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ANALYSIS OF THE COSTS AND BENEFITS OF ALTERNATIVE SOLUTIONS FOR RESTORING

BIODIVERSITY

Defra Competition Code: WC0758/CR0444

BUILDING AND EVALUATING ALTERNATIVE MANAGEMENT SCENARIOS

Appendix 1 to Final report to Defra - December 2010

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Hodder, KH; Douglas S; Newton, A; Bullock, JM; Scholefield, P.; Vaughan, R. Cantarello, E; Birch, J.

Contact: Dr Kathy H. Hodder CCEEC, School of Conservation Sciences Talbot Campus

Bournemouth University

Talbot Campus Poole, Dorset BH12 5BB Tel: 01202 966784, Fax: 01202 965046 Mobile: 07905 161180 khodder@bournemouth.ac.uk

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CONTENTS

1. CREATING SCENARIO MAPS .................................................................................................................... 3

2. VALUATION APPROACH FOR THE SELECTED ECOSYSTEM SERVICES..................................... 3

2.1 FOOD, RAW MATERIALS /FIBRE, AND FUEL / ENERGY .................................................................................. 3 2.2 FRESH WATER PROVISION ............................................................................................................................. 5 2.3 CARBON STORAGE ........................................................................................................................................ 5 2.4 FLOOD PROTECTION ...................................................................................................................................... 7 2.5 RECREATION/TOURISM ................................................................................................................................. 9 2.6 AESTHETIC BENEFITS .................................................................................................................................. 11

3. VALUATION APPROACH FOR BIODIVERSITY CONSERVATION ................................................. 12

3.1 AREA OF PRIORITY HABITAT ....................................................................................................................... 13 3.2 ECOLOGICAL IMPACT ASSESSMENT ............................................................................................................ 13 3.3 CONNECTIVITY ........................................................................................................................................... 15

4. ASSESSMENT OF COSTS ........................................................................................................................... 17

4.1 PRODUCTION COSTS .................................................................................................................................... 17 4.2 IMPLEMENTATION AND RUNNING COSTS ..................................................................................................... 17 4.3 OPPORTUNITY COSTS .................................................................................................................................. 18

5. THE CASE STUDIES .................................................................................................................................... 19

5.1 WILD ENNERDALE ...................................................................................................................................... 19 5.2 THE GREAT FEN PROJECT ........................................................................................................................... 33 5.3 HEATHER AND HILLFORTS PROJECT............................................................................................................ 45 5.4 THE KNEPP WILDLAND PROJECT ................................................................................................................ 54 5.5 PUMLUMON PROJECT .................................................................................................................................. 66 5.6 FROME CATCHMENT.................................................................................................................................... 81

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1. Creating scenario maps The scenarios were created in ArcGIS in collaboration with case study representatives: full details are given in section 5. The pre-project scenarios were made by reference to existing vegetation survey, such as NVC survey or remotely sensed land cover data. Mapping the future scenarios then involved modification of the existing maps using a combination of stewardship and management plans or strategy documents, where available, and expert opinion.

2. Valuation approach for the selected ecosystem services Where possible, the values were mapped to land-use / land-cover (henceforth ‘land cover’) for the scenarios, enabling visualisation of differences. While many recent studies have provided ecosystem service valuation (Natural England 2009a; O'Gorman & Bann 2008b; Tinch & Provins 2007b), there are few examples where the spatial dimension has been considered in detail. Mapping these values is a relatively novel approach and is important because benefits are not uniformly produced or used across the landscape.

2.1 Food, Raw materials /Fibre, and Fuel / Energy

These three benefit categories can be assessed using market price because they are tangible goods, frequently traded in established markets, with observed or estimated market prices. The approach has been widely adopted and advocated (Chan et al. 2006; Christie et al. 2008; Kettunen et al. 2009a; Natural England 2009a; Nelson et al. 2009; Pascual et al. 2010). However, a number of caveats should be considered when using market price. Firstly, it has been suggested that valuation should be based on sustainable production/extraction only, so that value is not ascribed to goods harvested at unsustainable levels incurring more damage to the ecosystem than they are worth (Eftec & Just Ecology 2005a; Kettunen et al. 2009a). This is a valid position: however, determining the sustainability of each benefit would be an enormous task, prone to difficult and potentially subjective decisions. Therefore, this has not been adopted. Secondly, market price may underestimate values because the price a consumer pays for a good or service is a minimum expression of their willingness to pay - i.e. consumer surplus is not accounted for (Eftec 2006b; O'Gorman & Bann 2008b). Currently though, the lack of reliable and locally relevant data on willingness to pay make market price a better choice of method. Finally, market prices can be distorted through monopoly, government intervention, taxes, subsidies, and so on (Eftec 2006b; Kettunen et al. 2009a). As this study is based on comparisons between scenarios this issue is of reduced importance. If comparisons were to be made between services within each site it should be given greater consideration. Method Valuation methods were developed for the food and fibre categories using a combination of site-based and UK standard or generalised data sources. The fuel and energy category was investigated but there was insufficient data available in the case studies to enable quantitative evaluation. (i) Food Recorded or predicted crop and dairy yields, and livestock number, were sourced for most scenarios. Ideally, locally available prices and production costs of these services would also be

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used. However, as there may be many products, produced by different means, by a large number of land managers, the local pricing approach was not feasible for some of the case studies, especially those covering a large area with complex ownership. Instead, our method used net standard values, giving a generalised estimate, which has reduced accuracy, but is valid for comparisons of relative values between scenarios. Estimates based on local monetary data were also made where possible, enabling comparison of the conclusions reached using the two approaches. For all data, yield or stock was given a value using the net market price. (ii) Fibre / Raw materials This service generally equates to timber, although reed production may also become a factor on the wetland site (Great Fen). Timber products may be recorded as both stock and yield, where data are available, and costs were subtracted to give a net value as above. Local sources such as farm business plans, forest design plans, and site management plans were used in consultation with local experts to assess production. (iii) Fuel / Energy The potential for development of fuels is acknowledged at the sites but there is currently not sufficient data for any quantitative evaluation. Values are available for quantity of hydroelectricity produced in two of the sites, Pumlumon and Ennerdale (although in Ennerdale it is negligible as it is only produced by 3 properties) so this does give an indication of the relative importance of this service; however, the potential impacts of land cover changes on production would be too complex to model. Local pricing Local pricing gave values for the business as usual scenarios and also projections for the landscape-scale scenarios. Annual yield or stock data was compiled from site-based sources. This was expressed as a net value per hectare in each land cover category where the benefit is produced by subtracting the variable production costs for each service. For some benefits, such as timber production, the yield will typically vary conspicuously due to extraction or production variation between years. In these cases estimates of an appropriate yield were based on a mean figure over a time period appropriate to that crop and site. Where possible, spatially variable costs were also be factored into the assessment to avoid overestimations of value. UK standard pricing For crops, livestock and dairy, the gross margin values (after variable costs) were used to convert the production to monetary value. These were obtained from Nix (2010) as these provide the most up to date and comprehensive values currently available. Welsh values were available for livestock from the Welsh Farm Income Booklet (IBER 2009) but the Nix (2010) were used for consistency between all case studies. For timber, the Forestry Commission1 provided cumulative yield per hectare (m3) values for generalised broadleaved and conifer production using their 'Forest Yield' software, which is based on 'Yield models for forest management' (Edwards & Christie 1981). Oak and birch were used to model the broadleaf yields and Sitka spruce for conifer. The cumulative yield approach is more realistic than using volume at clearfell, because it takes account of overall extraction throughout the rotation, including the value of timber removed through thinning. The average standing sale price for broadleaves and conifers, provided by the Forestry Commission2, was

1 Ewan Mackie, Centre for Forest Resources and Management, pers. comm., 27 May, 2010 2 Charene Winbow, Sustainable Forestry and Land Management Team, pers. comm., 24 May, 2010

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then used to calculate a monetary value per hectare. It can be interpreted as a net value; although the planting costs are not included, this is offset by the sale as a standing crop.

2.2 Fresh water provision

Fresh water provision can be assessed using observed market price, with exclusion of production related costs (such as costs of extraction) from the final estimate (Kettunen et al. 2009a). For upland sites feeding into reservoirs, there is a potential for landscape scale interventions to reduce the production costs through improvements in water quality resulting from blocking drains in peat bogs. Water companies are currently investing heavily in these interventions3 and evidence on the response of the moorlands to this management action is becoming available from intensive hydrometric monitoring, such as in the SCaMP project (Anderson 2010). Information from the individual monitoring projects is now being drawn together in the UK Peatland programme4, which will present its results in 2011. A review of the impact of peatland drain blocking in on water quality over a broad range of sites was able recommend drain blocking as a management strategy for reducing Dissolved Organic Carbon (DOC) and water discolouration in disturbed peat catchments. There was however, a caveat that ‘while in general there will be positive… outcomes, there will be a number of sites where no significant change will occur’ (Armstrong et al. 2010). Method Valuation using site-based data was explored through direct contact with water companies benefiting from supply from the case study areas. Data on annual volume of water extracted from the sites and the market price per unit were available. However, the valuation based on reduced production costs was not pursued for the case studies in this project because the water companies (United Utilities and West Wales Water) expressed the opinion that the quality of the water was already very high, and they were also unable to supply net costs, due to commercial sensitivity. Therefore, valuation is limited to a description of the volume extracted and market price as an indication of the magnitude of importance of the service.

