A framework for the assessment of ecosystem goods and services; a case study on lowland floodplains...

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Analysis

A framework for the assessment of ecosystem goods and services; a case study onlowland floodplains in England

H. Posthumus a,⁎, J.R. Rouquette b, J. Morris a, D.J.G. Gowing b, T.M. Hess a

a Cranfield University, Natural Resources, Cranfield, Bedfordshire MK43 0AL, United Kingdomb Open University, Life Sciences, Walton Hall, Milton Keynes MK7 6AA, United Kingdom

a b s t r a c ta r t i c l e i n f o

Article history:Received 26 August 2009Received in revised form 15 February 2010Accepted 17 February 2010Available online 11 April 2010

Keywords:AgricultureEcosystem servicesFloodplainsScenario modelling

The rural space is increasingly valued for the multiple ecosystem services that it can deliver. For example,priorities in many lowland floodplains in England have changed in recent years from a focus on agriculturalproduction towards environmental quality and the management of flood risk, in part linked to climatechange. Recent concerns about food security, however, may reinstate the importance of agriculturalproduction in these fertile areas. This paper explores changes in rural land use in floodplains by measuringthe range of ecosystem services provided under different management scenarios. Generic land use scenariosconsider management options that focus on single objectives, such as maximising agricultural production,maximising biodiversity and maximising flood storage capacity. Indicators are developed to value theecosystem services provided by floodplains under each scenario, identifying potential synergy and conflict.This integrated ecosystems approach can help to inform future policy and practice for floodplainmanagement, hopefully in ways that appeal to key stakeholders.

1. Introduction

The rural space has the potential to provide a wide range ofenvironmental and socio-economic services to society. It is here thatagriculture, the predominant type of rural land use in Europe, isincreasingly seen as multi-functional; delivering goods for market, inparticular food, fibre and fuel, as well as non-market goods andservices, such as recreation and amenity, habitats, landscape main-tenance and the sustenance of rural communities (Porter et al., 2009).Agriculture can, however, also produce a number of externalities, suchas soil erosion, water pollution, methane emissions and damage towildlife (Dobbs and Pretty, 2004; EA, 2002; EFTEC/IEEP, 2004; Prettyet al., 2001; Randall, 2007). Likewise, non-agricultural land uses, forexample fens or woodland, also deliver multiple services includinghabitat provision and recreation.

Lowland floodplains are able to accommodate various land usetypes, ranging from fens and grazing marsh to intensive arableagriculture and horticulture, each type delivering a unique set ofbenefits and externalities. The management of land and water in rurallowland floodplains in England has changed considerably over thepast 60 years. During the period between 1945 and 1985, publiclyfunded investments were made to protect farmland against floodingand enable land drainage in order to enhance agricultural production.

Such land drainage improvement schemes were designed to helpmeet the policy objectives of reliable food supply at reasonable prices,fair rewards to those engaged in farming and support to the ruraleconomy (Morris, 1992). By the early 1980s, however, concern aboutover-production, burgeoning costs of support, and environmentaldamage associated with intensive farming, questioned the validity ofcontinuing this predominantly productivist regime in Europe. Theseconcerns, and the realisation of the importance of non-marketservices provided by the rural space, led to changes in agriculturaland rural policy. The introduction in the 1980s of environmentalmanagement agreements with farmers and early attempts in the1990s to decouple farm income support and commodity prices, wereexamples of policy realignment. The action programme ‘Agenda 2000’of the European Union initiated further reforms of the CommonAgricultural Policy (CAP), giving greater weight to the protection ofnatural resources and the environment and decoupling incomesupport to farmers from commodity prices and production (Defra,2008; EC, 1999). In the UK, CAP reforms and the EnvironmentalStewardship scheme reflect a new virtual contract between landmanagers and wider society, emphasising the role of farmers inparticular as environmental guardians as well as producers (Banksand Marsden, 2000; Defra, 2002; Latacz-Lohmann and Hodge, 2003;Moxnes-Jervell and Jolly, 2003; PCFF, 2002; Potter and Burney, 2002).Changing priorities evident in current rural and environmentalpolicies such as the Water Framework Directive, Habitat Directive,CAP Reform, Making Space for Water, and the new Flood and WaterBill, are encouraging a re-appraisal of land management options forrural land in general (Winter and Lobley, 2009) and lowland

Ecological Economics 69 (2010) 1510–1523

⁎ Corresponding author. NRI, University of Greenwich, Chatham Maritime, Kent ME44TB, United Kingdom. Tel.: +44 1634 883942; fax: +44 1634 883706.

E-mail address: helenaposthumus@hotmail.com (H. Posthumus).

Contents lists available at ScienceDirect

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j ourna l homepage: www.e lsev ie r.com/ locate /eco lecon

floodplains in particular (Morris et al., 2009). This includes the use oflowland rural floodplains to temporarily store flood water in order toavoid the flooding of urban properties and infrastructure elsewhere inthe catchment. However, global food shortages in 2007 and associatedhigh and volatile agricultural commodity prices have put food securityand agricultural production back on the political agenda. Simulta-neously, the floods in the summer of 2007 that caused extensiveagricultural damage in England (Posthumus et al., 2009) showed howrural land can provide emergency storage of flood waters thatalleviates damage in urban areas.

In this context, a research project entitled ‘Integrated Land andWater Management in Floodplains’ carried out under the UK RuralEconomy and Land Use (RELU, 2008) Programme explored opportu-nities to integrate farming, nature conservation and flood manage-ment in eight lowland floodplain areas in England. These werepreviously engineered for agricultural flood defence purposes. Thispaper focuses on the methodology that was developed to measureand value ecosystem services under different land managementscenarios that reflect different priorities for floodplain areas. Thebroad aim is to help provide guidance to organisations involved in thedesign and promotion of sustainable land and water management inthese important areas. The approach also has potential for applicationin the wider countryside. The particular purpose of the methodologypresented here is to demonstrate the impacts of contrastinghypothetical land use scenarios with different policy objectives onthe delivery of ecosystem services and the synergies and trade-offsbetween them. The objective is not to determine ‘optimal’ land usesolutions, but rather to inform a systematic comparison of land andwater management options using a set of pre-defined criteria. It isintended to further develop this work to support decision-making,including cost-benefit analysis of different land management options.Themethodology is demonstrated using a selected case study site, theBeckingham Marshes, Nottinghamshire in central eastern England.

