Technical ReportPDF Available

Report on Economic Mapping and Assessment Methods for Ecosystem Services Deliverable D3.2 - EU Horizon 2020 ESMERALDA Project, Grant agreement No. 642007.

Authors:

Abstract

This report provides an overview of the main economic methods for mapping and assessment of ecosystem services.
Report on Economic Mapping and
Assessment Methods for Ecosystem
Services
Deliverable D3.2
Report on Economic Mapping and
Assessment Methods for Ecosystem
Services
25 February 2018
Coordinating Authors:
Luke Brander, Pieter van Beukering
Contributing authors:
Mario Balzan, Steven Broekx, Inge Liekens, Cristina Marta-Pedroso, Zbigniew Szkop,
James Vause, Joachim Maes, Fernando Santos-Martin, Marion Potschin-Young
Enhancing ecosystem services mapping for policy and
decision making
2 | Page D3.2: Economic Mapping Methods
__________________________________________________________________________________
Prepared under contract from the European Commission
Grant agreement No. 642007
EU Horizon 2020 Coordination and support action
Project acronym: ESMERALDA
Project full title: Enhancing ecosystem services mapping for policy and decision
making
Start of the project: February 2015
Duration: 42 months
Project coordinator: Prof. Dr. Benjamin Burkhard, Leibniz Universität Hannover
Project website www.esmeralda-project.eu
Deliverable title: Economic Mapping and Assessment Methods for Ecosystem
Services
Deliverable n°: D3.2 (merged D3.2 and D4.2)
Nature of the deliverable: Report
Dissemination level: Public
WP responsible: WP3
Lead beneficiary: Autonomous University of Madrid
Citation: Brander, L.M., van Beukering P., Balzan, M., Broekx, S., Liekens, I.,
Marta-Pedroso, C., Szkop, Z., Vause, J., Maes, J., Santos-Martin F.
and Potschin-Young M. (2018). Report on economic mapping and
assessment methods for ecosystem services. Deliverable D3.2 EU
Horizon 2020 ESMERALDA Project, Grant agreement No. 642007.
Due date of deliverable: Month n°36
Actual submission date: Month n° 37
Deliverable status:
Version
Status
Date
Author(s)
1.0
Draft
5 February 2016
Luke Brander, Pieter van Beukering
1.1
Draft
11 February 2016
Review by Fernando Santos-Martin
2.0
Draft
26 February 2016
Revised by Luke Brander
2.1
Draft
21 March 2016
Review by Mario Balzan, Inge Liekens,
Steven Broekx
3.0
Draft
21 December 2017
Revised by Luke Brander, Inge Liekens,
Cristina Marta-Pedroso
4.0
4.1
Draft
Draft
12 January 2018
20 January 2018
Reviewed by M. Potschin-Young and F.
Santos-Martín
Reviewed by B. Burkhard and J. Maes
The content of this deliverable do not necessarily reflect the official opinions of the European
Commission or other institutions of the European Union.
D3.2: Economic mapping and assessment methods 3 | Page
__________________________________________________________________________________
Table of contents
Preface .................................................................................................................................................... 5
Summary ................................................................................................................................................. 6
1. Introduction to economic mapping and assessment methods ...................................................... 8
2. Framework for economic methods and key concepts .................................................................... 8
2.1. What is economic value? ........................................................................................................ 8
2.2. Total Economic Value (TEV) .................................................................................................. 10
2.3. Exchange value ...................................................................................................................... 12
3. Methods for estimating economic values for ecosystem services ............................................... 12
3.1. Primary valuation methods ................................................................................................... 13
3.2. Value transfer methods ........................................................................................................ 17
4. Methods for mapping economic values for ecosystem services .................................................. 20
4.1. Representing economic values on maps .............................................................................. 20
4.2. Scaling up economic values .................................................................................................. 22
4.3. Example value mapping applications .................................................................................... 23
5. Economic assessment methods .................................................................................................... 32
5.1. Introduction to economic assessment methods .................................................................. 32
5.2. Cost-Effectiveness Analysis ................................................................................................... 34
5.3. Cost-Benefit Analysis ............................................................................................................ 35
5.4. Multi-Criteria Analysis ........................................................................................................... 40
5.5. Ecosystem Service Accounting .............................................................................................. 41
5.5.1. Introduction to ecosystem service accounting frameworks ......................................... 41
5.5.2. System of Environmental-Economic Accounts (SEEA) .................................................. 43
5.5.3. Wealth Accounting and Valuation of Ecosystem Services (WAVES) ............................. 45
5.5.4. Integrated system for Natural Capital and ecosystem services Accounting (INCA) ..... 45
5.5.5. National/Regional accounting initiatives in the EU ...................................................... 47
5.6. Corporate Ecosystem Service Review ................................................................................... 49
6. Distributional considerations ........................................................................................................ 51
6.1. Distribution of impacts across stakeholders ......................................................................... 51
6.2. Spatially distributed impacts ................................................................................................. 52
6.3. Temporally distributed impacts ............................................................................................ 52
7. A tiered approach to economic mapping and assessment methods ........................................... 54
4 | Page D3.2: Economic Mapping Methods
__________________________________________________________________________________
8. Integration of economic methods with socio-cultural and bio-physical mapping and assessment
methods ................................................................................................................................................ 57
9. Conclusions ................................................................................................................................... 57
10. Acknowledgements ................................................................................................................... 59
11. References ................................................................................................................................ 60
12. Annex 1: Guidelines on valuation methods .............................................................................. 64
13. Annex 2: Ecosystem service value databases ........................................................................... 65
D3.2: Economic mapping and assessment methods 5 | Page
__________________________________________________________________________________
Preface
Mapping and assessment of ecosystems and their services (ES) are core to the EU Biodiversity (BD)
Strategy. They are essential if we are to make informed decisions. Action 5 sets the requirement for
an EU-wide knowledge base designed to be: a primary data source for developing Europe’s green
infrastructure; resource to identify areas for ecosystem restoration; and, a baseline against which the
goal of ‘no net loss of BD and ES’ can be evaluated.
In response to these requirements, ESMERALDA (Enhancing ecoSysteM sERvices mApping for poLicy
and Decision mAking) aims to deliver a flexible methodology to provide the building blocks for pan-
European and regional assessments. The work will ensure the timely delivery of EU member states in
relation to Action 5 of the BD Strategy, supporting the needs of assessments in relation to the
requirements for planning, agriculture, climate, water and nature policy. This methodology will build
on existing ES projects and databases (e.g. MAES, OpenNESS, OPERAs, national studies), the
Millennium Assessment (MA) and The Economics of Ecosystems and Biodiversity (TEEB). ESMERALDA
will identify relevant stakeholders and take stock of their requirements at EU, national and regional
levels.
The objective of ESMERALDA is to share experience through an active process of dialogue and
knowledge co-creation that will enable participants to achieve the Action 5 aims. The mapping
approach proposed will integrate biophysical, sociocultural and economic assessment techniques.
The six work packages of ESMERALDA are organised through four strands (see Figure 1), namely policy,
research, application and networking, which reflect the main objectives of EMSERALDA.
Figure 1: ESMERALDA components and their interrelations and integration within the four
ESMERALDA strands.
This report sits within work packages WP3 “Mapping methods” and WP4 “Assessment Methods”.
When making the proposal, the original idea was to investigate similarities and differences when using
methods for the mapping and/or assessment of ecosystem services; as a result the effort was split
6 | Page D3.2: Economic Mapping Methods
__________________________________________________________________________________
across two different work packages, namely WP 3 “Mapping methods”, and WP4 “Assessment
Methods”. A draft deliverable (Del. 4.2) on Economic assessment methods and application was
submitted in month 24, approximately than half way through the project. The work found that it was
very difficult to make a clear distinction between economic methods for mapping and/or assessment;
there was also potential duplication of material between the two elements. A discussion with the task
leaders for the sociocultural, economic and biophysical method work streams, as well as the wider
project community, led to the decision to merge deliverables on methods for mapping (WP3) and
assessment (WP4) of ecosystem services. The submission time for the three deliverables was
harmonized to month 36. The merger of deliverables was submitted through amendment No 22 and
was accepted by the European Commission on 22nd January 2017.
This report therefore provides an overview of the main economic methods for mapping and
assessment of ecosystem services. This report also highlights the need to link and integrate
information from sociocultural and biophysical methods. ESMERALDA reports D3.1 and D3.3
specifically provide guidance on sociocultural and biophysical methods for mapping and assessment
of ecosystem services. ESMERALDA report D3.4 provides guidance on how biophysical, socio-cultural
and economic methods can be linked within an ecosystem service assessment and on methods for
integrating information outputs across disciplinary domains; and report D4.8 provides guidance on
integrated assessment of ecosystem services. All these deliverables address the challenge of
improving the applicability of these approaches with specific examples, particularly with respect to
the MAES process and the ESMERALDA case studies.
Summary
This report provides an overview of the main economic methods for mapping and assessment of
ecosystem services. Here we provide a brief summary of the main points of information addressed in
this report.
Economic mapping of ecosystem services involves the measurement of their economic value
accounting for spatial variation in supply and demand. Economic assessment of ecosystem
services involves the structuring and integration of value information into decision making and
the design of policy instruments.
Economic value of ecosystem services is a measure of the human welfare derived from the use
or consumption of ecosystem services. Economic valuation is one way to quantify and
communicate the importance of ecosystem services to decision makers, and can be used in
combination with other forms of information (e.g. socio-cultural values or biophysical indicators).
The concept of Total Economic Value (TEV) of an ecosystem is a framework for identifying the
comprehensive set of utilitarian values derived from that ecosystem. The word “total” in Total
Economic Value refers to the inclusion of different sources of value; TEV does not imply the
calculation of an aggregate value of a resource. The classification of different sources of economic
value within the concept of TEV is complementary to the classification of ecosystem services.
The System of National Accounts (SNA) used to produce conventional macro-economic statistics
(e.g. GDP) uses a non-welfare based concept of economic value termed exchange value. For the
purposes of producing ecosystem service accounts that are consistent with the SNA, it is necessary
to use estimates of ecosystem services values that are quantified as exchange values.
The economic value of an ecosystem service is determined by its supply and demand. The supply
side of an ecosystem service is largely determined by ecological processes and characteristics that
D3.2: Economic mapping and assessment methods 7 | Page
__________________________________________________________________________________
may be influenced by human activities, either deliberately or inadvertently. The demand side is
largely determined by the characteristics of human beneficiaries of the ecosystem service. The
determinants of both the supply and demand of ecosystem services are spatially variable, which
makes the estimation of ecosystem service values inherently spatial. Value mapping addresses
this spatial dimension of ecosystem service valuation.
Ecosystem services are often not traded in markets and so a number of “primary” non-market
valuation methods have been developed to estimate their economic values. These include the
use of replacement costs, avoided damage costs, production functions, revealed preferences (e.g.
hedonic pricing, travel costs), and stated preferences (e.g. contingent valuation, choice
experiments).
Value transfer (benefit transfer) is the use of research results from existing primary studies at one
or more sites or policy contexts (“study sites”) to predict welfare estimates or related information
for other sites or policy contexts (“policy sites”).
Value transfer methods are a relatively expeditious and inexpensive means of obtaining estimates
of ecosystem service values and can be applied at geographic scales that are not feasible for
primary valuation applications. The accuracy of value transfer is dependent on the similarities of
characteristics across study sites and policy sites and the extent to which differences are
controlled for.
Economic methods for the assessment of ecosystem services are frameworks for generating and
structuring economic information to support decision-making regarding ecosystem services.
These assessment methods include: cost-effectiveness analysis, cost-benefit analysis, multi-
criteria analysis, ecosystem service accounting and corporate ecosystem service reviews.
The decision-making context regarding the management of ecosystem services is often one of
spatial targeting or optimisation. Decisions are being made about where to invest in ecosystem
restoration, establish protected areas, or target financial incentives to change the behaviour of
land users. In such cases, the spatial correspondence of costs and benefits relevant to the decision
is of crucial importance and mapping these inputs is a necessary step in the assessment process.
The choice of which economic mapping or assessment method to use is largely determined by the
ecosystem service(s) under consideration, the type of decision problem and the availability of
information. To understand the differences between economic mapping and assessment
methods, we describe the procedural steps of each approach, provide brief example applications
and discuss the strengths and weaknesses of each approach. Each method is assigned to one of
the three defined tiers to reflect the precision of its output and the resources required for its
application.
The application of economic mapping and assessment methods will often require inputs from
socio-cultural and biophysical methods (and vice versa). In addition, the production of policy
relevant information may require the integration of separate outputs from biophysical, economic
and socio-cultural mapping and assessment applications.
8 | Page D3.2: Economic Mapping Methods
__________________________________________________________________________________
1. Introduction to economic mapping and assessment methods
This report provides an overview of economic methods for mapping and assessment of ecosystem
services. In this context, the term “mapping” is used to mean the description and representation of
spatial variation. Mapping therefore includes both the representation of data on maps and/or the
process of accounting for spatial variation in the phenomena under consideration. Economic methods
for mapping of ecosystem services examine spatial variation in the economic value of ecosystem
services.
The process of mapping ecosystem service values falls within the broader process of ecosystem service
assessment. The term “assessment” is defined in the ESMERALDA project as “the analysis and review
of information derived from research for the purpose of helping someone in a position of
responsibility to evaluate possible actions or think about a problem. Assessment means assembling,
summarising, organising, interpreting, and possibly reconciling pieces of existing knowledge and
communicating them so that they are relevant and helpful to an intelligent but inexpert decision-
maker. Assessment therefore focuses on how information on ecosystem services can be structured
to support decision-making.
Economic methods for mapping and assessing ecosystem services principally involve measuring the
economic value of ecosystem services, including its spatial variation, and structuring this information
to support decision making and the design of policy instruments. As such, economic methods operate
on the right side of the ecosystem services cascade model to quantify the benefits to humans (Potschin
and Haines-Young, 2011). Any economic mapping or assessment therefore fundamentally relies on
biophysical data and methods to quantify the capacity of ecosystems to supply ecosystem services
(i.e. the left side of the cascade model). Economic methods can also be used in combination with socio-
cultural methods to gain a broader understanding of the importance of ecosystem services to society.
Economic methods for measuring and mapping ecosystem services include primary valuation and
value transfer methods. The process of representing economic values on maps necessarily involves
some form of spatial extrapolation or transfer of value information. The principal primary and transfer
methods are explained in this report together with an evaluation of their strengths, weaknesses and
applicability to different ecosystem services.
Economic methods for assessing ecosystem services include cost-effectiveness analysis, cost-benefit
analysis, multi-criteria analysis, ecosystem service assessments, ecosystem service accounting, and
corporate ecosystem service review. These methods are explained in this report together with an
evaluation of their strengths, weaknesses and applicability to ecosystem service assessment. Where
relevant, the potential role of ecosystem service maps as input into economic assessments is
highlighted.
2. Framework for economic methods and key concepts
2.1. What is economic value?
Economic value of ecosystem services is a measure of the human welfare derived from the use or
appreciation of ecosystem services (Pascual et al., 2010). Economic valuation is one way to quantify
and communicate the importance of ecosystem services to decision makers, and can best be used in
combination with other forms of information to provide a complete picture of how human welfare
depends on natural capital (e.g. socio-cultural values or bio-physical indicators see ESMERALDA
reports D3.1 and D3.3 respectively). The comparative advantage of economic valuation is that it
conveys the importance of ecosystem services directly in terms of human welfare and uses a common
D3.2: Economic mapping and assessment methods 9 | Page
__________________________________________________________________________________
unit of account (i.e. money) so that values can be directly compared across ecosystem services and
across other goods and services in the economy.
