect relationship). Where
1 Natural capital – the elements of nature that directly or indirectly produce value to people, including
ecosystems, species, freshwater, land, minerals, the air and oceans, as well as natural processes and
functions (NCC 2014).
2 Ecosystem services - the outcomes from ecosystems that directly lead to good(s) that are valued
by people (UK NEA 2011a, b).
COMMISSIONED REPORT
Summary
ii
indicators were scored ‘red’ (not fit-for-purpose) it was commonly because changes in the
indicator were thought to be confounded by factors other than changes in the asset
(common for cultural indicators), or the data was not sensitive to change, or when an
indicator was extrapolated over more than five years.
The consequence of excluding the ‘red’ indicators on the magnitude and trends in the
NCAI was explored within all seven Broad Habitats. In general, it seemed to make little
difference to the decadal trends, possibly reflecting the similarity of many of the
indicators, which were at best ‘proxy’ measures of productivity of an asset (ecosystem
service flows), rather than indicators of its functional capacity. However, there were
sometimes substantial differences in the magnitude of fluctuations.
To construct the aggregate national NCAI, the contribution of both Broad Habitats to
services, and service groups within Broad Habitats were weighted, as was the
contribution of each Broad Habitat to the national index. However, given limited
quantitative data or only qualitative data in some cases, the relative importance of
provisioning, regulating/maintenance services, and cultural services, was an ‘expert’
judgement. Consequently we explored how the NCAI for each of four Broad Habitats
changed if the weightings of service groups were altered radically from those used in the
original method, including a scenario where provisioning, regulating and cultural services
were equal (33%), and another which contrasted with the original.
In general, the decadal trends were concordant, irrespective of the weights. However, in
some Broad Habitats the magnitude of relative change differed markedly, suggesting that
decision-making about management intervention and policy development could be
difficult, if the assumptions underlying the ‘expert’ weightings were viewed as contentious.
The NCAI indicators have understandably focused on readily available measures.
However, while many indicators measure ecosystem service flows, few are capable of
detecting changes in the potential capacity (productivity) of natural capital assets to
deliver ecosystem services. Thus the NCAI is a useful aggregate measure of ecosystem
service flows rather than a reflection of changes in the condition of the asset (stock) and
its capacity to sustain the flow of a suite of services. The risk is that the NCAI fails to
detect deleterious change in natural capital stocks, and the threat of collapse in services.
A way forward would be to focus on establishing the best measures of the functional
capacity of natural capital assets to sustain the delivery of ecosystem services. Here
there is an opportunity to review the Ecosystem Health Indicators recently proposed
under the 2020 Challenge for Scotland’s Biodiversity. Of particular relevance are the
plans for both the Freshwater Monitoring Plan and the Soil Monitoring Action Plan under
the proposed CAMERAS Scottish Environmental Monitoring Programme.
An advantage of linking the NCAI to the Scottish Environmental Monitoring Programme
and, in particular, the Ecosystem Health Indicators, is that it should provide disaggregated
data, at scales where local intervention could potentially restore degraded natural capital
assets and enhance productivity. Furthermore, comparisons within Broad Habitats of
paired measures of both ecosystem service flow and integrity of natural capital assets
from multiple sites would enable the shape of the relationship between productivity and
functional capacity of natural assets to be determined, including the existence of
thresholds, as envisaged in the Natural Capital Asset Check (NCC Report 2014).
For further information on this project contact:
Paul Watkinson, Scottish Natural Heritage, Great Glen House, Inverness, IV3 8NW.
Tel: 01463 725276 or paul.watkinson@snh.gov.uk
For further information on the SNH Research & Technical Support Programme contact:
Knowledge & Information Unit, Scottish Natural Heritage, Great Glen House, Inverness, IV3 8NW.
Tel: 01463 725000 or research @snh.gov.uk
iii
Table of Contents Page
1.INTRODUCTION 1
2.METHODOLOGY USED IN CALCULATING THE NCAI 2
2.1Background and rationale 2
2.2The hierarchical weighting of ecosystem services and Broad Habitats 3
2.2.1Weighting of Broad Habitat role in delivery of ecosystem services 4
2.2.2Weightings of importance of ecosystem services to Scotland 5
2.2.3Weightings of the Broad Habitats 5
2.3The weighting of condition indicators within ecosystem service groups
and Broad Habitats 7
3.THE EVALUATION OF THE CURRENT SUITE OF NCAI INDICATORS 10
3.1Background 10
3.2Development of a framework for evaluation of indicators 10
3.3Results of the evaluation of the current suite of indicators 12
4.THE EFFECTS OF EXCLUDING THE ‘RED’ INDICATORS ON THE NCAI 13
4.1The ‘sensitivity’ of the NCAI to the inclusion of indicators 13
5.THE INFLUENCE OF CHANGING THE WEIGHTINGS ON THE NCAI 15
5.1Rationale 15
5.2Approach 15
5.2.1Ecosystem service group weights 15
5.2.2Redistribution of provisioning weights on the relative importance of
Broad Habitats 15
5.3Apparent ‘sensitivity’ of NCAI to the weightings 16
5.3.1Ecosystem service group weights 16
5.3.2Redistribution of provisioning weights on the relative importance of
Broad Habitats 16
6.RECENT DEVELOPMENTS IN ASSESSING CHANGE IN NATURAL CAPITAL
ASSETS 18
6.1Background 18
6.2Experimental Ecosystem Accounting - The SEEA 2012 18
6.3Natural Capital Asset Check 19
7.OPTIONS FOR THE REFINEMENT OF THE NCAI 22
7.1Summary of the evaluation of indicators and weighting system used in
the NCAI 22
7.1.1Indicators 22
7.1.2The weighting system 22
7.2Future directions 23
8.REFERENCES 25
ANNEX 1: THE ECONOMIC VALUE SOURCES USED TO CALCULATE THE
RELATIVE CONTRIBUTION OF BROAD HABITATS TO THE DELIVERY OF
PROVISIONING SERVICES 27
ANNEX 2: THE RATIONALE FOR AGREEING THE ‘TRAFFIC LIGHTS’ FOR THE
INDICATORS IN EACH BROAD HABITAT 29
ANNEX 3: COMPARISON OF THE NCAI WITH AND WITHOUT THE ‘RED’
INDICATORS 33
ANNEX 4: THE POTENTIAL FOR ADDITIONAL/ALTERNATIVE INDICATORS IN A
REVISION OF THE NCAI 34
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Acknowledgements
We are particularly grateful to all the help given to the project team by Ralph Blaney, who led
the original work scoping and devising the NCAI. His advice was invaluable to understanding
the way indicators were selected and the weighting systems developed.
We also thank his successor Paul Watkinson for guidance in finalising this report. Our
evaluation was steered by Roddy Fairley, Mary Christie, Sue Marrs, Claudia Rowse, Des
Thompson and Paul Watkinson (all SNH), Rebecca Badger (SEPA), Joanna Drewitt and
Daniel Hinze (both Scottish Government, RESAS) and Darren Mosely (FRS). We are
grateful to all for their insights and helpful comments throughout the last year.
1
1. INTRODUCTION
By publishing a Natural Capital Asset Index (NCAI) in 2011, Scotland became, “The first
country in the world to publish a detailed attempt to measure annual changes in its natural
capital3, based on an evaluation of ecosystem service4 potential” (SNH 2012a). The
motivation for developing the NCAI was primarily to help inform decisions on the degree to
which economic development is being managed sustainably, in a way which could be easily
communicated (Blaney & Fairley 2012). The aspirations were to raise awareness of the
drivers of change in the nation’s natural capital assets and to facilitate enhanced methods for
assessing natural capital (Fairley, pers. comm.).
The methodology for constructing the NCAI is a development on an approach used by
Netherlands Environment Agency (ten Brink 2007), which also influenced the early thinking
instigated by the UN Committee of Experts on Environmental-Economic Accounting
(UNCEEA 2013). However, the robustness of the indicators and weighting system has only
ever been partially evaluated (Hambrey & Armstrong 2010).
Since the publication of the NCAI there has been wider recognition of the importance of
being able to detect change in the capacity of natural capital assets to sustain the delivery of
ecosystem services, because ultimately this influences economic and other human activity
(UNCEEA, 2013). For example, the first recommendation of the Natural Capital Committee
is “the development of a framework within which to define and measure natural capital,
which would draw on data and monitoring systems from across government departments,
non-governmental and research organisations” (NCC 2013). The task of developing
approaches to a natural capital asset check is a major part of the research being undertaken
through the UK National Ecosystem Follow-on work, which will report in June 2014, and will
be used by the NCC to inform their deliberations on metrics to measure changes in natural
capital (NCC 2014). However, while the conceptual frameworks linking natural capital
assets, ecosystem services and human well-being are becoming more unified, concerns
remain about the appropriateness of some of the environmental, social and economic data
used as indicators in the NCAI (Hambrey and Armstrong 2010). Therefore, SNH has
commissioned this review of the NCAI to better understand its strengths and weaknesses.
This evaluation is a preliminary step in seeking the wider adoption of the NCAI by others,
including business and local authorities - an aspiration of the 2020 Challenge for Scotland's
Biodiversity (Scottish Government, 2013).
Here we report an evaluation of the NCAI in six further sections, beginning with section 2)
Methodology used in calculating the NCAI, followed by a robust, 3) Evaluation of the
current suite of NCAI indicators, in order to enable, 4) The effects of excluding the ‘red’
indicators on the NCAI. We continue by considering, 5) The influence of changing the
weightings on the NCAI, before describing 6) Recent developments in assessing
change in natural capital assets, and finally exploring 7) Options for the refinement of
the NCAI.
3 Natural capital – the elements of nature that directly or indirectly produce value to people,
including ecosystems, species, freshwater, land, minerals, the air and oceans, as well as natural
processes and functions (NCC 2014)
4Ecosystem services are the outcomes from ecosystems that directly lead to good(s) that are
valued by people (UK NEA 2011a, b).
2
2. METHODOLOGY USED IN CALCULATING THE NCAI
2.1 Background and rationale
The development of an index of Scotland's natural capital assets was undertaken to find a
measure that, firstly, could easily communicate the overall change in Scotland's nature in a
way that reflects the importance of our natural assets to Scotland’s people and prosperity. A
natural capital asset index should highlight the factors which are driving this change, and so
inform action. Secondly, SNH wanted to both explore and inform the wider goal of assessing
natural capital as a measure of the sustainability of Scotland’s economic development, which
could be used alongside GDP to reflect the overall wealth of Scotland (Blaney and Fairley
2012). The NCAI project developed out of SNH’s Trends & Indicators work, through a pilot
research project, which included a workshop with SNH staff, Scottish Government, other SG
Agencies and NGOs (Hambrey and Armstrong, 2010). It was hoped that the index would
form a useful addition to the indicator information that SNH already publishes, and also, that
it would be more widely adopted.
The NCAI distinguishes ecosystems in Scotland using the ‘Broad Habitat’ classifications
based on those from Countryside Survey 2007. This is similar to the approach taken by UK
National Ecosystem Assessment (UK NEA 2011 a, b), though the marine ecosystem,
beyond the coast, was not considered in the NCAI. Otherwise, the only differences are in
some of the Broad Habitat ‘labels’ used (Table 1). For example, Cropland in the NCAI, which
includes both arable land and improved grassland, is called enclosed farmland in the UK
NEA.
The NCAI is structured around a method devised by the Netherland’s Environment Agency
(ten Brink 2007), where changes in extent (quantity) of a Broad Habitat are multiplied by
changes in the condition (quality) of that Broad Habitat. The NCAI is a measure of relative
change in the extent and condition of each Broad Habitat standardised to 100 in the year
2000. The intention is that is should reflect the Broad Habitat’s capacity to deliver
ecosystem services.