2. Conceptual Framework

2.1. Ecosystem Approach

The ecosystem framework is increasingly used to explain the roleof the rural space in supporting and improving human well-being.From an anthropogenic viewpoint, the concept of ‘ecosystemfunctions’ represents the capacity of natural processes (methods ofcontinuous operation) to provide goods and services (items thatconfer benefit and advantage) to meet human needs, directly orindirectly (Brauman et al., 2007; De Groot et al., 2002; Turner et al.,2000; Zhang et al., 2007). The concept has gained much currencyfollowing its adoption by the Millennium Ecosystem Assessment(MEA, 2005) to represent the flow of benefits to society arising fromstocks of renewable natural resources and related ecosystems. Morerecently, the concept is also increasingly used in ‘engineered’ecosystems such as agriculturally managed landscapes (e.g. Porteret al., 2009; Sandhu et al., 2008; Swinton et al., 2007). Although adistinction is made between flows of goods in the form of physicalitems such as agricultural commodities and flows of services in theform of beneficial processes and work, such as temporary storage offlood water, the term ‘ecosystem services’ is used here to representboth types of flows.

The ecosystem approach has been used to represent the variety ofservices provided by floodplains as these satisfy the interests of a rangeof stakeholders: including land managers, flood management agencies,conservation organisations, local communities and society as a whole.Ecosystems provide the following five functions (De Groot, 2006):

− Production functions: the capacity to provide resources e.g. water,food, raw materials, and energy (production is linked to con-sumption functions).

− Regulation functions: the capacity to regulate essential ecologicalprocesses and life support systems e.g. regulating climatic, water,soil, nutrients, ecological and genetic conditions.

− Carrier functions: the capacity to provide space and location foractivities and processes e.g. habitation, cultivation, energy gener-ation, conservation, and recreation.

− Habitat functions: Provision of unique refuges and nurseries forplants and animals, helping with the conservation of genetic,species and ecosystemdiversity (habitats are sometimes treated aspart of carrier function).

− Information / cultural functions: the capacity to contribute tohuman well-being through knowledge and experience and senseof relationship with context e.g. spiritual experiences, aestheticpleasure, cognition and recreation.

In the case of floodplains, these ecosystem functions can supportflows of beneficial ecosystem services that are realised throughdominant types of land use such as agriculture, nature conservationand flood storage (Fig. 1). These different land uses and related servicesare of value to, and serve the interests of, different stakeholders. Thevalue of ecosystem services can be determined by estimating economicgains (e.g. agricultural production), avoided damage costs (e.g.infrastructure or residential properties at risk of flooding), continuedaccess to resources (e.g. maintenance of soil quality), or contribution tohuman well-being (e.g. landscape value or recreation). These valuesmaybebased onfinancial, economic or social indicators. The frameworkcontained in Fig. 1 provides an overall logic for valuation of ecosystemservices which is further developed below.

2.2. Hydrological Regimes and Land Management in Lowland Floodplains

The ecosystem services delivered by floodplains are inextricablylinked to hydrology (Morris et al., 2009). The hydrological regime of afloodplain determines what will grow there and how it can be used.Plant growth rates are reduced in waterlogged (i.e. saturated) soil dueto anoxic conditions in the root zone, restricted nutrient uptake andlower soil temperatures. If waterlogged conditions persist, this canlead to death of plants not adapted to anoxia, which includes almostall crop species. The impact depends on the timing in relation togrowth stage and the tolerance of individual species to wetconditions. High water tables for example (within 0.3 m of thesurface), would not support arable cropping and would limit land useto grassland or non-agricultural land uses. Under extreme wetconditions, the only plants that will grow are those specially adaptedto waterlogging, which may have high biodiversity value but lowagricultural value. Wet soils also have a reduced bearing capacity,such that ‘trafficking’ by machinery and animals can lead to soilcompaction and structural damage. For this reason, wet floodplainsoften cannot be farmed in the winter and can only support agriculturein the summer. Inundation by floodwater not only raises the watertable and submerges plants, but can cause physical damage to plantsdue to the erosive effects of flowing water. Physical assets can bedamaged or destroyed and operations interrupted. The more valuable(in economic terms) are the crops in the ground or the assets at risk,the greater is the potential damage.

Historically, the most common land use in English floodplains washay meadow and the natural hydrological regimes were manipulatedto maximise production. With the advent of artificial fertilisers,floodplains lost their pre-eminence for hay production. Newmethodsfor flood defence, drainage, and pumping enabled the naturalhydrological regimes to be modified, permitting many more landuse options, from intensive arable farming to flood storage. Thus, thehydrological regimes of floodplains are now typically defined byhuman preference for types of land use and the services they provide.Where flood risk is low and field water levels can be controlled toavoid waterlogging, intensive arable farming is possible. Less

1511H. Posthumus et al. / Ecological Economics 69 (2010) 1510–1523

intensive farming methods, such as grazing of wet grassland, cantolerate lower standards of flood protection and land drainage.Extensive faming also tends to be more closely associated with theprovision of non-market goods, such as nature conservation andamenity. Each land use type has potential to deliver a specific set ofecosystem goods and services.

3. Estimation of Indicators for Ecosystem Goods and Services

For each ecosystem function, the major services provided by thefloodplain and the units of valuation were identified. Indicators weredeveloped to assess the delivery of each ecosystem services underdifferent land use scenarios (Table 1).

3.1. Agricultural Production (Gross Output)

Agricultural production is currently the dominant land use in mostfloodplains and marketable agricultural commodities are one of the

main types of ecosystems ‘goods’ provided. Conventional croprotations are assumed to correspond with general farm types. Themethodology explained by Morris et al. (2008) was used to estimateagricultural production. Fig. 2 depicts the conceptual model of thecalculations involved. Potential yields of arable crops (t ha−1) werebased on Nix (2005) and adjusted according to fertiliser input(England, 1986), field drainage conditions (Dunderdale and Morris,1997) and flood probability (Hess and Morris, 1988).

Potential grass yield was estimated from soil available watercapacity (depending on soil type; NSRI, 2006), summer rainfall andNitrogen application, using estimated yield-response functions fromThomas and Young (1982) and Doyle (1982). These estimated yield-response functions were originally determined for modern rye grass.Conversion factors were based on Tallowin and Jefferson (1999) inorder to obtain an estimate of utilised dry matter for other grasslandcommunities (e.g. hay meadow or wet grassland). A minimumpotential yield of 5 tDM ha−1 was assumed. The actual grass yieldwas calculated taking the drainage conditions and flood probability

Fig. 1. Conceptual model of ecosystems goods and services provided by rural floodplains.

Table 1Indicators for ecosystem goods and services provided by lowland floodplains.