Here we provide definitions of the various concepts of economic value that may be encountered when
valuing and mapping ecosystem services.
In neo-classical welfare economics, the economic value of a good or service is the monetary measure
of the wellbeing associated with its production and consumption. In a perfectly functioning market,
the economic value of a good or service is determined by the demand for and supply of that good or
service. Demand for a good or service is determined by the benefit, utility or welfare that consumers
derive from it. Supply of a good or service is determined by the cost to producers of producing it.
Figure 1 provides a simplified representation of demand (marginal benefit) and supply (marginal cost)
for a good traded in a market at quantity ‘Q’ and price ‘P’. The demand curve is represented as a
downward sloping line since marginal benefits are expected to decline with quantity (the more that
we have of a service, the lower the additional welfare of consuming more). The supply curve is
represented as an upward sloping line since marginal costs of production are generally expected to
increase with quantity (as low cost inputs become exhausted).
Figure 1: Demand and supply curves for a conventional good or service traded in a market
In Figure 1, area ‘A’ represents the consumer surplus, which is the gain obtained by consumers
because they are able to purchase a product at a market price that is less than the highest price they
would be willing to pay (which is related to their benefit from consumption and represented by the
demand curve). The producer surplus, depicted by ‘B’, is the amount that producers benefit by selling
at a market price that is higher than the lowest price that they would be willing to sell for (which is
related to their production costs and represented by the supply curve). The area ‘C’ represents
production costs, which differ among producers and/or over the scale of production. The sum of areas
A and B is labelled the ‘surplus’, and is interpreted as the net economic gain or welfare resulting from
production and consumption with a quantity of Q at price P.
In the case that ecosystem services are not traded in a market, the interpretation of the welfare
derived from their provision can also be represented in terms of surplus. Figure 2 represents the
supply and demand of a non-marketed ecosystem service. In this case, the ecosystem service does
Demand
Supply
A
BC
P
QQuan ty
Price
10 | Page D3.2: Economic Mapping Methods
__________________________________________________________________________________
not have a supply curve in the conventional sense that it represents the quantity of the service that
producers are willing to supply at each price. The quantity of ecosystem service that is ‘supplied’ is not
determined through a market at all but by other decisions regarding ecosystem protection, land use,
management, access etc. The quantity of ecosystem service supplied is therefore independent of its
value. This is represented in Figure 2 as a vertical line. For the most part, biophysical indicators of
ecosystem services measure the quantity supplied but not the welfare obtained. The demand curve
for non-marketed ecosystem services is still represented as a downward sloping line since marginal
benefits are expected to decline with quantity. In this case, consumers do not pay a price for the
quantity (Q) that is available to them and the entire area under the demand curve (D+E) represents
their consumer surplus. It is useful to keep this picture in mind when considering the measurement of
ecosystem service supply and the welfare people derive from it.
Note that the demand for ecosystem services that are inputs into the production of marketed goods
(e.g., pollination and erosion control are generally uncompensated inputs in agricultural production)
is derived from the demand for the good or service that is finally consumed (e.g. food). Figure 2 also
represents the conceptual value of ecosystem services that have a ‘derived demand’.
Figure 2: Demand and supply for a non-marketed ecosystem service
The marginal value of an ecosystem service is the contribution to wellbeing of one additional unit of
the service (V in Figure 2). It is equivalent to the price of the service in a perfectly functioning market
(P in Figure 1). Small changes in ecosystem service provision should be valued using marginal values.
The average value of an ecosystem service can be calculated as its total value divided by the total
quantity of the service provided and consumed. From Figure 2, average value can be calculated as
(D+E)/Q. Average values may be useful for comparing the aggregate value of an ecosystem service
relative to the scale of provision (defined in terms of units of provision, area of ecosystem, or number
of beneficiaries).
2.2. Total Economic Value (TEV)
The concept of Total Economic Value (TEV) of an ecosystem is used to describe the comprehensive
set of utilitarian values derived from that ecosystem (Pearce and Turner, 1990). This concept is useful
for identifying the different types of value that may be derived from an ecosystem. TEV comprises of
use values and non-use values. Use values are the benefits that are derived from some physical use
of the resource. Direct use values may derive from on-site extraction of resources (e.g. fuel wood) or
Demand
Ecosystem
service
provision
D
E
V
QQuan ty
Value
D3.2: Economic mapping and assessment methods 11 | Page
__________________________________________________________________________________
non-consumptive activities (e.g. recreation). Indirect use values are derived from off-site services that
are related to the resource (e.g. downstream flood control, climate regulation). Option value is the
value that people place on maintaining the option to use an ecosystem resource in the future. Non-
use values are derived from the knowledge that an ecosystem is maintained without regard to any
current or future personal use. Non-use values may be related to altruism (maintaining an ecosystem
for others), bequest (for future generations) and existence (preservation unrelated to any use)
motivations. The constituent values of TEV are represented in Figure 3. It is important to understand
that the “total” in Total Economic Value refers to the inclusion of different sources of value rather
than the sum of all value derived from a resource. TEV is a measure of total value as opposed to partial
value. Accordingly, many estimates of TEV are for marginal changes in the provision of ecosystem
services but “total” in the sense that they take a comprehensive view of sources of value.
Figure 3: The components of Total Economic Value (Pearce and Turner, 1990)
The classification of different types of economic value within the concept of TEV is complementary to
the classification of ecosystem services. Table 1 sets out the correspondence between categories of
ecosystem service and components of TEV.
Table 1: Correspondence between ecosystem services and components of Total Economic Value
Total Economic Value
Ecosystem service
Direct use
Indirect use
Option value
Non-use
Provisioning
X
X
Regulation and maintenance
X
X
Cultural
X
X
X
Total Economic Value
Use Value Non-Use Value
Direct Use Indirect Use Option Altruism Bequest Existence
12 | Page D3.2: Economic Mapping Methods
__________________________________________________________________________________
2.3. Exchange value
The concept of welfare value is used in most economic assessments of ecosystem services but it is not
used in the system of national accounts (SNA) that is used to calculate gross domestic product (GDP)
and other economic statistics. The SNA uses the concept exchange value, which is a measure of
producer surplus plus the costs of production. In Figure 1 this is represented by areas B and C, or
equivalently P times Q. Under the concept of exchange value, the total outlays by consumers and the
total revenue of the producers are equal. For national accounting purposes, this approach to valuation
enables a consistent and convenient recording of transactions between economic units since the
values for supply and use of products are the same. In the context of comparing the values of
ecosystem services with values in the system of national accounts, it is therefore necessary to value
the total quantity of ecosystem services at the market prices that would have occurred if the services
had been freely traded and exchanged. In other words, it is necessary to measure exchange value and
not welfare value.
The differences between the concepts of welfare value and exchange value are the inclusion of
consumer surplus (A) in the former and the inclusion of production costs in the latter (C). The concept
of welfare value corresponds to a theoretically valid measure of welfare in the sense that a change in
value represents a change in welfare for the producers and/or consumers of the goods and services
under consideration. The concept of exchange value does not correspond to a theoretically valid
measure of welfare and a change in exchange value does not necessarily represent a change in welfare
for either producers or consumers.
1
3. Methods for estimating economic values for ecosystem services
A variety of methods have been developed for estimating the economic value of ecosystem services
that are designed to span the range of valuation challenges raised by the application of economic
analyses to the complexity of the natural environment. Figure 4 provides a representation of the
available economic methods for valuing ecosystem services. A key distinction is between methods
that produce new or original information generally using primary data (primary valuation methods)
and those that use existing information in new policy contexts (value transfer methods). Primary
valuation methods are described in section 3.1 and value transfer methods are described in section
3.2.
1
See Day (2013) for a more detailed explanation of welfare and exchange values.
D3.2: Economic mapping and assessment methods 13 | Page
__________________________________________________________________________________
Figure 4: Overview of primary valuation and value transfer methods
3.1. Primary valuation methods
Primary valuation methods can be divided into three categories: 1. Cost-based approaches that use
some measure of the costs associated with an ecosystem service as a proxy for the value of the service;
2. Methods that estimate the value of ecosystem services as inputs into production; and 3. Methods
that use consumer behaviour to measure the value of ecosystem services. This third category can be
further usefully divided between revealed preference methods (those that observe actual behaviour
of the use of ecosystem services to elicit values) and stated preference methods (those that use public
surveys to ask beneficiaries to state their preferences for, generally hypothetical, changes in the
provision of ecosystem services). Revealed preference methods may be favoured since they reflect
actual behaviour but are limited in their applicability to some ecosystem services. Stated preference
methods on the other hand rely on responses recorded in surveys or experiments but are more flexible
in their application.
Table 2 provides an overview of primary valuation methods, typical applications, limitations and
indicates which primary valuation methods can be used to value which ecosystem service. It should
be noted that different valuation methods produce different measures of economic value that are not
equivalent and cannot necessarily be directly compared. The valuation method, and the measure of
economic value that it estimates, will have a substantial bearing on the magnitude of the value
estimated. It is therefore important to understand what each measure is and to select a measure that
is relevant to the case in hand. There are numerous existing publications that provide guidance on the
use of primary valuation methods. A selection of these is listed in Annex 1.
MarketPrices
NetFactorIncome
Produc onFunc on TravelCostMethod
HedonicPricing Con ngentValua on
PrimaryValua onEs mates
ChoiceModelling
ReplacementCost
DamageCost
OpportunityCost
BehaviouralLinkagesProduc onLinkagesCostApproaches
StatedPreference
RevealedPreference
DefensiveExpenditure
Restora onCost Input-OutputModels GroupValua on
PublicPricing
UnitValues Meta-analy cFunc on
ValueFunc on
Primary
valua on
methods
Value
transfer
methods
Table 2: Primary valuation methods, applicability to ecosystem services, examples and limitations (adapted from Table A2, Brander 2013)
Valuation
method
Approach
Application to ecosystem
services
Example ecosystem service
Limitations
Tier2
Market prices
Prices for ES that are
directly observed in
markets
ES that are traded directly in
markets
Timber and fuel wood from
forests; clean water from
wetlands
Market prices can be distorted e.g. by
subsidies. Most ES are not traded in
markets
1
Public pricing
Public expenditure or
monetary incentives
(taxes/subsidies) for ES
as an indicator of value
ES for which there are public
expenditures
Watershed protection to
provide drinking water;
Purchase of land for
protected area
No direct link to preferences of
beneficiaries
1
Defensive
expenditure
Expenditure on
protection of ES
ES for which there is public
or private expenditure for
its protection
Recreation and aesthetic
values from protected areas
Only applicable where direct
expenditures are made for
environmental protection related to
provision on an ES. Provides lower
bound estimate of ES benefit
1
Replacement
cost
Estimate the cost of
replacing an ES with a
man-made service
ES that have man-made
equivalents
Coastal protection by dunes
(replaced my seawalls);
water storage and filtration
by wetlands (replaced by
reservation and filtration
plant)
No direct relation to ES benefits. Over-
estimates value if society is not
prepared to pay for man-made
replacement. Under-estimates value if
man-made replacement does not
provide all of the benefits of the original
ecosystem.
1
Restoration cost
Estimate cost of
restoring degraded
ecosystems to ensure
provision of ES
Any ES that can be provided
by restored ecosystems
Coastal protection by dunes;
water storage and filtration
by wetlands
No direct relation to ES benefits. Over-
estimates value if society is not
prepared to pay for restoration. Under-
estimates value if restoration does not
provide all of the benefits of the original
ecosystem.
1
2
Each method is assigned to a tier (1-3) to broadly reflect the accuracy, detail, technical capacity and data requirements of the method. See section 7 for a full explanation
of the approach used to assign methods to tiers.
D3.2: Economic mapping and assessment methods 15 | Page
__________________________________________________________________________________
Valuation
method
Approach
Application to ecosystem
services
Example ecosystem service
Limitations
Tier2
Damage cost
avoided
Estimate damage
avoided due to
ecosystem service
Ecosystems that provide
storm, flood or landslide
protection to houses or
other assets
Coastal protection by dunes;
river flow control by
wetlands; landslide
protection by forests
Difficult to quantify changes in risk of
damage to changes in ecosystem
quality.
2
Social cost of
carbon
The monetary value of
damages caused by
emitting one tonne of
CO2 in a given year. The
social cost of carbon
(SCC) therefore also
represents the value of
damages avoided for a
one tonne reduction in
emissions.
Carbon storage and
sequestration
Carbon sequestered and
stored by protected or
restored forests
SCC is a specific application of the
"damage cost avoided" method. SCC is
characterised by high modeling
uncertainties and partial coverage of
climate change impacts.
1
Opportunity
cost
The next highest valued
use of the resources
used to produce an
ecosystem service.
All ecosystem services
The opportunity cost of
ecosystem services from a
natural ecosystem might be
the value of agricultural
output if the land is
converted to agricultural
instead of conserved in a
natural state.
Measures the cost of providing
ecosystem services instead of the
benefit.
1
Net factor
income
(residual value)
Revenue from sales of
ecosystem-related good
minus cost of other
inputs
Ecosystems that provide an
input in the production of a
marketed good
Filtration of water by
wetlands; commercial
fisheries supported by
coastal wetlands
Tendency to over-estimate values since
all normal profit is attributed to the ES
2
Production
function
Statistical estimation of
production function for a
marketed good including
an ES input
Ecosystems that provide an
input in the production of a
marketed good
Soil quality or water quality
as an input to agricultural
production
Technically difficult. High data
requirements
3
16 | Page D3.2: Economic Mapping Methods
__________________________________________________________________________________
Valuation
method
Approach
Application to ecosystem
services
Example ecosystem service
Limitations
Tier2
Input-Output
Models
Quantifies the
interdependencies
between economic
sectors in order to
measure the impacts of
changes in one sector
to other sectors in the
economy. Ecosystems
can be incorporated as
distinct sectors.
Ecosystem services with
direct and indirect use
values, particularly inputs
into production
Ecosystem inputs into
agriculture; or into the
tourism sector
Requires substantial data on ecosystem-
economy linkages to parameterise
connections between sectors
Hedonic pricing
Estimate influence of
environmental
characteristics on price
of marketed goods
Environmental
characteristics that vary
across goods (usually
houses)
Urban green open space; air
quality moderated by
ecosystems
Technically difficult. High data
requirements. Limited to ES that are
spatially related to property locations.
3
Travel cost
Estimate demand for
ecosystem recreation
sites using data on travel
costs and visit rates
Recreational use of
ecosystems
Recreational use of national
parks
Technically difficult. High data
requirements. Limited to valuation of
recreation. Complicated for trips with
multiple purposes or to multiple sites.