Table 1. The NCAI classification of ecosystems into Broad Habitats and their respective
areas in Scotland (2000). Even over a decade there is comparatively little change in the
extent of most Broad Habitats. However, Woodland has expanded a little at the expense of
Moorland and Grassland, while Cropland appears to be quite variable from year to year, with
some losses overall to urban settlement.
Broad Habitat Ecosystems included in Broad Habitat % Area
Coast Dunes, cliff, beach and tidal mud-flats 2.0
Cropland Arable land and improved grazing 13.7
Grassland
Moorland
Woodland
Freshwater
Greenspace
Rough/semi-natural grasslands
Heather moor, montane and peatland/bog
Woods/forests, including commercial forestry
Lochs, rivers and fens
Urban parks, gardens, etc.
18.0
39.3
19.6
6.5
1.0
3
Figure 1. The grouping of a range of ecosystem services under the Common International
Classification for Ecosystem Services (CICES) adopted in the NCAI methodology.
Recognising that Broad Habitats vary in their capacity to deliver different groups of
ecosystem services (see UK NEA 2011a, p.11), the method is based upon earlier versions in
the evolution of the Common International Classification for Ecosystem Services (CICES
2013) framework (see Figure 1). This facilitates a hierarchical system of weighting
provisioning, regulating/maintenance, and cultural services within each Broad Habitat. Also,
the method weights across Broad Habitats (see Figures 2 & 3), to derive the overall NCAI
index. Weighting the indicators of changes in ecosystem services within each Broad Habitat
was done separately.
2.2 The hierarchical weighting of ecosystem services and Broad Habitats
Since there are major issues about the most appropriate methods of valuation across a
diverse range of natural assets and the ecosystem services they produce, any weighting
system has to be based around a combination of market values, non-market values, non-
monetary values, and expert judgement (Turner & Daily 2008). Here we go into considerable
detail to explain the methods used because the existing descriptions are somewhat limited
and not easily accessible.
SNH adopted a hierarchical approach with three stages for weighting: the relative role of
Broad Habitats in delivering each ecosystem service (2.2.1), the importance to Scotland of
ecosystem services, between and within provisioning, regulating/maintenance, and cultural
groups (2.2.2), and the area adjusted Broad Habitats weights (2.2.3), after multiplying
weighting regimes 2.2.1 and 2.2.2.
4
2.2.1 Weighting of Broad Habitat role in delivery of ecosystem services
The relative weights of Broad Habitats were obtained in different ways for each of the
provisioning, regulating/maintenance, and cultural ecosystem service groups. For
provisioning services the weights relate to published measures of the economic value of
food, fibre, water, etc., attributed to each Broad Habitat (for details see Annex 1). The
weights for the regulating and maintenance services were obtained from a survey of
scientists (using SurveyMonkey), basically asking them to score the importance of each
habitat in delivering each service. For cultural services different sources were used to
estimate the importance of each of the three service sub-groups. The recreation value was
based on SNH Recreation Survey (number of visits per Broad Habitat) multiplied by an
enjoyment value associated with each Broad Habitat (from the Omnibus survey of the
Scottish population).The heritage value was based just on the Omnibus survey, while the
tourism value was from a survey of tourism experts.
The Broad Habitat values shown in Figure 2 represent the percentage of a given service (the
rows of the table each totalling to 100) attributed to each hectare of that particular Broad
Habitat (columns of the table). The very high percentage of the provisioning service
attributed to Freshwater (89.1%) reflects the high value of water (£520M; see Annex 1) and
the fact that it accounts for a comparatively small area (6.5% or 171,654 ha in 2000) of the
total area across all seven Broad Habitats. The estimate of provisioning services delivered
by Freshwater habitats is therefore just over £3,000 per hectare, almost twenty times more
than c. £160 per hectare for Cropland.
Figure 2. The percentage of each ecosystem service attributed to each hectare of each
Broad Habitat and the expert judgement of the importance of each ecosystem service to
Scotland (Scotland Weight).
5
2.2.2 Weightings of importance of ecosystem services to Scotland
Based on the survey of scientists, the Omnibus survey and the relative economic
contribution of nature-based tourism, ecosystem service group weightings were derived, as
25% (provisioning), 50% (regulating/maintenance – split equally) and 25% (cultural). Specific
services within each group were also weighted, for example, the Scotland-wide importance
of carbon sequestration (weight 10) was estimated to be twice as important as the
Freshwater quality regulation (weight 5) (see Figure 2, last column labelled ‘Scotland
Weight’).
2.2.3 Weightings of the Broad Habitats
These weightings were generated by multiplying stages i) and ii) above. In other words, the
Broad Habitat percentage values for the delivery of a given ecosystem service in Figure 2,
multiplied by the national importance of that ecosystem service to Scotland (the ‘Scotland
Weight’ in the last column in Figure 2) to produce Figure 3. For example, in the case of
Woodland, multiplying the 2.4% contribution attributed to provisioning, by the ‘Scotland
Weight’ of 25, gives 61 units (after rounding). Whereas, multiplying the 26% of all carbon
sequestration attributed to woodland, by the ‘Scotland Weight’ of 10 gives 260 units. And so
on.
Figure 3. The derived values of the delivery of each ecosystem service per hectare of each
Broad Habitat, after weighting both the role of the Broad Habitat in delivering an ecosystem
service and weighting the overall importance of each ecosystem service to Scotland (Figure
2). Comparing the aggregate measures (Grand Total) to the smallest value (Cropland)
permits relative ranking of the Broad Habitats (red values in last row) and is used in the
overall NCAI.
6
Summing across all ecosystem service values within a Broad Habitat generated an
aggregate measure for the contribution of that Broad Habitat, per hectare, in delivering a
bundle of ecosystem services (penultimate row Figure 3). Comparing these aggregate
measures between Broad Habitats suggests that Cropland delivers the smallest bundle of
ecosystem services (649 units per hectare) and Freshwater the largest (3,278 units per
hectare – five times as much as Cropland). These relative ranks (see the red values in the
last row of Figure 3) were used to combine across Broad Habitats, by multiplying the area of
a Broad Habitat by its relative rank, to give a Scotland NCAI.
Figure 3 also provides the values to calculate the contribution of each ecosystem service
group within a Broad Habitat (Figure 4). For example, in Woodland, the 61 units of
provisioning services is 5% of the total 1,295 units of ecosystem services, and across all
regulating/maintenance services the 1,078 units are 78% of the aggregate total. The cultural
services add up to 218 units, making up the remaining 17% of services provided by
woodland (Figure 4). This is important, since each of the individual services may not have an
appropriate condition indicator (see Section 2.3 and Figure 5).
Figure 4. The distribution of the % ecosystem service delivery (weights), for each of
provisioning, regulating/maintenance, and cultural service groups for each of the seven
Broad Habitats. All columns total 100.
7
Figure 5. The indicators used for in the calculation of the Woodland NCAI sorted by
provisioning, regulating/maintenance, and cultural service groups, and aligned with the most
relevant service within a group. Note that for many specific services there is no specific
indicator. (NB. Two regulating/maintenance indicators are not attributed to a specific service
here: Woodland Site Condition Index and Area of Certified Forest.) The latter is also used as
a cultural service indicator.
2.3 The weighting of condition indicators within ecosystem service groups and
Broad Habitats
The indicators of ‘condition’ of an ecosystem should ideally reflect the capacity of the Broad
Habitat to deliver ecosystem services. However, since the choice of condition indicators was
limited by the availability of pre-existing data5, there was no one-on-one match of an
indicator for each individual ecosystem service: some had none, while others two or more
(e.g.: Woodland: Figure 5). Thus the 100 ‘condition’ indicators were brigaded to reflect their
relevance to ecosystem service groups in each Broad Habitat.
5 Includinginformationonbirdandbutterflypopulationdata,siteconditionmonitoring,CountrysideSurvey,
pollutionrecords,andotherphysicalmeasuressuchasvolumeofpesticideuse,salmoncatchandtimber
production,etc.
8
Figure 6. The number of ‘condition’ indicators used within provisioning,
regulating/maintenance, and cultural service groups in each of the seven Broad Habitats.
Each of the ‘condition’ indicators associated with an ecosystem service group of a Broad
Habitat was assigned a relative weight, so that collectively all the indicators within that
particular ecosystem service group summed to the net weight (percentage value) of that
service group (Figure 7). Thus, in the case of Woodland, the nine indicators relevant to
regulating/maintenance services add up to 78, the percentage total for this ecosystem
service group. Similarly the six cultural service indicators add up to 17, reflecting the
percentage total for this ecosystem service group. Finally since there was only one indicator
of provisioning services, this assumed the total ecosystem service group value of 5%.
The relative weights of the indicators was based on ‘expert’ judgement of the data quality
and impact of change on ecosystem services, thus reflecting the perceived importance of a
particular indicator for its ecosystem service group within a Broad Habitat
9
Figure 7. The indicators of woodland condition were brigaded to provisioning, regulating/
maintenance, and cultural service groups. The ‘Weight’ column shows the importance
attributed to that indicator in terms of its relative contribution to the delivery of that
ecosystem service group. The weights of indicators within an ecosystem service group total
to the net weight of that particular group of ecosystem services derived from the hierarchical
method illustrated in Figures 2, 3 & 4.
10
3. THE EVALUATION OF THE CURRENT SUITE OF NCAI INDICATORS
3.1 Background
The SNH choice of ‘quality’ indicator was based partly on relevance, and partly on regularity
of collection. However, in many instances data availability was limited and ‘proxy’ indicators
have been used. The technical document outlining the method comments that “Trying to
identify indicators for environmental quality in the various Broad Habitats has highlighted the
absence of information about much of our natural environment” (SNH 2012b). Currently
there are 100 indicators of quality used in the NCAI, including: Site Condition Monitoring
data, Countryside Survey data (e.g.: no. butterfly food species in broad-leaved woodland),
pollution records and other physical measures (e.g.: volume of pesticide use), bird
population data, salmon catch data, timber production, measures of visitor use, etc.
3.2 Development of a framework for evaluation of indicators
The systematic evaluation of these 100 indicators used across the seven Broad Habitats
(ecosystems) considered in the NCAI was based around an adaptation of a set of criteria
used previously to evaluate the appropriateness of biodiversity indicators (Biodiversity
Indicators Partnership 2011). Seven criteria were selected against which the strength of
evidence supporting the use of each indicator was judged (Figure 8), generally using a three
level score (1=low to 3=high, with 0=unknown), and included:
the nature of the cause-effect relationship (0-2 only6);
whether the current use of indicator is sensitive to change in the asset;
the methodological soundness/transparency;
the data availability;
the frequency of updates;
the spatial coverage of Scotland; and
the potential for disaggregation.
Figure 8. The seven criteria used to assess the degree to which the NCAI indicators were
‘fit-for-purpose’. The levels of ‘fit’ (typically 0-3) within each of the criteria are described.
6 Other than Unknown there were only two categories 1 = Theoretical but qualitative relationship, and
2 = Quantifiable relationship between the indicator and the integrity of the asset’s condition.
11
Rather than sum the scores across the seven evaluation criteria, a ‘traffic light’ (green=fit-for-
purpose, amber=possibly fit-for-purpose, red=not fit-for-purpose) was used to give a simple
overview of the extent that the indicator was considered robust. This was done because
some criteria were considered to be more crucial than others. For example, for Woodland
the indicator ‘net annual change in carbon’ meets the top level on most of the seven criteria
(see Figure 9) and is awarded a ‘green’ light. However, in contrast, the area of certified
forest, which includes all Forestry Commission forests (currently 56% of Scotland’s forest
stock), will only reflect small changes in accreditation given to other owners of forests. Thus,
this indicator tells us nothing about the change in most of the nation’s forestry asset, hence
we scored it 1 (i.e.: Does NOT detect change within scale of decision-making) in terms of
sensitivity to change. Nor is it clear that the 20% decadal increase in area of certified forest
reflects the capacity of the asset to deliver regulating services, so the cause-effect
relationship was considered unknown (0), at best. However, although we had some
reservations about re-using the same indicator, in this case the area of certified forest may
reflect a perception by visitors of a well-managed forest, and therefore reflect a qualitative
cause-effect (1) in terms of changes in cultural services. Nonetheless it would be better to
try and ascertain if the public does make a distinction between certified and non-certified
forest. Thus, overall we awarded the area of certified forest a ‘red’ light.
