Spatial framework for assessing evidence needs for operational
ecosystem approaches
Attachment 1 to Annex A of the project specification
There are some fairly robust conceptual models now available to link ecosystem services and their
valuation to biodiversity. The next step therefore appears to be to link these models to practical ways
of quantifying biodiversity and its functional contribution to ecosystem services.
The goal is to create rapid means of assessing the multiple service contributions made by
ecosystems at any given location, in a way that can be scaled up to inform decision-making,
assessment and valuation at local, landscape and country levels.
Widely discussed in the ecosystem service assessment and valuation models are the linkages
between the biotic and physical properties of an ecosystem and the functions (and services) these
ecosystems provide. A method is needed to link the provision of services by ecosystems to the
underlying attributes that make up that ecosystem and its processes.
Use of spatial frameworks
Digital, polygon-based data sets are becoming a mainstay for ‘traditional’ biodiversity conservation.
Spatial frameworks and the component habitat polygons are used for determining conservation
objectives, planning management actions, assessing status of protected sites, among other tasks.
These habitat polygons can also serve a role in defining the ecosystem service contributions
of the associated environments.
Each habitat polygon can be described in terms of its biophysical structure, which reflects the biotic
and physical properties of that location (e.g. soil pH, elevation, water status). These properties can
be defined as the attributes of the habitat. The existing attributes of an area affect what ecological
processes will occur there (e.g. primary production, water infiltration), and thus what functions the
habitat area provides (e.g. biomass production, water regulation), and what ecosystem goods and
services are thus produced (e.g. food production, flood risk reduction).
Both habitats and ecosystem processes or functions can be linked to the underlying attributes of the
area. Therefore polygons of specific habitats should be able to be linked to the provision of
ecosystem services. For spatial frameworks to be useful in ecosystem service assessment and
valuation, such attributes need to be:
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Related to key functions needed for ecosystem services
Easy to measure
Able to be mapped
Potentially manageable (for scenario generation)
Quantified in existing, accessible datasets (including non-UK datasets when transferable)
Related to / used to measure habitat condition
For example, peat surface wetness, infiltration rate, and condition of the primary peat forming
vegetation cover are attributes relevant to both hydrological and carbon processes. Some of
these same attributes also could contribute to assessments of peatland biodiversity status, as
well as the condition of the peatland vis-à-vis validated Emission Factors for greenhouse gases
(GHGs).
Association of attributes with habitat polygons would allow these attributes to be mapped and
compared, to each other and to the ecosystem services provided by the ecosystem processes in that
area. Quantification of ecosystem services can then be connected to the functions of that habitat and
their associated attributes.
Existing monitoring of habitats could then be modified to pick up values for the key functionallyrelevant attributes of the habitats, providing change and trend information for these functions.
Developing the framework
Developing this framework will require the comparison of fairly comprehensive lists of identified UK
habitats, and ecosystem services these provide. The UK NEA definitions of broad and component
habitats, and specific UK-agreed definitions of priority BAP habitats should form the basis of this;
ecosystem service definition should follow the NEA division of regulating, supporting, provisioning and
cultural services. The initial cut of habitat levels and attributes would be quite crude, but the structure
and content would have the potential to be refined as more data become available (examples of
linking these kinds of habitats to their provided services is provided in the attached spreadsheet).
A set of basic attributes could be defined that could be applied to all types of a component habitat
(e.g. peat bog; deciduous woodland), and which would describe the provision of processes and
functions for regulating, supporting, provisioning and cultural services. The measure of these
attributes (e.g. wetness and surface structure) for any one habitat polygon could then be varied
according to local conditions when additional information is known, such as sub-habitat type (e.g.
blanket bog, fenland), management state (e.g. cultivated, eroded, restored), and even region or
country specific values (e.g. blanket bog in Scotland maybe different than blanket bog in Southern
England).
At this stage it would not be important to worry about whether the final service valuation was likely to
be significant, but rather that attributes can be linked to service provision and that habitats can be
strongly linked to attributes (similarly, double accounting is a risk to be dealt with in the accounting
methods and not in the assigning of attributes). Bog structure or vegetation, for example, can be
linked to cultural service provision, but its final value will vary with accessibility.
Measuring / valuing of habitat ecosystem services (e.g. Peat bog)
 Biophysical attributes (biotic / physical characteristics of the ecosystem)
 Biophysical / ecosystem processes (e.g. primary productivity)
 Function (e.g. Carbon cycling in biomass)
 Ecosystem service (e.g. Carbon sequestration)
 Benefits / Goods (e.g. reduction in atmospheric C)
 Value (e.g. marketable carbon credits)
Using validated parameters
The framework structure can use validated parameters (where available from research) to quantify
the scale of the function associated with the habitat’s attributes. The parameter values should ideally
be related to the habitat attributes.
Service quantification could then be calculated using rules within GIS, applying the attributes to
habitat polygons by type, and adding information from other data sets relevant to service quantity
delivered (e.g. slope data available from digital terrain models can be added to each specific polygon
to help understand hydrological functions; information on peat depth from soil data sets for carbon
storage calculations).
For example, green house gas emission factors available from extensive research on peat habitats
may serve as validated parameters for peatlands of different types, and under different management1.
Emission factors, which help in the assessment of the carbon regulation function of peat, are currently
being determined by intensively instrumented research. Once available these factors can be related
to various habitat types and management states, and also to the habitat attributes that are easily and
inexpensively measured, or for which information already exists (e.g. wetness, vegetation types, and
vegetation structure).