3
Contingent
valuation
Ask people to state their
willingness to pay for an
ES through surveys
All ecosystem services
Biodiversity; recreation;
landscape aesthetics; flood
risk attenuation
Expensive and technically difficult to
implement. Risk of biases in design and
analysis
3
Choice
modelling
(choice
experiment)
Ask people to make
trade-offs between ES
and other goods to elicit
willingness to pay
All ecosystem services
Biodiversity; recreation;
landscape aesthetics; flood
risk attenuation
Expensive and technically difficult to
implement. Risk of biases in design and
analysis
3
Group /
participatory
valuation
Ask groups of
stakeholders to state
their willingness to pay
for an ES through group
discussion
All ecosystem services
Biodiversity; recreation;
landscape aesthetics; flood
risk attenuation
Risk of biases due to group dynamics
3
Box 1. Choice experiment valuation of nature restoration in Drongengoed, Belgium (De Valck et
al., 2014)
To ensure the long-term survival of its most valuable and threatened habitats, the European Union
(EU) is committing its Member States to develop a network of protected areas. Flanders (northern
Belgium) is a highly urbanised region, where natural environments are scarce. Policy-makers are
converting existing forest plantations (mostly former coniferous plantations) into natural areas to
comply with the EU requirements about nature restoration and satisfy the growing demand for
recreation and amenity spaces. The conversion of forest plantations into higher value nature,
however, sometimes meets public opposition because it often involves clearcuts and landscape
modification. Regional planning authorities are looking for case studies demonstrating which type
of nature restoration is valued and thus supported by citizens. Past valuation studies show that
personal, site-specific and spatial characteristics influence preferences. However, little is known
about the relative importance of such factors. We conduct a discrete choice experiment to
investigate preferences for nature restoration scenarios that involve forest conversion.
A mixed logit and a latent class model are estimated and the influence of socio-demographic
characteristics is explored. Willingness-to-pay (WTP) estimates are elicited. Though people
generally prefer the forest habitat type, our results suggest that public support exists for converting
forest plantations if this contributes to increasing landscape diversity and species richness
(coniferous forest plantation into deciduous forest and heathland). People in Flanders prefer also
large variation in a landscape so a preference in changing the total area are less preferred than
changing smaller parts. Based on our findings, we recommend small scale cuts. This in order to
gently open the landscape, assist the natural regeneration process and help current species adapt
to that landscape modification. The willingness to pay estimates are also transferred through a
value function transfer to similar restoration projects in order to estimate the benefits of this
restoration.
3.2. Value transfer methods
Decision-making often requires information quickly and at low cost. New ‘primary’ valuation research,
however, is generally time-consuming and expensive. For this reason, there is interest in using
information from existing primary valuation studies to inform decisions regarding impacts on
ecosystems that are of current interest. This transfer of value information from one context to another
is called value transfer.
Value transfer is the use of research results from existing primary studies at one or more sites or policy
contexts (“study sites”) to predict welfare estimates or related information for other sites or policy
contexts (“policy sites”) (Johnston et al., 2015). Value transfer is also known as benefit transfer but
18 | Page D3.2: Economic Mapping Methods
__________________________________________________________________________________
since the values that are transferred may be costs as well as benefits, the term value transfer is more
generally applicable.
In addition to the need for expeditious and inexpensive information, there is often a need for
information on the value of ecosystem services at a different geographic scale from that at which
primary valuation studies have been conducted. So even in cases where some primary valuation
research is available for the ecosystem of interest, it is often necessary to extrapolate or scale-up this
information to a larger area or to multiple ecosystems in the region or country. Primary valuation
studies tend to be conducted for specific ecosystems at a local scale whereas the information required
for decision-making, and indeed the MAES (Mapping and Assessment of Ecosystems and their
Services
3
) process, is often needed at a regional or national scale. Value transfer therefore provides a
means to obtain information for the scale that is required.
The number of primary studies on the value of ecosystem services is substantial and growing rapidly.
This means that there is a growing body of evidence to draw on for the purposes of transferring values
to inform decision-making (see Annex 2 for an overview of databases that compile existing valuation
studies). With an expanding information base, the potential for using value transfer is improved.
Value transfer can potentially be used to estimate values for any ecosystem service, provided that
there are primary valuations of that ecosystem service from which to transfer values. Value transfer
methods have been employed widely in national and global ecosystem assessments (e.g. the UK NEA,
2011; Hussain et al., 2011), value mapping applications (see Schaegner et al., 2013) and policy
appraisals (e.g. World Bank, 2002). The use of value transfer is widespread but requires careful
application. The alternative methods of conducting value transfer are described here.
Unit value transfer uses values for ecosystem services at a study site, expressed as a value per unit
(usually per unit of area or per beneficiary), combined with information on the quantity of units at the
policy site to estimate policy site values. Unit values from the study site are multiplied by the number
of units at the policy site. Unit values can be adjusted to reflect differences between the study and
policy sites (e.g. income and price levels).
Value function transfer uses a value function estimated for an individual study site in conjunction with
information on parameter values for the policy site to calculate the value of an ecosystem service at
the policy site. A value function is an equation that relates the value of an ecosystem service to the
characteristics of the ecosystem and the beneficiaries of the ecosystem service. Value functions can
be estimated from a number of primary valuation methods including hedonic pricing, travel cost,
production function, contingent valuation and choice experiments.
Meta-analytic function transfer uses a value function estimated from the results of multiple primary
studies representing multiple study sites in conjunction with information on parameter values for the
policy site to calculate the value of an ecosystem service at the policy site. A value function is an
equation that relates the value of an ecosystem service to the characteristics of the ecosystem and
the beneficiaries of the ecosystem service. Since the value function is estimated from the results of
multiple studies, it is able to represent and control for greater variation in the characteristics of
ecosystems, beneficiaries and other contextual characteristics. This feature of meta-analytic function
transfer provides a means to account for simultaneous changes in the stock of ecosystems when
estimating economic values for ecosystem services (i.e. the “scaling up problem”). By including an
explanatory variable in the data describing each “study site” that measures the scarcity of other
ecosystems in the vicinity of the “study site”, it is possible to estimate a quantified relationship
between scarcity and ecosystem service value. This parameter can then be used to account for
changes in ecosystem scarcity when conducting value transfers at large geographic scales (see Brander
et al., 2012, for a detailed explanation of this method).
3
http://biodiversity.europa.eu/maes
D3.2: Economic mapping and assessment methods 19 | Page
__________________________________________________________________________________
These three principal methods for transferring ecosystem service values are summarised in Table 3
together with their respective strengths and weaknesses, and the tier to which they are assigned. The
choice of which value transfer method to use to provide information for a specific policy context is
largely dependent on the availability of primary valuation estimates and the degree of similarity
between the study and policy sites. In cases where value information is available for a highly similar
study site, unit value transfer may provide the most straightforward and reliable means of conducting
value transfer. On the other hand, when study sites and policy sites are different, value function or
meta-analytic function transfer offers a means to systematically adjust transferred values to reflect
those differences. Similarly, in the case that value information is required for multiple different policy
sites, value function or meta-analytic function transfer may be a more accurate and practical means
for transferring values. Using meta-analytic functions that include a parameter for ecosystem scarcity
provides a means to account for simultaneous changes in the stock of ecosystem on the value of all
ecosystem services (i.e. more accurately “scale-up” ecosystem service values). See Brander (2013) for
further guidance on value transfer methods.
Table 3: Value transfer methods, strengths, weaknesses and tier (adapted from Table 3, Brander
2013)
Approach
Strengths
Weaknesses
Tier
Unit value
transfer
Select appropriate
values from existing
primary valuation
studies for similar
ecosystems and socio-
economic contexts.
Adjust unit values to
reflect differences
between study and
policy sites (usually for
income and price levels)
Simple
Unlikely to be able to
account for all factors
that determine
differences in values
between study and
policy sites. Value
information for highly
similar sites is rarely
available
1
Value function
transfer
Use a value function
derived from a primary
valuation study to
estimate ES values at
policy site(s)
Allows differences
between study and
policy sites to be
controlled for (e.g.
differences in population
characteristics)
Requires detailed
information on the
characteristics of policy
site(s)
2
Meta-analytic
function transfer
Use a value function
estimated from the
results of multiple
primary studies to
estimate ES values at
policy site(s)
Allows differences
between study and
policy sites to be
controlled for (e.g.
differences in population
characteristics, area of
ecosystem, abundance
of substitutes etc.).
Practical for consistently
valuing large numbers of
policy sites.
Requires detailed
information on the
characteristics of policy
site(s). Analytically
complex
3
20 | Page D3.2: Economic Mapping Methods
__________________________________________________________________________________
4. Methods for mapping economic values for ecosystem services
The economic value of an ecosystem service is determined by its supply and demand. The supply side
of an ecosystem service is largely determined by ecological processes and characteristics that may be
influenced by human activities, either deliberately or inadvertently. The demand side is largely
determined by the characteristics of human beneficiaries of the ecosystem services. The determinants
of both the supply and demand of ecosystem services are spatially variable, which makes the
estimation of ecosystem service values inherently spatial. Value mapping addresses this spatial
dimension of ecosystem service valuation. Economic value mapping can be defined as the valuation
of ecosystem services in monetary terms across a relatively large geographic area that includes the
examination of how demand and supply vary across space. It therefore includes not only studies that
produce graphical value maps but also studies that explicitly address spatial variability in values.
The estimation of accurate values for ecosystem services requires that account is taken of spatial
heterogeneity in biophysical and socioeconomic conditions. Spatial factors that affect the supply of
ecosystem services include among others: ecosystem area (possibly characterised by a non-linear
relationships and thresholds), networks, resilience, biodiversity, fragmentation, disturbance, and
accessibility. Spatial factors that affect demand for ecosystem services include: the number of
beneficiaries, culture and preferences, ecosystem area, distance to the ecosystem, and the availability
of substitutes and complements.
4
Value mapping thereby reveals additional information as compared to conventional valuation, which
is potentially useful for designing effective policies and institutions for maintaining ecosystem service
supply. Besides communication and visualisation, value mapping makes site-specific ecosystem
service values available on a large spatial scale. Spatially explicit ecosystem service value maps have
specific advantages for several policy applications including ecosystem service accounting, land use
policy evaluation, conservation planning, targeting land restoration activities and designing payments
for ecosystem services. It allows decision makers to extract estimated values from a map or database
for the locations or areas of policy interest in order to evaluate potential policy measures.
4.1. Representing economic values on maps
The representation of economic values on maps involves estimating variable combinations of supply
and demand across spatial units and plotting the resulting values. The spatial units used in a value
map can be land parcels (e.g. polygons representing ownership), ecosystem patches (e.g. polygons
representing distinct ecosystems of different type), ecosystem units (e.g. raster grids of ecosystem
type), grid cells (e.g. raster grids with land use/land cover), or beneficiaries (e.g. people plotted using
residential or activity location). In most cases, spatial units are used to represent the ecosystem that
supplies the ecosystem service, but mapping values by the location of beneficiaries can be useful in
some decision making contexts (e.g. for representing the distributional consequences of changes in
ecosystem service provision across communities; or for designing payment mechanisms for ecosystem
services).
Figure 5 provides a conceptual representation of spatially variable combinations of supply and
demand across nine spatial units within a mapped study area. In order to map ecosystem service
values, each spatial unit is treated as a separate sub-market for the ecosystem service; variation in
both supply and demand results in variation in economic value. Spatial unit 2 is characterised by both
high demand and supply, and consequently high value for the ES; whereas spatial unit 3 represents
the case of high demand but low supply, and consequently lower value. Spatial unit 5 represents a
location with high supply but low demand, and consequently low value. Spatial unit 6 represents a
4
See Bateman et al. (2002), Hein et al. (2006), and Schaafsma (2015) for more detailed discussions of spatial
determinants of ecosystem service demand and supply.
D3.2: Economic mapping and assessment methods 21 | Page
__________________________________________________________________________________
location with demand for the ES but zero supply, and consequently zero value. Conversely, spatial unit
9 represents a situation with ES supply but zero demand, and again zero value.
Methods for mapping ecosystem service values can focus on spatial variations in supply, demand, or
ideally the combination of both determinants. In general terms, bio-physical methods are used to
estimate the spatially variable quantities of ecosystem services supplied (e.g. probability of flood
damage, quantity of clean water, area of recreational space, tonnes of carbon stored) and economic
methods are used to estimate spatially variable marginal values per unit of ecosystem service used or
consumed. Mapping economic values therefore necessarily involves linking biophysical ecosystem
supply maps with economic valuation methods.
Figure 5: Conceptual representation of variation in supply and demand for an ecosystem service
across spatial units within a mapped study area. Each spatial unit is a separate sub-market in which
the value of an ecosystem service can vary substantially depending on location specific demand and
supply.
Methodologies for biophysical mapping of ecosystem service supply are addressed in ESMERALDA
report D3.3. These methods are be summarised in the following categories: 1. Spatial proxy methods;
2. Phenomenological models; 3. Macro-ecological models; 4. Trait-based models; 5. Process-based
models; 6. Statistical models; 7. Ecological connectivity models; 8. State and transition models; 9.
Conceptual models; 10. Integrated modelling frameworks; 11. Direct measurements.
Economic methods for estimating spatially variable ecosystem service demand, or marginal values per
unit of ecosystem service supplied, are described in section 3. The process of representing these
D
S
1
D
S
2
D
S
4
D
S
5
D
S
D
S
D
S
D
S
9
3
6
7 8
22 | Page D3.2: Economic Mapping Methods
__________________________________________________________________________________
values on maps mirrors that of conducting value transfers. Following Schaegner et al. (2013), these
methods can be placed into four categories:
1. Unit value approach: a constant value per unit of ecosystem service is applied to estimates of
supply (or a constant value per unit area of ecosystem is applied to the area of ecosystem as
a proxy of supply). Thus, variations in ecosystem service value across space result only from
variations in supply. Unit values can be obtained from existing applications of the valuation
methods reviewed in section 2. The unit value approach has been the predominant
methodology used for valuing ecosystem services within the value-mapping literature
(Schaegner et al., 2013).
2. Adjusted unit values approach: adjusts values per unit of ecosystem service across spatial
units using simple variables in order to account for spatial variations in value. Typically, such
variables are population density, income levels or price levels. Thereby, such adjustments
respectively account for the number of beneficiaries of an ecosystem service, the effect of
income levels on willingness to pay, and differences in price levels.
3. Value function approach: estimates spatially variable unit values across the study area using
a value function, which may contain multiple spatial variables (e.g. income, household size,
distance to ecosystem). A value function is typically estimated from a single primary valuation
study, which may be conducted within the mapped study area (subsequent use for mapping
involves spatial extrapolation of results) or outside of the mapped study (in which case the
mapping involves value transfer in a strict sense). Parameter values for each spatial unit in the
study area are plugged into the value function to estimate unit values vary across spatial units.
Value functions can be obtained from a number of primary valuation methods including
hedonic pricing, travel cost, production function, avoided damage cost, contingent valuation
and choice experiment methods.
4. Meta-analytic value function transfer approach: also enables the estimation of unit values
that vary across spatial units within the study area by applying a value function containing
multiple spatial variables. In this case, however, the function is estimated from the results of
multiple primary valuation studies, which increases the scope for including additional spatial
variables that might not be feasible within a single primary valuation study (e.g. crowdedness,
accessibility, fragmentation, scarcity).
4.2. Scaling up economic values
The currently available information on the value of ecosystem services is mostly for relatively small
spatial scales (e.g. distinct individual ecosystems). Assessments of changes in ecosystem service
provision at larger geographic scales, e.g. national level reporting of ecosystem services, require the
“scaling-up” of value information. The term “scaling up” is used to describe the transfer and
aggregation of values that have been estimated for localised changes in individual ecosystem sites to
assess the value of simultaneous changes in multiple ecosystem sites within a large geographic area
(e.g. country or region). Scaling-up ecosystem service values is therefore highly relevant for the MAES
process and ecosystem service accounting.