Figure 9. The scores for four of the criteria and the overall ‘traffic light’ of ‘fit-for-purpose’
from the evaluation of the 16 Woodland indicators. Key: for the evaluation criteria Figure 8;
‘green’= fit-for-purpose, ‘amber’=possibly fit-for-purpose, ‘red’=not fit-for-purpose, ‘brown’=
Countryside Survey data with long intervals (8-9 years) between measures.
The ‘brown’ light was awarded to all Countryside Survey data because although these may
reflect direct measures of some aspects of the functional capacity of ecosystem assets, it’s
not useful in an annual index because each is incorporated as an average change from 1998
to 2007, and then extrapolated from 2008 onwards at the same rate of change. However,
like the ‘amber’ (possibly fit-for-purpose) traffic light, these Countryside Survey indicators
would be worthy of consideration as part of a future systematic monitoring of natural capital
assets, especially as they are easily disaggregated to smaller geographical scales.
12
The evaluation criteria were first trialled for Woodland with all four members of the research
team applying the criteria to each indicator, independently. This was done to highlight
differences that might arise from our disciplinary and research backgrounds (two plant
ecologists, one animal population ecologist and one economist), and to then try and
harmonise “rules” for the application of the criteria. Each member of the research team
reviewed three of the other six Broad Habitats, so that the set of indicators for each
ecosystem was evaluated by two people, independently. The pairings of evaluators were
designed so that each person worked with each of the other team members, and the same
pair did only one Broad Habitat. Having undertaken the evaluation separately the “pairs” met
to discuss differences and agree a common ‘traffic light’. The rationale for the agreed ‘traffic
light’ colour for each indicator in each Broad Habitat can be found in Annex 2.
3.3 Results of the evaluation of the current suite of indicators
Although the proportion of indicators viewed as ‘green’ (fit-for-purpose) was disappointingly
low (< 30% for all Broad Habitats), there were a large number viewed as ‘amber’ (possibly
fit-for-purpose) (Figure 10). Typically concerns in the ‘amber’ class were around the extent to
which changes in the indicator reflected changes in the asset (cause-effect relationship).
Where indicators were scored ‘red’ (not fit-for-purpose), this was commonly because
changes in the indicator were probably confounded by factors other than changes in the
asset (particularly common for cultural indicators), or data was not sensitive to change,
and/or had been extrapolated over periods of more than five years (e.g.: Countryside Survey
data). The latter was considered a fatal flaw for an annual NCAI index, unless the indicator
had a strong cause-effect relationship reflecting the functional capacity of the asset. In this
case it might be considered as ‘amber’, if similar data could be acquired more regularly.
Figure 10. ‘Traffic light’ pie-charts showing the proportion of indicators in each Broad Habitat
assessed as ‘green’ (fit-for-purpose), ‘amber’ (possibly fit-for-purpose), or ‘red’ (not fit-for-
purpose). In these assessments the Countryside Survey data indicators are shown as ‘red’
even though they may be particularly relevant if they were collected more regularly.
13
4. THE EFFECTS OF EXCLUDING THE ‘RED’ INDICATORS ON THE NCAI
Clearly, unless there is strong concordance between the eleven or more indicators used
within a Broad Habitat, then which ones are actually used could have an influence on
changes in the habitat specific NCAI. Consequently, we explored the effect of excluding the
‘red’ indicators (not fit-for-purpose), as a guide to the ‘sensitivity’ of the original NCAI within
each Broad Habitat (Figure 11).
Figure 11. The original NCAI for each Broad Habitat from 2000 until 2010 (from Blaney and
Fairley 2012).
4.1 The ‘sensitivity’ of the NCAI to the inclusion of indicators
In general, it seemed that excluding the ‘red’ indicators made little difference to the decadal
trends within a Broad Habitat. In Woodland, Moorland, Freshwater and Coastal habitats, not
only were the trends over time similar but the magnitude of the temporal changes were
similar regardless of whether the ‘red’ indicators were included, as in the original NCAI, or
excluded (Figure 12). Furthermore, when averaged across all Broad Habitats to give a
Scotland NCAI, the differences were never more than 2% (Annex 3).
Broad habitat Changes compared against original NC
A
i
Cropland
An increase from 2003-2007; no significant change in other years
Grassland
Significant fall from 2001-07, then a mild increase until up to 2011.
Moorland
No significant change (more or less stable)
Woodland
No significant change (more or less stable)
Freshwate
r
No significant change (more or less stable)
Greenspace
Significant lower for most of decade compared to the original NCAi
Coast
Increased (but not that much)
Figure 12. Summary of changes in the NCAI when excluding the ‘red’ indicators compared
with the original set used for each Broad Habitat (see Figure 13 and Annex 3 for details).
Broad habitat
14
However, substantial differences in the magnitude of fluctuations were seen in three Broad
Habitats (Annex 3). For example, in Grassland the decline over the first five years was more
pronounced when the ‘red’ indicators were excluded, followed by an equally more marked
recovery to 2011, than when the original set of indicators was used (Figure 13c). The
differences appeared to be associated with the inclusion/exclusion of indicators based on
Countryside Survey data: when included, and averaged across years, the effect was to
smooth out the annual changes. In contrast, in ‘Greenspace’ (urban parks, etc.), excluding
the ‘red ‘indicators reduced markedly the change in NCAI (Figure 13d). Here the strong
increase using the original indicator set appeared to be driven by measures of use (the
Omnibus survey), which may have little to do with changes in the integrity of ‘Greenspace’
per se.
In conclusion, since in some Broad Habitats the NCAI appears to be dependent upon the
indicators used, care needs to be taken in their selection, especially if changes in the NCAI
are the basis of management decisions.
Figure 13. The relative effect of excluding the ‘red’ indicators compared to the full set
(original) indicators on the NCAI for a) Woodland, b) Cropland, c) Grassland, and d)
‘Greenspace’.
15
5. THE INFLUENCE OF CHANGING THE WEIGHTINGS ON THE NCAI
5.1 Rationale
As described in Section 2, the methodology of calculating the NCAI within Broad Habitats
requires a system of weighting i) the Broad Habitat role in the delivery of ecosystem
services, ii) weighting of the importance of ecosystem services to Scotland, and iii) the
weighting of condition indicators within ecosystem groups of Broad Habitats. The
methodology uses a range of quantitative and qualitative data. Many aspects of these
weights were based on the judgement of experts, and sometimes quite small numbers of
experts, or are drawn from Omnibus surveys, all of which can raise issues about the
representativeness of the values attributed. For example, would another set of experts have
given the same weight to a particular Broad Habitat in delivering a given ecosystem service,
or attributed the same level of importance of that ecosystem service on a Scottish scale?
Also, currently there is a limited understanding of the propagation of these values after
multiplication across the various weighting matrices. Within the scope of this project it was
not possible to undertake a full simulation modelling exercise of how changing the values at
successive stages would lead to the NCAI changing. Nonetheless, it was considered
worthwhile exploring how ‘sensitive’ the NCAI was to the weighting regimes. First, to
changes in the distribution of the % ecosystem service weights for each of the provisioning,
regulating/maintenance, and cultural service groups within each Broad Habitat (see Figure
4). And, second to a redistribution of provisioning weights, in particular, a halving of the
percentage of all provisioning services per hectare attributed to Freshwater (89.1%), on the
relative importance of Broad Habitats (see Figure 2)
5.2 Approach
5.2.1 Ecosystem service group weights
We explored the ‘sensitivity’ of the NCAI to the relative weighting of the ecosystem service
groups by considering both a ‘naïve’ scenario with 33.3% split across each of provisioning,
regulating/maintenance, and cultural services, and a scenario that contrasted with the one
actually used by SNH. The exercise was undertaken for an illustrative selection of four Broad
Habitats (Cropland, Woodland, Grassland and Freshwater see Table 2). The outcome is
illustrated in Figure 14.
Table 2. The weightings used to explore the sensitivity of the NCAI in four Broad Habitats.
Weightings of Ecosystem Service groups
(Provisioning : Regulating : Cultural)
Broad
Habitat
NCAI
original
Equal Contrasting
Cropland 18:57:25 33:33:33 75:15:10
Woodland 5:78:17 33:33:33 25:30:45
Grassland
Freshwater
3:79:18
68:22:10
33:33:33
33:33:33
25:45:30
20:60:20
5.2.2 Redistribution of provisioning weights on the relative importance of Broad Habitats
In this case we reduced the original 89.1% of the total provisioning service attributed to each
hectare of Freshwater (based on the economic GVA values across all Broad Habitats - see
16
Figure 2 and Annex 1) to 45% and redistributed the other 44% equally between the other six
Broad Habitats (7.3%). We then recalculated both the total ecosystem service delivery per
hectare of each Broad Habitat and derived a new relative Broad Habitat weight (Figure 15).
5.3 Apparent ‘sensitivity’ of NCAI to the weightings
5.3.1 Ecosystem service group weights
Generally, the trends in the NCAI for the four Broad Habitats we considered appear
insensitive to changes in weightings of the ecosystem service groups (Figure 14). However,
with the exception of Grassland (Figure 14c) the original weightings (blue lines) tended to
generate the biggest temporal range over the 12 years. Interestingly our ‘contrasting’
scenario (green lines) consistently showed the most conservative temporal change over
time. In some Broad Habitats the percentage values within a year varied by as much as 8%
(range 86-94: Grassland in 2010 – Figure 14c), which could have significant implications for
managers trying to decide whether intervention is necessary.
Figure 14. The relative effect of changing the weights of the full set (original) indicators on
the NCAI for a) Cropland, b) Woodland, c) Grassland, and d) Freshwater.
5.3.2 Redistribution of provisioning weights on the relative importance of Broad Habitats
The effect of halving the apparently skewed value of the percentage of all provisioning
services in Scotland attributed to Freshwater (89.1%) on a per hectare basis, and
redistributing the rest between the other six Broad Habitats, reduced the relative importance
of Freshwater from a multiplier of 5.0 to 2.6 (compared to Cropland – the least important for
overall ecosystem services). However, the effect on the other Broad Habitats was very
17
marginal (Figure 15). Furthermore, since the area of Freshwater is comparatively small
(6.5% of Scotland), the halving of its provisioning weight has very little effect when multiplied
through to derive an aggregate Scotland-wide NCAI.
Consequently, it seems that given the final weights were derived after multiple steps of
normalization and aggregation, the influence of any one individual indicator in either the
Broad Habitat or Scotland-wide NCAI is ameliorated. This is a potential strength given that
often for provisioning services there was only one indicator available. Nonetheless we think
that since most of the weightings were based on the judgement of a few
experts/stakeholders, there is a need to revisit the assumptions influencing the relative
weightings. If some of the judgements that derived the values were viewed as contentious
then this might undermine confidence in using the NCAI.
Figure 15. The effect of halving the % provisioning services per hectare attributed to
Freshwater and redistributing the remainder equally between the other Broad Habitats. This
changes the total ecosystem services delivered and hence their weights relative to the
smallest (Cropland).