Function Good or service Indicator Unit

Production Agricultural production 1. Gross output £ha−1 year−1

Financial return 2. Net margin £ha−1year−1

Employment 3. Labour Man hours ha−1 year−1

Soil quality 4. Soil carbon stock kg C ha−1

Regulation Floodwater storage 5. Time to fill capacity daysWater quality 6. Nutrient leaching kg NO3 ha−1 year−1

Greenhouse gas balance 7. Global Warming Potential kg CO2 equiv. ha−1 year−1

Habitat Habitat provision 8. Habitat-conservation value ScoreWildlife 9. Species conservation value Score

Carrier Transport 10. Risk exposure road infrastructure £ha−1year−1

Settlement 11. Risk exposure residential properties £ha−1year−1

Space for water 12. Proportion of area annually inundated by fluvial flood ProportionInformation Recreation 13. Potential recreational use Score

Landscape 14. Landscape value Score

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into account, following the methods of Dunderdale andMorris (1997)and Hess and Morris (1988) respectively. The actual grass yield, interms of utilised metabolisable energy, was subsequently convertedinto a potential livestock carrying capacity and, depending on thelivestock system, converted into financial returns using standardestimates based on farm management data (Nix, 2005; ABC, 2006).Total agricultural production (including arable and livestock produc-tion) was estimated in terms of gross output (£ha−1), assuming thatmarket prices reflect the value of agricultural output. 2006 priceswere used throughout.

3.2. Financial Return (Net Margin)

Rural livelihoods are often supported by income derived from land-based activities. It is important, therefore, to consider financial returnsfrom different land use options. The financial returnswere based on thegross outputs for agricultural production (as above) and estimates ofvariable and fixed costs for the identified crop, grassland and livestockenterprises drawing on published farm business data (ABC, 2006; Nix,2005) and information collected from farm surveys in the study areas.The net margins (gross output less variable and fixed costs) includedanyfinancial support received by farmers under theprevailing CommonAgricultural Policy and Environmental Stewardship scheme (Defra,2005) if applicable to the scenario. For example, it was assumed that noagri-environment payments were received under the agricultural

production scenario. However, under the agri-environment scenario,only land use options that were eligible under the EnvironmentalStewardship scheme were considered.

3.3. Employment (Labour)

Different land use options generate different employment oppor-tunities and contributions to local rural economies. The annual labourrequirements (h ha−1) for agriculture was calculated as the total sumof all field operations, dependent on crop, soil type and machinery,based on standard estimates (Nix, 2005).

Labour requirements for non-agricultural purposes (e.g. natureconservation) were based on standard estimates provided by twonature conservation organisations (the RSPB and the Bedfordshire,Cambridgeshire, Northamptonshire and Peterborough Wildlife Trust)on the number of people employed (full-time equivalents) on naturereserves. Types of work included reserve management, survey andmonitoring, and visitor services, but did not include employmentthrough grazing lets and agricultural tenancies in order to avoid doublecounting these agricultural activities. Information was also collected onthe number of volunteer hours spent on reserve work and volunteerwardening. The sum of paid and volunteer employment was thendivided by the total size of nature reserve holdings in England held bythe two organisations to produce a mean estimate of labour require-ments (h ha−1). It was assumed that only sites managed under the

Fig. 2. Conceptual model for financial appraisal of land use in floodplains (Morris et al., 2008).

biodiversity scenario would be managed as nature reserves. Landmanaged under the agri-environment scenario was assumed to remainas part of agriculturally managed landholdings.

3.4. Soil Quality (Soil Carbon Stock)

Soil is a natural resource that, if well managed, can support futuredemands for ecosystem goods and services. The soil quality indicatorwas measured by estimating the soil carbon stock at equilibriumunder each scenario. This was based on estimates of equilibrium soilcarbon for different land uses classes provided by Adger et al. (1992).In order to accommodate a greater range of habitat types, a slidingscale was developed to determine soil carbon estimates based onestimates for “lowland rough grass” or “rough pasture” and “improvedgrass,” modified by their yield relative to improved grass.

3.5. Floodwater Storage (Time to Fill Capacity)

Floodplains are inherently prone to flooding and thus can providea mechanism for flood risk management by providing temporarystorage of flood water. The aim of flood water storage is to havemaximum attenuation of the flood peak in the river. The degree ofattenuation depends on the volume of storage relative to the flows inthe river (Förster and Bronstert, 2009). Thus an index of flood storagecapacity can be estimated from:

86400Qmed

where:

T Index of flood storage (days)S Storage volume (m3)Qmed Median annual flood (m3 s−1)

The storage volume, S, is comprised of above- and below-groundstorage. The above-ground storage was estimated from the area of theindicative floodplain (m2) multiplied by the depth of flooding (m),which is given by the height of the flood bank above average groundlevel. A minimum flooding depth of 1 metre is assumed if there is noflood bank. The height of the flood banks does not change betweenscenarios, except for the biodiversity scenario where flood banks arebreached to allow more frequent uncontrolled flooding. Although theagri-environment scenario assumes more frequent flooding, this iscontrolled by sluices.

The below-ground storage was estimated from the drainableporosity of the soil (dimensionless) multiplied by the depth to thewater table (m) and the area of the indicative floodplain (m2). Thedepth to the water table is dependent on land use and thus variesbetween the scenarios. For example, Acreman et al. (2007) estimatedthat storage in the soil and ditches lost by conversion of grazing to wethabitat was equivalent to 61% and 12% of the volume of medianannual flood respectively and was equivalent to 0.12 m of surfacestorage.

3.6. Water Quality (Nutrient Leaching)

Given its proximity to water courses, land use in floodplains tendsto have an immediate effect on water quality, in particular if there is achance of nutrient leaching caused by farming practices. The indicatorfor potential nitrate leaching (kg NO3 ha−1) was estimated based onthe agricultural productivity and associated inputs (Williams et al.,2006).

3.7. Greenhouse Gas Emissions (CO2 Equivalents)

Release of greenhouse gases, in particular carbon dioxide andmethane, is also closely linked with agricultural productivity. Theindicator for global warming potential (kg CO2 eq. ha−1) wasestimated using standard rates for farming systems and associatedinputs (Williams et al., 2006). Greenhouse gas fluxes for wetlandhabitats were based on Kasimir-Klemedtsson et al. (1997). Emissionsfrom peat soils are particularly significant and on sites containing thissoil type, additional emission data were incorporated for all land usetypes (based on Kasimir-Klemedtsson et al., 1997).