At the level of individual ecosystem sites, marginal unit values for ecosystem services are likely to vary
with the characteristics of the ecosystem site (area, integrity, and type of ecosystem), beneficiaries
(number, income, preferences), and context (availability of substitute and complementary sites and
services). The estimation of the value of ecosystem services from individual ecosystem sites therefore
needs to account for these characteristics. Localised changes in the extent of an individual ecosystem
may be adequately evaluated in isolation from the rest of the stock of the resource, which is effectively
assumed to be constant.
D3.2: Economic mapping and assessment methods 23 | Page
__________________________________________________________________________________
When valuing simultaneous changes in multiple ecosystem sites within a region, however, it is not
sufficient to estimate the value of individual ecosystem sites and aggregate them without accounting
for the changes that are occurring across the stock of the resource. As an environmental resource
becomes scarce, its marginal value will tend to increase. This means that ignoring the scarcity effect
on the marginal values of individual ecosystem sites, as is often done in scaling up exercises, is likely
to underestimate the value of the change. Valuations of changes in the stock of ecosystems across
large geographic areas, such as for national ecosystem assessments or ecosystem service accounts,
therefore need to account for the effects of scarcity on marginal values. Brander et al. (2009; 2012)
propose an extension of the meta-analytic function transfer methodology to specifically address the
challenge of scaling up ecosystem service values. The steps in this method for scaling up values for
changes in across the stock of ecosystems within a region are summarised here:
1. Construct a database of primary valuation estimates for the ecosystem of interest.
Standardise value estimates in terms of monetary units per unit area of ecosystem per year
(e.g. per hectare per year).
2. Estimate a meta-analytic value function for the ecosystem in question. The dependent
variable in the value function is the standardised value (defined in step 1). The estimated value
function should include explanatory variables that capture study site characteristics (i.e. size,
services provided); context characteristics (i.e. abundance of the ecosystem in the region);
socio-economic characteristics of beneficiaries (i.e. size of relevant population, income); and
study characteristics (i.e. valuation method used to produce each primary value estimate
included in the meta-analysis).
3. Construct a database of policy sites(ecosystems) in the region of interest using a Geographic
Information System (GIS) to include information on the variables in the meta-analytic value
function (i.e. size of each ecosystem site, abundance of the ecosystem within the vicinity of
each site, population in the vicinity of each site, and income level of the population). The
database should contain values for each of these variables at pre- and post-change states for
each policy site (e.g. at two different points in time or for two different policy scenarios).
4. For each policy site, estimate the marginal value per hectare at the pre-change and post-
change levels. This is done by substituting in pre- and post-change variable values into the
meta-analytic value function. Calculate the average of the pre-change and post-change
marginal values per hectare for each site in order to approximate the average per hectare
value of the area that is lost.
5. Multiply the value per hectare for each site by the change in area for each site. This gives an
estimate of the value of the change in size of each ecosystem site.
6. Aggregate the estimated changes in value of individual policy sites to the regional or national
level. This gives the annual value of the change in ecosystem service provision at that scale.
4.3. Example value mapping applications
In this section, we provide a selection of value mapping applications that illustrate alternative
approaches to mapping ecosystem service values. Box 2 presents the mapped economic values of five
provisioning and regulating ecosystem services provided by the Serra de S. Mamede national park in
24 | Page D3.2: Economic Mapping Methods
__________________________________________________________________________________
Portugal; unit values for each ecosystem service are estimated using market prices and value transfer
methods. Box 3 presents a national map of the value of agricultural production in Spain (estimated
using market prices) and its spatial correspondence with ecological values (estimated using socio-
cultural valuation methods). Box 4 presents some of the results of a spatially explicit scenario analysis
for the UK National Ecosystem Assessment, which mapped a wide range of market and non-market
ecosystem services. Box 5 presents mapped values for changes in landslide risk in Adjara autonomous
republic of Georgia; avoided damage costs from landslides under alternative scenarios are estimated
and mapped for individual villages. Box 6 summarises the results of a study that maps changes in the
value of coral reef recreation in Southeast Asia using a predictive model of recreational visits and a
meta-analytic value transfer approach to estimate spatially variable values per visit. Box 7 presents a
global map of changes in human welfare resulting from projected changes in freshwater quality;
spatially variable values are estimated using a meta-analytic value function for water quality.
Box 2. Mapping the economic value of ecosystem services provided by the Natural Park of Serra de S. Mamede (PNSSM), Portugal (Marta-Pedroso
et al., 2014).
Based on land-use and cover, a mapping approach for economic value was implemented (Table 1) and the outcomes presented in Figure 1.
Figure 1 Economic value of ES considered in the PNSSM.
Table 1 Overview of selected ES, ES indicators and value mapping approaches (Tier 1) used to estimate the economic value of the PNSSM.
Biophysical Mapping
Economic Value Mapping
(€.ha-1.yr-1)
26 | Page D3.2: Economic Mapping Methods
__________________________________________________________________________________
Section
Division
Group
Class
ES Specification
Indicator unit
Valuation
Method
Description
Provisioning
Nutrition
Biomass
Crops
Crops production
ton.ha-1.yr-1
Market Price
Standard Gross margin (SGM) of each crop.
SGM for each land use class was estimated as
SGMLUC j = ΣAiSGMi/ΣAi,, where Ai represents
the area of crop i in the land use class (LUC) j.
SGMi and Ai were obtained from official
statistics.
Livestock
Stocking rate
LU.ha-1.yr-1
Market Price
Standard Gross margin (SGM) of pastures
typologies. An average LU (livestock unit) for
each different type of pasture was
considered.
Materials
Biotic materials
Non-food vegetal
fibers
Timber
production
m3.ha-1.yr-1
Market Price
ANPV (Annualized Net Present Value) of
timber given the Investment Return Analysis
for the species of interest provided by
Machado & Louro (2009). For mixed LULC
classes (i.e., when more than one forest
species was present), the value was weighted
according to an estimated cover percentage
per species.
Regulating
Regulation of
physico-chemical
environment
Atmospheric
composition and
climate
regulation
Global climate
regulation by
reduction of
greenhouse gas
concentrations
Carbon
sequestration/
emission
tonCO2.ha-1.yr-1
Value transfer
Unit Value: 79,5€/ton based on Stern (2006)
social cost of carbon estimations.
Amount of carbon sequestered/emitted
estimated in each pixel by considering the
land use transitions observed between 1990-
2006) was multiplied by the unit value.
Mediation of
flows
Mass flows
Mass
stabilisation and
control of
erosion rates
Avoided erosion
ton.ha-1.yr--1
Value Transfer
Unit value: (4.75 €. ha-1.yr-1) based on Marta-
Pedroso et al. (2007).
The avoided erosion value estimated in each
pixel was multiplied by the unit value.
Notes: Economic values adjusted using consumer price index when appropriate; ES Classification accordingly to CICES 4.3; Machado, H.& LOURO, G. Análise de Rentabilidade das
Áreas Submetidas a Regime Florestal. In Actas do 6.º Congresso Florestal Nacional. Ponta Delgada: Sociedade Portuguesa de Ciências Florestais, 2009. Pp. 883-889; Stern, N., 2006.
Executive summary (full). Stern Review Report on the Economics of Climate Change. http://webarchive.nationalarchives.gov.uk/20130129110402/http://www.hm-
treasury.gov.uk/d/Executive_Summary.pdf; Marta-Pedroso et al. (2007). Incorporating the benefits supplied by soil in agri-environmental policy efficiency analysis: the case of the Zonal
Program of Castro Verde (Portugal). Soil & Tillage Research 97: 7990
Box 3. Integrating economic and ecological values of agricultural ecosystem services in Spain
(Santos-Martín F. et al., 2016)
This study present a nationwide study of Spanish agro-ecosystems in which the spatial distribution of
food provisioning services indicators has been mapped. First we quantify and mapped the value of
Spanish agricultural provisioning services expressed in biophysical (t/ha/yr) and monetary (€/ha/yr)
units. Secondly we mapped High Nature Value farming areas” in Spain, with the aim of identify
important and valuable habitats for species with a high ecological value. Finally we explore the spatial
correlations between the economic and ecological value with the objective to identify those areas
with high values on both dimensions that should be considered as priority for landscape management
intervention. These results show how current land-use management in Spain is creating a landscape
dichotomy between areas with agricultural practices with a high ecological value and other land-uses
managed under intensification practices that is creating a clear negative effect on the maintenance
of essential functions to maintain the good condition of majority of Spanish agro-ecosystems.
Figure 1: Superimposition of the spatial representation of the economic value of the agricultural
production of Farming Areas with High Nature Value in Spain. In red: areas with a high economic value
and a low ecological value; In green areas with a high ecological value and a low economic value; in
black: areas with a high economic value and a high ecological value.
Box 4. Scenario, mapping and valuing ecosystem services in the UK National Ecosystem
Assessment
The UK National Ecosystem Assessment (NEA) provides a good example of bringing together the
development of plausible future scenarios using different socially developed story lines, modelling
the impacts of these to understand biophysical changes and then building on this to understand
changes in associated monetary and non-monetary values. The scenarios used had similar
foundations e.g. aging populations and declining global resource availability, but were augmented
28 | Page D3.2: Economic Mapping Methods
__________________________________________________________________________________
with different emphases on development choices ranging from environmental awareness and
ecological sustainability to national self-sufficiency and pursuit of economic growth irrespective of
the wider implications. To compare the outcomes, a range of market and non-market ecosystem
service benefits were valued. However, the authors felt it was inappropriate to value biodiversity,
citing particularly controversies around the robustness of valuing non-use existence values, and
hence the analysis across the scenarios was presented in a range of ways. This included, for example,
ranking scenarios in terms of their economic value, but excluding scenarios which led to a decline in
biodiversity; and also by presenting maps of the market and non-market values alongside the
estimated impacts of the chosen indicator of biodiversity (bird diversity) as illustrated in the maps
below. The links between the economic value and the biophysical underpinning is clear for example
in the maps of changes in urban green space value (fourth from left), which are focused around major
cities. Being unable to value biodiversity means that cost benefit analysis (CBA) alone cannot be used
to judge between scenarios, but as the UK NEA itself points out CBA is simply an informational input
to the decision making process, using more of the supporting information by comparing across maps
of values (monetised or not) more of the trade-offs and complementarities become visible.
Box 5. Mapping the economic value of landslide regulation by forests in Georgia (Brander et al.,
2017)
This study develops a methodology for mapping the value of forests in mitigating landslide risks and
applies it at a regional scale for the Adjara Autonomous Republic, Georgia. Like the rest of Georgia,
Adjara is mostly mountainous and its steep slopes are prone to landslides. By mapping the value of
landslide regulation by forests, the study aims to deliver information to support political and
administrative decision-making regarding long term forestry management.
The general methodological framework for quantifying the economic value of landslide regulation
as an ecosystem service provided by forests is represented in Figure 1. The approach involves first
developing land cover maps for a baseline scenario and alternative policy scenarios. Spatial data on
land cover is then combined with a bio-physical model of sediment retention and export to estimate
spatially variable rates of sediment export as a proxy measure of landslide susceptibility. In the case
study application we use the InVEST model to quantify changes in sediment export resulting from
changes in land cover. The data on sediment export is combined with spatially referenced historic
data on the frequency of landslide damage to houses and used to estimate a predictive function for
landslide damage. To model changes in the frequency of landslide damages under alternative policy
scenarios, spatial data on sediment export under each future scenario is fed into this function to
predict changes in landslide damage frequency. The costs of predicted damages are estimated using
data on compensation payments to impacted households.
Figure 1. Methodological framework for the valuation of landslide damages
The case study application for Adjara developed a baseline land cover scenario for the period 2015-
2035 and two alternative future scenarios representing increased forest degradation and
restoration storylines respectively. Land cover changes under each scenario are modelled in a GIS
and the resulting changes in sediment export are modelled using the InVEST tool. Changes under
each scenario are assessed at two points in time (2020 and 2035) in order to enable the evaluation
of short term and long term impacts on landslide damages. The mapped changes (relative to the
Historicallandslide
damagefrequencies
Sedimentexportdata
forbaselinescenario
InVEST
Sedimentreten onand
exportmodule
Data
Landslidedamage
frequencyequa on
Sedimentexportdata
forpolicyscenarios
Predictedlandslide
damagefrequencyfor
policyscenarios
Historicdamage
costperlandslide
Predictedlandslide
damagecostsforpolicy
scenarios
Landcoverdata
(baselineandpolicy
scenarios)
Model
Predic ve
model
es ma on
Scenario
modelling
30 | Page D3.2: Economic Mapping Methods
__________________________________________________________________________________
baseline) in landslide damage under each alternative scenario and time step are represented in
Figure 2.
Figure 2. Spatial distribution of annual change in landslide damages (US$/year)
Box 6. Coral reef recreation values in Southeast Asia (Brander et al., 2015)
This study illustrates the process of mapping ecosystem service values with an application to coral
reef recreational values in Southeast Asia. The case study provides an estimate of the value of reef-
related recreation foregone due to the decline in coral reef area under a baseline scenario for the
period 2000-2050. This value is estimated by combining a visitor model, meta-analytic value
function and spatial data on individual coral reef ecosystems to produce site-specific values.
Following Sen et al. (2014), the selected methodology uses a combination of a validated model for
visits to coral reefs and a meta-analytic value function to estimate the value per visit. The
methodology involves the following steps:
1. Estimate a model of recreational visits to individual coral reef sites. The visitor model
relates the number of visits per day to the site and context characteristics of each coral
reef ecosystem such as degree of siltation or fishing damage.
2. Estimate a value function for coral reef recreation through a meta-analysis of existing
monetary estimates. The value function relates the value per visitor day to the
characteristics of the ecosystem and its surroundings.
3. Develop a database of coral reef ecosystems in Southeast Asia containing information on
the variables included in the visitor model and value function estimated in steps 1 and 2.
4. Develop a baseline scenario for the change in the quality and spatial extent of coral reef
ecosystems in Southeast Asia for the period 2000-2050. This baseline scenario is spatially
variable to reflect variation in location-specific pressures on coral reef ecosystems.
5. Combine the models and data generated in steps 1 through 4 to produce estimates of the
value of the loss in coral reef-related recreation under the baseline scenario. This
Degrada on2020 Restora on2020
Degrada on2035 Restora on2035
D3.2: Economic mapping and assessment methods 31 | Page
__________________________________________________________________________________
approach allows the estimation of spatially variable, site-specific values that reflect the
characteristics and context (e.g. pressure or threat) of each coral reef.
Values are mapped in order to communicate the spatial variability in the value of coral reef
degradation (see Figure 5). Although the aggregated change in the value of reef-related recreation
due to ecosystem degradation is not high, there is substantial spatial variation in welfare losses,
which is potentially useful information for targeting conservation efforts.
Figure 1: Loss in the annual value of coral reef-related recreation in 2050 due to business-as-usual
coral reef degradation.