The flow of ecosystem services is an important consideration to take into account when considering
valuation, as a service may not be directly used by people in the area within which it is generated
(e.g. flood protection provided to downstream areas by upstream trees).
1
Worrall, F., Chapman, P., Holden, J., Evans, C., Artz, R., Smith, P. & Grayson, R., (2011), A review of current
evidence on carbon fluxes and greenhouse gas emissions from UK peatlands, JNCC Report 442, ISSN 0963
8901 http://jncc.defra.gov.uk/page-5891
Spatial framework example – peat bog, primary productivity
This table shows an example of the relationship between the primary productivity process, functions, and attributes of a peatland habitat, how these
may be measured, and the currently-available data for the identified attributes.
Ecosystem
service
Primary
Carbon
Carbon
productivity regulation sequestration
/ atmospheric
removals
Process
Function
Carbon
store
Carbon stock
Attributes
Measurement of attributes
Currently available data?
Habitat extent
Management regime
Condition assessment
Peat depth
Carbon concentration
Habitat extent
Bulk density
Surface structure
Primary Productivity
Net Ecosystem Respiration
the annual flux of Particulate Organic Carbon
annual Dissolved Organic Carbon flux
the annual flux of excess dissolved CO2
the annual methane flux
the annual N2O flux
Area of peat habitat; BAP maps
Management actions (grazing, burning, etc)
Condition status
Soil cores and soils mapping
%C in peat material
Area of peat habitat; BAP maps
peat oven-dry mass per unit volume
% degraded; vegetation height
Ongoing work; Site-specific studies
Ongoing work; Site -specific studies
Ongoing work; Site-specific studies
Ongoing work; Site-specific studies
Ongoing work; Site-specific studies
Ongoing work; Site-specific studies
Ongoing work; Site-specific studies
Mapping (CS / NSI / LCM); BAP
CA records; Mapping (LCM etc)
Sphagnum condition
% cover live Sphagnum - mapping
Surface wetness
topographic wetness index
Emission factors
(tCO2e)
(-ve or +ve)
CSM for protected sites
National Soils Inventory
Site-specific studies
Mapping (CS / NSI / LCM); BAP
Site-specific studies
Some remote sensing studies; Sitespecific studies
Some remote sensing studies; Sitespecific studies
Topographic maps
Mapping the framework
Habitat polygons could be generated utilising the spatial framework of Land Cover Map 2007 (LCM2007), or the new habitat map of Wales (Gwylio),
and refined using other data, such as Priority Habitat mapping. Each country agency is already working to improve mapping and assessment of
higher quality habitats (priority and habitats directive) to meet reporting obligations and plan delivery.
Some similar work has already been done in existing research projects, even to quite a large scale; for example, the Wales NEF has pioneered using
digital habitat data sets to quantify ecosystem function and service. There is a need to pull these initiatives together into a pragmatic approach for
rapid development of habitat datasets and the attribute/parameter matrix data; this will provide a clearer basis for developing models, scenarios,
services valuation, and options appraisals at various operational scales.
Use of multiple datasets in spatial mapping
Example: Cumbrian peat bogs
LCM2007 - Habitat polygons
Special Areas for Conservation (SAC)
British Geological Survey - Superficial
geology (peat)
Combined mapping – LCM2007 and SAC
BAP Habitat Map – Blanket Bog
 Attributes can be refined further with
information from protected site monitoring /
other data sources that could give additional
information on condition
 Data could then be broken down by region
e.g. watershed to analyse / model effects of
changes in condition (or any attribute).
 Attributes that contribute to multiple
services can be shown together.
JNCC’s role in establishing the framework
JNCC is tasked with helping the country agencies to access evidence that can support practical
application of an ecosystem approach in environmental management. Collaborative work is already
underway with all agencies and Defra to make ongoing mapping developments more achievable and
cost effective through tiered use of remote sensing, improved data processing and ultimately field
techniques in on-the-ground monitoring (including promotion of the Crick Framework of determining
habitats, condition and functional attributes by remote sensing).
A key consideration is the characterisation and valuation of ecosystem services with a view to
practical application in policy and planning decisions. Such measurements require comprehensive
data to be available quickly; the UK NEA demonstrated that there were limitations in suitable data and
that a more integrated approach to data generation and sharing would be beneficial.
The intention of this framework is to support decision-making at a variety of scales, allowing for
assessment of multiple ecosystem services of any given location. Supported decisions should
include (but are not limited to):
1) Quantification (as appropriate) of stocks / flows of ecosystems services for a given area.
2) Identification of ‘best-fit’ areas for policy actions (e.g. country-level woodland expansion
targets, identifying the most appropriate place to plant required trees)
3) Determining the most effective actions for a specific desired outcome / service (e.g.
improvement of flood defence in a catchment).
4) Large-scale assessments of ecosystem service provision, at catchment / landscape /
national scales (e.g. NEA follow-up work; country assessments, etc)
There is a need to understand the implications of any difference in approach between countries, and
identify opportunities to share conceptual or practical development, where appropriate. The intention
for the framework to be modifiable by local information should avoid inappropriately constraining
countries into ‘one size fits all’ approaches while allowing for sharing of existing data.
The framework is intended to have a trans-disciplinary approach including: input from economists
involved with the valuation of ecosystem services; input from social scientists when consideration of
cultural services is needed; involvement with the science community to help advancing their work on
ecosystem services, and provision of an interface for collection of the knowledge gained from
research.