3.8. Habitat Provision (Habitat-Conservation Value)

Lowland floodplains can support unique habitats that perform keyecological functions. Rouquette et al. (2009) reviewed a number ofdifferent techniques to assess the value of these habitats. Thetechnique deemed to be most appropriate in the context of thecurrent study was a derived score based on the Ecological ImpactAssessment (EcIA) method. EcIA guidelines state that the potentialvalue of an ecological resource or feature should be determinedaccording to its importance at a defined geographical scale. Here,categories are identified, ranging from International Importancedown to Parish/Neighbourhood Importance. A set of simple decisionrules was developed in order to assign an ecological feature to anappropriate category, based on conservation priorities and signifi-cance of the habitat. Conservation priority was established byconsulting the EU Habitats Directive, Guidelines for the Selection ofBiological SSSIs (NCC, 1989), the UK Biodiversity Action Plan (BAP),Regional and County BAPs, and Environmental Stewardship TargetingStatements. The significance of the habitat was determined bycalculating the proportion of the national and regional resource thatoccurred for each habitat type at each site, and particular site-specificfeatures. Predicted habitats were assumed to have been restored orcreated successfully.

3.9. Species (Species Value)

Wet habitats that are unique to lowland floodplains provide avaluable repository of biodiversity. A species value indicator wasdeveloped based on the UK Biodiversity Action Plan (BAP) vertebrateand vascular plant species that could potentially occur under each ofthe scenarios given local conditions. To develop this indicator, anumber of species experts were asked to examine a list of the UK BAPspecies and to assign a habitat suitability score for each speciesranging from 0 (totally unsuitable) to 1 (ideal, primary habitat) foreach habitat that could potentially occur at the study sites. The scoreswere then weighted so that each species contributed equally to thetotal, regardless of howmany habitat types it occurred in. The speciesexperts also provided a score (from 0 to 1) assessing the colonizationpotential for each species at each site, based primarily upon thespecies’ existing range and its dispersal ability. By multiplying the twoscores together, values were derived for each habitat-speciescombination at each site, which were then summed to provide atotal species score for each habitat type. Finally, this score wasmultiplied by the area of each habitat that was projected to occurunder each scenario, divided by the total area, to produce a final scoreshowing mean species value per hectare for each scenario.

3.10. Transport (Flood Risk Infrastructure)

Floodplains can provide space for infrastructure. Any change in theprobability of flooding of infrastructure will result in a change in theeconomic damage. The indicator was based on the cost of flooddamage to transport infrastructure (£ha−1). This is given by the costof disruption to transport per day, multiplied by the annual flood

probability and the average duration in days of a flood event. The totalflood damage costs were divided by the size of the floodplain.

The daily cost of transport disruption was calculated usingstandard methods (Penning-Rowsell et al., 2005) whereby the costof travelling along the normal transport route is compared to the costof travelling along a diversion route, based on traffic volume, distance,speed of travel and type of traffic. Traffic volume was taken fromaverage volumes for different road classes given in National RoadTraffic Surveys (Department for Transport, 2005). Speed of travel(dependent upon class of road) and type of traffic were based onstandard estimates (Penning-Rowsell et al., 2005).

The average duration of a flood event was based on assumptionsinherent within each scenario. For the agricultural production andfloodwater storage scenarios, it was assumed that floodwaters wouldbe evacuated within 48 h of the flood peak passing, to give an averagedisruption period of four days in total. Under the biodiversity scenario,removal of flood waters would mostly be natural, relying on gravity,thereby causing disruption for an estimated mean of ten days. Floodduration under the agri-environment scenario would fall betweenthese two extremes.

3.11. Settlement (Flood Risk Residential Properties)

Floodplains often accommodate residential properties, such asfarmhouses, which are at risk of flooding. The hydrological regimedetermines the flood risk to these properties. The average annual costof flood damage to residential buildings (£ha−1) was calculated usingstandard estimates for flood damage costs depending on the annualflood probability and the number of existing residences in the casestudy site. The standard estimates for flood damage to residentialproperties of Penning-Rowsell et al. (2005) were used to calculate thetotal flood damage. These total flood damage costs were divided bythe size of the floodplain.

3.12. Space for Water (Proportion of Area Flooded Annually)

The flood risk management strategy for England ‘Making Space forWater’ (Defra, 2004) aims to manage flood risk in a more integratedand holistic way. One of the mechanisms is to widen river corridorsand reconnect rural floodplains with rivers to enlarge the spaceavailable for flood water storage. This indicator reflects the naturalfunction of floodplains referred to under ‘Making Space for Water’strategies (Defra, 2004). It was calculated by dividing the area of theindicative floodplain by the total area of the floodplain, andmultipliedby the annual flood probability as defined in the hydrological regimeof each scenario. In natural rivers, the bank full discharge is exceededon average every two years (Leopold et al., 1964). We have assumedtherefore that the ‘natural’ ‘space for water’ for the indicativefloodplain area approaches the ratio of 0.5, and that under managedscenarios, with a lower flood frequency, the space for water is reducedproportionally. If the indicative floodplain covers only a smallproportion of the entire floodplain under consideration, the ‘natural’value for space for water will be lower than 0.5, indicating that thisfloodplain might be less suitable for space for water purposes becauseof its topography.

3.13. Recreation

Floodplain areas are potentially important locations for recrea-tional activities. Studies that have attempted to predict recreationaluse (e.g. Brainard et al., 2001; Chan et al., 2006; Gimona and van derHorst, 2007; Haines-Young et al., 2006) have shown that the mainattributes affecting recreation are access, land cover, visitor facilities,number of alternative sites, and size of population. Therefore, ascoring system was developed, with each scenario scored on a scalefrom 1 to 5 against each of the following attributes; density of public

rights of way (footpaths, bridleways), cultural heritage value of theprojected land uses, and proximity of alternative similar sites. Thisscore was then multiplied by a score (also out of 5) for the populationliving within 3 km travel distance of any part of the site. Populationdata were extracted from the 2001 UK Census. The population sizewas classified into five population bands so that this factor was of thesame scale as the other three attributes.

3.14. Landscape Value

Producing an indicator for landscape value is complex. There arefew standard procedures to follow and several recent studies havesuggested that landscape values cannot be estimated in monetaryterms at present. There is significant potential for double counting;recreation, aesthetics, cultural heritage, and enjoyment of wildlife areall intrinsically linked and difficult to separate (Swanwick et al.,2007). Indeed, there has been a shift away from attempting toperform absolute landscape valuations to valuing change in landscapecharacter, representing its marginal value. Hence the method adoptedhere was based on the latter approach and is an extension of the“Countryside Quality Counts” project (CQC, 2009; Haines-Young et al.,2004; Haines-Young, 2007).

The UK statutory agencies have divided England into areas withsimilar landscape character known as Joint Character Areas (JCAs) andthe Countryside Quality Counts (CQC) project was commissioned toassess changes in the landscape character of each of these areas.Consistent with the CQC methodology, the impact of each scenariowas assessed over a number of themes: trees and woodland,boundary features, agriculture, semi-natural habitats, and river andcoastal. An assessment was made of whether any projected changewould be consistent or inconsistent with the appropriate JCA visionstatement, with the following categories:

• Enhancing — changing and consistent with vision (score of +2)• Maintained — stable and consistent with vision (score of +1)• Neglected — stable and inconsistent with vision (score of −1)• Diverging — changing and inconsistent with vision (score of −2).