18
6. RECENT DEVELOPMENTS IN ASSESSING CHANGE IN NATURAL CAPITAL
ASSETS
6.1 Background
Around the globe, there is widespread interest in assessing the state and trends in both the
stock and quality of natural capital assets, since these underpin the sustained delivery of
ecosystem services, and hence influence economic and non-monetary well-being (MA 2005,
TEEB 2010, UK NEA 2011). However, as England’s Natural Capital Committee (NCC) has
pointed out, the range of metrics currently used as an evidence base are typically a mix of
stocks, flows, quality and benefits – which are not necessarily the appropriate metrics for
accounting for natural capital within policy frameworks aimed at sustainable development
(NCC 2013, NCC 2014). The NCC is recommending that the Office for National Statistics
(ONS) meet the challenge of developing robust methods of ecosystem accounting, through
its collaboration with the European Commission (EC), Organisation of Economic
Cooperation and Development (OECD), the United Nations (UN) and the World Bank (WB)
(UNCEEA 2013). An accounting framework enables the stock of ecosystems – ecosystem
assets – and flows from ecosystems – ecosystem services -to be defined in relation to each
other, and also in relation to other environmental, economic and social information. Since the
system of ecosystem accounting is a relatively new and emerging field of measurement, the
work is deliberately labelled “experimental” ecosystem accounting. The ONS has recently
published a description of its methods to achieve partial monetary valuation of natural capital
using the framework developed by UNCEEA (ONS 2014).
6.2 Experimental Ecosystem Accounting - The SEEA 2012
The System of Environmental-Economic Accounting 2012 – Experimental Ecosystem
Accounting (SEEA-EEA) tabulates non-monetary information about natural capital based on
measurement of changes in both ecosystem extent, typically a land cover (the Broad
Habitats in the NCAI), and the condition of that ecosystem (Broad Habitat). The product of
the extent and condition of an ecosystem provides a means of tracking changes in the
natural capital asset over an accounting period (a year in the case of the NCAI).
The SEEA-EEA recommends that changes in ecosystem condition are measured in terms of
indicators representing a suite of relevant key characteristics/ecological processes (water,
soil, vegetation, biodiversity, carbon, nutrient cycling, etc.), with the aim of providing an
overall assessment of the on-going functioning and integrity of the ecosystem asset (Figure
16). The criteria advocated for selecting appropriate indicators is that they are responsive to
changes in the functioning and integrity of the ecosystem as a whole, over the accounting
period.
As appreciated when the NCAI was developed, a fundamental problem is the limited
availability of suitable data on relevant key characteristics/ecological processes to detect
change in the functional capacity of Broad Habitats. As a result, many of the current NCAI
indicators reflect changes in the flow of ecosystem services, which may or may not reflect
the capacity of a Broad Habitat to sustain the delivery of those services. Where we were
more confident that indicators reflected the integrity of the Broad Habitat to deliver
ecosystem services, the usefulness was often compromised because of long intervals
between sampling, for example the Countryside Survey data. In this case the annual rate of
change between the 1998-2007 surveys, has been extrapolated across the period 2000 to
2011 inclusive, and therefore is effectively only able to describe long-term decadal change,
and clearly nothing is known about what actually happened after 2007. We return to these
issues when discussing the options for refinement of the NCAI, in the next section.
The SEEA-EEA approach also recommends a separate accounting table for ‘expected’
ecosystem service flows. Clearly, estimates of expectations not only require an
19
understanding of the factors determining the delivery of the current suite of ecosystem
services, but also an understanding of the impacts of changes in ecosystem condition, and
extent, on the capacity to deliver those ecosystem services in the future. In many cases this
is a considerable challenge for researchers, and the basis for on-going research
programmes, including the NERC programme Biodiversity and Ecosystem Service
Sustainability.
Characteristicsofecosystemcondition
Vegetation Biodiversity Soil Water Carbon
Woodland
LeafAreaIndex(LAI),
biomass,etc
Spp.richness,
relativeabundance
Soilorganicmatter
(SOM),groundwater
Riverflow,water
quality, fishspp.
Netcarbonbalance,
primaryproductivity
Opening condition
Improvements in
condition
Natural
regeneration
Humanactivity
Reductionsin
condition
Extraction and
harvest
Ongoing
humanactivity
Catastrophic
losses
Closingcondition
Figure 16. A schematic tabulation of the changes in condition of a Woodland ecosystem over
an accounting period (e.g.: a year) suggested under the Experimental Ecosystem
Accounting framework (UNCEEA 2013).
6.3 Natural Capital Asset Check
Recognising that there are significant data gaps for many natural capital assets and
imperfect knowledge about the uses to which those assets might be put in future, the NCC
has proposed the development of a risk register for natural capital assets which would
assess the implications of excessive depletion (or a lack of restoration) systematically
against a set of specific criteria (NCC 2014). This work, taken forward as part of the UK
National Ecosystem Assessment Follow-on (NEAFO) project, has explored methods for a
Natural Capital Asset Check (NCAC). The UK NEAFO recommends the adoption of an
NCAC that can assess how much natural capital asset we have; its condition; what it
produces; and how our decisions affect stocks, condition and flows of services over time.
20
The NCAC conceptual framework explicitly defines a Natural Capital Asset as, “The
configuration (in time, space, functionality and/or with other capital) of natural resources and
ecological processes that contributes through its existence and/or in some combination to
human welfare” (see Figure 17). Analysis of natural capital using this definition requires
economics to use a holistic approach that takes account of ecological properties, and to look
at how parts of ecosystems combine to produce services. For example, looking at intertidal
ecosystems, we can identify their role as natural capital through different property
combinations: along with populations of the fish species for which they provide nursery
habitat, they form natural capital supporting fish stocks. Together with adjacent habitats (e.g.
freshwater and sub-tidal), they form natural capital that supports recreation.
Figure 17. A schematic representation of natural capital, showing how component parts of
ecosystems are recognised as interacting in productive configurations with other types of
capital to influence well-being.
The NCAC focuses on the relationship between the productivity of an asset in terms of the
capacity to deliver ecosystem services and the integrity of the asset (Figure 18). The NCAC
approach recommends that the uncertainties in the available evidence, likelihood of
thresholds, and sustainability of the natural capital asset are classified.
21
Figure 18. A schematic representation of the relationship between the productivity of a
natural capital asset and its integrity (extent x condition), showing ‘red flags’ as warnings of
thresholds and the potential consequences of crossing them. The lack of quantification of
these flow and stock relationships is a major gap in our evidence base which compromises
decision-making.
22
7. OPTIONS FOR THE REFINEMENT OF THE NCAI
7.1 Summary of the evaluation of indicators and weighting system used in the NCAI
7.1.1 Indicators
In our view one of the most significant issues with the NCAI is the fact that very few of the
indicators truly reflect changes in ‘condition’ of a natural capital asset (the functional
capacity/integrity of a Broad Habitat), and therefore the implications for the sustained
delivery of a suite of ecosystem services are largely unknown. Unfortunately, those
indicators that do reflect functional capacity, like many of those derived from Countryside
Survey data, are only available periodically (every 8-9 years). Instead, many of the available
indicators gathered more frequently are often only ‘proxy’ measures reflecting the delivery of
a somewhat random selection of provisioning, regulating and cultural services. However,
what the NCAI currently does do is effectively aggregate within and between all Broad
Habitats to dynamically capture the trends in the flows of a bundle of ecosystem services.
Therefore, the NCAI is a useful index of ‘actual’ ecosystem service flows, rather than the
potential capacity (productivity) of natural capital assets to sustain the delivery of ecosystem
services. It this sense it is a helpful summary of one of the most complex outputs of the UK
NEA (see Figure 19).
Figure 19. The relative importance of Broad Habitats in delivering ecosystem services and
overall direction of change in service flow since 1990 (from the UK National Ecosystem
Assessment (2011)).
7.1.2 The weighting system
A major strength of the current NCAI is its basic hierarchical structure which allows one to
amalgamate measures of change in natural capital asset indicators across a range of
ecosystem services within a Broad Habitat (ecosystem) and then across Broad Habitats to
give a single value for Scotland’s Natural Capital Asset (or as suggested above, an
aggregate measure of the delivery of a bundle of ecosystem services). However, concerns
have been expressed about the rationale of the relative weights assigned to ecosystem
23
services between and within provisioning, regulating and cultural services groups, as well as,
the relative weights of Broad Habitats (Hambrey and Armstrong 2010). Our exploration of
the ‘sensitivity’ of the NCAI showed that quite radical changes in the relative weights of
ecosystem service groups may have little effect on the magnitude and trends in the index.
Nonetheless, one needs to bear in mind that the changes are measured in percentages, so
in absolute terms the differences may still be significant, and there is a risk that seemingly
small variations could have important implications, particularly if the asset was close to an
ecological threshold. Therefore, it would seem appropriate to consider re-examining the
weightings with one or more groups of ‘experts’ across a range of disciplines and
management backgrounds.
7.2 Future directions
There are essentially four areas of development work which could be undertaken to refine
the NCAI and make it more fit-for-purpose. First, more thought needs to be given to the
removal of problematic indicators. Second, alternative measures of key properties, and/or
ecological processes that better reflect the functional capacity of natural capital assets need
to be considered. Third, assuming the development of new indicators of the functional
capacity of natural capital assets, it would be useful to re-consider the need for weighting
across ecosystem service groups. Fourth, we should consider the appropriate interval for the
collection of indicators of functional capacity and the update of the NCAI.
It is proposed that these issues will be taken forward by joint working of the Natural Capital
and Science and Technology groups of the Scottish Biodiversity Strategy. Nonetheless
some preliminary thought was given to the second and fourth issues during this evaluation.
For example, in terms of the indicators of the functional capacity, this is embedded in the
System of Environmental-Economic Accounting 2012 – Experimental Ecosystem
Accounting, which suggests measuring a variety of functional characteristics of ecosystem
condition including vegetation (e.g.: primary production), soil (e.g.: soil organic matter), water
(e.g.: quality ), among others (UNCEEA 2013; see also Figure 16). Unfortunately, our review
of the current potential for additional/alternative indicators relevant to Woodland, and
therefore potentially available in any revision of the NCAI for this Broad Habitat, was not
particularly promising (see Annex 4). However, a way forward would be to focus on
establishing the best measures of the functional capacity of natural capital assets to sustain
the delivery of ecosystem services. Here there is an opportunity to review the new
Ecosystem Health Indicators (Figure 20) proposed under the 2020 Challenge for Scotland’s
Biodiversity (Scottish Government 2013). Of particular relevance are the plans for both the
Freshwater Monitoring Plan and the Soil Monitoring Action Plan under the proposed
CAMERAS Scottish Environmental Monitoring Programme. An advantage of linking the
NCAI to the Scottish Environmental Monitoring Programme and, in particular, the Ecosystem
Health Indicators, is that it should provide exactly the type of data recommended by the
Experimental Ecosystem Accounting system (UNCEEA 2013). Furthermore, such data can
be disaggregated at scales where local intervention could potentially restore degraded
natural capital assets and enhance productivity. Furthermore, comparisons of site specific
measures of both ecosystem service flow and functional capacity from multiple sites within
ecosystems (Broad Habitats), would enable the shape of the relationship between
productivity and integrity of natural capital assets (see Figure 18) to be determined, including
the existence of thresholds, as envisaged in the Natural Capital Asset Check.
Finally, there is a need to decide over what interval (annual, biennial, every five years, etc.)
the NCAI should be collated. Some indices are likely to change slowly but where there are
potential thresholds (the approach to which one needs to ‘flag’) there may be a need for a
system of spatio-temporal sampling. So while one may only return to a specific site every
five years, others might be monitored in the intervening years, and the rolling programme of
measurement should be capable of detecting general trends.