Box 7. Global value of changes in water quality 2000-2050 (Hussain et al., 2011)
This study combines output data from a validated model (IMAGE-GLOBIO) with a meta-analytic
value function to estimate the economic value of global changes in water quality under a business-
as-usual scenario for the period 2000-2050. The analysis is performed at the resolution of 50km grid
cells. The supply of ecosystem services from water bodies (rivers and lakes) is implicitly modelled
within the meta-analytic value function. The results of this value transfer application are mapped
in order to communicate the spatial distribution of benefits (losses) derived from improvements
(declines) in water quality (see Figure 8). In this application, the spatial units used to map changes
in value are beneficiaries (households aggregated within 50km grid cells) rather than the rivers or
lakes providing the ecosystem services.
32 | Page D3.2: Economic Mapping Methods
__________________________________________________________________________________
Figure 1: Value map for changes in water quality 2000-2050 (Annual willingness to pay; USD; 2007
price levels)
5. Economic assessment methods
5.1. Introduction to economic assessment methods
Economic assessment methods are used for structuring information on the value of ecosystem
services into decision making, often in combination with other forms of information. It is important to
recognise that the economic assessment methods reviewed in this report are each applicable to
different decision contexts. The choice of which assessment method to use will largely be determined
by the type of decision problem and the availability of relevant information. Table 5 provides a
summary of each economic assessment method with a description of its application, strengths,
weaknesses and an indication of the tier to which it is assigned.
Table 5. Summary of economic assessment methods for ecosystem services
Economic
assessment
method
Application
Strengths
Weaknesses
Tier
Cost-Effectiveness
Analysis
Used for identifying
lowest cost policy
options to achieve a
given objective
Does not require
assessment of benefits
and is analytically
relatively
straightforward
Limited applicability to
ecosystem services
given complex and
multi-functional nature
of ES provision; and the
absence of single
quantified policy targets
1
Cost-Benefit
Analysis
Used to estimate the
economic performance
of investments and
policies
Provides a measure of
how much an
investment or policy
contributes to societal
wellbeing
Requires that all costs
and benefits are
quantified in monetary
terms; can result in
omission of important
effects
3
Multi-Criteria
Analysis
Used to rank alternative
investments and policies
Allows the inclusion of
effects that cannot be
expressed in monetary
terms
Heavily reliant on the
subjective judgement of
the analytical team
2
D3.2: Economic mapping and assessment methods 33 | Page
__________________________________________________________________________________
Economic
assessment
method
Application
Strengths
Weaknesses
Tier
Ecosystem Service
Accounting
Provides a structured
way of measuring the
economic significance of
ecosystem services that
is consistent with
existing macro-
economic accounts
Consistent accounting
rules enable the direct
comparison of ES
economic contribution
over time and with
other parts of the
economy
Methodological
challenges to include
highly important
ecosystem services
within the existing
accounting framework
(e.g. cultural services)
3
Corporate
Ecosystem Service
Review
Supports private sector
decision-makers to
manage business risks
and opportunities
arising from their
company's dependence
and impact on
ecosystems
Flexible methodology
allows firms to tailor
assessments to needs
Challenge to integrate
ecosystem service
assessments into core
business decision
making
2
Making decisions between alternative investments, projects or policies that affect the provision of
ecosystem services often involves weighing up and comparing multiple costs and benefits that are
measured in different metrics and are incurred at different locations and points in time. For example,
the establishment of a new protected area might involve costs in terms of the purchase of land,
compensation of local communities, and on-going maintenance and enforcement costs; and benefits
in terms of biodiversity conservation, recreational use and improved watershed services. These costs
and benefits are likely to be measured in different units, be incurred at different locations by different
groups of stakeholders, and have different time profiles. Organising, comparing and aggregating
information on such a complexity of impacts; and subsequently choosing between alternative options
with different impact profiles requires a structured approach. Economic methods for assessment,
evaluation or appraisal of complex decision contexts provide systems for structuring the information
and factors that are relevant to a decision.
There are a number of economic assessment methods available to help decision makers to structure
the information and factors that are relevant to a decision and to select between alternative
investments, projects or policies. The choice of which assessment method to use will largely be
determined by the type of decision problem and the availability and nature of information related to
each potential option. To understand the differences between economic assessment methods, we
describe the procedural steps of each approach, which are often comparable yet differ in subtle ways.
For decisions that involve selecting between options to achieve a single specific goal (e.g.
meeting a specified ecological standard, supplying a specified quantity of clean water,
sequestering a targeted quantity of carbon) and where all costs can be expressed in monetary
terms, the cost-effectiveness analysis (CEA) method can be used. This approach therefore
does not involve any assessment of what the benefits are of meeting the objective but only
compares alternative options in terms of their costs.
When all the impacts of alternative options can be quantified in monetary terms, the most
common economic assessment method is cost-benefit analysis (CBA). This assessment
method involves summing up the value of the costs and benefits of each option and comparing
options in terms of their net benefits (i.e. the extent to which benefits exceed costs).
In the situation that the relevant criteria (costs and benefits) to the decision cannot be
expressed in monetary values, but can only be expressed in other units or in qualitative terms
34 | Page D3.2: Economic Mapping Methods
__________________________________________________________________________________
(i.e. impacts can be ranked in order of importance), multi-criteria analysis (MCA) is a useful
assessment method.
Ecosystem service accounting is a structured way of measuring the economic significance of
nature that is consistent with existing macro-economic accounts. The general aim of
ecosystem service accounting is also to highlight and quantify the importance of ecosystem
services to society and enable direct comparisons with other parts of the economy.
Corporate ecosystem service review is a structured methodology that helps private sector
decision-makers to proactively develop strategies to manage business risks and opportunities
arising from their company's dependence and impact on ecosystems.
It should be noted that CEA, CBA and MCA are general economic assessment methods (i.e. not
ecosystem service specific) that can be applied to help select between alternative investments,
projects and policies. In this report, the focus is on supporting decision-making regarding ecosystem
services. Although the main steps in the assessment methods remain relevant, the nature of
ecosystem-related decisions may require emphasis on specific types of input, particularly spatial
analysis. The decision-making context regarding the management of ecosystem services is often one
of spatial targeting or optimisation. Decisions are being made about where to invest in ecosystem
restoration (e.g. EU Biodiversity Strategy Target 2 to restore at least 15% of degraded ecosystems
5
),
establish protected areas, or target financial incentives to change the behaviour of land users. In such
cases, the spatial correspondence of costs and benefits relevant to the decision is of crucial
importance and mapping these inputs is a necessary step in the assessment process.
5.2. Cost-Effectiveness Analysis
Cost-effectiveness analysis (CEA) involves identifying the lowest cost option to achieve a given
objective.
6
CEA is an applicable assessment method for decisions that involve selecting between
alternative measures or technologies to achieve a single specific goal (e.g. meeting a specified
ecological standard, supplying a specified quantity of clean water, or sequestering a targeted quantity
of carbon) and for which all costs can be measured in monetary terms. The use of CEA is required in
river basin management plans under the EU Water Framework Directive
7
.
The steps in conducting a CEA are take the following sequence, but there may be feedback loops
between steps during the process. Step 1: Identify the environmental objective(s) involved (target
situation). Step 2: Determine the extent to which the environmental objective(s) is (are) met Step 3:
Identify sources of pollution, pressures and impacts now and in the future over the appropriate time
horizon and geographical scale (baseline situation). Step 4: Identify measures to bridge the gap
between the reference (baseline) and target situation (environmental objective(s)). Step 5: Assess the
effectiveness of these measures in reaching the environmental objective(s) Step 6: Assess the direct
(and if relevant indirect) costs of these measures. Step 7: Rank measures in terms of increasing unit
costs. Step 8: Determine the least cost way to reach the environmental objective(s) based on the
ranking of measures.
5
http://ec.europa.eu/environment/nature/biodiversity/comm2006/2020.htm
6
Note that the term “cost-effective” is often used to describe investment or policy options that result in a gain
in efficiency or, equivalently, for which benefits exceed costs. A “cost-effectiveness analysis”, however, only
involves ranking options that achieve a given target in order of their cost.
7
http://ec.europa.eu/environment/water/water-framework/index_en.html
D3.2: Economic mapping and assessment methods 35 | Page
__________________________________________________________________________________
This approach therefore does not involve any assessment of the benefits of meeting the policy target
but only compares alternative options in terms of their costs. As such, CEA is a relatively
straightforward assessment method to apply and is relevant to decision contexts in which a specific
policy target has been set. It does not, however, provide an indication of the magnitude of changes in
societal welfare resulting from implementing policy options (i.e. whether society is better or worse off
as a result of the decision). CEA of policy targets for ecosystem service provision are likely to require
mapped inputs given the underlying spatial variation in determinants of both ecosystem services and
the costs of supply (e.g. the opportunity costs of alternative land uses).
In practice, this economic assessment method is not frequently used in the context of managing
ecosystem services due to the complex and multifunctional nature of their provision. It is generally
not the case that a single specific goal for ecosystem service provision can be set and it becomes
necessary to consider the multiplicity and variability of benefits derived from alternative options.
Crossman and Bryan (2009) provide an example of how a cost-effectiveness analysis of meeting a
specified planning target for ecological restoration requires a spatial analysis of both the costs and
benefits resulting from alternative land use allocations. The multiple benefits from ecological
restoration and the many relevant secondary policy targets mean that it is not applicable to address
the land allocation decision in terms of meeting a single target at minimum cost. The assessment
therefore extends beyond a CEA and assesses both costs and benefits.
5.3. Cost-Benefit Analysis
Cost-benefit analysis (CBA) is the most commonly used economic assessment method for evaluating
and comparing investments, projects and policies. There is a call for the use of CBA in the appraisal of
investments under the Cohesion Policy 2014-2020 (European Commission 2014).
It is important to recognise the difference between a CBA that is carried out from the perspective of
society as a whole and CBA that is conducted from the perspective of an individual, group, or firm. If
applied from this latter perspective, CBA is generally used to determine the financial return of private
investments. This private application is commonly known as a ‘financial CBA’. Alternatively,
government departments apply CBA as the standard tool for evaluating investments, projects and
policies from the perspective of society as a whole. This so-called ‘extended CBA’ is used as a method
in which the societal costs and benefits of alternative options are expressed and compared in
monetary terms. The extended CBA provides an indication of how much a prospective project or
investment contributes to social welfare by calculating the extent to which the benefits of the project
exceed the costs essentially society’s ‘profit’ from a project. In this application, the CBA provides a
framework into which monetised ecosystem service values can be integrated. The main steps in
performing a CBA are presented in Figure 1. These steps are described below:
Figure 6: Methodological steps in cost-benefit analysis (source: Brander and van Beukering, 2015)
Define options
Identify negative impacts
(costs) and positive
impacts (benefits)
Identify distribution of
impacts
Quantify costs and
benefits in physical units
Value costs and benefits
in monetary terms
Calculate present value
of costs and benefits
Calculate net present
value subtract costs
from benefits
Conduct sensitivity
analysis on main
assumptions
Consider non-monetary
impacts
Select option
Impact
assessment
Scenario
development Valuation &
evaluation Selection
process
Advocacy of
preferred
options
Use of
valuation
Define options
Identify negative impacts
(costs) and positive
impacts (benefits)
Identify distribution of
impacts
Quantify costs and
benefits in physical units
Value costs and benefits
in monetary terms
Calculate present value
of costs and benefits
Calculate net present
value subtract costs
from benefits
Conduct sensitivity
analysis on main
assumptions
Consider non-monetary
impacts
Select option
Impact
assessment
Scenario
development Valuation &
evaluation Selection
process
Advocacy of
preferred
options
Use of
valuation
36 | Page D3.2: Economic Mapping Methods
__________________________________________________________________________________
The first step in a CBA is to identify the alternative options or alternatives to be considered. The
options under consideration will generally be specific to the particular problem and context, but may
include investments, projects, policies, development plans etc.
The impact assessment in a CBA starts with the identification of the complete set of negative impacts
(costs) and positive impacts (benefits) related to the policy or intervention options under
consideration. This includes costs and benefits accruing to all affected groups and individuals (not just
those involved in the project development) and costs and benefits that are incurred in the future. It is
important to describe the geographical and temporal boundaries of the analysis. This is especially
crucial for ecosystem services impacts since effects emerging from ecosystem change often show
major variations in time and space. The final step in the impact assessment phase is to quantify each
cost and benefit in relevant physical units for each year in which it occurs. Estimating changes in
ecosystem services requires specific expertise and models on ecological, hydrological and climatic
processes. For performing this last important step, the Esmeralda project develops a multi-tiered
flexible method for mapping and quantifying the impact on ecosystem services in biophysical units.
To conduct a CBA, all of the quantified positive and negative effects need to be expressed in monetary
units. In cases where costs and benefits are not directly observable in monetary terms in well-
functioning markets (as is the case for many ecosystem services), estimates need to be generated
using non-market valuation methods or value transfer. A summary of these methods is provided in
Annex 1. After estimating annual values, the time-series of costs and benefits are converted to present
values (PV), which involves discounting and summing values that occur in future years.
The economic performance of each alternative option can be calculated in three different ways: 1.
The net present value (NPV) of each option is calculated by subtracting the present value costs from
present value benefits. A positive NPV indicates that implementing a project will improve social
welfare. The NPVs of alternative investments can be compared in order to identify the most beneficial
project; 2. The benefit cost ratio (BCR) is the ratio of discounted total benefits and costs, and shows
the extent to which project benefits exceed costs. A BCR greater than 1 indicates that the benefits of
a project exceed the costs; 3. The internal rate of return (IRR) is the discount rate at which a project’s
NPV becomes zero. If the IRR exceeds the discount rate used in the analysis, the project generates
returns in excess of other investments in the economy, and can be considered worthwhile.
A final step in a CBA is to conduct sensitivity analysis to check the robustness of the conclusions to the
assumptions made. Another element is to estimate whether or not the omission of certain costs and
benefits that cannot be monetised affects the decision result.
An important drawback of CBA is the requirement that all costs and benefits need to be expressed in
monetary terms. Although a range of economic valuation methods are available to estimate values
for marketed and non-marketed ecosystem services, there are still considerable limitations to the
accuracy of estimated value in some cases. Furthermore, the application of non-market valuation
techniques can be expensive and time-consuming. For these reasons it may not be possible to
estimate monetary values for some costs and benefits and they cannot be entered into a CBA. In some
cases, the omitted impacts can be significant and therefore alternative evaluation methods are
needed.
Box 8. Cost-Benefit Analysis of expanding marine protected areas (Brander et al., 2015)
This study provides an example application of a spatial CBA that estimates the net benefits of
expanding global marine protected areas (MPAs) to 10% and 30% coverage of total marine area.
The study developed a set of six mapped scenarios for the global expansion of MPAs (see Figure 2).
The scenarios vary along two dimensions: 1. the coverage of MPAs as a proportion of total marine
area; 2. the characteristics of target locations for MPAs in terms of biodiversity and degree of human
impact.
D3.2: Economic mapping and assessment methods 37 | Page
__________________________________________________________________________________
Figure 1. Current and future global distributions of marine protected areas
The methodological framework for the CBA follows that of Balmford et al. (2011), Bateman et al.
(2011), Hussain et al. (2011) and Brander et al. (2012) and is represented in Figure 1. In particular it
incorporates spatially explicit estimations of bio-physical effects, benefits and costs.
The results of the cost-benefit analysis show that all six scenarios for expanding MPAs to 10% and
30% coverage are economically advisable. The ratios of benefits to costs are in the range 3.17
19.77. In the case of the scenario that achieves 10% coverage of total marine area and targets areas
with high biodiversity and low human impact, each dollar invested yields a return of around 20
dollars in benefits.