2.3 Carbon storage

If primary data are not available, carbon values may be calculated from average values from ecosystems similar to those in the study area (Kettunen et al. 2009a) so values for habitat types in the south-west of England were used from (Cantarello et al. in press). For any land cover type, the carbon budget and the overall Global Warming Potential (GWP) will be affected by the management practices (e.g. intensity of tillage on arable land) (Dawson & Smith 2007). Two case studies in this project include extensive wetland areas (Pumlumon and the Great Fen), and in these cases the potential effects of changes in habitat condition are such that this assessment is included in the discussion. However, quantifying these differences would be complex and the data are not available. The market value of the carbon was calculated using UK Government official values (DECC 2009b). Valuation of carbon was previously based on estimates (drawn from the Stern Review on the Economics of Climate Change) of the damages associated with the impact on climate caused by emissions; the so-called Shadow Price of Carbon (DECC 2008). However, the Government's approach to carbon valuation has recently undergone a major review to produce new guidelines

3 E.g. South West Water, Mires on the Moors 4 http://www.iucn-uk- peatlandprogramme.org/commission/water

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(DECC 2009b). The new approach moves away from a valuation based on the damages associated with climate change and instead refers to the cost of mitigating emissions (DECC 2009a). The costs chosen can lead to very different estimations (Kettunen et al., 2009a) so the range of costs provided by DECC (2009b) were applied. Rewetting peat soils

The carbon balance of peatlands is a special case, because of their high importance for terrestrial carbon storage, and because management actions, such as drainage for agriculture, have resulted in net carbon loss in these areas (Worrall 2010). These considerations, along with water management, are one of the major drivers for restoration in wetlands, and hence, need to be included in any evaluation. Although the potential benefits of rewetting for reductions in global warming have been have been widely discussed in the literature (e.g. Dawson & Smith 2007; Ostle et al. 2009; Whiting & Chanton 2001) the carbon budgets are extremely complex: depending on soil chemistry, water content, temperature among other factors, as well as being time dependent (Gauci et al. 2004; Worrall et al. 2010 ).

A recent meta-analysis of the probability of carbon and greenhouse gas benefit from the management of peat soils found that the predicted benefits were equivocal because management often leads to increase in uptake in one pathway while increasing losses in another (Worrall et al. 2010). For drain blocking, the meta-analysis found that most studies showed a benefit for DOC but there was no field data on POC, dissolved CO2, or on total carbon budgets. One study, in press, proposed total C budgets, but had no pre-blocking data. The analysis of combined studies only suggested a 55% probability of carbon budget improvement and a 35% chance of greenhouse gas improvement. This was caused by the increase in methane flux that has notably been reported in all studies (Worrall et al. 2010 ). This is currently an area of intense research and new results from monitoring projects in upland areas with restoration by rewetting, such as SCaMP, will inform future analyses. The four year report from SCaMP shows a decrease in the levels of carbon in a dissolved form being flushed from the catchment. They illustrate this as a reduction in carbon loss which is the equivalent of 239 car kilometres per hectare of catchment per year. They also showed changes in aerial loss of carbon following re-wetting (Anderson 2010). However, the methane fluxes that are thought to contribute to a positive (i.e. harmful) impact on global warming are thought to decline over time, so that over a long time scale, such as 500 years, peatlands will act as carbon sinks and have a negative (beneficial) effect on global warming (Whiting and Chanton 2001, Gauci 2008). Method (i) Land cover change The land cover categories in each scenario were reclassified where necessary to align with land cover categories with available C values (Cantarello et al. in press). The carbon storage values were generated from these average values and the range of costs calculated. Details of the land cover reclassification may be found in Appendix 2. The DECC (2009b) values for the non-traded price of a tonne of carbon dioxide are: lower £26, central £52, upper £78. As the carbon density values from Cantarello et al. (in press) are in tonnes of carbon the DECC values were adjusted using the conventional conversion factor (3.67) to obtain values of: lower £95.42, central £190.84, upper £286.26. These values were applied to the maps to obtain a monetary value for each land cover type.

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(ii) Rewetting peat soils A detailed assessment of the carbon balance and offset potential has been produced for the Great Fen project and includes quantitative estimates based on field sampling. This study concludes that the project represented “an important opportunity to prevent the loss of carbon from long-term soil stores” (Gauci 2008). Similar work is not in existence for the Pumlumon project, and although the progress report from March 2007 suggests that large benefits could be accrued by both sequestration and the prevention of atmospheric release of carbon in re-wetted bogs, there is no supporting evidence at present. The literature review concluded that the information on effects of rewetting on peat was equivocal so the potential for rewetting to impact the carbon budgets of the two relevant case studies (Wild Ennerdale and Pumlumon) was considered through the associated land cover changes. For instance, rewetting in Pumlumon is projected to result in major land cover changes, from fen and marsh to bog, and the absence of rewetting in the Business as Usual scenario is associated with land cover change from bog to grassland.

2.4 Flood protection

Damage costs avoided is a potential method to value flood protection, as cost-based approaches have been successfully applied to estimate the value of ecosystems in regulating water runoff and controlling floods (Kettunen et al. 2009a) and the market price (costs of flood damage) is the currently recommended method for assessing physical damages from flooding events (Natural England 2009b). Differences in land cover will affect flood risk through effects on surface roughness or infiltration capacity, which will affect water retention rates, and hence the volume and timing of flow (Nelson et al. 2009). Ideally, water retention capacity of land cover types should be linked to the risk of flooding downstream by modelling the changes in run-off within each site; however, this is beyond the scope of this project. The relationship between land cover and flood protection is complex, depending on many factors such as slope, soils, geology and rainfall. This makes estimates of water retention capacity based on land cover complex (O’Connell et al. 2005; Orr et al. 2008) so valuation studies tend to either give an entirely qualitative description of the potential changes in flood risk (Natural England 2009a) or may adopt a scoring system based on land cover type, such as that used by Collingwood Environmental Planning (2008) in their Green Infrastructure study. The potential impact of upland peat restoration on flood control is cited as a rationale for restoration of such areas. Early monitoring results suggest that the hoped-for benefits in stabilising flow rates may be realised but they also indicate that it is too early for firm conclusions to be drawn (Anderson et al. 2009). Similar conclusions were drawn from the catchment-scale experimental study on drain blocking in upland bogs in Wales (Wilson et al., 2010). “Increases in water retention and water tables within the bog after restoration” were found but the study also “demonstrated the importance of small and large scale topography in determining the degree of these responses”. Other indicators of flood mitigation benefits were observed in the study: lower discharge rates in the drains and hill streams; greater water table stability, reduction in peak flows, and increases in water residency after rainfall. Although these results indicated positive effects of drain blocking on flood mitigation, there were strong catchment scale differences in response, and a very gradual recovery of water tables. The authors concluded that more research was required at the landscape scale and over longer time periods (Wilson et al., 2010).

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Methods Our method sought to develop a novel approach to estimate an index for overland flow based on the CEH Land Cover Map categories. A similar approach was used to estimate flood prevention and mitigation capacity using land cover characteristics such as the percent of land in agriculture (Chan et al. 2006). Our initial approach was to combine this index with estimates of the potential damage to give an indication of the potential savings. A second approach was taken focussing on a single upland case study, Wild Ennerdale. JULES (Blyth, 2010) land surface model runs were performed for a range of sites across the UK, and the outputs were analysed in the context of this project. JULES is the Joint UK Land Environment Simulator (www.jchmr.org/jules/). It calculates updates to soil water and heat and above- and below-ground carbon and nitrogen stores for given weather variables (air temperature and humidity, wind speed, radiation and precipitation) through a series of interconnected calculations which are linked to vegetation development and land use. JULES outputs relevant to this project include runoff and storm frequency. However owing to the number of land uses and soil types at the case study sites, the model output was not considered reliable. Ideally the JULES model should be run for all of the permutations of land use and soil type across each case study site. Detailed use and modifications to JULES relevant to ecosystem service provision and land management will be made in the new Defra project BD 5005 “The provision of ecosystem services in the environmental stewardship scheme”. In this project a low level approach was used to provide an assessment of the land use risk in relation to the land uses scenarios provided. In this assessment, three land use scenarios were used for the Ennerdale case study. The land use data was at 25m resolution and describes land cover using the Broad Habitats classification as used in Land Cover Map 2000. Land cover classes were each given a score based on our expert judgement (Table 1). Ideally more experts would be consulted to make the index more robust. This approach was used because of the lack of flow data for the case study sites. By overlaying the spatial datasets on each case study site, a cumulative index of potential for flood could be assigned to each grid cell. Each land cover layer (3 scenarios) which had been provided in raster format was converted to a point shapefile in ArcGIS (ESRI). These point layers were each spatially joined, to for a single point file describing all three scenarios. The point shapefile was then used to sample the altitude, slope and HOST class (Boorman, 1995) at each point. The resultant data was then exported to excel. The land class and HOST class were used to lookup the appropriate standard percentage runoff, and moisture retention index values. A simple model was then used to derive a risk index value for each point. The model was of the form:

The mean of the Land Use Risk values for each case study were then calculated, and these values were used as the basis for the indicator. The model makes the assumption that an increase in the moisture retention index value at a given point will decrease the risk of excess storm driven runoff.