24
Indicator Source Spatial Metric Provider
a) Condition of components
1. Habitat Quality and Condition EUNIS Habitat
Maps
Habitat extent
mapped by
EUNIS category
SNH
2 Site Condition
Monitoring
Condition of
notified feature on
protected areas
SNH
3 National Forest
Inventory
Area and
condition of
woodland types
FC
4 Extent of semi Natural habitat High Nature
Value Farming
HNV
Characterisation
SRUC
5 Species Diversity Bird diversity To be determined BTO
Notified species To be determined SNH
Species diversity To be determined NBN
6 Ecological Status of Water
Bodies
Water Framework
Directive
Ecological Status SEPA
7 Soil Soil carbon Soil carbon James Hutton
Institute
b) Function
8 Fragmentation Habitat networks Indices of habitat
connectivity
SNH
9 Carbon Sequestration Soil carbon Soil carbon James Hutton
Institute
10 Soil Critical Load
Exceed modelling
of soils
Critical load
Exceed
CEH/BGS
11 Habitat Critical load
Exceedance of
habitat
Critical load
Exceedance
CEH/BGS
c) Sustainability / Resilience
12 Restoration Biodiversity
Action Recording
System (BARS)
Extent of
restoration action
SNH
13 Invasive Non Native Species NBN/GB non-
native information
portal
Extent of selected
INNS
NBN / DEFRA
14 Climate Change ClimateXChange (risk assessment
maps – to be
determined)
To be specified
15 Soil Land capability Land Capability
for Agriculture
classes
James Hutton
Institute
Soil erosion risk
maps
Soil erosion risk James Hutton
Institute
Figure 20. The candidate indicators being consider as Environmental Health Indicators as
part of the 2020 Challenge for Scotland’s Biodiversity.
25
8. REFERENCES
Blaney, R. & Fairley, R. 2012. Valuing our ecosystems: Scotland’s Natural Capital Asset
Index. In Agriculture and the Environment IX, Valuing Ecosystems: Policy, Economic and
Management Interactions. pp 8–13. www.sruc.ac.uk/download/downloads/id/1394/8-
13_fairley.
CICES. 2013. Towards a Common International Classification for Ecosystem Services
http://cices.eu/.
Hambrey, J. & Armstrong, A. 2010. Piloting a Natural Capital Asset Index. Scottish Natural
Heritage Commissioned Report No.750 http://www.snh.gov.uk/publications-data-and-
research/publications/search-the-catalogue/publication-detail/?id=2118.
MA. 2005. Millennium Ecosystem Assessment. Ecosystems and Well-being: Synthesis.
Island Press, Washington, D.C. http://www.maweb.org/en/Synthesis.aspx.
NCC. 2013. The State of Natural Capital: Towards a framework for measurement and
valuation. First report to the Economic Affairs Committee.
http://www.naturalcapitalcommittee.org/state-of-natural-capital-reports.html.
NCC. 2014. The State of Natural Capital: Restoring our Natural Assets. Second report to the
Economic Affairs Committee. http://www.naturalcapitalcommittee.org/state-of-natural-capital-
reports.html.
ONS. 2014. The UK Natural Capital – Initial and partial monetary estimates.
http://www.ons.gov.uk/ons/rel/environmental/uk-natural-capital/initial-estimates/index.html.
Scottish Government. 2013. 2020 Challenge for Scotland’s Biodiversity: A Strategy for the
conservation and enhancement of biodiversity in Scotland. ISBN 978-1-78256-586-4
http://www.scotland.gov.uk/Publications/2013/06/5538/downloads.
SNH. 2012a. Scotland’s Natural Capital Asset (NCA) Index.
http://www.snh.gov.uk/docs/B814140.pdf.
SNH. 2012b. NCA index technical document. V 1.0 12 April 2012
http://www.snh.gov.uk/docs/B1070304.pdf.
TEEB. 2010. The Economics of Ecosystems and Biodiversity. Mainstreaming the
Economics of Nature: A Synthesis of the Approach, Conclusions and Recommendations of
TEEB. http://www.teebweb.org/our-publications/teeb-study-reports/synthesis-
report/#.Ujxmnn9mOG8.
ten Brink, B. 2007. The Natural Capital Index framework (NCI). Contribution to Beyond GDP
“Virtual Indicator Expo“. http://unstats.un.org/unsd/envaccounting/seeaLES/egm/NCI_bk.pdf.
Turner, R.K. & Daily, G.C 2008. The Ecosystem Services Framework and Natural Capital
Conservation. Environmental and Resource Economics, 39: 25-35.
UK NEA. 2011a. UK National Ecosystem Assessment. Synthesis of the Key Findings.
UNEP-WCMC, Cambridge. http://uknea.unep-wcmc.org/Resources/tabid/82/Default.aspx.
UK NEA. 2011b. UK National Ecosystem Assessment. Technical Report. UNEP-WCMC,
Cambridge. http://uknea.unep-wcmc.org/Resources/tabid/82/Default.aspx.
26
UNCEEA. 2013. System of Environmental-Economic Accounting 2012 – Experimental
Ecosystem Accounting. http://unstats.un.org/unsd/envaccounting/eea_white_cover.pdf.
27
ANNEX 1: THE ECONOMIC VALUE SOURCES USED TO CALCULATE THE RELATIVE
CONTRIBUTION OF BROAD HABITATS TO THE DELIVERY OF PROVISIONING
SERVICES
Coastincludingdunes,cliffbeachandtidalmudflats:thevalueofseaweedharvestingis
estimatedat£800kayear(basedoncurrentindustrydataandaneconomicstudyfromthemid
1990s);andthevalueofhandpickedandtidalshellfishisestimatedat£1.1mayear(reviewof
literature).Materialsandornamentalproducts(sand,pebbles,driftwood,andshells)are
estimatedtobeworth£100kayear.Thisgivesavalueof£2m/year.
Croplandincludingarableandintensivegrass:avalueoffoodisderivedbyconsideringthe
relevantagriculturelandusedatareportedinScottishGovernmentstatistics.However,notallof
the£792mGVAisusedsince22%ispigs,poultry,etc.(which,duetothenatureofproduction,
arehumancapitalintensiveandhaveminimalrelianceuponScottishecosystems).Ofthis
adjustedGVAfigure,49%isbasedonthevalueofoutputunderactivityheadingscropsanddairy,
andisincludedinthisbroadhabitat,alongwithonethirdofthevalueofunimprovedgrassland
livestockoutputtotakeaccountoflivestockfinishingonimprovedgrasslandsandfeedtransfers
fromcropland.Thevalueofpollinationservicesequivalentto£41m(adjustedUKNEAfigure)are
deductedasthisvalueisassignedunderadifferentecosystemserviceheading.Thisgivesafinal
valueof£300m/year.
Grasslandincludingroughgrazingandseminatural:theagriculturalGVAisusedaboveasfor
croplandandintensivegrass,with29%underactivityheadingscattleandsheep,whichisreduced
totakeaccountofvaluesassignedtocroplandandintensivegrasslands(livestockfinishingand
feed)andmoorland(grazing).Thisgivesavalueofalmost£80m/year.
Moorlandincludingmontane,peatland&bog:onesixthofthevalueofunimprovedgrassland
livestockoutput(£19m)isusedtotakeaccountoflivestockgrazingonmoorlands,alongwith
£1mestimatedfrompeatextraction(UKNationalEcosystemAssessmentvaluereducedby50%
toestimateGVA),and£1mfromwildvenison(UKNEAaveragebetween20022009of£3mtotal
wildvenisonwholesalevalue,reducedby50%toestimateGVA;twothirdsassignedtomoorland
onethirdtowoodlandtoaccountfordeermovementsbetweenthesehabitats).Thenetvalueof
thishabitatforhoneyproductionisestimatedat£1m,givingatotalvalueof£22m/year.
Woodlandincludingcommercialforestry:£106mGVA(from‘Theeconomicandsocial
contributionofforestryforpeopleinScotland’‐researchnoteSep2008)isused;addedtothisis
£5mfromChristmastreeproduction,£0.4mfromwoodlandmosscollection,and£0.04million
fromwildmushroomandfruitharvesting,aswellas£0.5mfromwildvenison(varioussources
seealsoheathermoorland).Thisgivesavalueofapprox£110m/year.
Freshwaterincludinglochs,riversandfen/mirewetland:awatervalueisderivedfromScottish
Water’sgrosssurplus(i.e.revenueminuscostofsales2010,takenfromtheconsolidatedincome
statementintheannualreport)of£450m.Afurtherdeductionof£20m(fromliteraturereviews)
ismadetotakeaccountofwaterqualityfunctionsassignedtootherbroadhabitats.Addvalueof
watertakendirectlyfromenvironmentviaboreholes,springsetc.(agriculture,distilling,and
paperindustriesonly)of£90m.Thisgivesavalueof£520m/year.Freshwaterfishingisassigned
toculturalservicesratherthanprovisioningservices,astheprimeintentionisrecreational.
Greenspace:thevalueisbasedonproductioningardensandallotments.Vegetableseedsales
acrosstheUKin2010were£60m,withScotlandassigned1/12thofthisbasedonpopulation,and
thus£5m.Itisassumedthattheaveragevalueofproductionissixtimesthecostofseeds,£30m.
Labourandequipmentcosts(i.e.depreciationvalueofspades,wateringcans,etc.)arededucted,
estimatedat£20m(labourat£17mandequipmentdepreciationat£3mayear).Theseedcostis
28
alsodeducted.Afurtherdeductionof10%ofvalueismadeforpollinationservices.Thisgivesa
roundedvalueof£5m/year.
29
ANNEX 2: THE RATIONALE FOR AGREEING THE ‘TRAFFIC LIGHTS’ FOR THE
INDICATORS IN EACH BROAD HABITAT
Croplands‐finalcolourcoding Finalcomments
Potentialforprovisioningservices‐
Grazing potential(areaofseededgrassunder5yearsold) Grazingpotentialasanindicatorseemsok.Buttheproblemisthewayitismeasured.Because,thege neral
formulafortheNCAiis:quantityxquality,wherethe'quantity'isreprese nted bytheareaand'quality'bythe
capacity ofBroadHabit attodeliverES.How eve r,forthisparticularindicator,qualityisalsoexpressedby'area',
whcihmakesthemeasurementofthisindicatorinconsistentwiththeunderlyingformulaoftheNCAindex.
Arablelandcapability(5yearyieldplussoilfertilityscore) Relatestotheserviceandnottheassest;unsustainableagriculturalpracticesmayproducehighyieldsbut
erodethecapi tal(soilqualityandstability).Amoredirectindicatoroftheassetisrequirede.g.asoilhealth
indicator(pH,soilorganiccarbon,comp actio n)
Potentialforregulating&maintenanceservices‐
Barefallow/setasidearea No tice able change inareasofsetasidesince2007duetoCAPpolicychangewhereitnolongerarequirementto
setapercentageoflandreceive theSFP.Itisstillaproxyindicator.
Fertiliseruse(inverse) Fromtherepor twherethedatawasdrawnitimpliesthatitisintonnesofnutrientsusedperyearratherthan
anapplicationrateperha.Itneedstobeexpressedasanaverage fertiliserapplicationrate(perhectare)e.g.
increaseinfertiliserusecouldmeanthattheareaofarablehasincreased,ratherthanincreasedintensityof
use
Pesticideuse(inverse) Detoxificationdemandswillbedirectlyrelate d
Farmlandbirdindex Limitedsamplinginhighlandsandwestcoast, tenuouslinktoregul atin g‐pollination(foodsources).Possibly
betterasacultu ralserviceindicator‐thiswouldals oavoiddouble ‐accounting
Hedge sspeciesrichne ss BasedonCountrysidesurveydatawhichiscolle cted every10years‐suitabilityforanannualindexis
questionable.Somewhatteniouslinkstoregulat ingservice?
SpeciesrichnessarablelandThese appeartogoodindicators,butthefrequencyofcountrys ide surveylimiteditsuseforannualindex.So,
darkamber!