Basemap Credits: Esri, DeLorme, GEBCO, NOAA NGDC, and other contributors
Current M PAs E2E-10%
E2E-30%
P2M-10%
P2M-30%
P2P-10%
P2P-30%
Easy to Expand
Protect to Mitigate
Present
Protect to Preserve
38 | Page D3.2: Economic Mapping Methods
__________________________________________________________________________________
Figure 2. Methodological framework for assessing the net benefits of expanding marine protected
areas. Adapted from Figure 2, Balmford et al. (2011); and Figure 2, Hussain et al. (2011).
Box 9. Example application of a spatial Cost-Benefit Analysis, River Schelde, Belgium (Broekx et
al. 2011)
Major infrastructure works were planned in the Scheldt estuary, flowing from Belgium into the
Netherlands, including the deepening of the fairway to the harbour of Antwerp and complementary
measures to protect the land from storm floods coming from the North Sea.
A Cost-Benefit Analysis was carried out, taking into account the value of ecosystem services using a
number of valuation methods. In addition to technical measures such as a storm surge barrier and
dikes, two types of floodplains were considered: a system where the existing land use is maintained
(mostly agriculture) and a system with controlled reduced tide that delivers a large number of ES.
Regulating services were quantified through the OMES-model. This process based ecosystem model
was developed for the Scheldt estuary in order to study the possible impact of different water
management strategies on the ecosystem. This model was based on a monitoring program for all
major groups (plankton, benthos, avifauna, fish, and littoral vegetation), carried out by different
universities and institutes, and simulated major ecosystem processes, such as the C, N and P cycles.
The OMES-model makes distinctions between the impact of riverine wetlands in the fresh water,
brackish and salt zone of the river. The value was estimated through replacement costs and avoided
costs.
The flood control service was quantified by a large hydrodynamic model. Based on land use data,
damage factors and replacement values for houses, household furniture, roads, industry, crops and
other damage categories the flood damages in the inundated area were estimated. A contingent
valuation study was performed to value the recreational value of new floodplains.
Results of the cost benefit analysis show that an intelligent combination of dikes and floodplains
can offer similar safety benefits, but far more co-benefits at lower costs compared to more drastic
measures such as a storm surge barrier near Antwerp. The hydrodynamic modelling also indicated
that floodplains are necessary to ensure safety levels in the longer term in the Scheldt basin. Merely
dike heightening mainly causes a shift in flooded areas but does not suffice to importantly reduce
D3.2: Economic mapping and assessment methods 39 | Page
__________________________________________________________________________________
future flood risk. Additionally results showed that the benefits of the controlled reduced tidal areas
(RTA) mostly exceed the benefits of the controlled inundation area (CIA) with agricultural use.
The Dutch and Flemish government approved an integrated plan consisting of the restoration of
approximately 2500 ha of intertidal and 3000 ha of non-tidal flooding areas, the reinforcements of
dikes and dredging to improve the fairway to Antwerp.
Table 1: Alternative options for flood protection in the Cost-Benefit Analysis (phase 1: different
measures, phase 2 optimisation)
Phase 1
Phase 2
Storm
surge
barrier
Over-
schelde
Dykes
(340km)
Floodplains
(CIA, 1800
ha)
Floodplains
(RTA, 1800
ha)
Floodplains
(1325 ha) +
dykes (24
km)
Investment and
maintenance costs
387
1.597
241
140
151
132
Loss of agriculture
16
19
12
Flood protection
benefits
727
759
691
648
648
737
Ecological benefits
8
56
9
Other impacts:
- shipping
- visual intrusion
-1
-3
-3
-5
Total net benefits
339
-837
451
498
530
596
Payback period
(years)
41
/
27
17
14
14
All figures are net present values in million Euro 2004, based on central estimates for economic
growth and discounting (4%). Non-use values for nature development are not included in the figures.
40 | Page D3.2: Economic Mapping Methods
__________________________________________________________________________________
5.4. Multi-Criteria Analysis
Multi-criteria analysis (MCA) has become a well-established tool for decision-making that involves
conflicting or multiple objectives. MCA can be used to establish preferences between alternative
options by reference to a set of measurable criteria that the decision making body has defined. Unlike
in a CBA, criteria do not need to be quantified in a common metric (i.e. money). Instead MCA provides
a number of alternative ways of aggregating the data on individual criteria to provide indicators of the
overall performance of options. This allows the inclusion in the analysis of effects that cannot be
expressed in monetary terms. The basic idea behind MCA is to allow the integration of different
objectives (or criteria) without assigning monetary values to all of them. In short, MCA provides a
systematic method for comparing these criteria, some of which may be expressed in monetary terms
and some of which are expressed in other units. The main steps in performing a MCA are presented
in Figure 4.
Figure 7: Methodological steps in multi-criteria analysis (source: Brander and van Beukering, 2015)
Impact assessment in a MCA involves identifying and defining all criteria that are relevant to the
decision problem. These include all important categories of negative and positive effects resulting
from the options under consideration. In a MCA it is possible to include criteria that are difficult to
quantify and can perhaps only be assessed in qualitative terms such as political sensitivity, equity and
irreversibility. The quantification of the different effects is summarised in an “effects table”, which is
a matrix with the alternative options listed in the columns and the criteria listed in the rows. The
effects table is completed by assigning scores to each criterion for each alternative. Information on
the magnitude of each criterion can be expressed in monetary units, physical units, or simply on a
qualitative scale. Data on impacts can be collected from surveys, existing data, experts, or
stakeholders. In cases in which the spatial distribution of impacts is important to the decision, the data
on impacts can be represented on maps. To enable the direct comparison of different criteria,
standardisation of scores for each criterion to a common interval scale is conducted (usually to values
between 0-100 or 0-1). There are several software packages available that can be used to help with
the computations in MCA.
8
MCA does not explicitly value the criteria in monetary terms but instead applies weighting of criteria
to quantify the relative importance of each criterion in the decision process. Weights can be derived
from existing information or from stakeholders by asking them to state their preferences for the
8
A number of software packages are available to structure and process information in an MCA, including:
DEFINITE, HIVIEW, MACBETH, VISA and ILWIS.
Define options
Define criteria
(costs & benefits)
Create effects table
Assign scores for each
criteria
Weigh criteria
Rank options
Conduct sensitivity &
uncertainty analysis on
main assumptions
Select option
Impact
assessment
Scenario
development Valuation &
evaluation Selection
process
Standardise scores
to common interval scale
Advocacy of
preferred
option
Use of
valuation
Create
consensus &
awareness
Define options
Define criteria
(costs & benefits)
Create effects table
Assign scores for each
criteria
Weigh criteria
Rank options
Conduct sensitivity &
uncertainty analysis on
main assumptions
Select option
Impact
assessment
Scenario
development Valuation &
evaluation Selection
process
Standardise scores
to common interval scale
Advocacy of
preferred
option
Use of
valuation
Create
consensus &
awareness
D3.2: Economic mapping and assessment methods 41 | Page
__________________________________________________________________________________
various criteria. By combining the standardised scores and weights of the criteria, the alternative
options can be ranked, usually through a weighted summation of criteria scores for each alternative.
Similar to CBA, MCA applies sensitivity and uncertainty analysis to assess the robustness of the ranking
result to changes in weights and scores. Finally, based on the ranking of options and the sensitivity of
the results, a decision maker can select the most preferred option.
A key strength of MCA is that it is not necessary to quantify all impacts in monetary terms. This means
that complex and time-consuming valuation studies of all environmental impacts can be avoided, and
that qualitative criteria such as political sensitivity can be included in the decision framework. MCA
can therefore provide a degree of structure, analysis, and openness to decision problems that lie
beyond the practical reach of CBA.
MCA is, however, heavily reliant on the judgement of the analytical team for defining alternatives and
criteria, estimating the relative importance of criteria and, to some extent, in calculating and inputting
data into the effects table. The subjectivity that pervades these processes can be a matter of concern.
The involvement of stakeholders in defining criteria and setting weights can also be time consuming
process if conducted using surveys, interviews or deliberative methods. Another important limitation
of MCA is that the results do not necessarily show whether alternative options produce welfare gains
or losses. Unlike CBA, there is no decision rule (such as a positive NPV, a BCR greater than 1, or an IRR
greater than the market interest rate) that indicates that benefits exceed costs. In MCA, as is also the
case with CEA, the analysis can only produce a ranking of alternative options and does not indicate
whether the options result in a welfare improvement. It is, however, often possible to include a
business-as-usual alternative in the set of options, and this can be used as a reference point to indicate
whether the other options are better or worse than undertaking no action.
Box 10. Spatial Multi-Criteria Analysis of habitat restoration in the River Frome catchment,
Dorset, England (Newton et al., 2012)
This study provides an example of a spatial MCA of ecosystem restoration options for potential
landscape-scale habitat restoration in the catchment of the River Frome in Dorset, England. The
analysis involved mapping 8 ecosystem services, four of which were quantified in monetary terms
using market prices (carbon storage, arable crops, livestock and timber) and four that were
qualitatively assessed using a survey of stakeholders and a ranking approach (flood risk mitigation,
aesthetic, recreational and cultural value). Maps were produced for each ecosystem service and
habitat restoration scenario by estimating values according to land cover type. The costs of
restoration were estimated as capital cost of habitat establishment and a maintenance cost per
hectare; and the opportunity cost of ecosystem services negatively affected by restoration (i.e.
arable crops and timber). A 10-m grid cell raster map was generated for each criterion (ecosystem
service) for each of the scenarios, and all criterion maps were combined in a spatial MCA using a
weighted-sum method. The results if the MCA consistently ranked restoration scenarios above a
non-restoration comparator, reflecting the increased provision of multiple ecosystem services.
However, restoration costs consistently exceeded the market value of ecosystem services.
5.5. Ecosystem Service Accounting
5.5.1. Introduction to ecosystem service accounting frameworks
Ecosystem service accounting frameworks aim to provide a structured way of measuring the economic
significance of nature that is consistent with existing macro-economic accounts. They can help to
42 | Page D3.2: Economic Mapping Methods
__________________________________________________________________________________
identify trends and drivers of ecosystem change within the wider economy and society. By linking to
the System of National Accounts (SNA) they can provide comprehensive, integrated and consistent
data sets to support national decision-making. Ecosystem service accounting is part of Action 5 of the
EU Biodiversity Strategy, requiring Member States to “promote the integration of these [ecosystem
service] values into accounting and reporting systems at EU and national level by 2020”.
This section provides a review of selected ecosystem services accounting initiatives in Europe and
elsewhere. The descriptions of the initiatives focus on operational details (agency, timeframe,
ecosystems, ecosystem services, goals) and valuation methods (general methodology, specific method
per ecosystem service).
There are a number of on-going initiatives that aim to develop recommendations for integrated
natural capital accounting and the incorporation of ecosystem service values in national accounts.
These initiatives are at various stages of development and closely linked to already existing satellite
accounting systems around the core SNA in several countries, focusing primarily on provisioning
services such as timber, and natural capital such as subsoil minerals. An important question is to what
extent ES can be fully integrated into the core SNA or included as satellite accounts around the SNA,
either in physical or monetary terms. The approach taken will (or should) ultimately depend on the
question one would like to see answered. The SEEA guidance on ecosystem accounting encompasses
a broad description of the conceptual framework, which includes discussion on the scope and purpose
of the accounts along with the proposed accounts, the classification of ecosystem services, the
definition and measurement for the ecosystem accounting units and the valuation and recording
methods of physical and monetary flows and stocks (United Nations Statistical Division, 2012).
An important issue for accounting is the distinction between ecosystem services whose values are
already implicitly accounted for in conventional SNA (e.g., pollinators to agricultural production) and
those services whose values are not (e.g., free access recreation in nature areas). In the former case,
the challenge is mainly attribution: what fraction of value added of a sector or the economy should be
attributed to what ecosystem services? In the latter case, conventional GDP will be augmented by
hitherto unpriced goods and services (e.g., carbon storage or flood protection). This involves extending
both the production boundary (i.e. the flows / transactions) and the asset boundary (i.e. the assets
that are recorded in balance sheets) of the SNA (Edens and Hein, 2013; Pettini et al., 2013).
For the ecosystem services within the production boundaries of SNA (that are implicitly accounted
for), market prices can be used to calculate their values. In theory, however, one would need to use
empirically estimated production function approaches (e.g. bio-economic modelling) to assess the
marginal value of the ecosystem service involved. For other ecosystem services, where such market
prices do not exist, it is necessary to “conduct valuations at a scale which is feasible, credible and
policy relevant. In order for these valuations to be consistent with the SNA, they will need to
approximate prices, and not to attempt to represent a holistic or social identity of value” (United
Nations Statistical Division, 2011, p.9).
There are different views on what valuation methods are “feasible, credible and policy relevant”.
Weber (2011) for example, asserts that “compatibility with SNA excludes some methods frequently
used in cost-benefit analysis (typically contingent valuation)..,” and proposes to use “remediation
costs” to value the degradation of ecosystems. In contrast, the UK National Ecosystem Assessment,
has, for reasons of consistency with economic theory, “excluded the use of restoration or replacement
costs as a proxy for the value of ecosystem services”(UKNEA, 2011, p. 1072). Glenn-Marie Lange of
the WAVES project summarizes this issue as follows: valuation techniques must stay within the SNA
concept of value, that is: market-based/marginal. Cost-based, remediation, approaches are “third-
best” (Lange, 2011).
D3.2: Economic mapping and assessment methods 43 | Page
__________________________________________________________________________________
5.5.2. System of Environmental-Economic Accounts (SEEA)
The System of Environmental-Economic Accounting (SEEA) provides detailed methodological guidance
on how to prepare environmental-economic accounts.
9
The SEEA includes three volumes: the Central
Framework, Experimental Ecosystem Accounts, and Applications and Extensions.
The SEEA ‘Central Framework’ (SEEA-CF) was adopted as an international statistical standard for
environmental-economic accounting by the United Nations Statistical Commission at its 43rd session
in 2012. It has been prepared jointly by the United Nations, the European Commission, FAO, IMF,
OECD and the World Bank. It provides an accounting framework that is consistent and can be
integrated with the structure, classifications, definitions and accounting rules of the System of
National Accounts (SNA), thereby enabling the analysis of the changes in natural capital, its
contribution to the economy and the impacts of economic activities on it. SEEA-CF focuses on the
stock of natural resources and the flows that cross the interface between the economy and the
environment.
The SEEA ‘Experimental Ecosystem Accounting’ (SEEA-EEA) has been published as a white cover
publication in 2013.
10
It aims to measure ecosystem conditions (with a particular focus on carbon and
biodiversity) and the flows of ecosystem services into the economy and other human activities. SEEA-
EEA offers a synthesis of the current knowledge of ecosystem accounting and serves as a platform for
its development at national and sub-national levels. It provides a common set of terms, concepts,
accounting principles and classifications, and an integrated accounting structure for ecosystem
services and characteristics of ecosystem condition, in both physical and monetary terms. It also
includes a chapter on the main challenges and methodological options for the monetary valuation of
ecosystems and ecosystem services.
The SEEA ‘Applications and Extensions’ is currently under development. It will provide compilers and
users of SEEA-based environmental-economic accounts with examples showing how the collected
information can be used in decision-making, policy review and design, analysis and research.