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Table 1. Soil Moisture Retention Index Values based on expert judgement. High values represent high potential to maintain a low soil moisture deficit.

LCM habitats Water retention index

Acid grassland 8

Arable and horticulture 8

Bogs (deep peat) - degraded 10

Bogs (deep peat) - rewetted 11

Bracken 7

Broadleaved woodland 10

Built-up areas, gardens 6

Calcareous grassland 4

Coniferous woodland 9

Dwarf shrub heath 4

Fen, marsh and swamp - rewetted 10

Fen, marsh and swamp -degraded 10

Improved grassland 6

Inland rock 2

Montane habitats 3

Neutral grassland 6

Standing water/canals 10

For the remainder of the case studies, a qualitative assessment of relative risk was made based on the relevant literature.

2.5 Recreation/tourism

Market prices (such as entrance fees) provide easily observable and obtainable values based on real payments for tourism and recreation, but do not take account of the fact that many recreational activities may be free and free access does not mean zero value (Natural England 2009b). Therefore, the most appropriate method for valuing recreation/tourism is through on-site assessment of willingness to pay (WTP). Although there are some issues with the use of WTP values, such as whether respondents’ hypothetical answers correspond to their behaviour if they were faced with costs in real life, these can be largely minimised by good survey design (Pascual et al. 2010). Initial consultation indicated that WTP studies were not available for any of the case study sites so benefits transfer was used, based on studies that have implemented WTP for similar areas. This approach has been widely applied in recent studies: for instance Natural England (2009b) used benefits transfer of WTP for valuing recreation in upland areas, Tinch and Provins (2007a) also transferred WTP values and admission prices for their Wareham Managed Realignment case study and, O’Gorman and Bann (2008a) took a similar approach in their wider study of England’s terrestrial ecosystem services. In benefits transfer, the simplest option is to transfer an average WTP estimate, which implies that the preferences of the average individual are the same in the original and new study (EFTEC & Just Ecology 2005b). In reality, this is unlikely and so some form of adjustment may be necessary and this is the approach that we have adopted here to make the values more locally relevant.

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Method for collation of WTP values WTP studies were identified through a literature review; preferentially for UK studies - see Appendix 3 for search terms and Appendix 4 for studies collated. Studies were obtained by using Web of Science and the Environmental Valuation Reference Inventory database (EVRI; http:www.evri.ca) and selected on the basis of the following criteria:

(i) Use of the WTP (not WTA5) approach, with sound method (e.g. large sample size, covering range of socio-economic groups).

(ii) The WTP values should be for recreational activities in ‘natural areas’. Some activities may be excluded where adequate values are not available e.g. swimming, picnicking, camping and air sports.

(iii) Assessment of WTP for access/recreational use, rather than for a change in quality or marginal change as these would be too specific to the original study.

(iv) WTP values per trip. This value can be multiplied by the annual number of trips to the case study sites.

(v) Assessment of WTP values for users (e.g. carried out at the site or by known users), rather than general population/household surveys.

(vi) Assessment of WTP in addition to other costs of the trip (e.g. travel and equipment costs).

(vii) Ideally, studies using an appropriate payment vehicle for the case study areas, such as an entrance fee. Include values with zero bids.

Method for benefits transfer The WTP values were converted to current prices using the retail price index value6, (Officer 2009) and transferred to each case study. Where possible values from sites of comparable character were sought using the following criteria (EFTEC 2010):

(i) Similar activity provision in terms of quality, location, size, accessibility etc. (Pascual et al. 2010).

(ii) If possible, similar affected populations, especially in terms of income and available substitutes. This is because WTP may fall as the availability of substitutes increases (EFTEC 2010).

The number of appropriate WTP studies was limited. For some activities (horse riding, cycling and nature-watching, boating/water sports) it was possible to obtain suitable travel cost values instead. Travel cost involves measuring the costs that people have incurred travelling to and gaining access to a site, such as travel expenditures, entrance fees and the value of time (Ozdemiroglu et al. 2006), and could be considered as the amount that visitors are willing to pay to visit a site. There were some activities for which no appropriate values were available (swimming, picnicking, camping, air sports), so overall WTP values may be underestimated. For each scenario, the WTP values were adjusted for by weighting them using the significance values for each activity from the scoping form sent to case study representatives. Then combining the values for all activities provided a WTP value for all valued activities except hunting.

5 Willingness to Accept is less appropriate for this application because it is concerned with the value of foregoing gain or allowing loss (Defra, 2007). 6 Tool for conversion to current price http://www.measuringworth.com/ppoweruk/?redirurl=calculators/ppoweruk/

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Hunting was valued separately, because the average value obtained from the literature for hunting was £329.65 per trip, which was significantly greater than the values obtained for any of the other activities (£1.74 - £68.07) but there were relatively fewer trips so the overall WTP value (£329.65 x number of trips) will be more comparable to other activities with lower WTP values but a much greater number of trips. Separate valuation is therefore likely to be more informative in this case. Method for estimating overall recreational value

The overall recreational value for each scenario was then obtained by multiplying the number of visits by the WTP value, and summing for general recreation and hunting. The total number of visits under each scenario was obtained from case study literature or estimated by case study representatives. Aside from hunting, the number of visits was not broken down by activity type, as suitable data was not available.

2.6 Aesthetic benefits

Aesthetic value was assessed using scores based on GIS indicators of aesthetic attributes identified from the CPRE Tranquility Mapping study (Jackson et al. 2008b). This study was selected because it was based on a substantial survey of UK public (4000 people) and the indicators used were spatially linked to aesthetic features. Alternative aesthetic indicators were considered but lacked these advantages (Chhetri & Arrowsmith 2008; Dramstad et al. 2006; Ode et al. 2008; Tveit et al. 2006; Van Eetvelde & Antrop 2009). Many of the possible methods for identifying potential aesthetic attributes are subjective, not easily mapped with GIS, do not provide values for different levels of the attributes, and have not been thoroughly tested. Indeed, it has been shown that different groups of people show different preferences for landscape types (Dramstad et al. 2006; Kettunen et al. 2009a, b; Tveit 2009). The perception of aesthetic qualities is very subjective. It is therefore important to select indicators based on robust testing using a large sample size with wide coverage. The CPRE ‘naturalness’ indicator is based on land cover type and hence is likely to differ between scenarios. The method has an underlying assumption that perceived ‘naturalness’ is an aesthetic benefit and accepts that naturalness may be perceived rather than actual/ecological naturalness (Tveit et al. 2006).This is supported by previous research which has shown that ‘naturalness’ is a major factor in preference for landscape and that ‘naturalness’ is associated with vegetation and the type and amount of human-induced change (Jackson et al. 2008b; Purcell & Lamb 1998). To obtain a monetary value for aesthetic benefits stated preference methods would be required (Natural England 2009b). However, this is not within the scope of this project, and a benefits transfer of WTP values is not appropriate because landscapes are unique, so values from elsewhere are not transferrable. Method The CPRE ‘naturalness’ score, with a range of 0-10 where 10 is extremely natural, was used to reclassify land cover (Jackson et al. 2008b). First, the CPRE ‘naturalness’ values were aligned to LCM 2000 habitat types (Table 2).

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Table 2. Aesthetic/naturalness index for CEH LCM2000 habitat classifications developed by interpretation of the land classes used in the CPRE Tranquility Mapping study (Jackson et al. 2008b).

LCM broad habitats LCM subclass habitats Naturalness score

1. Broadleaved woodland 1.1. Broad-leaved/ mixed woodland 7.5 2. Coniferous woodland 2.1. Coniferous woodland 7

4.1. Arable cereals 5

4.2. Arable horticulture 5

4. Arable and horticulture

4.3. Non-rotational horticulture 5

5.1. Improved grassland 7 5. Improved grassland

5.2. Setaside grassland 7 6. Neutral grassland 6.1. Neutral grassland 7 7. Calcareous grassland 7.1. Calcareous grassland 7 8. Acid grassland 8.1. Acid grassland 7 9. Bracken 9.1. Bracken 9

10.1. Dense dwarf shrub heath 8 10. Dwarf shrub heath

10.2. Open dwarf shrub heath 8 11. Fen, marsh and swamp 11.1 Fen, marsh and swamp 9 12. Bog 12.1. Bogs (deep peat) 9 13. Standing water/canals 13.1. Water (inland) 9 15. Montane habitats 15.1. Montane habitats 8 16. Inland rock 16.1. Inland bare ground 5

17.1. Suburban/rural developed 3.3 17. Built-up areas, gardens

17.2. Continuous urban 1.6

21.1. Littoral sediment 9 21. Littoral sediment:

21.2. Saltmarsh 9 Habitat classifications for each of the case study sites were aligned to the LCM2000 habitat classifications using the ‘NBN dictionary of habitat correspondences’7. Expert judgement was used where equivalent classifications were not provided (e.g. for Heather and Hillforts and the Knepp Wildlands project). The overall score of naturalness for each scenario was calculated as sum(area* naturalness score1) / total area.