Speciesrichnessimprovedgrass Theseappeartogoodindicators,butthefrequencyofcountrysi de surveylimiteditsuseforannualindex.So,
darkamber!May be forbratiowouldbeabetterindicatorforpollinators.
Agrienvironmentarea Theassumptionherethattheagrienvi.schemesimprovebiodiversity,landscape,etc.theevidenceisnot
conclu siv e.
Butterflies‐generalists Butterfliesarenotkeypollinatorsforcropspecies.Datafromallspecie sinScotlandisnotsufficienttoprovide
afullpicture.May be betterasacult uralindi cator.Becarefulofdouble accounti ng.
Mix e dfarming Mixedfarmingcanbeanycombinationofarablelivestockagriculture. Itdoesn'tshowtheintensityoffarming
orfarmingmanagementsystem.Soitisn'tanassetattribute.
Soilcarbon BasedonCountrysidesurveydatawhichiscoll ecte devery10years‐suitabilityforanannualindexis
questionable.
Potentialforculturalservices‐
Hedge sinthelandscape(totallengthofhedgrows) Thisseemsagoodcultur alservi ceindicator,butdataisbasedonCountrysideSurvey;doesn'tshowannual
change s.So,darkamber!
Lowlan dboundarywallsinlandscape(totalwalllength) AgainaCountrysidesurveydataset,soinfrquentcoll ecti onanissue
Butterfliesavailabilitytowatch‐generalists DatafromallspeciesinScotlandisnotsufficienttoprovideafullpicture.Improvedsamplingcoverage would
help.Gene ral trendstablebutcover supsig.declinesinsomespecies
Birdsavailabilitytowatch:farmlandbirdindex Generallyacceptedasarobustmeasure ofarablecrop land s.
Farmanimals:no.livestockinnonLFA(cattle&sheep) Thelinkbetweennumberoflivestockandcult uralserviceprovisionisnotknown.Howmanycowsistoomany?
Ortoolittle ?Andwhataboutifallthecows wereonIsla
y
butnowwhereelse?
Amountoflandscapecovered inpolytunnels(inverse) Thisindicatorneedstobebackedupwithevidenceonthepublicdislikeofpolytunnelsinthelandscape.
Figure A1. The final ‘traffic light’ for Cropland indicators.
30
Grasslands‐Finalcolourcoding Combinedcomments
Potential for provi sioning services -
Grazing - total no. Livestock Unit s in the LFA
Hardtoseehowthislinkstograzingoutputsfromgrasslandingeneral.Be ttermetricsmaybeavail ableintheagricu ltural
censusdata.Hardtocaptureissuessuchasovergrazing,becauseinthisconte xtagreaternumberoflivestockisconside red
ashavingapositiveeffectontheindex.
Potential for r egulating & maintenance services -
Level of cattl e grazing (t otal no. in the LFA)
Thelinkisunclearbutitmightbetoclimateregul atio n,withcattlenumberslikelytobelinkedtosomeextenttoGHG
emmissi onsfromfarming,butagainwhyuseonlylivestockdatafromLFA?Inaddition howdoesthenegativeeffectofthis
factorheretradeoffagainstitspositive effectontheindicatorthroughprovisioningservices,above?
Farmland & Upland birds (com bined index )
Notveryclearthatthesetwomeasuresofbirdabundancearereallyrelatedtodeliveryofregul ating services.Notleastthe
linktograsslandassetssee msveryweak‐thisindexcombi ne sbirdsfromawidevarietyofhabitats,onlysomeofwhichare
gasslands.inadditi onthelinkfrombiodiversity(especiallyhightrophicleveldiversity) andregulati ngfunctionscouldbe
quiteweak.Thismaybeabetterindicatorofculturalservices.
Butterflies (specialists)
Approachbywhichsitedatahavebeenagrgegate dtoScotlandlevelisnotclear. Basedonvolunteereffortinmanycases,so
presumablythereisspatialvariabilityinrecordereffort.Finally,notclearthatbutterlfy numbersrefl ectoverallsystem
capacity forpollination,sincemanyotherinsectsmaybeinvolved,andtheirnumbersmight/mightnotbeassociatedwith
butterflynumbers.
Area of hay meadow
Note‐shouldbeareaofgrasscutforhay,whichissubtlydifferent.Unde rl yi ng assumpti onisthathaymeadowspromote
pollinatinginsects‐notabadassumption.
Level of sheep grazi ng in nort h west (n o. ewes)
Doesn 'tseemrel evant toanationalscaleindicator.Uncle arwhyitisnotincludedunderprovisioning.
Neutral gras sland s pecies ric hness
Worksontheassu mpti onthathighNloadsetc.wouldreducespecie srichn ess, whichinturnwouldalternutrie ntcycling
processes.SourcedataisCountrysideSurvey,sohasgoodspatialbutpoortemporalresolu tion.Ma jo rproblemistemporal
resol utionand extr apolat ionbe tweentime points
Festuca ovina+ Galium saxatile in acid grassland
Hardtoseewhattheabundanceofthisspeciesinaparticulargrasslandtypetellsyouaboutregulat ingservi cesingrasslands
overall.IsalsoCountrysideSurveydata.
Grassland Si te Condition (favourable condition)
Limit ingfactoristheextenttowhichsitesincludedinSCMarerepresentative ofgrasslandsitesingeneral.Normallythey
areprotectedareasandsomightbeunrepresentativ e.
Potential for cultural services -
Number of working occupiers in t he LFA
Impossibletoassesswhetherincreasingordecreasingvaluesforthismetricwouldbegoodorbadforcultural services.In
additi onthedataisagainonlyforLFA.
Farmland & Upland birds (com bined index )
Betterherethanunderregul atin gservices,altho ughthelinktospecificallygrasslandassetsremai nsweak‐th isindex
combi nesbirdsfromawidevarietyofhabitats,onlysomeofwhicharegrasslands,henceanambe rratherthangreenrating .
Neutral grassland s pecies ric hness t arget plots
SourcedataisCountrysideSurvey,sohasgoodspatialbutpoortemporalresol utio n.Dataavailabilitydependsonparticular
reque sts,e.g.theneedforfinespatialscaleres olu tion ondatapoints.Major problemistemporalreso luti onand
extrapolationbetweentimepoin ts;alsotheissueofrepresentativenessforgrasslandsoverall.
Area of hay meadow
Note‐shouldbeareaofgrasscutforhay,whichissubtlydifferentandperhapsmorerele vant herethanunderregulatin g
services,i.e.genuinehaymeadowmighthavehighcul tural valuethannonhaygrasslandscutforhay.Nolinkgiven,butdata
comefromDecemb eragricul turalcensus.Scoringsaremadeonthisbasis.
Figure A2. The final ‘traffic light’ for Grassland indicators.
Moorland‐finalcolourcoding Comments
Potential for provisioning services
Gra zin gpotential (no.moorlandewes &d eerforveni son)
Number ofewes onthehillislargelyanartefactofchangesinCAPandsocioeconomicfactor s.Deer
populati onsareincreasingduetoamelioratingwintercl imateand/orreductionsinsheep numbers.
Potential for regulating & maintenance services
Brack en encroachm ent (inverse)
CountrysideSurvey‐soanextrapolationoftheaverageoftheannual tren dbetweenthelasttwo
surveys(1998‐2007)
Upl an dbi rdindex
Annualval uesbutdoesitreflectregulating/maintenancesurveys?Betterasapotential culturalservice
indi cator.
Heathspeciesrichness
Bogmoi s tur escore
CountrysideSurvey‐soanextrapolationoftheannualtr end betweenthelasttwosurveys(1998‐
2007)
Boggra ss :for bratio(invers e)
CountrysideSurvey‐soanextrapolationoftheannualtr end betweenthelasttwosurveys(1998‐
2007)
Heathbu tterfl yfood
CountrysideSurvey‐soanextrapolationoftheannualtr end betweenthelasttwosurveys(1998‐
2007)
Soil carbonconcentrationinbogs
CountrysideSurvey‐soanextrapolationoftheannualtr end betweenthelasttwosurveys(1998‐
2007)
Upl an dSi teCondition(favourab le) Onl yconductedin2005,2010&2011
Potential for cultural services
Bir dsofpreyavailableforwatching‐persecution(inverse) Da taisveryspecificandofquestiona bleaccuaracy.Seemsunnecessarygi venth eUpl an dbi rdindex
Otherbirds availableforwatching‐upla ndbirdi ndex Probablyagoodmeas u reofth eattr a cti ven ess /r ecr ea tio npotential
Bir dsavailableforsportshooting‐redgrous enumbers
Dataisveryspecificapplyi ngtoami no ri ty ,andhighlyvari abl ebetweenyears duetospringweather .
Seemsunnecessa rygi ventheUp la nd bir dindex
Deeravailableforsportshooting‐numberofdeershot
Deershotdoesn'treflecttheherdsizeorthecarryingcapacity.Givenhinds areshotbylocalstalkersit
mayha veli ttl etodowi thnumbersofclients
Landscape - brac ken encroac hment (i nverse)
CountrysideSurvey‐soanextrapolationoftheannualtr end betweenthelasttwosurveys(1998‐
2007).Als o,isth ereanyevi den c etha tpeopleperceivebrackenasaproblemandsignofdegradation
Landsca pe‐impactofwindfarms Datafr omjust2002and2008
Figure A3. The final ‘traffic light’ for Moorland indicators.
31
Freshwater‐Finalcolourcoding Combinedcomments
Potentialforprovisioningservices‐
Availablestockofwater
Doesn 'tmeasuresupplyofwaterjustprecipitationasit'sawatercycle/supportingservice.Basedonthreeyear
averageddata.
Rawwaterquality:nitratesinriversatsafelevel Aregulati ngservice.Confusionoverdata‐justnitratesorotherwaterqualityindices?
Potentialforregulati ng&maintenanceservices‐
Fen,marsh,swampspeciesrichness
Basedoncountrysidesurveydata(every10years)‐questionableuseforanannualindex.Notsurespecies
richnessisagoodproxyforregul atin gservicesoffreshwaterasthecausal linksarenotknown.
Streamsidespeciesrichness
Basedoncountrysidesurveydata(every10years)‐questionableuseforanannualindex.Notsurespecies
richnessisagoodproxyforregul atin gservicesoffreshwaterasthecausal linksarenotknown.
Pooledheadwaterplantspeciesri chne ss
Basedoncountrysidesurveydata(every10years)‐questionableuseforanannualindex.Notsurespecies
richnessisagoodproxyforregul atin gservicesoffreshwaterasthecausal linksarenotknown.
Polluti on:orthophosphateatsafelevel Goodmeasureofdetoxification
Rawwaterabstractions(inverse)
Theeffectofabstractiononecosystemsisnotfullyknown.Datanotavailab leforviewing
Nonnativeinvasivespecies(inverse)
INNSonlyrecent lyestablishe d‐unsurehowdatawillbecomp il edtoformanindicator.Currentindexis
invariantasitis.Goin gforwardmaybepossibletouseasanindicator.
Rive rwaterquality(%unpollutedsites) Isthisnotthesamedataasusedforwaterqualityindices?Possibleduplication?Doubleaccounting?
FreshwaterSiteCondition(favourablecondition) Somewhatselectiveinitschoiceoforiginalsite s(betterqualityoneswithqualifyingfeatures)
Potentialforculturalservices‐
Numberofponds Unsurewhichaspectofcultu ralservicesitrepre sent s.CSdata‐every10yearswhichexplainslineartrend.
Headw ate rstreamshabitatqualityassessment(HQA) Unsureofitsrelationtocu ltur alservices.Suspi ciouslineartrends.CSsurveydata.
Otteravailab il itytowatch:population
Only2datapoints(greaterthan5years).Notsurecultu ralservi cesassetsshouldbebasedononemammal
whichisknowntoberecover ingbutelusive?