The themes were weighted, with double weight provided to thosethemes identified in the CQC as being key to the character of the JCA(ibid), to give an overall score on the impact of each scenario on thelandscape value of the area.

3.15. Normalisation of Outcomes

The estimated values for the indicators were normalised in orderto be able to compare the performance of each scenario against theindicators. This was achieved by dividing the outcome for indicator xof scenario i by the maximum value of xi. The normalised value for themaximum indicator score (i.e. the scenario with the best performancefor indicator i) is thus equal to one. The normalised values of theindicator scores for other scenarios are relevant to the maximumscore, within the range of zero to one. The values for indicators ofundesirable impacts (e.g. greenhouse gas emissions, nutrient leach-ing, flood risk for settlement and transport), however, are negative.This means that the score for the scenario with the worstperformance, that is the highest value for the undesirable impact, isset at minus one for these indicators. The normalised values of theundesirable impacts for the other scenarios are thus within the rangeof minus one to zero.

After normalising all values, the indicators can be given weightsaccording to their importance. For the purpose here, all indicators areconsidered of equal importance thus having equal weights, as theweighting depends on the context as well as stakeholder preferencesand policy objectives.

4. Case Study

The analytical framework is demonstrated here using one of thestudy sites from the RELU ‘Integrated Floodplain Management’ project(RELU, 2008).

4.1. Study Area

The Beckingham Marshes is a floodplain covering about 900 ha,situated on the left bank of the River Trent in Nottinghamshire,opposite the town of Gainsborough, in the east Midlands of England(Fig. 3). Prior to 1950, the area was almost entirely grassland andmarsh (used for willow production) and acted as a natural washlandfor the protection of Gainsborough. However, in the 1950s, about onequarter of the area was converted to arable. The flood defences(designed for 1:20 year flood events) were strengthened in the 1960sand in the 1970s the arterial drainage system was improved and newpumps installed to lower water levels in the main drains by up to0.3 m. By 1983, 82% of the land was arable and 74% had new fielddrainage installed (Morris et al., 1984). By 2000, almost the entirefloodplain had been converted into arable land for predominantlywheat and oilseed rape production.

This situation prevailed until 2005 when a collaborative venturebetween the Environment Agency and the Royal Society for theProtection of Birds (RSPB) planned to revert (initially) about 10% ofthe area to wet grassland for nature conservation. In 2005, RSPBreverted 90 ha of arable land back into grassland, and intended toraise water levels in the designated area in order to create habitatssuitable for lapwing (Vanellus vanellus) and other wading birds.However, concerns were raised that this could reduce the floodwaterstorage capacity, as well as affect agricultural productivity on adjacentland. As a consequence, there are unresolved differences betweenstakeholders with potentially competing interests in farming, floodmanagement and habitat provision.

Of the six farmers interviewed, fivewere arable farmers cultivatingmainly winter wheat and oilseed rape. The sixth grazed beef cattle onthe RPSB grassland. Five farmers had joined an agri-environmentscheme to obtain additional payments. Only one farmer was entirelyreliant on the farm for his income. The others also obtained incomefrom activities such as contracting or renting out farm cottages. Fourfarmers were aged between 50 and 65. Three farmers said therewould be no successors within the family to take over the farm infuture, whereas only two were fairly certain to have successors andone was uncertain. The absence of a successor on a farm is likely toinfluence the attitude of a farmer towards land management in thelonger term. Posthumus and Morris (2007) found that farmerswithout successors are more likely to adopt less intensive farmingpractices, possibly in combination with the implementation of agri-environment schemes, when approaching retirement.

4.2. Data Collection

The six farmers occupying the Beckingham Marshes were inter-viewed during 2006/7. Structured questionnaires were used to collectdata on current farming systems, land use, farm inputs and outputs,and field drainage. Ecological surveys were undertaken in summer2007 to determine current habitats and biodiversity. Secondary datawere collected from previous studies and regional and national datasets as referred to in Section 3.

4.3. Land Use Scenarios

Six alternative scenarios were developed in order to examine thepotential synergies and conflicts in the delivery of ecosystem goodsand services between land uses. These were chosen to reflect thecurrent situation and alternative uses under different policy options.For each scenario, expert judgement was used to determine the typeof land use required to meet the scenario's objective, subject toconstraints. Typical constraints taken into account were climate, soil

Fig. 3. Map of the Beckingham Marshes, England.

type, and for some scenarios current farming systems. However, itwas assumed that the hydrological regime is adjusted to suit land useby imposing required levels of control over drainage and floodprobability. For each scenario, land use is thus determined by theinteraction of site characteristics and the scenario objectives. This, inturn, determines the seasonal hydrological regime required to sustainthat particular land use. The seasonal hydrological regimes aredefined in terms of the number of days with surface water, meanwater-table depth and flood probability.

Six different land management scenarios were developed with thefollowing objectives and restrictions:

1. Current situation (2006): based on land use and managementinformation (including actual level of inputs and outputs) collectedduring farmer interviews and ecological surveys carried out in2006 and 2007. This baseline scenario for the BeckinghamMarshesis typified by winter wheat, in rotation with oilseed rape, fieldbeans and peas, as the heavy clay soils are less suitable formechanised root crop production. The RSPB-managed grasslandsupports an extensive beef system and it is assumed that thissystem will prevail under other ‘wet’ scenarios.

2. Agricultural production: comprises intensive agricultural land usefor food production. This was the objective when land drainagewas improved in the 1960s and 1970s. Land use is defined by soiland climatic potential, and themain farming systems in the area. Inmainly grassland areas, this scenario involves intensive dairy. Inpredominantly arable areas, this scenario mainly consists ofcereals, legumes, oilseed rape and root crops such as sugar beetand potatoes, depending on soil suitability. For the BeckinghamMarshes, the land use is similar to the 2006 scenario, but farmingsystems are more intensive. The recently established RSPB areawith grassland is converted back into arable land. The hydrologicalregime is characterised by rapid drainage and controlled, low floodfrequency by maintaining the flood banks and pumping station.