3. Valuation approach for biodiversity conservation For consistency and comparability, suitable methods for valuing biodiversity benefits were sought in ‘Biodiversity Indicators in your Pocket’ (Defra 2009). The most suitable indicators were the area of ‘priority habitats’ and ‘habitat connectivity’. Although the area of priority habitats is a good indicator of conservation achievement there are also more sophisticated tools to assess the ecological impact by scoring based on conservation priorities and habitat significance (Rouquette et al. 2009). This Ecological Impact Assessment

7 Available from http://www.jncc.gov.uk/page-4266 (Accessed 1 April, 2010).

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(EcIA) adds further scope for differentiating between scenarios, and so was included in this report.

3.1 Area of priority habitat

As the landscape-scale scenarios are created on the assumption of achievement of conservation objectives it is inevitable that areas of the priority habitats will increase. The most interesting feature may therefore be the relative increase of the different habitats as well as the increase in relation to national targets.

3.2 Ecological Impact Assessment

Our method followed Rouquette et al. (2009) using two criteria to score blocks of habitat and combining these scores for the site. The two criteria are determined by (i) assigning each land cover type to a category of conservation priority and (ii) calculating the proportion of the national and regional resource that the habitat represents (Table 3). Table 3. Decision rules for assigning a score to habitat types adapted from J. Rouquette pers comm.. AES is agri-environment scheme.

Score Importance Significance of habitat

Conservation priority (minimum)

6 International >5% national resource Habitats Directive

5 National >1% national resource Habitats Directive or UK BAP

4 Regional >5% regional resource UK or Regional BAP

3 County >1% regional resource LBAP priority

2 District <1% regional resource and >10 Ha in size

LBAP priority or AES target

1 Parish <1% regional resource and <10 Ha in size

AES target

(i) Conservation priority To establish the occurrence of habitats of conservation priority in the case study areas it was necessary to align the habitat records for each site with BAP and EU habitat types using the ‘NBN dictionary of habitat correspondences’8. Where information on correspondences was not available, expert judgement was sought. To resolve uncertainties on Habitats Directive habitats9 distribution maps were used to indicate the likelihood of the habitat occurring in the project area. If at least part of a habitat was listed under the Habitats Directive it was assigned EU level of significance. For BAP habitats which did not correspond easily with case study habitats, reference was made to supplementary BAP information and maps10 from Natural England11 and the Countryside Council for Wales12.

8 Available from http://www.jncc.gov.uk/page-4266 (Accessed 1 April, 2010). 9 http://www.jncc.gov.uk/Publications/JNCC312/UK_habitat_list.asp 10 Downloaded from http://www.gis.naturalengland.org.uk/pubs/gis/GIS_register.asp 11

http://www.ukbap.org.uk/newprioritylist.aspx 12

J. Rothwell, Species Technical & Support Officer, CCW, pers. comm.

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‘New’ BAP habitats from Natural England’s new priority list were excluded from the assessment because no national or regional resource data were available. However, it should be noted that some of these habitat types may be relevant at the case study sites. For example, ‘upland flushes fens and swamps’ in Pumlumon, and ‘inland rock outcrop and scree habitats’ in Ennerdale. It was expedient to use the ‘old’ names and scope for BAP habitats which had been renamed/expanded as data on these were more readily available. For example, ‘Fens’ was used rather than ‘Lowland fens’ (new name). The only agri-environment target habitat included in this study was ‘neutral grassland’ because this was an important habitat in one case study that would otherwise have been excluded because it is not BAP habitat. Scrub would also be excluded for the same reason yet is an important habitat and a successional stage in the development of broadleaved woodland. To include this habitat, a modification to the method was made to calculate areas of broadleaved woodland both with and without scrub. (ii) Significance of the habitat Firstly, the combined extent of each priority habitat to be created/restored/maintained under each scenario was calculated (successful establishment was assumed). The distinction between ‘upland’ and ‘lowland’ BAP habitats, for example heathland in Pumlumon and Ennerdale, was determined by calculating the area above or below 300m using a DTM (Maddock 2008). Then the national and regional resource for each habitat, in terms of total area, was determined. The proportion of the resource found in each scenario was then calculated as an indication of its ‘significance’ at a regional or national level. The national resource was represented by the total areas for the BAP habitats, which were obtained from online habitat action plans for each habitat type13. The years in which these figures were assessed ranged from pre-1995 to 2008, although the majority were from 2008. The sources also varied from full surveys, samples or partial surveys to ‘best guesses’.

The regional resource values for the England case studies were obtained from the appropriate regional organization for each case study (Table 4).

Table 4. Source of values for regional resource for English case studies.

Case study

Region Organisation Source of regional resource information

Ennerdale North West

North West Biodiversity

NW Habitat Targets April 08 with county spreadsheet (maintaining extent column), downloaded from www.biodiversitynw.org.uk

Frome catchment

South West

SW Regional Biodiversity Partnership

Bristol Regional Environmental Records Centre (2006). Analysis of UK BAP Priority habitats within agri-environment schemes and SSSIs in South West England. Report for the South West Regional Biodiversity Partnership

Great Fen East East of England Biodiversity

Land Use Consultants (2009). Review of the extent and condition of Biodiversity Action Plan habitats in the East of England

13

Obtained from http://www.ukbap-reporting.org.uk/plans/national.asp?S=&L=1&O=&SAP=&HAP=&submitted=1&flipLang=&txtLogout= (Accessed 22 June, 2010).

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Case study

Region Organisation Source of regional resource information

Forum Supplemented data from Natural England

Knepp South East

SE England Biodiversity Forum

South East England Biodiversity Forum pages on each BAP habitat: strategy.sebiodiversity.org.uk/pages/habitats-.html

It was not possible to obtain the regional resource for separate BAP woodland types, so the overall value for all BAP woodland was used. It was also not possible to obtain the regional resource for eutrophic standing waters for Knepp or Great Fen, so as the areas of this BAP habitat type remained the same under each of the scenarios, this habitat type was excluded from the EcIA score calculation.

The regional resource of some habitats may be over-estimated due to the difficulties in defining boundaries. In these cases regional mapping had tended to map general areas containing some of the resource (Alexander 2004). This uncertainty results in slightly odd results - the reedbed resource for the east of England appears higher than the value obtained for the UK. So in the Great Fen, a score of 3 (<1% of regional resource) was assigned, but it may be that given more accurate regional resource data, the score should have been higher. The regional resource for lowland raised bog was given as zero in the Natural England GIS data, however, remnants of this habitat are currently found in the East of England (Maddock 2008), so the score for this habitat was adjusted from 5 to 2 on the assumption that this was a better reflection of the significance of the 10ha of this habitat. The national resource of neutral grassland was obtained from Carey et al. (2008). These values include neutral grasslands that are also classified as BAP lowland meadows as well as non-BAP neutral grassland. Therefore, the values for the percentages of the national and regional resource will be higher than the true value, meaning that scores applied to the non-BAP habitat neutral grassland in the EcIA may be lower than expected. Assigning a score Decision rules were used to assign each priority habitat in the case study sites a score from 1 to 6. The habitat in question needed to fulfil the requirement of both criteria (priority and significance) to receive that score. Rather than calculating a total score for each scenario as the mean average score for all habitats across the site following Rouquette (2009), the sum score was assessed to give a more appropriate indicator for this study that reflected the overall contribution of the site and all the BAP habitats therein.

3.3 Connectivity

The functional connectivity of priority habitats was approached by focussing on one of the case studies, Frome catchment, and employing method similar to the least-cost distance method developed by Watts et al. (2008b) to estimate the potential ease with which species could move between habitat patches (Defra 2009). Lack of empirical data on the ‘costs’ of moving through the landscape means that generic focal species had to be adopted, as in Watts et al (2008). The analysis was only really meaningful on the larger case studies: Frome catchment and Pumlumon and the latter could not be included because the use of habitat networks estimation in development of the landscape-scale scenario would introduce an unacceptable level of circularity to the analysis.