Salmonavailabil itytowatch/fish:populationest
fromcatch
Integritymeasureofsalmonstockbutnotoffreshwater.Couldbeimprovedbyusingfishcountdatarather
thanrodcatchdata.
Figure A4. The final ‘traffic light’ for Freshwater indicators.
GREENSPACE‐FINALCOLOURCODING COMBINEDCOMMENTS
Ability to provide provisioning services
Landproductivity‐garden /all otment foodproduction
Dataisnotavailable onannualbasis.SeemstobebasedonOmnibussurveyof%adultsproducing
someoftheirownfoodbutnomeasureofquantitites.
Ability to provide regulating & ma intena nce services
Pollution‐urbanbackgroundNO2deposition
Ifitisnonroadsid emaybeOK.Butifroadsideasseemslikelyfromdatabasethenisprobablyapoor
refl ecti onoftheassetbecausecarshavebecomemorefuelefficient.Also,hasNO2depositioninnon
greenurbanareasbeenfactored?
LocalAuthorityareascove redbygreenspacestrategies
Looksverydodgygivenex ponetialris einlasttwoyears.Notclea ritrefle ctsregu lati ngservices
capaci ty .Dataisnotonannualbasis,butpotentialtohavedataonannualbasis.
Urban bird(gardenbirds)abundance
Notaregulati ngservicenoranindexofmainten ancebutexcludeheresincealso acultural service.
Also,itisrestri cted toSouthScotland.
Ability to provide cultural services
A place for children to pl ay
Provides a spa ce to rel ax
Att ract ive green areas
A plac e to s ee nature
Q
ua
lit
y re
d
uce
d
i
n
l
as
t
5
years
Birdsavai labl etowatch‐gardenbirds(urban) Goodindicator,butappearsunderregulati ng/ main tenan ceservicestoo.
Landscap e‐amountofabandonedgreenspace(inverse) Concernthatlandpreviouslyvacantislosttodevelopment
Accessibility‐visitstourbanparks
Itdoesn'tnecessairlyrefle ctthechang esinasset;itmaybeduetoweatherconditions.This tellsus
aboutdemandwhichmayhavenothingtodowithintegrityofstock.
Thes eindicatorstoacertain degreeshowflowsofecosystemservicesfromthegreenspace.Howeve r,
theyarehighl ycorrelatedandbasedonperceptionsofindividualsintervewedatapointintime.No
evidencetorelate theperceptionchan getoelementsoftheasset.Alltheseomnibussurveystellsyou
aboutperceptionsofsupplywhataretheyreallymeasurin gaboutthestock?
Figure A5. The final ‘traffic light’ for Greenspace indicators.
32
Coasts‐Finalcolourcoding Combinedcomments
Potentialforprovisioningservices‐
Stock of shellfish for picking (cockle biomass & quality)
Fisheryclo sed in2011andspatialcove rage islimitedtoSolwayfirth
Potentialforregulati ng&maintenanceservices
Bathingwaterquality(guideline ) Whynotusemandatorydata?
Winte rin gwaterbirdindex Causallinksbetweenwaterbirdsandregulati ngservicestooteni ousThe re aretoomanyfactorsgoverni ngthe
numbersofbreedingbirdsoncoasts, waterqualitybeingonlyoneofthe m.
Nonnativeinvasivespecies(inve rse) Furtherclarificati onofmethodology/datatobeusedisrequired:itmightbepossibletodisaggregatethedatabut
withlimitationswithrespectotvariablerecorde reffort.Like lytobeincreasingnumberofdatasetsrelev antto
thistype ofindicator.
CoastalSiteCondition(favourablecondition) LimitingfactoristheextenttowhichsitesincludedinSCMarerepresentativeofcoastalsitesingeneral .Normally
theyare protectedareasandsomightbeunrepresentative.Inadditiontherearecurren tly onlytwodatapoints‐
2005and2010‐butSCMisswitchingtoarollingprogramme.
Erosio n(sealevelrise ) Onl ytwotimepoints andsealevelrisemaynotbetheonlyfactorforcoastal erosion.
Potentialforculturalservices‐
Bathingwaterquality(mandatory) Goodqualitytransparentmethodologycoll ecte dannually
Coastalbirds Issuewiththeintegrityofsomeofthedatae.g.eagledata;decisionrerelati vewei ghtingofdifferentdatatypes
isalsounclear.
Beachlitte rcount(inverse) Furtherexplorationofthemethodologyisrequi redtoensureconsistencybetweensurveys.
MCS beachqualitymeasure BasedinSEPAdataandsoaduplicateindicator.Theydoincludeanadditionalcate gory ‐recommended‐whi chis
ausefuladdition.
Use ofmarkedcoastalpaths Thisismoreofaserviceorusageindicatorratherthanassest.Mayb esomethinglikethenumberofmilesof
accessi ble coast li ne, orstateofcoastalfootpathswouldbemoreappropriate.
Figure A6. The final ‘traffic light’ for Coastal indicators.
33
ANNEX 3: COMPARISON OF THE NCAI WITH AND WITHOUT THE ‘RED’ INDICATORS
Broad Habitat 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
Cropland original 100 99 100 103 104 107 108 105 99 100 100 101
Excl. red indicators 100 101 102 106 106 112 113 109 99 101 99 101
Grassland original 100 94 90 88 87 88 91 92 94 94 94 91
Excl. red indicators 99 90 80 80 76 81 90 91 95 99 104 101
Moorland original 100 100 99 97 96 97 96 95 96 95 95 94
Excl. red indicators 100 100 100 96 95 96 95 95 97 96 95 96
Woodland original 100 101 103 105 106 105 105 104 104 103 100 102
Excl. red indicators 100 101 104 106 109 107 107 105 105 104 99 100
Freshwater original 100 97 98 95 102 104 108 109 111 112 105 109
Excl. red indicators 99 96 98 94 103 105 109 111 112 113 106 110
Greenspace original 100 101 105 106 107 110 112 115 119 118 115 115
Excl. red indicators 100 96 104 103 101 100 101 102 104 105 105 110
Coast original 100 104 106 119 120 120 121 115 115 116 112 116
Excl. red indicators 100 104 106 121 121 122 123 116 117 120 116 119
Scotland NCAI (org) 100 99 99 98 98 99 100 99 99 99 98 98
Excl. red indicators 100 98 97 97 97 99 100 100 100 100 99 100
Figure A7. The NCAI for each Broad Habitat, and also aggregated for Scotland, comparing
the original values calculated using all the indicators and then excluding the ‘red’ indicators
for each year 2000 to 2011.
34
ANNEX 4: THE POTENTIAL FOR ADDITIONAL/ALTERNATIVE INDICATORS IN A
REVISION OF THE NCAI
In this section we look at the potential for the use of additional and/or alternative indicators in
the NCAI, in particular for those assets for which there are currently either no, limited or poor
indicators. To explore this potential we focus primarily on indicators relating to woodland
habitats. Also, we consider some additional inputs for urban (green-space) and enclosed
farmland (cropland in the NCAI). However, as we will see it is likely that these findings will be
relevant to the other Broad Habitats.
A3.1 The Ecosystem Services Indicator database
The Ecosystem Service Indicator (ESI) database is one of the identified outputs of the
Ecosystem Services Theme of the Scottish Government Research Programme,
Environmental Change (2011-2016). Like the NCAI, the database is organised according to
Broad Habitats. For example, ‘Woodlands’ in the ESI database comprises broadleaved,
mixed and yew woodlands as well as coniferous woodland. In addition, for policy relevance,
fields within the database relate each indicator to a broad policy objective within the Scottish
Land Use Strategy (Scottish Government, 2011) such as, for example, a ‘low carbon
economy’ or ‘sustainable water management’. Although the main purpose of the ESI
database is to review and identify potential ecosystem service indicators, with a focus on
those which relate directly to goods and benefits, there are synergies with the purpose of the
NCAI, in that, through the ecosystem services cascade (Haines-Young and Potschin, 2010,
see Figure A8 below), it attempts to identify indicators of ecosystem function. These
indicators of ecosystem function relate to the integrity and quality (condition) of the
ecosystem or, in other words, natural capital. It is noteworthy that the ESI database includes
indicators across a range of scales, from individual fields/plots to regional and national
scales.
Figure A8. A simplified framework of relationships between ecosystem services and benefits.
Adapted from Haines-Young and Potschin, 2010.
35
A3.2 Potential woodland/ urban greenspace tree indicators
In reviewing the ESI database for woodlands and filtering out potential indicators, only those
indicators which directly assessed the condition (quality) or extent (quantity) of the natural
asset and scored highly against the criteria used in the indicator evaluation framework were
selected (e.g. only those that showed a cause-effect relationship, or where data were
collected over a range of spatial scales etc. see chapter 2).
A review of the database revealed five potential indicators, which are listed in Table A1
along with information on monitoring frequency, data sources, comments and traffic light.
Two of the woodland indicators scored ‘green’ traffic lights, despite monitoring frequencies of
every five years. First, the number of households (only settlements > 500 people) with visible
woodlands, within both 1 km and 300 metres, is an indicator identified by Edwards et al.
(2009) in a report on the social and environmental benefits of woodlands to Scotland. The
indicator uses the data from the NFI and combines it with a “view shed” GIS analysis to
calculate how many households had a view of woodland within both a 1 km and 300 m
radius of their house. This indicator could be further refined as currently it does not
distinguish between the different types of woodland, for example, coniferous plantations or
native broadleaved woodlands, that are visible from settlements. National surveys (e.g. FC
Public Opinion Surveys), choice experiments (Willis et al., 2003) and evidence from local
case-studies indicate that people have a preference (in terms of landscape aesthetics) for
native, mixed species and open woodlands. This could be seen as evidence for quality
attributes that contribute to the natural asset of woodland.
The second indicator that scored a ‘green’ traffic light was the area of broadleaved/native
woodlands, mixed woodland and open space available from the NFI. This is similar to the
existing NCAI indicator from Countryside Survey (CS) data - the area amount of broadleaved
woodland in Scotland. However, the NFI is collected on a rolling basis every 5 years, rather
than the 8-9 years of CS data, and also uses additional condition/quality attributes, such as
native Scots pinewood, openness of woodland and mixed species woodland.
Three of the indicators, amount of riparian woodland, woodland recreation opportunities, and
visitor use of woodlands, all scored an ‘amber’ traffic light. The amount of riparian woodland
is a very good indicator of the potential of natural capital to attenuate flood risk and improve
water quality. However, there needs to be further exploration of the quality and frequency of
the data collected by the Native Woodland Survey of Scotland (NWSS) and whether NFI
data will distinguish riparian woodlands separately from broadleaved woodlands.
The other two ‘amber’ indicators related to the supply and demand for recreation. First, the
supply of woodland recreation opportunities is based on a biennial public opinion survey by
the Forestry Commission. With this indicator, it is difficult to discern between, or draw links,
to the quality (condition) of the natural asset and hence ranked values of performance. For
example, particular woodland may score highly in terms of recreation opportunities, but this
may not reflect the quality of the woodland asset, representing instead the quality of
footpaths or the children’s play park, both infrastructure assets. This complication of
interactions between natural capital and other types of capital (built infra-structure, human)
has been recognised and explicitly incorporated into the conceptual framework for
developing a Natural Capital Asset Check by the UK National Ecosystem Assessment
Follow on project (Dickie et al. 2013; see also Figure 18 earlier in this report).
36
Table A1 Potential woodland indicators from the ESI database
Indicator Service Frequency Data
sources
Notes Traffic
light
Amount of riparian
woodland
Flood
attenuation/Water
Quality
5 years NFI, NWSS
Will NFI have a
separate report for
riparian woodlands?