3. Agri-environment: seeks to enhance biodiversity with the imposedconstraint that the land remains predominantly agricultural. Landuse options are those promoted by current agri-environmentschemes, in particular the Higher Level Scheme (Defra, 2005). Localsoil conditions, topography and historical context, together withlocal and regional conservation and land use priorities are used todetermine the specific habitat types that would be created. Thehydrological regime attempts to combine the requirements ofagriculture and wildlife habitat. Under this scenario, the mostappropriate land use in the Beckingham Marshes is a combinationof wet grassland for breeding waders and species-rich haymeadow, which supports an extensive beef system. This cantolerate medium-duration flooding and moderate drainage. Theflood banks and pumping station remain in place, but the inflow ofwater from the river is controlled by a sluice system.

4. Biodiversity: seeks to enhance biodiversity, without imposedconstraints, guided by local and national Biodiversity Action Plantargets. The same criteria are used for determining the habitattypes as for the previous scenario except for the constraintsimposed by agricultural production. Therefore, under this scenariothe BeckinghamMarshes is converted into a large area of reed bedand wet woodland, along with some wet grassland. The hydrolog-ical regime is characterised by frequent flooding and slow naturaldrainage by gravity. The flood banks are breached by insertingspillways and the pumping station becomes redundant.

5. Floodwater storage: seeks to maximise the attenuation of the floodhydrograph as part of a strategic flood risk management scheme.The floodplain is managed to maximise flood water storagepotential when the river reaches design discharge and to evacuatestored floodwater as quickly as possible after the event (in order toprovide storage for subsequent events). This scenario thus requiresa hydrological regime with controlled low flood frequency

(1:10 year) and rapid drainage, which is compatible with arableland use. A land cover type with high transpiration rates (eitherimproved grass or winter cereals) maximises below-groundstorage. As the Beckingham Marshes is currently predominantlyarable, cereals (in rotation with oilseed rape and legumes) aregrown under this scenario. The flood banks and pumping stationare maintained.

6. Income: seeks to maximise the income derived from the land. Theland use for this scenario is determined by one of the previousscenarios with the highest estimated annual profitability perhectare (defined in terms of the difference between total revenuesand total average costs, where the latter includes both variable andfixed costs). At 2006 prices (wheat price is taken as £68 per tonne),the highest income in the Beckingham Marshes is obtained fromgrazing marsh with extensive beef. For this scenario, farmersreceive payments under the Higher Level Stewardship scheme of£335 a year for maintenance of wet grassland for breeding waders.Thus the Income scenario is similar to the agri-environmentscenario.

Table 2 summarises key characteristics of the different scenariosfor the BeckinghamMarshes. The scenarios that prioritise biodiversityhave a ‘wetter’ hydrological regime than the agricultural productionand water storage scenarios, which involve short duration floodingand rapid drainage of soils. Although it seems counterintuitive, theincome scenario has the highest flood probability. Under theeconomic conditions in 2006, floodplain grazing marsh is the mostprofitable land use option due to the agri-environment paymentsawarded to this habitat type. To obtain maximum income, this habitatwould need to cover a large proportion of the floodplain. However,this habitat requires frequent flooding to be sustained, resulting in ahigh flood probability.

The values of the indicators vary between scenarios as land useand hydrological regime change. Note that, when calculating theindicators, it is assumed that the scenarios are under full establish-ment and differences in financial performance reflect differences inaverage annual benefits and costs.

4.4. Scenario Outcomes: Ecosystem Goods and Services

Indicator values for various ecosystem services are shown inTable 3, assuming that the scenarios for BeckinghamMarshes are fullyestablished. The indicators confirm the environmental impact ofintensive agriculture: scenarios with intensive farming systems showhigh values for global warming potential and nitrate leaching.Scenarios featuring low-input wet grassland and extensive agricultureexhibit low environmental impacts. The scenarios with intensiveagricultural systems (maximum production and maximum floodstorage) also have the lowest scores for habitat-conservation value;marginally lower than the conservation value of the current land useand considerably lower than the maximum value that could beachieved. The habitat-conservation value achieved under the agri-environment scenario is marginally higher than that under thebiodiversity scenario, primarily due to the high nature-conservationvalue of alluvial hay meadows. Flood risks vary between scenarios asthe flood probabilities vary: the higher the flood probability, thehigher the average annual costs of flood damage within thefloodplains. Flood damage costs are low in comparison with themonetary values of other indicators. This is because total flooddamage costs for infrastructure and residential homes are divided bythe total size of the floodplain to enable comparison betweenfloodplains of different sizes. Most rural floodplains in the UKcomprisemainly agricultural land; the density of roads and residentialhouses is generally low. Therefore, the average flood damage cost perhectare is relatively small.

Fig. 4 shows the total sum of normalised values of the indicators forBeckingham Marshes. The agri-environment and maximum income(based on environmental payments) scenarios achieve the highestcumulative scores for ecosystem goods and services. It should benoted that these two scenarios are similar in terms of land use andfarming systems. The production and flood water storage scenariosare also similar and achieve similar scores for the indicators. Bothscenarios negatively impact water quality and greenhouse gas balance(meaning that the emissions of greenhouse gases is higher). Theimpact on landscape is also negative because landscapes under thesescenarios diverge from the landscape character that is encouraged byUK statutory agencies (see Section 3.14). The biodiversity scenarionegatively impacts on transport and settlement because of increasedflood risk. Note that the scores shown are unweighted and thus all theecosystem services listed are considered of equal importance.

5. Discussion

Fig. 5 illustrates the potential synergies and conflicts in ecosystemservices under different scenarios for the Beckingham Marshes case.The performances of the floodwater storage and production scenariosare very similar in terms of key indicators. Indeed, both scenarios havesimilar hydrological regimes, and similar land uses. Both scenariosscore highly on production and flood water storage, but they score

low on environmental indicators (e.g. water quality and greenhousegas balance). In contrast, the agri-environment and biodiversityscenarios have generally a positive environmental impact. However,the biodiversity scenario results in an increased flood risk forsettlement and transport, and reduced flood water storage as floodbanks are breached and flooding is uncontrolled. By comparison,flooding is controlled with sluices and pumps under the agri-environment scenario. Hence there is little increase in flood risk andthe floodplain can be used for flood water storage.

Some of the results are sensitive to price fluctuations, particularlyfor the income scenario. The results shown here reflect 2006 marketconditions. However, wheat prices doubled in 2007 as a result ofglobal shortage of cereals. If a 2007 price of £136 per tonne of feedwheat is used instead of the 2006 price of £68 per tonne, cerealproduction is more profitable than the Higher Level EnvironmentStewardship payments. The income scenario would then be similar tothe production scenario. Indeed, farmers interviewed in the firstquarter of 2007 commented that it was more profitable to give upintensive farming and receive agri-environment payments to createhabitats for breeding waders. In 2006, the year taken as a baseline forthe scenarios, extensive arable (cereals) and grassland (beef) farmingsystems were not profitable as they had negative net margins if farmincome support payments are excluded. But farmers interviewed late2007 and early 2008 suggested that, if cereal prices were to stay high

Table 2Scenario characteristics for the Beckingham Marshes.