Furthermore, the TEEB Secretariat at UNEP and the UN Statistics Division, in collaboration with the
CBD Secretariat, have been implementing a project entitled, "Advancing SEEA-EEA in pilot countries",
funded by the Norwegian Government, which aims at supporting selected Governments in initiating
the testing of SEEA-EEA. The national level activities focus on the assessment of policy priorities, data
availability and tools used for ecosystem accounting, stakeholder meetings, the preparation of reports
outlining national programmes of work on the advancement of the testing of the SEEA-EEA, as well as
relevant national stakeholders to be engaged in the processes. In addition to these national level
activities, the project also focuses on facilitating a forum of experts in ecosystem accounting, the
preparation of guidance training material and a global strategy for testing the SEEA-EEA, as well as
outreach and communication.
9
See http://unstats.un.org/unsd/envaccounting/seea.asp
10
http://unstats.un.org/unsd/envaccounting/eea_project/default.asp
44 | Page D3.2: Economic Mapping Methods
__________________________________________________________________________________
Box 11. Experimental Ecosystem Accounts for Uganda
The Government of Uganda, UN Environment World Conservation Monitoring Centre and Institute
for the Development of Environmental-Economic Accounting have recently worked together to
develop experimental ecosystem accounts for Uganda. The report compiled is a first attempt to
develop the required underlying spatial-data infrastructure and the compilation of key ecosystem
and biodiversity related accounts using the System of Environmental-Economic Accounting
Experimental Ecosystem Accounting (SEEA-EEA) framework. The accounts compiled for Uganda
concern land cover, ecosystem extent, three non-timber forest products (Gum Arabic, Shea butter
tree nuts and Prunus africana) and two flagship mammals (Chimpanzees and Elephants) species.
Collectively, these accounts provide significant insights into the state and trends in ecosystems and
biodiversity for Uganda.
The map below is one of the inputs to those accounts. It shows the natural areas which have
potential for Shea Butter tree nut harvesting (Red). The Shea tree is slow growing native African
tree that occurs natural in dry savannah. Based on a combination of land cover mapping over time
(derived from remote sensing) and understanding of original ecosystem cover (22 main vegetation
types) it shows the potential area suitable for supporting Shea trees and therefore producing Shea
Butter tree nuts (for which there is a strong international market not currently exploited by
Uganda).
The accounts generated present information by Sub-Region of the country over the period from
1990 to 2015 and show that the change in potential Shea butter tree nut provisioning services that
have occurred. The spatial mapping also allows understanding of where there may and may not be
conflicts with Protected Areas and can highlight where further sustainable harvesting may be
possible.
https://www.unep-
wcmc.org/system/dataset_file_fields/files/000/000/445/original/Ecosystem_Accounting_in_Ugan
da_Report_FINAL.pdf?1494865089
D3.2: Economic mapping and assessment methods 45 | Page
__________________________________________________________________________________
5.5.3. Wealth Accounting and Valuation of Ecosystem Services (WAVES)
WAVES is an initiative of the World Bank to implement green accounting in a critical mass of countries,
both developed and developing. The project was launched in October 2010 at the CBD meeting in
Nagoya and will last five years. The first two years are the preparation phase to establish the global
partnership, to establish a Policy and Technical Experts Committee, and conduct feasibility and
planning studies in pilot countries. The implementation phase of the project is from 2012 through
2015. Partner countries currently include: Botswana, Colombia, Costa Rica, Madagascar, the
Philippines, Australia, Canada, Japan, Norway, and the United Kingdom. Mauritius will join with
funding provided directly by France.
“The partners want to take natural capital accounting beyond the SEEA-approved material resources,
such as timber and minerals, to include ecosystem services and other natural resources that are not
traded or marketed and are therefore harder to measure. That includes the “regulating” services of
ecosystems, such as forests for pollination and wetlands for reducing the impact of floods. A Policy and
Technical Experts Committee, working closely with the processes set up by the UN Statistical
Commission, has been established to take this forward.” (http://www.wavespartnership.org
/waves/natural-capital-accounting?active=2)
The country plans are driven by the countries’ needs and preferences. Each partner country is
developing a road map to take the initiative further. For Botswana and Madagascar the road map
includes developing and implementing macro-indicators such as the Adjusted Net National Income
and the Adjusted Net Savings. In addition, the focus in Botswana is on energy resources and energy
use, ecosystem-based tourism, and water accounts. In Madagascar, the additional focus is on mining,
river basins, ecotourism, coastal zone management, and fishery accounts. The other countries have
also presented progress reports on the recent second WAVES partnership meeting Washington D.C.:
http://go.worldbank.org/O3A2TJSP30
The approach towards the valuation of non-marketed goods and services is spatially-explicit and
demand-based. The challenge to use spatially-specific and demand-based value estimates for national
accounting is best described by the World Bank:
“The power of the national accounting approach is to provide an economy-wide picture of the value of
ecosystem services. There are many challenges to incorporating natural capital in a national
accounting framework, due to the unique characteristics of natural capital. Many case studies of
ecosystem services have been done, but there remain many gaps where services are not covered. In
some cases, these gaps can be filled by scaling out or borrowing values from other studies. But the
value of many ecosystem services is highly site-specific, which makes gap filling and scaling out a
potentially complex undertaking. To address this, country implementation teams will be encouraged
to seek and use values from local or sub-national case studies for ecosystem services, and identify
reasonable methods for scaling up local value to fill data gaps. Technical advice will also be provided
to draw on meta-data analyses, and ecosystem models such as InVEST from the Natural Capital
project, ARIES or local models to do this.” (World Bank, 2011).
It is also one of the tasks of the Policy and Technical Experts Committee to think about how case study
value data can be aggregated, scaled-up and reported in National Accounts (Lange, 2011b).
5.5.4. Integrated system for Natural Capital and ecosystem services Accounting (INCA)
The European Commission has launched an internal initiative on natural capital accounting
(Knowledge Innovation Project: Integrated system for Natural Capital and ecosystem services
46 | Page D3.2: Economic Mapping Methods
__________________________________________________________________________________
Accounting KIP-INCA
11
), in line with the objectives of the 7th Environment Action Programme (EAP)
and the EU Biodiversity Strategy. The project aims to design and implement an integrated accounting
system for ecosystems and their services in the EU by connecting relevant existing projects and data
collection exercises to build up a shared platform of geo-referenced information on ecosystems and
their services. This system will be used to derive indicators and assess the economic importance and
value of ecosystems and their services, in a manner that is consistent with UN standards on
environmental accounting (SEEA-EEA). An innovative outcome of the project is that biophysical and
economic data related to the extent and condition of ecosystems can be integrated in a systematic
way, so that they can be aggregated and disaggregated at the required scale, including at national
level, to complement figures of economic performance.
The project is structured in two main phases, a feasibility and design phase which lasted until May
2016 and a follow-up implementation phase, running until 2020. The project focuses on establishing
an accounting system for the EU level, primarily using EU-wide data sources, thereby contributing the
EU layer to the MAES initiative. The main project partners are Eurostat, the European Environment
Agency, DG Environment, the Joint Research Centre and DG Research and Innovation.
KIP INCA will work in line with the UN System of Environmental-Economic Accounting- Experimental
Ecosystem Accounts (SEEA-EEA) and will make proposals for improving approaches to accounting
based on experience in the EU. With respect to ecosystem services accounts, the general approach of
KIP INCA is to quantify supply and use tables and link these tables to the tables which describe the
extent and condition of ecosystem assets on the one hand and tables which describe the benefits from
ecosystem services on the other hand. This approach differs to some extent with the SEEA-EEA but
the resulting accounting tables are fully compliant with the technical recommendations.
A first technical INCA report (La Notte et al. 2017a) outlines initial proposals for the ecosystem service
supply and use tables that will be produced by KIP INCA. So far, supply and use tables at EU scale are
available for three ecosystem services: recreation and pollination including a description of the models
used to quantify the accounts are presented in Vallecillo et al. (2018); water purification accounts are
methodologically described in La Notte et al. (2016) whereas the supply and use tables for water
purification can be consulted in La Notte et al. (2017b).
The KIP will connect relevant existing projects (in particular ESMERALDA) and data collection exercises
(such as LUCAS land use/cover statistics
12
) to enable them to contribute more information about the
ecosystem components of natural capital. JRC will be responsible for feeding outputs of ESMERALDA
into the KIP. In particular tier-3 physical and economic mapping approaches of ecosystems, ecosystem
condition and ecosystem services would be relevant input of ESMERALDA to INCA.
Box 12. How to read ecosystem services supply and use tables?
The main purpose of supply and use tables for ecosystem services is to show the origin of the actual
flow of the service and which economic actor is using it. Figure 1 (taken from La Notte et al. 2017a)
presents a graphical simplification of a supply and use table.
The supply table can show the physical or monetary flows of ecosystem services from ecosystems
(assets) into the economy (actual flows in figure 1).
The use table records the use of ecosystem services by types of economic units as input to further
production or as final consumption. The use table also recognises the possibility of recording the
use of ecosystem services by other ecosystem types, i.e. intermediate ecosystem services.
11
http://ec.europa.eu/environment/nature/capital_accounting/index_en.htm
12
http://ec.europa.eu/eurostat/web/lucas/overview
D3.2: Economic mapping and assessment methods 47 | Page
__________________________________________________________________________________
The supply and use tables can also record flows of economic products to which ecosystem services
contribute.
In an accounting framework, total supply of ecosystem services equals total use. La Notte et al.
(2017) propose extensions to the supply use table to also include quantities such as the capacity of
ecosystems to deliver ecosystem services, the potential or the sustainable supply.
Figure 1. Simplified model of a supply use table to report ecosystem services in a natural capital
account (taken from La Notte et al. 2017a)
5.5.5. National/Regional accounting initiatives in the EU
UK Office of National Statistics
The UK Office for National Statistics (ONS), working closely with the UK Department for Environment
Food and Rural Affairs (DEFRA), engages in the international developments on experimental
ecosystem accounts; and works closely with experts and users in the UK to inform the development
of a roadmap for further improvements up to 2020.
In December 2012, the ONS published a Roadmap Accounting for the value of nature in the UK,
which set out a strategy to incorporate natural capital into UK Environmental accounts by 2020.
13
The
13
The Roadmap and related documents on natural capital accounting can be found at:
48 | Page D3.2: Economic Mapping Methods
__________________________________________________________________________________
Roadmap includes the development of a number of ecosystem accounts based around the eight broad
habitats set out in the UK National Ecosystem Assessment. The ONS has also published a set of basic
principles to be followed when developing ecosystems accounts (see ONS DEFRA, 2014).
In May 2014, the ONS published UK Natural Capital - initial and partial monetary estimates, which
sets out some experimental methods to estimate the value of a selected number of natural capital
assets (see Kahn et al., 2014). The ecosystem services included in these accounts are timber, fisheries,
water abstracted for public water supply, outdoor recreation and net greenhouse gas sequestration.
These estimates provide an initial overview of the possible value of certain components of natural
capital but they also highlight the importance of developing physical accounts, and more detailed and
spatially disaggregated ecosystem-based accounts.
Statistics Netherlands
Statistics Netherlands has a long history in developing and implementing integrated environmental-
economic accounting. In the beginning of the 1990s, parallel to the publication of the UN’s first
handbook on integrated environmental and economic accounting (SEEA), Statistics Netherlands
extended the National Accounting Matrix (NAM) with a ‘satellite account’, which includes the
environmental pressures related to the production of goods and services and the consumption of
households. This resulted in the National Accounting Matrix including Environmental Accounts
(NAMEA) (de Haan et al., 1993; de Haan and Keuning, 1996). The NAMEA provided the basis for a
Dutch Government commissioned comprehensive macro-economic modelling exercise using an
applied general equilibrium model by Gerlagh et al. (2002) to estimate a sustainable national income
measure for the Netherlands based on the macro-economic adjustments needed to meet ecological
threshold values, which were considered crucial to sustainable environmental development.
Based on the NAMEA and linked to the implementation and reporting requirements of the EU Water
Framework Directive (WFD), an integrated water accounting system was developed in 2004, called
National Accounting Matrix including Water Accounts for River Basins NAMWARiB (Brouwer et al.,
2005). Physical water and pollution flows are linked in this system of integrated accounts to the core
System of National Accounts, and disaggregated to the different river basins in the Netherlands using
GIS. Time series linking financial transactions in economic sectors to water abstraction, wastewater
discharge, corresponding pollution loads of close to 100 chemical substances (including nutrients,
heavy metals and other chemical compounds which are systematically monitored in Dutch water
bodies), and wastewater treatment are available since 1996. Annual financial flows related to the
water services as defined in Article 2 of the WFD (about which MS have to report cost recovery rates
to the European Commission) are distinguished explicitly in NAMWARiB. This integrated water
accounting system was the basis for another macro-economic modelling exercise using an updated
version of the existing applied general equilibrium model for the Dutch economy to estimate the
macro-economic and sector impacts of different WFD implementation scenarios (Brouwer et al., 2008;
Dellink et al., 2012).
Spanish Agro-forestry Accounts System
The Spanish accounting system for agro-forestry ecosystem services has been developed and tested
(Campos and Caparrós, 2006; Caparrós et al., 2003). The accounting unit is a forest ecosystem, e.g.
the Mediterranean Monfragüe cork oak forest or the Guadarrama pine forest. Services accounted for
are timber, cork, firewood, grazing, hunting, wild mushrooms collected, public recreation, and
http://www.ons.gov.uk/ons/guide-method/user-guidance/natural-capital/index.html
D3.2: Economic mapping and assessment methods 49 | Page
__________________________________________________________________________________
conservation (existence) value. It also includes a value category called “owner’s self-consumption of
environmental services”.
The innovation of the Agro-forestry Accounts System (AAS) is the way in which shadow prices for non-
marketed good and services (e.g. mushrooms, public recreation) are estimated. Standard benefits
estimates would measure consumer surplus over a change in the level of provision of service.
Consumer surplus is not consistent with the concept of exchange values used in the SNA. Therefore
the AAS estimates the income that would be earned in a hypothetical market in which ecosystem
services would be bought and sold. They estimate hypothetical demand and supply curves for the
ecosystem services and make further assumptions on the price that would be charged by a profit
maximizing resource owner under alternative market structures (monopoly, competition). Campos et
al. (2003) call this the Simulated Exchange Value approach. The hypothetical income of the resource
owner thus derived is consistent with the general valuation approach of the SNA.
Another difference is that Campos et al. (2003) include government expenditure in the forests as a
cost rather than as output (as is standard in SNA) because, as they argue, the lion’s share of
government expenditure in forest in Spain is fire fighting and this has a direct impact on commercial
timber output. The fire fighting service is therefore already (to a certain extent) valued by the ‘saved’
timber output. To avoid double counting, government expenditures are therefore only recorded on
the cost side.
5.6. Corporate Ecosystem Service Review
The majority of economic methods for assessing ecosystem services focus on decision-making in the
public domain. Private sector decision-making may also apply the CBA and MCA frameworks using a
private perspective of relevant impacts. The private sector, however, often fails to make the link
between ecosystem health and business performance. Many companies are not aware of the extent
of their dependence and impact on ecosystems and the possible consequences. As a consequence,
corporate environmental management rarely takes into account the risks and opportunities arising
from the degradation and use of ecosystem services. Most companies consider ‘traditional issues of
pollution and natural resource consumption and therefore focus on environmental impacts, not
dependence. Furthermore, they typically address corporate risks, not business opportunities. As a
result, companies may be caught unprepared or miss new sources of revenue associated with
ecosystem change.