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Potential habitat networks for woodland, heathland and grassland species were identified by using a least-cost approach with a buffer equal to the maximum dispersal distance of the woodland species. The habitat network analysis was performed by using the ‘cost distance’ spatial analyst tool of ArcGIS 9.2 (Catchpole 2006). The ‘cost distance’ tool identifies the least accumulative cost distance over a cost surface which defines the cost to move through the surrounding land cover. The four land cover maps representing land cover types under the current situation, the 30% scenario, the 60% scenario and the 30-60% scenario were rasterized at 10 m resolution as described in ‘Building the Scenarios’. The movement cost of each land cover type was calculated by dividing the maximum dispersal distance by the ecological cost. Ecological costs were based on Annex 6 of Catchpole’s report (Catchpole 2006). Three maximum dispersal distances were considered: 500 m, 1000 m and 2000 m (Table 5). For each scenario, and each dispersal distance, the areas where the accumulative cost distances were smaller than the maximum dispersal distance were merged and defined as potential habitat networks. All potential habitats networks that were created therefore contained one or more habitat fragments that were present under the scenario considered within the Frome catchment area.

Table 5: Ecological costs adopted from Catchpole 2006, Annex 6.

Land cover types Woodland species

Heathland species

Grassland species

Acid grassland 20 10 1 Arable cereals 35 50 50 Arable horticulture 35 50 50 Arable non-rotational 35 50 50 Broad-leaved / mixed woodland 1 40 12.5 Calcareous grassland 25 50 1 Coniferous woodland 5 10 10 Continuous urban 50 50 50 Dense dwarf shrub heath 23 1 20 Fen, marsh, swamp 20 50 7.5 Improved grassland 35 50 30 Inland bare ground 30 50 40 Littoral sediment 50 50 30 Neutral grassland 20 50 2 Open dwarf shrub heath 23 1 20 Saltmarsh 45 50 30 Set-aside grassland 25 50 5 Suburban / rural developed 20 30 47.5 Water (inland) 40 50

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4. Assessment of costs Costs include project implementation, running and opportunity costs. The estimation of costs needed to be addressed with a variety of approaches because some were closely associated with services and others applied across the case study sites.

4.1 Production costs

Ecosystem services that were valued using market price (e.g. food, fibre/raw materials) were adjusted for production costs by subtraction of these costs. However, this was not appropriate for the benefits which are not valued by market price. For example, the running costs for delivery of aesthetic appeal may be covered in maintaining habitat condition. However, this maintenance will be a general cost of the project and will be attributable to many of the other ecosystem services as well (such as carbon storage/sequestration), so it would be difficult to determine what proportion of those costs were attributable to each of the ecosystem services. Therefore, all other costs were assessed separately.

4.2 Implementation and running costs

These costs were estimated for the conservation work being carried out or envisaged in each scenario based on consultation with case study partners and reference to known costs for habitat management. Costs for managing the sites for purposes other than conservation were not considered. This might have been feasible for running the Knepp estate as a commercial farm. For the other sites, which had more complex ownership, any attempt to estimate these other costs would be too complex, and in the future scenarios, too speculative, to be of any use to the evaluation. Useful guides exist in the literature to enable estimation of implementation and running costs. For instance, the Environment Group (2004) outline the different types of site management costs considered in their economic assessment of the costs and benefits of Natura 2000 sites in Scotland. These implementation and running costs include:

• The designation process: administration of selection process; survey, mapping and condition assessment; consultation and preparation of information and publicity material; land purchase (Naidoo & Ricketts 2006);

• Occasional and annual management planning and administration (preparation and review of management plans, strategies and schemes; establishment and running costs of management bodies; provision of staff (wardens, project officers etc.), buildings and equipment; public consultations and liaisons with landowners; rent and administration);

• Ongoing management actions and incentives: conservation management measures such as maintenance of habitat/species status; research, monitoring and survey; visitor management; provision of information, interpretation and publicity material; training and education;

Many of these are relevant to the case studies in this project but are necessarily site-specific. Therefore, details on implementation and running costs for the scenarios were obtained from each of the case studies using consultation and reference to available documents, such as business plans.

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4.3 Opportunity costs

The costs of forgone opportunities (Naidoo et al. 2006; Naidoo & Ricketts 2006) can lead to loss of economic output (e.g. agricultural, industrial, fishery, property and tourism yields) and social impacts such as loss of income and employment opportunities (Environment Group 2004). For example, creation of a new forest implies the loss of land, typically for agricultural purposes. The opportunity cost of this action is then, the value (net of subsidies) of agricultural production foregone from land taken for the forest (EFTEC 2006a). Estimation of opportunity costs is complex as these vary depending on the characteristics of the site in question and issues such as the likelihood of an alternative activity being undertaken and the availability of alternative sites to undertake such activities need to be factored in. Furthermore, agricultural output is often subsidized, so price support, subsidies and tariffs need to be excluded from opportunity costs, resulting in potential social costs being a fraction of the financial costs (Environment Group 2004). For our case studies, the opportunity costs from implementation of the different scenarios can be determined by comparing the value for each of the ecosystem benefits. For example, if there is a reduction in food production under the landscape vision scenario compared to the business-as-usual scenario, this would be an opportunity cost. In other words some of the opportunity costs are integral to the valuation. Consultation with case study representatives determine whether likely alternative land uses (e.g. residential, commercial) would be prevented under each scenario and could indicate an additional opportunity cost. Case study representatives were also consulted about potential competing interests and missed or gained opportunities that may occur under the scenarios (e.g. grant aid or alternative recreational opportunities, such as more consumptive ones).

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5. The Case Studies

5.1 Wild Ennerdale

5.1.1 Creating scenario maps

Three scenarios were created for this case study in close collaboration with a Wild Ennerdale project representative, G. Browning (henceforth GB) who provided tree species maps, forest design plans, expertise in the Wild Ennerdale vision, and interpretation of possible trajectories for the site in a business as usual scenario. Existing spatial data, such as vegetation maps, were combined and modified to provide the necessary detail. Pre-project scenario Under this scenario, land cover is based on a baseline NVC survey recorded in 2002-2004 at the outset of the Wild Ennerdale project (Jerram 2003a, b, 2004). The NVC map was modified, using raster calculator, with Forestry Commission ‘current tree species’ GIS data which provided a greater level of detail on forestry species, to aid in timber valuation. Landscape-scale scenario This scenario entailed predicting how the land cover might change as the Wild Ennerdale landscape-scale project develops to 2060. The landscape-scale project involves a shift away from economic productivity as the primary output, with a move towards lower input, more sensitive management, allowing natural processes a greater hand in determining how the valley will evolve in the future (United Utilities et al. 2006). Notably, there were no existing maps of this vision, as the philosophy of the project is not driven by specific targets and so does not attempt to model or map the envisaged landscape. It was therefore necessary to work with GB to create a possible future map from expert opinion. The Wild Ennerdale landscape-scale scenario was developed using the 2002-4 NVC map as a base and modified using the Wild Ennerdale Stewardship Plan, which replaces the Forestry Commission Forest Design Plans for Ennerdale as the primary management document (United Utilities et al. 2006). Additional information and close collaboration with GB result in the following steps: 1. Firstly, woodland areas that would be felled prior to 2060 were identified using the ‘Future Woodland’ element of the Wild Ennerdale Stewardship Plan. 2. The replacement habitat in the felled areas was reclassed using a ‘Future Species’ map developed as part of the Forestry Commission’s production forecast modelling and gave details of tree species and some other habitat . This was not part of the Wild Ennerdale Stewardship Plan as the latter does not aim to predict future species distribution. This provided 2060 habitat for the part of the site managed by the Forestry Commission. 3. Areas felled in step 1 that were managed by the other Wild Ennerdale partners and so outside of the Future Species map were assigned habitat at 2060 using expert opinion (GB). 4. A small number of patches classed as ‘recent felled’ in the NVC classification could not be reclassified using the Future Species map. Expert opinion (GB) was sought on what habitats might develop in these in a Wild Ennerdale 2060 scenario.

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Business-as-usual scenario Under a business-as-usual scenario, forestry operations were assumed to continue with economic productivity as the primary output. This scenario is based on the baseline NVC maps and modified using Forestry Commissions Forest Design Plans (FDP) from 1999 with the assumption that these plans would have been implemented if the Wild Ennerdale project had not been realised. 1. As in the pre-project scenario, the baseline NVC map was updated with a Forestry Commission ‘current tree species’ GIS map which provided a greater level of detail on forestry species, to aid in timber valuation. 2. This new map was then modified with the FDP to simulate felling and subsequent restocking. These plans were provided in GIS format by GB for the three Forestry Commission sites present in the Wild Ennerdale project area (Heckbarley and Crag, Ennerdale and Broadmoor) and were combined. The vegetation map from step 1 was combined in the GIS with the areas from the FDPs which were to be felled in 2060 and the restocking data. 3. Areas of ‘open’ habitat in the FDP were assumed to have the NVC habitat from step 1. This made the assumption that if those areas were not restocked, they would revert to the previous vegetation type. 4. Areas that were felled but not assigned to be restocked or to be open habitat and those classed as ‘recent felled’ were allocated future habitat using expert opinion (GB). Characteristics of the scenarios at Ennerdale The main difference between the Wild Ennerdale scenario compared to the pre-project and business-as-usual scenarios is a significant decrease in conifer woodland, which is replaced by broadleaved woodland. The increase in inland rock also reflects the exposure of this habitat as overlying conifer woods are removed. There is also an increase in heath and, to a lesser extent, fen, marsh and swamp. There is a slight increase in broadleaved woodland in the business-as-usual scenario compared to the pre-project scenario and this mainly replaces heath (Table 6, Figure 1).