2006 Agriculturalproduction

Agri-environment Biodiversity Flood waterstorage

Income

Total days with surfacewater

35 3 73 115 0 113

Mean water table depth (m) 0.5 0.6 0.4 0.1 1.0 0.3Annual flood probability (%) 10% 10% 50% 50% 10% 60%Land use Cereals, grazing

marshCereals, root crops Grazing marsh, floodplain

meadowReed beds, wet woodland,grazing marsh

Cereals Grazingmarsh

Cereals 39% 64% 63%Oilseed rape 19% 21% 25%Peas / beans 19% 11% 13%Potatoes / sugar beet 4%Set-aside 6%Improved permanentpasture

15% 6% 15% 20%

Alluvial hay meadow 48%Floodplain grazing marsh 46% 8% 80%Reed bed 46%Woodland 32%Livestock Extensive beef – Extensive beef Extensive beef – Extensive

beefStocking rate during grazingseason (LU ha−1)

2.59 0 2.41 2.86 0 2.58

Table 3Scenario outcomes for the Beckingham Marshes.

Indicator Unit 2006 Agricultural production Agri-environment Biodiversity Flood water storage Income

Gross output £ ha−1 404 591 332 85 544 346Net margin £ ha−1 168 176 483 376 204 538Employment hours ha−1 11 15 16 30 13 16Soil quality t C ha−1 69 60 204 310 65 277Flood water storage days 0.85 0.85 0.85 0.32 0.86 0.84Water quality kg NO3 ha−1 29 34 24 6 37 25GWP kg CO2eq. ha−1 3426 4789 1649 2390 4573 1720Habitat score – 1.32 1.01 5.82 5.07 1.01 4.60Species score – 1.33 1.22 2.15 1.64 1.13 2.29Flood risk infrastructure £ ha−1 0.04 0.04 0.06 0.68 0.04 0.06Flood risk properties £ ha−1 5.86 5.86 5.86 26.26 5.86 5.86Space for water – 0.08 0.13 0.49 0.55 0.10 0.61Recreation score – 16.2 15.2 53.5 56.3 15.5 46.0Landscape score – 4 −10 13 6 −10 13

Note: see text for descriptions of scenarios.

Fig. 4. Normalised scores for ecosystem goods and services under different land use scenarios.

Fig. 5. Synergies and conflicts between ecosystem goods and services under different scenarios.

they would consider abandoning agri-environment schemes in favourof a return to cereal production. Indeed, with 2007 prices net marginsfor wheat production become positive. It is clear from our discussionswith floodplain farmers at Beckingham Marshes and elsewhere thatthe rewards for commercial farming provide a reference point againstwhich farmers compare other land use options. It is perhaps atautology to suggest that the preference of famers is to farm. But it isclear that strong prices for agricultural commodities, whether drivenby policy or market processes, put greater emphasis on productionfunctions and related ecosystem services in floodplains.

The objective herewas to develop a framework for the assessmentof ecosystem goods and services for rural floodplains. Identificationof the most appropriate set of indicators is critical. For the purposehere, indicators must be: a) sensitive to changes in the ecosystemgood or service; b) objectively verifiable, generating results that arerepeatable by others; c) practicable in terms of easiness andconvenience of estimation; and d) reliable in most conditions, withlittle interference from other factors andwith an acceptable degree ofuncertainty.

Table 4 summarises the methods used to estimate the indicators,including their strengths and weaknesses. Most indicators used forecosystem services associated with production and regulation func-tions of the ecosystemwere found to be reliable and repeatable. Theseindicators were based on well-established methods and datasets.Methods are also being developed for ecosystem services under thehabitat function (see Rouquette et al., 2009 for a review). Indicatorsconcerning carrier functions, especially impact of flooding on housing,transport and infrastructure, can draw on data and methodsdeveloped for flood risk management purposes (Penning-Rowsellet al., 2005). However, the development of appropriate indicators andestimation methods for information and cultural functions, notablylandscapes, remains a particular challenge because of (a) limitedunderstanding of the processes by which the values of these servicesto society are formed (Swanwick, 2009) and (b) lack of data andmethods to derive values to support land management decisions.

There is considerable scope to improve the estimates of someindicators. For example, the indicators for ‘space for water’, floodwater storage, settlement and transport can be improved by usingtopographical data and hydrological models that allow more accurateestimation of the extent and depth of flooding. Stated preferencetechniques, such as contingent valuation and choice experiments, canbe used to estimate monetary values for nature conservation,recreation and landscape in floodplain areas. There is scope to derive‘standard’ values for these services for specific types of floodplainscharacteristics which can be ‘transferred’ to similar sites elsewhere tosupport land use appraisal.

Despite the limitations, the indicators developed here provideuseful instruments for the comparison of ecosystem servicesdelivered by specific floodplain areas under different managementscenarios. However, it needs to be stressed that non-monetaryindicators developed here provide relative rather than absolutescores, and are better suited for comparing options for a given siterather than comparing the same option on different sites.

In recent years, the literature on the analysis of multi-functionalityand the valuation of ecosystem services has expanded considerablyand various assessment methods have been developed (e.g. Boyd,2007; De Groot, 2006; Fisher et al., 2009; Paracchini et al., in press).Assessments that take multiple ecosystem services into account oftenapply cost-benefit analysis (e.g. Boyd, 2007; Costanza et al., 1997; DeGroot, 2006) or multi-criteria analysis (e.g. Brouwer and Van Ek,2004; Prato and Herath, 2007). Although land use planning decisionscan be informed by cost-benefit analysis, it is difficult to derive‘objective’ values for intangible non-market services such as habitatprovision or landscape values, especially as these are typicallydependent on circumstantial factors such as the time frame, scale,personal preferences, and cultural bias (Mitsch and Gosselink, 2000).

Furthermore, landowners typically evaluate alternative managementsystems based on their preferences for multiple criteria (Prato andHerath, 2007). The inclusion of qualitative social criteria in the multi-criteria analysis of management options for floodplains can lead todifferent outcomes compared with cost-benefit analysis (Brouwerand Van Ek, 2004). In this respect, the type of multi-criteria analysisapplied here enables a comparative assessment of ecosystem servicesfor alternative land and water management scenarios, especiallyregarding the assessment of non-monetary values.