Although the interest of the overall business community in ecosystem services may still be relatively
small, there is a growing number of firms that recognise the importance of healthy ecosystems to their
operations. This growing recognition is supported by international initiatives and organisations such
as The Economics of Ecosystems and Biodiversity (TEEB), the World Business Council for Sustainable
Development (WBCSD), The Natural Capital Coalition, and the World Resources Institute (WRI) who
have developed assessment tools that aim at integrating natural capital in business and investor
decision-making. Ecosystem services approaches for business, among others, focus on various
corporate interests such as strategic planning, management of supply chains, procurement, corporate
reporting/disclosure and assessing new markets.
One of the challenges in the uptake of ecosystem services approaches by business is the lack of a
harmonized approach to clarify why and how the concept of ecosystem services can be practically
used in business and finance sector applications. For example, in 2013 the WBCSD published an
overview of ecosystem services and biodiversity tools to support business decision-making, containing
more than 30 examples of business applications (WBCSD, 2013). To illustrate this rapidly emerging
field, we describe the Ecosystem Services Review (ESR), which is one of the most prominent and
50 | Page D3.2: Economic Mapping Methods
__________________________________________________________________________________
popular ecosystem services tools in business (Hanson et al. 2012).
14
The ESR consists of a structured
methodology that helps managers proactively develop strategies to manage business risks and
opportunities arising from their company's dependence and impact on ecosystems. It is a tool for
strategy development, not just for environmental assessment. Businesses can either conduct an
Ecosystem Services Review as a stand-alone process or integrate it into their existing environmental
management systems. In both cases, the methodology can complement and augment the
environmental due diligence tools companies already use.
The ESR involves five steps, shown in Figure 8. The first step involves selecting the scope or boundary
of the ESR assessment by specifying the stage of the value chain (e.g. suppliers, company, customer)
while focussing on strategic, timely and supported business aspects. Candidates of scope include a
business unit, product, market, corporate landholdings, infrastructure project, major supplier, or
major customer segment, among others.
Figure 8. Steps in a Corporate Ecosystem Services Review (Hanson et al. 2012, p.11).
In step 2, priority ecosystem services are identified through a systematic evaluation of the company’s
dependence and impact on more than 20 ecosystem services as defined by the MA (2005). The priority
services are the ones most relevant to corporate performance. A company depends on an ecosystem
service if that service functions as an input or if it enables, enhances, or influences environmental
conditions required for successful corporate performance. What is also important is that, if indeed the
ecosystem service serves as a crucial input or enhances conditions for successful performance,
whether this ecosystem service has cost-effective substitutes. If there is no such substitute, then the
company is considered to be highly dependent upon that service. A company impacts an ecosystem
service if it affects the quantity or quality of that service. The degree to which a company impacts an
ecosystem service in a manner that might pose a business risk or opportunity for itself is a function of
whether or not the impact limits or enhances the ability of others to benefit from the service.
Step 3 involves the analysis of the conditions and trends in the priority services, as well as the drivers
of these trends. The purpose of this assessment is to provide managers with sufficient relevant
information so that they can later identify business risks and opportunities that may arise from these
trends. This involves the identification of the present and expected future supply and demand for the
services which can be affected by a range of influences such as changes in land use and land cover,
over-consumption, climate change, discharge of pollution and overuse of fertilizers, introduction of
invasive non-native species. The methodologies developed in ESMERALDA may help companies to
map current and expected future supply and demand for priority services.
The fourth step is to evaluate the implications for the company of the trends in the priority ecosystem
services. The purpose of this step is to identify the business risks and opportunities that might arise
due to these trends. Types of risks and opportunities include (a) operational, (b) regulatory and legal,
(c) reputational, (d) market and product, and (e) financing, which are summarised in Table 4.
14
WRI developed the ESR in collaboration with the Meridian Institute and the World Business Council for
Sustainable Development (WBCSD). Since 2008, an estimated 300 companies have used the Ecosystem Services
Review.
1. Select
the scope
2. Identify priority
ecosystem
services
3. Analyze
trends in priority
services
4. Identify
business risks &
opportunities
5. Develop
strategies
D3.2: Economic mapping and assessment methods 51 | Page
__________________________________________________________________________________
Table 4. Risks and opportunities arising from trends in ecosystem services
Type
Risks
Opportunity
Operational
Increased scarcity or cost of inputs
Reduced output or productivity
Disruption to business operations
Increased efficiency
Low-impact industrial processes
Regulatory and
legal
Extraction moratoria
Lower quotas
Fines
User fees
Permit or license suspension
Permit denial
Lawsuits
Formal license to expand operations
New products to meet new
regulations
Opportunity to shape government
policy
Reputational
Damage to brand or image
Challenge to social ‘license to
operate’
Improved or differentiated brand
Market and
product
Changes in customer preferences
(public sector, private sector)
New products or services
Markets for certified products
Markets for ecosystem services
New revenue streams from company-
owned or managed ecosystems
Financing
Higher cost of capital
More rigorous lending requirements
Increased investment by progressive
lenders and socially responsible
investment funds
Source: Hanson et al. (2012) p.24
The fifth step is to develop and prioritize strategies for minimizing the risks and maximizing the
opportunities identified in the previous step. Strategies for responding to ecosystem service-related
risk and opportunities fall into three broad categories: (a) internal changes in the company through,
for example, changes in operations and product/market strategies; (b) partnering with industry peers,
collaborating with other sectors, or structuring transactions with partners through sector and/or
stakeholder engagement; and (c) engage policy makers and voice support for incentives or effective
government rules for sustainable management of ecosystem services.
After the identification and prioritization of strategies to address ecosystem service risks and
opportunities, companies can implement a number of follow-up activities. Building on the ESR
experience in one part of the company, managers can extend the methodology to additional divisions,
markets, customers, suppliers, or other aspects of their business. Managers can also incorporate the
ESRor elements of itinto their existing environmental management and due diligence systems or
into their corporate strategy development processes in order to augment them.
6. Distributional considerations
6.1. Distribution of impacts across stakeholders
The distribution of costs and benefits across different groups in society is usually an important
criterion in public decision-making and needs to be addressed as part of the assessment process. The
allocation of the benefits and costs among different groups within society may well determine the
political acceptability of alternative options.
The uneven distribution of costs and benefits has both practical and ethical consequences. In practical
terms, it is important to assess the burden of costs and benefits received by local stakeholders, as they
often have a strong influence on how successful project implementation will be. It is often the case
with the establishment of protected areas that attempting to exclude local stakeholders from
52 | Page D3.2: Economic Mapping Methods
__________________________________________________________________________________
accessing an environmental resource will not be successful without sharing the benefits of
conservation with them. Understanding who gains and who loses from each policy option can provide
important insights into the incentives that different groups have to support or oppose each project.
This approach can thus provide useful information in the design of appropriate responses and increase
success in implementing projects/plans.
In terms of ethical considerations, the analysis of the distribution of costs and benefits is important to
ensure that conservation interventions do not harm vulnerable groups within society. Identifying and
estimating the distribution of costs and benefits across different groups is the first step in designing
measures to avoid disproportionate or undesirable allocation of impacts, compensation mechanisms,
or payment schemes between gainers and losers. A general approach to identifying which groups will
be affected by alternative options is through stakeholder analysis. One way of displaying the
distributional effects of alternative options is to construct a distributional matrix, which displays the
costs and benefits of a policy option, and shows how they are distributed among different socio-
economic groups.
Information on the distribution of the impacts of alternative options may be included directly in a MCA
as an additional criterion in the analysis, which then contributes to the overall weighted standardised
score of each option. It is technically more challenging to include distributional considerations directly
in a CBA. Generally the distributional consequences of alternative options can be provided alongside
the outputs of the analysis as additional information for decision-makers to consider. To this end,
ESMERALDA deliverable 3.1 provides an overview and guidance on socio-cultural mapping and
assessment methods.
Including the consideration of distributional consequences in the ESMERALDA case studies will
enhance the real use of assessment results since decision-making, for a large part, is based on the
stakeholders involved and their reactions to proposed projects.
6.2. Spatially distributed impacts
As noted earlier, the decision-making context regarding the management of ecosystem services is
often one of spatial targeting. Decisions are being made about where to invest in ecosystem
restoration, establish of protected areas, or target financial incentives to change the behaviour of land
users. In this case, the spatial correspondence of costs and benefits relevant to the decision is of crucial
importance and mapping these inputs is necessary.
The spatial distribution of impacts from alternative policy options may also be of interest to decision
makers, particularly where different user groups are located in different areas. The analysis of the
spatial distribution of impacts may be seen as an extension of the distributional analysis described in
the previous section and may be a useful approach to identifying different societal groups that are
impacted by a project. For example, projects that address water management at a river basin level are
likely to affect upstream and downstream stakeholders differently and this should be identified
through spatial analysis. Alternative policy options will generally result, not only in different aggregate
costs and benefits, but also in the spatial distribution of impacts. If these differences in spatial
distribution are considered of importance, they also need to be represented to decision makers.
6.3. Temporally distributed impacts
Most policy options will result in impacts not only in the year in which they are implemented but also
over a number of years into the future. Both the costs and benefits of a project will therefore have a
temporal distribution. It is often the case that projects involve initial investment costs followed by a
stream of benefits received over several years in the future. It is important to account for this
distribution of costs and benefits over time because people tend to value a benefit or cost in the future
less than a benefit or cost now. The practice of accounting for this time preference is called discounting
and involves putting a higher weight on current values.
D3.2: Economic mapping and assessment methods 53 | Page
__________________________________________________________________________________
There are two motivations for this higher weighting of current values. The first is that people are
impatient and simply prefer to have things now rather than wait to have them in the future. The
second reason is that, since capital is productive, a Euro’s worth of resources now will generate more
than a Euro’s worth of goods and services in the future. Therefore, an entrepreneur is willing-to-pay
more than one Euro in the future to acquire one Euro’s worth of these resources now. In most cases,
the discount rate is therefore based on the opportunity cost of capital the prevailing rate of return
on investments elsewhere in the economy, i.e. the interest rate.
The usual way to deal with temporal effects in the analysis is to apply a discount rate to future impacts.
Suppose an annual value of an ecosystem service X $ will occur over a period of T years, and a discount
rate of r per cent is applied, then the present value of the total damage over time is:
The present value of the value X in any given year with t>0, X/(1+r)t, is smaller than the value X in year
t=0. From the equation it can be seen that the higher the discount rate r and the higher the number
of years (t), the lower the discounted value of future damage in any given year.
The choice of the appropriate discount rate remains a contentious issue because it often has a
significant impact on the outcome of the analysis.
15
Various respected organisations provide advice
on the discount rate to be used. For example, the UK Treasury guidelines recommend a discount rate
of 6% for public sector projects while for most environmental and social impact studies 3.5% is
recommended.
16
There is evidence to suggest that people discount the future differently for different goods. If people
have lower rates of time preference for environmental goods than for money, a lower discount rate
than the interest rate should be used. It is also possible that rates of time preference diminish over
time, i.e. that the discount rate declines for impacts in the far future. The choice of discount rate can
have a large impact on the findings of an evaluation or valuation study, and should therefore be varied
in a sensitivity analysis to check how it influences the results.
15
For a comprehensive discussion about the discount rate in environmental assessments, visit the website of
the US Environmental Protection Agency (EPA): http://www.epa.gov/ttnecas1/econdata/Rmanual2/8.3.html.
See also Pearce, D. (2003) Valuing the future: Recent advances in social discounting. World Economic, 4 (2);
and Kahn and Greene (2013) Selecting discount rates for natural capital accounting, ONS-DEFRA.
16
See The Green Book
https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/220541/green_book_compl
ete.pdf
X r t
t
T/ ( )1
0
54 | Page D3.2: Economic Mapping Methods
__________________________________________________________________________________
7. A tiered approach to economic mapping and assessment methods
Based on the conceptualisation of a tiered approach for classifying ecosystem service mapping and
assessment methods developed by Grêt-Regamey et al. (2017), we adapt that framework to provide
guidance on the selection of economic mapping and assessment methods. In order to provide practical
guidance, the intention is to assign each method to one of three tiers reflecting the accuracy, detail,
technical capacity and data requirements. For example, methods that produce information with a high
level of accuracy and detail but have high technical and data requirements are assigned to tier 3. Table
6 provides a definition of each tier. The assignment of economic mapping and assessment methods to
a specific tier, however, is not straightforward since each method can be applied with varying degrees
of complexity to produce information with varying degrees of accuracy and detail, largely dependent
on the availability of data and resources for conducting the analysis. Nevertheless, we have attempted
to make generalisations regarding the accuracy and complexity of each method.
Table 6. Definition of tiers for economic mapping and assessment methods
Accuracy
Detail
Technical Expertise
Data
Tier 1
(Usually) lower
accuracy and
robustness of
results (suitable for
awareness raising)
Lower level of
detail and spatial
specificity
Requires some
technical expertise
Uses readily
available data
Tier 2
Moderate accuracy
and robustness of
results (suitable for
informing broad
policy direction)
Moderate level of
detail and spatial
specificity
Requires some
technical expertise
across multiple
disciplines
Requires processing
existing data from
multiple sources
Tier 3
Higher accuracy and
robustness of
results (suitable for
informing the
selection of
investments)
Higher level of
detail and spatial
specificity
Requires high levels
of technical
expertise across
multiple disciplines
Requires collection
of detailed new
data from multiple
sources
D3.2: Economic mapping and assessment methods 55 | Page
__________________________________________________________________________________
Figures 9, 10, and 11 provide representations of guiding questions for selecting economic valuation
methods, value transfer methods and economic assessment methods respectively. The tiers of each
specific economic mapping and assessment method addressed in this report are reported in Tables 2,
3 and 5.
Figure 9. Tiered approach to selecting appropriate primary economic valuation methods. Adapted
from Grêt-Regamey et al. (2017)
Shouldthevaluesreflect
spa alvaria onindemand
andsupply
Isthemapping
purposeexclusivelya
roughes mateofES
values?
Isadeeperunderstandingofunderlying
socio-economicand/orgeo-bio-physical
processesneeded?
Process-understanding
necessary?
Yes
(Partly) Yes
(Totally)
Roughoverview?
Yes
TIERI
TIERII
TIERIII
No Contextspecific
valuesneeded?
Aredataandresourcesavailable?
Aredatainsufficientquality,quan ty,scaleandresolu on
availabletoconductanESvalua oninthis er?Arethere
enoughtechnical,humanandfinancialresourcesavailable?
No Yes
Marketprices;Costbased
approaches
Netfactorincome;Input-Out
models
Produc onfunc ons;Revealedand
Statedpreferencemethods
56 | Page D3.2: Economic Mapping Methods
__________________________________________________________________________________
Figure 10. Tiered approach to selecting appropriate value transfer methods. Adapted from Grêt-
Regamey et al. (2017)
Figure 11. Tiered approach to selecting appropriate economic assessment methods. Adapted from
Grêt-Regamey et al. (2017)
Shouldthevaluesreflect
spa alvaria onindemand
andsupply
Isthemapping
purposeexclusivelya
roughes mateofES
values?
Isadeeperunderstandingofunderlying
socio-economicand/orgeo-bio-physical
processesneeded?
Process-understanding
necessary?
Yes
(Partly) Yes
(Totally)
Roughoverview?
Yes
TIERI