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Table 6. Area of habitat types in Ennerdale under alternative scenarios and change in area between the scenarios. PP is Pre-Project, BAU is Business-as-Usual, LS is Landscape-Scale scenario and shaded cells accentuate increases in habitat area.

Area (ha) in case study site Difference in area (ha)

Habitat type PP BAU LS LS - PP LS - BAU

BAU - PP

Acid grassland 1172 1167 1057 -115 -110 -5

Bog 41 39 39 -2 0 -2

Bracken 256 229 223 -33 -6 -27

Broadleaved woodland 174 271 511 337 240 97

Coniferous woodland 1016 1008 55 -961 -953 -8

Dwarf shrub heath 992 941 1116 124 175 -51 Dwarf shrub heath with native trees 0 4 24 24 20 4

Fen, marsh, swamp 44 34 63 19 29 -10

Inland rock 171 172 193 22 21 1

Mixed woodland 0 8 588 588 580 8

Montane habitats 2 2 2 0 0 0

Neutral grassland 196 190 191 -5 1 -6

Standing water/canals 302 301 302 0 1 -1

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Figure 1 Differences in land cover for each scenario in Wild Ennerdale

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5.1.2 Evaluating costs and benefits for Wild Ennerdale

Information, interpretation and future projection on ecosystem services in the area was provided by several case study partners and supplemented with more generalised data where necessary. Personal communications are listed in the text: Gareth Browning (GB), Rachel Oakley (RO), and Simon Webb (SW). The valuation of timber entailed particular detail and considerable input from GB. 5.1.2.1 Ecosystem Services

Food – Lamb Estimates for stocking rates and the areas grazed in each scenario were provided by the partners. The overall vision was to reduce sheep stocking rates and move to grazing predominantly by cattle (RO). A map of areas for grazing under each scenario, provided by GB, showed that this would remain the same in the business-as-usual future as it was in the pre-project scenario, but under the Wild Ennerdale scenario it would be reduced. Estimates of total number of sheep and the proportion sold for meat under each scenario were provided by SW. Sheep numbers were the highest under the pre-project scenario and lowest under the Wild Ennerdale scenario. In the business-as-usual future, Natural England agreements were still expected to reduce stocking rates, but to a lesser degree than under the Wild Ennerdale project (SW). Local monetary values for lamb were not available, so standard values were used (Nix 2009). The value was taken as the gross margin per ewe for upland flocks, after forage costs and with the value of wool subtracted because it is currently unviable commercially. A total monetary value for lamb production was obtained by multiplying the total number of sheep sold for meat by the standard net price per animal. This total value for the study area was then divided by the total number of hectares in which sheep may occur under each scenario, to obtain a value per hectare. Food - Beef Beef was excluded from the valuation because they were only included in the Landscape-Scale scenario, and in this, the number of cattle sold for meat is likely to be negligible. The animals will be primarily present for conservation benefit and future numbers will depend on what subsidies are available (RO). Food - Venison A GIS layers of the areas used by deer under each scenario showed that their range would be the same in the business-as-usual and pre-project scenarios but differ in the Landscape-Scale future. The area used by deer is expected to expand under the Wild Ennerdale scenario as deer may be more likely to use the open fell due to increased cattle in the valley and reduced sheep on the fells (GB). Although a valuation was possible for the current resource of venison, no difference was postulated between scenarios by the partners due to uncertainty about how deer populations would respond to the landscape changes. The valuation was therefore the same for all scenarios, and was based on current data for the small number of deer culled annually and market price, which equates to the net price as production costs were negligible (GB). Other food In addition to the food described above, the use of wild foods was also mentioned, but thought to be a minor and non-commercial component. Fish was also disregarded as production was

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thought to be negligible under all scenarios. Fibre - Timber The valuation of timber was carried out in close collaboration with GB, based on expert knowledge and acknowledging that many assumptions and generalisations were necessary for this simplified model. Although there was no separate fuel valuation, it should be noted that the value of woodfuel is the same as woodchip, which is included in the timber valuation (GB). The net timber value in Ennerdale is dependent on where the timber is extracted as extraction costs increase with slope. A simple cut-off of 25% slope was used (GB) by using DTM data (Edina Digimap14) to estimate slope. For the pre-project and business-as-usual scenarios, it was assumed that only conifers would be felled. Net per hectare values were provided for thinning and clear-felling of different conifers: either ‘Hybrid, European and Japanese Larch’ or ‘Sitka spruce and other conifers’ (GB). A cycle of 60 years was assumed for all species, with the first thinning at age 20, followed by thinning every 5 years until clear felling in year 60 on slopes up to 25%. Different net values for thinning were provided, depending on the age at which the crop was thinned. For slopes exceeding 25%, it was assumed that no thinning would take place due to the high costs, and only the clear felling at age 60 would occur. The costs of restocking with conifers after clear felling (GB) were subtracted from the total per hectare value. Under the Wild Ennerdale landscape scenario there is a substantial decrease in timber harvesting and there is no longer any productive timber harvesting in the ‘Eastern Valley and High Mountain Green Zone’ or on slopes exceeding 25% incline (GB). The total area of woodland from which timber is harvested is therefore substantially smaller and is composed mostly of broadleaved and mixed woodland, rather than coniferous, which has a higher net value. The planned thinning of lower slopes could carry on indefinitely, but for consistency with the other scenarios, a time span of 60 years was used. For the conifers, thinning was assumed to commence at 20 years, followed by thinning every 4 years until age 40, then thinning every 8 years until age 60. For the ‘native broadleaves’, thinning was assumed to commence at 15 years, and then follow the same pattern of thinning as the conifers. Replanting costs should be avoided in this scenario, as woodland is expected to regenerate (GB). Net values per hectare were provided for different timber species: ‘hybrid, European and Japanese larch’, ‘sitka spruce and other conifers’ and ‘native broadleaves’; and an average of the overall net value for mixed conifer and broadleaved woodland (GB). Then annual values were calculated by dividing the total values per hectare for the 60 year cycles by 60.This produced the valuation based on local information. To calculate ‘standard values’ standing sale price was applied, which can be considered a net price. The total area of timber in each scenario was multiplied by a standard value per hectare. This constituted conifers under the business-as-usual and pre-project scenarios, and the total area of conifer and broadleaf for Wild Ennerdale. The standard value was calculated by multiplying average cumulative production values for conifers and broadleaves15 by the average standing sale prices16. For mixed conifers and broadleaves, an average of the two was used.

14 http://digimap.edina.ac.uk/main/download.jsp (Accessed 4 June, 2010). 15

Provided by E. Mackie, Forestry Commission 16

Provided by C. Winbow, Forestry Commission

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Differences in timber value between the scenarios could be explained by (i) differences in area of crop (ii) change from conifer to broadleaf harvest and (iii) effects of slope on the costs of extraction. Under the pre-project and business-as-usual scenarios, it is assumed that only conifer is harvested, but under both of these scenarios, the area of such woodland is much greater than the landscape scenario, and coniferous timber has a higher value than broadleaved timber. The relatively low value of timber in the Wild Ennerdale scenario is accentuated when local values are used as only these take into account the differing value of timber extracted from slopes of different steepness. This emphasises the utility of incorporating local knowledge. Hydroelectricity Hydroelectricity production in the Wild Ennerdale project area is for local use only. There is currently one property generating hydroelectricity, with the possible addition of two further properties which currently have plans for hydroelectric power generation. However, this would occur under either scenario. Therefore, as hydroelectricity production was minimal, it was not valued. Fresh water Fresh water is extracted from Ennerdale Lake in the project area, and this will remain the same under each of the scenarios. Average annual extraction values were provided by B. Swinburn (United Utilities). Although net unit values were not available, this was not important as the water extracted from the lake is of extremely high quality so production costs are not expected to change under either scenario (RO).