How often is NWSS
planned? Uncertainty
regarding frequency of
systematic monitoring.
Woodland
recreation
opportunities (Very
good, Good, Fair,
Poor, Very poor, No
experience/Don't
know)
Recreation
opportunities
2 years Public
Opinion
Survey (FC
)
Could indicate
combined asset rather
than natural asset.
Does not distinguish
between local and
Scotland wide
woodlands.
No. of households
(settlements > 500
people) with visible
woodland
Landscape
aesthetics
5 years NFI with
GIS view
shed
analysis
(FR)
Requirement of FR to
conduct view shed
analysis. No
distinction between
the type of woodland
e.g. conifer plantation
of native broadleaf
Amount of
broadleaved/native
woodlands, mixed
woodland and open
space
Aesthetics 5 years NFI, NWSS
No. of visits to
Scottish woodlands,
distance travelled to
woodland, duration
of visit
Recreation Annual The Scottish
Recreation
Survey
The last year of the
survey is 2013. No. of
visits is a proxy
measure of asset as
asset may deteriorate
with increased usage
(erosion, dog fouling,
litter)
Table A2 Potential tree indicator for green space from the ESI database
Indicator Service Frequency Data
sources
Notes Traffic
light
No. of street
trees
Air pollution ? ? Could something like the
English ‘Trees in Town II’
survey be commissioned? Or
could data from councils be
used? Could the Urban Tree
Survey run by the Natural
History museum provide future
data?
Second, the demand for recreation, as indicated by the number of visits to a woodland or distance
travelled, may reflect more about the proximity of urban concentrations of people, than the
condition of the natural asset. Furthermore, an increase in the number of visits to woodland may
actually lead to the deterioration of the condition of the asset, by means of erosion, litter or dog
fouling. Therefore caution must be used (hence the amber traffic light score) in the application of
these indirect indicators.
37
Although perhaps more commonly associated with green space, or urban areas, than woodlands
per se, the number of street trees was identified as an additional metric in the current NCAI
indicator portfolio (Table A2). While this potential indicator was identified from the ESI database,
the data is based on the Trees in Town II (Britt & Johnston, 2008) survey which is restricted to
England, and the frequency of future monitoring is uncertain. The potential for developing a similar
indicator in Scotland would need further exploration to see whether current data sources exist
(e.g.: local authority registers), or whether fit-for-purpose surveys could be commissioned to fill the
substantial gap in NCAI indicators in our cities and urban spaces.
6.3 The search for a natural capital asset indicator for soils
From the evaluation of indicators for enclosed farmland (cropland) and subsequent discussions
with soil science experts at the James Hutton Institute (Willie Towers, Helaina Black and Jason
Owen) it became apparent that a suitable indicator to measure the critical natural asset of our soils
was missing from the NCAI. The key attributes of arable soils that indicate ‘asset quality’, or in
other terms, soil health, would be soil pH, soil organic matter, aggregate stability and compaction.
For example, arable crops will only grow in a very narrow pH range (5.9-6.4), while the level of soil
organic matter is related to how well soil holds and filters water, an important regulating service
with regards to flood risk attenuation and water quality (Towers, pers. comm., ).
A review of the ESI database identified a number of potential indicators for monitoring soil health in
arable ecosystems (see Table A3). However, on closer inspection and upon applying the
evaluation criteria, they all score poorly, either in terms of monitoring frequency, spatial coverage
or data availability. This evaluation concurs with the State of Scotland’s Soil report (Dobbie,
Bruneau & Towers 2011) which, despite identifying 31 different monitoring, surveillance and data
sources, recommended that there needed to be a concerted effort to tackle the lack of systematic
spatio-temporal soil data.
6.4 Further challenges
A review of the ESI database for woodlands identified a number of potential indicators that could
be used to enhance the existing indicators used in the NCAI. However, as indicated by those with
an ‘amber’ traffic light scoring there is still ‘room for improvement’, especially when considering
complex combined assets commonly found in green space. From our findings in the woodland
habitat it is anticipated that there may be additional opportunities for improving indicators, and for
gap filling in the other Broad Habitats.
However, as the current lack of suitable indicators for soil quality reflects, along with the large
proportion of indicators in the NCAI evaluation that scored a red traffic light, there still remains a
significant challenge in compiling a suite of indicators that directly assess the quality/condition of
Scotland’s natural assets, and that have the spatial and temporal coverage necessary for an
annual index of natural capital. The recently established CAMERAs environmental monitoring
network, through its monitoring action plans (MAPs) such as the soil MAP, may in the next few
years deliver more fit-for-purpose indicators of natural capital. However, this can be guaranteed
only if these plans address the monitoring and data synthesis requirements for the NCAI as well. In
addition, with increased citizen science and web-based tools, such as BeeWatch and Urban Tree
Survey, there may be further monitoring and data collection opportunities to capitalise on, but only
if they prove to be methodologically robust and fulfil the evaluation criteria for a national natural
capital asset.
38
Table A3. Potential indicators for assessing the natural capita of soils for enclosed
farming (cropland)
Indicator Service Frequency Data
sources
Notes Traffic
light
Soil health
indicator: pH
(5.9-6.4), soil
organic
carbon,
compaction,
aggregate
stability
Flood
attenuation/Water
Quality,
Provisioning -crops
25 years JHI- NSIS
The National Soil
Inventory of Scotland is
based on two data
monitoring points,
1978-1987 and 2007-
2010. Although
comprehensive it does
not provide the
monitoring frequency
required for an annual
index
Soil
compliance
monitoring;
pH, N, P, K,
Carbon, toxic
elements,
microbial
carbon
biomass,
earthworms
Flood
attenuation/Water
Quality,
Provisioning -crops
Every year SEPA Limited sampling in
Scotland (e.g. 22 farms
in 2010) and a bias to
sites which apply
waste; sewage sludge,
distillery waste
(potential
contamination)
GAEC Soil
Protection
Reviews: – soil
organic matter,
erosion risk
Flood
attenuation/Water
Quality,
Provisioning -crops
Every year Self-
reported
by farmers
Farmers have to
complete an annual
Soil Protection Review
as part of cross
compliance for single
farm payment. Unsure
how self-reported
monitoring can be
utilised as a data
source?
Soil carbon Flood
attenuation/Water
Quality,
Provisioning -crops
8-10 years CS Data collected every 8-
10 years
References
Britt, C. and Johnston, M. 2008. Trees in Towns II: A new survey of urban trees in England
and their condition and management. ADAS UK Ltd. and Myerscough College. A report for
the Department of Communities and Local Government, London.
Dobbie, K.E., Bruneau, P.M.C and Towers, W. 2011. The State of Scotland’s Soil. Natural
Scotland. www.sepa.org.uk/land/land_publications.aspx.
Edwards, D., Elliott, A., Hislop, M., Martin, S., Morris, J., O’Brien, L., Peace, A., Sarajevs, V.,
Serrand, M. and G. Valatin. 2009. A valuation of the economic and social contribution of
forestry for people in Scotland. Forestry Commission Research Report. Forestry
Commission Scotland, Edinburgh.
Haines-Young, R. and Potschin, M. 2010. The links between biodiversity, ecosystem
services and human well-being. Chapter 6, pp. 110-139. In: Raffaelli, D.G. and Frid, C.L.J.
(eds). Ecosystem Ecology: A New Synthesis. Cambridge University Press, Cambridge.
39
Natural History Museum. 2013. Urban Tree Survey http://www.nhm.ac.uk/nature-
online/british-natural-history/urban-tree-survey/index.html.
Scottish Government. 2011. Getting the best from our land: A land use strategy for Scotland.
http://www.scotland.gov.uk/Publications/2011/03/17091927/0.
Willis, K.G., Garrod, G., Scarpa, R., Powe, N., Lovett, A., Bateman, I.J., Hanley, N., and
Macmillan, D.C. 2003. The social and environmental benefits of forests in Great Britain.
Social Benefits of Forestry: Phase 2. Report to Forestry Commission. Centre for Research
and Rural Appraisal and Management, University of Newcastle.
www.snh.gov.uk
© Scottish Natural Heritage 2014
ISBN: 978-1-78391-149-3
Policy and Advice Directorate, Great Glen House,
Leachkin Road, Inverness IV3 8NW
T: 01463 725000
You can download a copy of this publication from the SNH website.
... Whilst not directly related to the SEEA-EEA, The Netherlands have constructed national accounts of biodiversity which have been developed based on a system of species abundance weighted habitat areas under the Natural Capital Index project (ten Brink & Tekelenburg, 2002). This approach has also been developed for Scotland as a Natural Capital Asset Index (Albon et al., 2014). ...
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... • The general approach described has been employed by Albon et al., (2014) for producing a Natural Capital Asset Index. They made use of existing indicators of biodiversity, inter alia, that were readily available and relevant to different ecosystem services. ...
Technical Report
Full-text available
This technical guidance document has been prepared in the context of the Advancing the SEEA-EEA project. It is aimed at practitioners who wish to collect and organize data to understand the status and trends of ecosystem and species diversity and incorporate this into the SEEA-EEA framework for national accounting.
... Indicators are judged by six main criteria; type of indicator, date first available, frequency of updates, spatial coverage, correlation and whether there are annual fluctuations. In 2014 a systematic evaluation of the indicators was conducted by the James Hutton Institute (Albon et al., 2014). Using a traffic light system, the indicators were flagged as 'fit for purpose', 'possibly fit for purpose' or 'not fit for purpose'. ...
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... arguments for conservation-oriented decision making ( Balmford et al., 2011;Eastwood et al., 2016;69 Fisher et al., 2011;Mace, 2014;Mace et al., 2012), and it is increasingly being incorporated into 70 government policy making on land-use ( Albon et al., 2014;DEFRA, 2007;Natural Capital 71 Committee, 2015). In 2016, the Natural Capital Coalition launched a protocol intended to act as a 72 standardised framework for organisations to identify, measure and value their reliance and effects on 73 natural capital. ...
Article
Coastal managed realignment has the potential to deliver both nature conservation and other benefits to people, but these are rarely quantified. We used an ecosystem services assessment toolkit, TESSA, at two locations in the UK; Hesketh Outmarsh West (northwest England), where realignment has already been carried out, and the Inner Firth of Forth (central Scotland), where realignment is proposed for multiple sites. At the Inner Forth we focus on one site, Inch of Ferryton, in Clackmannanshire but also assess ecosystem services across several sites. Using dedicated data collection where possible, and site-appropriate existing data, we estimate the value of these sites to people in the realigned state compared with the most realistic alternative: continued agricultural production behind hard flood defences (agricultural state). Services assessed were climate change mitigation, agricultural production, nature-based recreation, and flood risk protection. At both sites agricultural production was estimated to be greater in the agricultural state, while other services were estimated to be greater in the realigned state. We are cautious about assigning overall monetary values based on biophysical attributes, particularly considering that climate change mitigation is highly sensitive to carbon prices, and that by necessity we were unable to quantify all services. Nevertheless, using a price for carbon that incorporates the societal cost of emissions, we estimate that the net annual provision of services is £262,935 (£1460.75/ha) at Hesketh Outmarsh West and £93,216 (£574.70/ha) at Inch of Ferryton. At both sites, sequestered carbon in accreting sediments outweighs greenhouse gas emissions from intertidal habitats, and the net value of this in turn outweighs the income foregone from crops and grazing. At Hesketh Outmarsh West the value of ecosystem services is increased by the reduction to flood risk arising from the coastal managed realignment action. Nature-based recreation is estimated to increase at both sites under realignment, with the visitor profile expected to be strongly local. Decisions about coastal management, including realignment, should incorporate information about the ecosystem services provided under different scenarios. This applies beyond coastal ecosystems, and the site-scale is often the most appropriate scale to carry out such assessments, as this is the scale at which decisions are often taken.