Whereas the purpose here was to develop a comprehensive set ofindicators for the integrated assessment of ecosystem services underdifferent landmanagement scenarios, previous studies have tended tofocus on a limited number of economic and environmental indicators(e.g. Santelmann et al., 2004; Prato and Herath, 2007). Furthermore,they have mainly assessed land use at regional or global scales (e.g.Costanza et al., 1997; Paracchini et al., in press; Santelmann et al.,2004), or at the farm scale (e.g. Prato and Herath, 2007). The methodpresented here considers land use planning at the local andpotentially catchment scale. Indeed, Janssen et al. (2005) argue thatsuch a method is required to provide decision support for localstakeholders.

6. Conclusion

Six alternative floodplain management scenarios were developedto reflect different priorities for land use in lowland floodplain areas. Aset of indicators were used to measure and value the ecosystemservices produced by each scenario on a case study site.

There are both synergies and conflicts between ecosystemservices delivered by lowland floodplains. Some are as expected.There is conflict, for example, between agricultural production andenvironmental outcomes such as water quality, greenhouse gasbalance, habitat and species. Other relationships are less obviousand may challenge commonly held beliefs. There is for example,potential synergy between short duration flood storage (to deliverbenefits to urban areas downstream) and agricultural production.Contrary to popular belief, there can be potential conflict betweenflood storage and biodiversity. Some wetland habitats and speciesare sensitive to flooding and yet require high ditch and water tablelevels that use up potential flood storage capacity. ‘Making space forwater’ that aims amongst other things to reconnect rivers withfloodplains, may not always provide flood risk managers with thedegree of hydraulic control required to hold back flood waters andprevent downstream urban flooding. The methods here provide abasis for quantifying these relationships, recognising the impor-tance of local conditions.

The financial performance of different land uses under eachscenario is sensitive to farm output and input prices and agri-environment payments. This has implications for the design andimplementation (i) of hybrid or composite land and water manage-ment scenarios that will be beneficial and robust under a range offuture possible conditions, and (ii) of policy and support regimes thatwill make such scenarios appealing to the main stakeholders,especially land managers, conservationists, flood managers and localcommunities.

Developing methodologies to estimate quantities and values forecosystem services is challenging but necessary in order to take theecosystem approach forward. This case study shows that estimationof indicators enables synergies and conflicts between ecosystemservices to be revealed. Modelling scenarios for different land usescan support decision-making of policy makers and planners. Theycan also be used to inform discussions amongst stakeholders aboutoptions that can serve a range of different interests. However, cautionis required. Not all data needed for reliable estimates are availableand estimates are thus dependent on assumptions and informedjudgements of experts and citizens. The interrelationships are

complex and vary according to local conditions. The valuation of non-market goods remains a particular challenge. Nevertheless, acombination of scenarios and indicators, set in an ecosystems

framework, can help if used judiciously, to assess managementoptions for land and water resources, as shown here for thefloodplain case.

Table 4Assessment of suitability of indicators for ecosystem goods and services.

Ecosystemfunction

Ecosystem goodor service

Indicator Units Sensitivityto change

Objective Practicable Reliable Strengths Weaknesses

Production Agriculturalproduction

Gross output £ha−1

year−1X X X Reasonably good

standard estimatesavailable from annualnational farm surveys.

Values will vary on individual farmsbecause of local factors such as soil type,management, weather conditions, pestsand diseases.

Financial return Net margin £ha−1

year−1X X X Same as for Agricultural

productionValues will vary on individual farmsbecause of differences in managementand farm assets.

Employment Labour man hoursha−1

year−1

X X Good standard estimatesfor farming systems.

Values will vary on individual farmsbecause of differences in managementand machinery. Estimates for naturereserves are less reliable.

Soil quality Soil carbonstock

kg C ha−1 X X Easy to apply. Valuesare estimated forbroad categoriesof land use and do not distinguishvariations within land use class. Valuesare based on one scientific study and notvalidated. Values at local scale will differbecause of differences in soil, climate andland management practices.

Regulation Floodwaterstorage

Time to fill days X X X Good estimates offloodplain area anddischarge are easilyavailable.

Does not consider the catchment-specificimpact of floodwater storage facility onflood risk to downstream receptors.

Water quality Nutrientleaching

kg NO3

ha−1

year−1

X X X Entire agriculturalproduction system istaken into account

Values for individual farms will varybecause of differences in managementand environment.

Greenhouse gasbalance

GlobalWarmingPotential

kg CO2

equiv.ha−1

year−1

X X X Entire agriculturalproduction system istaken into account,including fabrication offertilisers andmachinery.

Same as for Water quality

Habitat Habitatprovision

Habitat-conservationvalue

score X X X Assessment againstwell-understood pre-defined prioritizationcriteria.

Assumes all habitats have been createdsuccessfully. Some subjectivity inapplication. Insensitive to small changeswithin a site.

Wildlife Speciesconservationvalue

score X X Represents current UKconservation priorities.

Results are dependent upon speciesselected for UK BAP list which do notequally represent all habitats or taxa.High uncertainty.

Carrier Transport Risk ofdisruption toroadinfrastructure

£ha−1

year−1X X Allows estimations of

economic cost ofdisruption.

Is not taking local traffic flows andinfrastructure into account. Any repaircosts are ignored. Also, local topographyhas not been taken into account toestimate actual flood depth on the roads.Therefore estimates have high degree ofuncertainty.

Settlement Risk ofdamage toresidentialproperties

£ha−1

year−1X X Allows estimation of

flood damage cost.Is not taking attributes of individualhouses and contents into account. Also,local topography has not been taken intoaccount to estimate actual flood depth ofthe houses. Therefore estimates have highdegree of uncertainty.

Space for water Proportion ofareainundated byfluvial floodeach year.

year−1 X X It gives a value for the‘naturalness’ and extentof the flood regime.

The assumption is made that the entireindicative floodplain (representing thearea flooded for a 1:100 flood if there areno flood banks) is flooded during eachflood event. Local height differences andmagnitude of flood events are not takeninto account. Hydrologicalmodelswouldallow the estimation of the actual areaflooded.

Information Recreation Potentialrecreationaluse

score X X Allows comparison ofrecreation potentialbetween scenarios andbetween sites.

Scoring system is not based on empiricalresearch, nor does it estimate thevalueofrecreation to society. High uncertainty.

Landscape Landscapevalue

score X Allows assessment ofhow each scenariocontributes or obstructsgovernment policy onlandscape conservation.

Scoring system does not allowestimation of the value of landscapes tosociety. High uncertainty

Acknowledgements

This work was carried out under the Rural Economy and Land UseProgramme (http://www.relu.ac.uk) funded by the UK ResearchCouncils, the Scottish Government and the Department for Environ-ment, Food and Rural Affairs. The contributions from Eric Audsley andAdrian Williams of Cranfield University to the analysis are mostappreciated.

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A framework for the assessment of ecosystem goods and services; a case study on lowland floodplains...

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