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Carbon There is an increase in carbon value under the Wild Ennerdale landscape scenario compared to the pre-project and business-as-usual scenarios, mainly due to the significant decrease in coniferous woodland, which is replaced by an increase in broadleaved woodland, which has a higher carbon storage value. There is also a slight increase in carbon value from the pre-project to the business-as-usual scenario, which is also largely due to an increase in broadleaved woodland, although this is mainly replacing heath, which has a lower carbon storage value than both conifer and broadleaved woodland. There is a difference of over £11 million between the upper and lower values for carbon when calculating the difference between the landscape and pre-project scenarios, demonstrating the sensitivity of the method to the monetary values. Flood mitigation The main land cover changes in Ennerdale in the landscape scenario compared to the pre-project scenario are an increase in broadleaved and mixed woodland in place of coniferous woodland. There is also an increase in broadleaved woodland under the business-as-usual scenario compared to the pre-project scenario, although this is not as great as the change under the landscape scenario, accompanied by a decrease in dwarf shrub heath. The overall area of woodland (broadleaved, mixed and coniferous combined) is largely unchanged between the 3 scenarios, with a 36 ha loss of woodland in the landscape scenario compared to the pre-project scenario (although there is a loss of 133 ha compared to the business-as-usual scenario). Over an annual cycle evergreen coniferous species such as pine exhibit higher interception losses than deciduous species, such as oak, which drop their leaves in winter (Calder et al. 2002). However, broadleaved or coniferous woodland will generally reduce run-off rates compared to heathland or grassland, due to increased evaporation losses and the increased water storage capacity of soils under trees (Calder et al. 2002; Gilman 2002; Robinson & Dupeyrat 2005). The management of the woodland will change under the landscape scenario, with a move from clear-felling and other heavy forestry operations involved in timber production, to more continuous cover and much smaller scale thinning. Overall, it is unlikely that the changes to woodland type and management will have a significant effect on flood mitigation. Other factors may also contribute to a slight decrease in run-off. For example, there is an increase in dwarf shrub heath, with some loss of acid grassland, under the landscape scenario compared to the pre-project scenario. Surface run-off in heathland is likely to be less rapid than in grassland because heathland vegetation is likely to be taller and tall vegetation generally intercepts more rainfall, reducing rapid surface runoff (Gilman 2002; Orr & Carling 2006). Another factor in Ennerdale which may influence flooding to some extent, is the decrease in sheep stocking density under the landscape scenario (and to a lesser extent the business-as-usual scenario) compared to the pre-project scenario. High stocking rates have been shown to decrease surface infiltration and lead to increased surface runoff from grazed land at the field and hill slope scale (Carroll et al. 2004b; O'Connell et al. 2004; Wheater et al. 2008). Other factors that may have a positive effect of flood mitigation are the enhancements of the natural dynamics of the river system within the project area, such as the removal of artificial features (GB). Ennerdale is an upland area, and although flood risk is not an issue within the project area as there are no settlements, upland areas are source areas for runoff generation (Wheater et al. 2008) and impacts on surface run-off could have an impact on downstream flood risk outside of the project area. This risk is likely to be mitigated by Ennerdale Water, which is a large lake and

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will have a significant influence on hydrological activity within the site, as it acts as a buffer (GB). So overall, it is unlikely that any changes will have much influence beyond the local scale. In contrast to the qualitative assessment, the modelling approach described in section 3.2.4 yielded results which indicate that there is an increased flood risk resulting from the LS scenario compared to the PP scenario and the business as usual scenario. The magnitude of this risk cannot be estimated, as these are effectively arbitrary values or scores, however percentage increases relative to the Business as usual scenario are presented in Table 7.

Table 7. Scores based on the assessment of the model results for the Ennerdale Case Study.

Scenario BAU PP LS Score 204.3073 204.6355 208.8644 % 100 104.64 109.02

The modelled data presented here was then mapped to give a spatial assessment of the areas exposed to high runoff. These areas are indicated in red on the map, and are the areas with high altitude, high slope, high Standard Percentage Runoff values, and low moisture retention (Figure 2). This result is in contrast to the qualitative assessment of flood risk mitigation, which might reflect the increase in some minor land areas such as bare rock under the wildling scenario. It is also possible that it could reflect the inability of the early version of the model to incorporate landscape and management details that could have a significant impact on soil moisture retention capacity. For Ennerdale, these might include differences in soil compaction due to changes in grazing intensity. However, the contrast between the approaches more generally reflects inherent uncertainty in making predictions about flood risk without well-parameterised models. Qualitative assessments may over-emphasise the impacts of certain land use changes because they ignore the complexities such as the possibility that local scale changes in runoff may not have any effect downstream because complex processes elsewhere in the catchment swamp or cancel out these effects. There is a therefore a need to develop accurate models which can allow scaling up of processes from local to catchment scales.

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Figure 2. Ennerdale model results showing predicted run-off for the 3 scenarios (BAU : top, PP : middle, and LS : bottom)

Recreation Recreation value (Table 8) was estimated by combining WTP values, adjusted by local ‘significance’ value, from the scoping survey, and the number of visits to the site. An estimate of the pre-project/business-as-usual annual visits to the project area was made by RO and GB. This estimate was based on vehicle counter numbers from 2006/7 which estimated the number of visits at 64,000. However, R.O and GB suggested that these numbers may already have been influenced by the Wild Ennerdale project, as changes were already underway at that time. However, there are no earlier figures available, so the assumption was made that the vehicle counter numbers were likely to be a 10-15% increase on pre-Wild Ennerdale numbers. This gave a pre-project / business-as-usual estimate of visits of 54,000, assuming that everything stays the same under a business-as-usual scenario in terms of trends in visitors to the Lake District and tourism in general. The recorded value of 64,000 visits per year was then adopted for the Wild Ennerdale scenario.

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Annual hunting visits were thought to be unlikely to change significantly in the future (GB) so the same figure was used for all scenarios. Table 8. Calculation of WTP values for Ennerdale. Significance values provided by RO and adjusted significance values for hunting provided by GB. Recreational activity

Literature WTP (£) -converted to current values

WTP value reference

PP / BaU scenario significance value

Adjusted WTP value BaU (£)

LS scenario significance value

Adjusted WTP value LS (£)

Walking 1.74 Bennett et al. (2003)

5 1.74 5 1.74

Horse riding 15.89 Christie et al. (2006)

2 6.36 2 6.36

Cycling 16.75 Christie et al. (2006)

3 10.05 3 10.05

Climbing 30.55 Hanley et al. (2002)

3 18.33 3 18.33

Nature-watching

8.84 Christie et al. (2006)

4 7.07 5 8.84

Boating, water sports

68.07 Hynes and Hanley (2006)

2 27.23 2 27.23

Fishing 8.80 Peirson et al. (2001)

3 5.28 3 5.28

Swimming Not available 1 1

Picnicking Not available 5 5

Pleasure driving

0.97 Hanley (1989)

2 0.39 2 0.39

Air sports Not available 1 1

Camping Not available 2 2

Average overall WTP value (£):

Pre-project/ business-as-usual scenario:

9.56 Landscape scenario:

9.78

Hunting 329.65 Bullock et al. (1998)

1 329.65 1 329.65

The recreational value increases by 21% under the Wild Ennerdale landscape scenario compared to the pre-project and business-as-usual scenarios due to an expected increase in visitor numbers under the Wild Ennerdale scenario and a slightly higher willingness-to-pay value for this scenario, due to an increase in importance of nature-watching. Aesthetic The highest aesthetic score is obtained for the Wild Ennerdale landscape scenario. This is largely due to the replacement of conifer with broadleaved woodland, which has a slightly higher aesthetic score. There is a slight decrease in aesthetic score from the pre-project to the business-as-usual scenario, which is mainly due to a decrease in heath and fen, marsh and swamp, which both have high aesthetic scores, offsetting the increase in broadleaved woodland.

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Summary: contrasting the ecosystem services for the three scenarios The overall effect of the landscape-scale, Wild Ennerdale scenario is to decrease the delivery of food and fibre, while increasing the potential for carbon storage recreational opportunities and aesthetic appeal (Tables 9 and 10). The carbon values varied considerably, depending on the method employed but this did not affect the comparison between scenarios. The use of local values in timber was more important as these accentuated differences due to the complexities of differing extraction costs as slope varied through the site. The two analyses of flood mitigation using a qualitative assessment and a prototype model gave conflicting results reflecting the complexity of the landscape factors affecting this ecosystem service.

Table 9. Difference in overall value of ecosystem services in the Ennerdale project area. LS is the Wild Ennerdale landscape-scale scenario; BAU is the business-as-usual scenario.

Difference in overall value for project area – local values

LS minus BAU LS minus Pre-project BAU minus Pre-project Ecosystem service

Monetary (£)

% difference

Monetary (£)

% difference

Monetary

(£) % difference

Venison 0 0.0 0 0.0 0 0.0

Timber -13,588 -30.7 -19,562 -38.9 -5,974 -11.9

Fresh water 0 0.0 0 0.0 0 0.0

Table 10. Difference in overall value of ecosystem services in the Ennerdale project area. LS is the Wild Ennerdale landscape-scale scenario; BAU is the business-as-usual scenario.

Difference in overall value for project area – standard values

LS minus BAU LS minus Pre-project BAU minus Pre-project Ecosystem service

Monetary17 (£)

% difference

Monetary1 (£)

% difference

Monetary1

(£) % difference

Lamb -4,758 -42.0 -9,856 -60.0 -5,098 -31.0

Venison Standard values not available

Timber -80,886 -73.7 -81,757 -73.9 -871 -0.8

Fresh water Standard values not available Carbon – Lower 4,569,611 8.5 5,609,379 10.7 1,039,768 2.0 Carbon - Central 9,139,222 8.5 11,218,758 10.7 2,079,535 2.0 Carbon - Upper 13,708,834 8.5 16,828,138 10.7 3,119,304 2.0

Aesthetic 0.14 1.9 0.12 1.6 -0.02 -0.2

Recreation 109,680 21.2 109,680 21.2 0 0.0

17 The values are monetary except for aesthetic, which are scores.

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5.1.2.2 Ecological Impact Assessment The same overall EcIA score (of 3.4) was achieved for the pre-project and business-as-usual scenarios for Ennerdale. This was because the area for most of the BAP habitat types was very similar under these two scenarios, except for the area of BAP woodland, which more than doubles under the business-as-usual scenario compared to the pre-project scenario. However, this is not enough of a difference to produce a change in score for BAP woodland. Moving from the pre-project to the landscape scenario, there was a slight increase in the overall EcIA score to 3.5. This is a result of an increase in the individual score for BAP woodland, which increases from 3 (district importance) in the pre-project and business-as-usual scenarios, to 4 (country importance) in the landscape scenario. There is no difference in the other individual scores, although the area of ‘upland heathland’ and ‘lowland heathland’ increases under the landscape scenario compared to the other two scenarios. However, this difference is not enough to produce a change in the scores for these habitat types. Nonetheless, there is an increase of 365 ha of BAP habitat in the landscape scenario compared to the business-as-usual scenario and an increase of 437 ha of BAP habitat in the landscape scenario compared to the pre-project scenario. The national and regional resource figures used for BAP woodland include all the BAP woodland types, whereas in Ennerdale the main BAP woodland types are ‘upland oakwood’ and ‘wet woodland’. If the national resource figures could have been obtained for these woodland types, rather than combined for all woodland, a higher score may have been achieved, but this was not possible due to lack of data. There is no difference in scores depending on whether national resource was defined as UK or England and Wales. 5.1.2.3 Costs RO provided information on Wild Ennerdale project set-up and running costs and J. Butler (Natural England) provided information on the implementation of agri-environment schemes under the alternative scenarios. J. Butler confirmed that the Higher Level Stewardship schemes in place would occur under either scenario. Wild Ennerdale is facilitated through the agri-environment schemes, but without Wild Ennerdale, Natural England would still have acted to prevent over-grazing. The total costs of the agri-environment schemes in the project area were obtained from the Natural England Environmental Stewardship GIS data18. Costs for one agreement were excluded, as the area farmed was mainly outside of the project area. This left one agreement (Organic Entry Level plus Higher Level Stewardship) and this figure was divided by 10 (the usual length of HLS agreements) to obtain an average annual cost - (Natural England 2010b).

18

http://www.gis.naturalengland.org.uk/pubs/gis/gis_register.asp (Accessed 3 June, 2010) - tile 'NY'.

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Table 11. Set up and conservation costs for conservation in the Ennerdale scenarios. Total costs are indicated in bold, with component costs listed below. Set-up costs are only applicable to the landscape-scale scenario. Costs Landscape-scale project (£) Pre-Project and Business-

As-Usual (£) Set-up 73,000 Cattle purchase 5,000 Ground work 35,000 Surveys and monitoring 8,000 Signage and visitor information

15,000

N/A

Average annual running 84,064 64,064 Project officer and public events costs

12,300 -

Miscellaneous costs 7,700 - Agri-environment schemes 64,064 64,064 The only additional running cost of the Wild Ennerdale project is employment of a dedicated project officer. There are also minimal costs (£300 per year) of running public events in the project area and the general miscellaneous costs of running a project (e.g. website, equipment, and volunteer expenses). The bulk of the Wild Ennerdale project work is funded by the Wild Ennerdale partners (National Trust, Forestry Commission and United Utilities), along with funding from Natural England for both the project officer post (contribution) and for conservation grazing with cattle. Other smaller pots of funding come from organisations such as the Lake District National Park Authority and the Environment Agency (RO). Much of the funding for Wild Ennerdale is achieved by redirecting funds. For example, the money that was previously spent on commercial planting by the Forestry Commission is now used for thinning work and replanting of broadleaves, and grants issued to farmers are being made available for extensive cattle grazing rather than sheep grazing (RO). Forecasting the costs was difficult because activities of the project will be influenced by a combination of factors such as legal compliance (e.g. SSSI condition), policies (e.g. National Park status), aspirations for less intensive management (the ‘Wilding’ approach), public opinion (e.g. signage), natural processes (e.g. weather events such as flooding/storm damage). The 10 year period since Wild Ennerdale began could be considered the ‘start-up’ period in which money has been spent on gathering baseline information to develop an understanding of the project starting point and needs. The next 10 years will see a continuation of project work and monitoring, with continued consultation with a wide range of stakeholders. How funding patterns might change is difficult to predict but it is hoped that there should not be a need to source large grants from outside the Wild Ennerdale Partnership (RO). The agri-environment scheme payment costs are expected to be the same under the alternative scenarios (J. Butler, Natural England).

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5.2 The Great Fen project

4.2.1 Creating scenario maps

Two scenarios were created for this case study based on remotely sensed land cover data, NVC habitat maps and expert local knowledge provided by the Great Fen project manager, Chris Gerrard (CG). A business-as-usual 2060 map was not developed for Great Fen, as consultation with CG indicated that there was no suitable information to project a future land cover different from the pre-project scenario. It was thought that the amount of peat would be likely to decline under a business-as-usual scenario, but this would not cause a change in land cover type for the 2060 business-as-usual scenario.

Pre-project scenario In this scenario, recent remotely sensed data was used to represent the land cover prior to project implementation. The landscape consists of isolated fenlands, Woodwalton Fen National Nature Reserve and Holme Fen National Nature Reserve, with arable land separating them. The CEH LCM2000 map (licence agreement ref LCM 2010-061) was modified to correct misclassifications (as outlined in Mountford et al. 2002). These adjustments were: Area of fen, marsh swamp in north-west tip of project area should be arable (4.2).

i. Polygon of acid grassland and urban in central north of project area should be arable (4.2).

ii. Two polygons of improved grassland in Holme Fen should be standing water (13.1). iii. Two polygons of improved grassland in Holme Fen should be broadleaved woodland

(1.1). iv. Four arable polygons (plus 2 polygons of set aside 5.2) in Holme fen should be

broadleaved woodland (except polygon to west of standing water, which should be bog, 12.1).

v. All remaining improved grassland polygons (8 in total) in Holme Fen should be acid grassland (8.1).

vi. All improved grassland in Woodwalton Fen should be fen, marsh, swamp (11.1). vii. One polygon of bog to east of Woodwalton fen should be arable (4.1). viii. Area of improved grassland in south-west of project area should be improved grassland. ix. Two polygons of neutral grassland in very east of project area should be improved

grassland x. Urban classification was particularly poor but as the total area of urban land was negligible urban classifications were reclassed to the adjacent habitat type.

Landscape-scale scenario The Great Fen project will connect Woodwalton Fen National Nature Reserve with Holme Fen National Nature Reserve, through land purchase and restoration. Neither of the nature reserve sites are sustainable at their present size, due to intensive arable cultivation around them and uncontrollable water levels (Great Fen Project 2005). A GIS map of the future habitat scenario, classified by NVC, under the Great Fen project was provided by CG. This is a map of the ultimate vision for the project, as set out in 2001, and is largely based on LIDAR data, topology, water levels and ‘gut feeling’ (CEH 2006; C. Gerrard, pers. comm. 31 March, 2010). This future scenario map is for ‘scenario 2’ of 3 possible scenarios proposed at the start of the project (CEH 2006; CG). Although the project partners are not entirely sure at what point in time each piece of land will become fen, the assumption is that all

34

of the land will be in conservation management by 2060. The map shows the land cover as predominantly neutral grassland, with substantial areas of fen. All habitat types may also potentially support areas of woodland as part of the heterogeneous landscape (CG). The land cover map provided for the future habitat scenario did not provide coverage for the whole of the Great Fen project area due to the costs of obtaining the LIDAR data. The remaining areas were mapped using expert knowledge provided by CG. This was largely informed by adjacent habitat type: i. S4 for the missing part in the north-west. ii. MG5 (dry grassland) for the missing area in the south. iii. An approximately 50:50 split of M24 and S24 for the missing part in the east. A final adjustment involved adding areas of standing water in Holme Fen and excluding urban areas for consistency with the business-as-usual scenario. Characteristics of the scenarios at Great Fen There is a highly significant change in land cover from the pre-project scenario to the Great Fen landscape scenario with a complete loss of arable land, replaced by fen, marsh and swamp and neutral grassland (Table 12, Figure 3). The landscape-scale scenario also shows a loss of broadleaved woodland in our modelling but it should be noted that it is possible that the new habitats created in the restoration may also support areas of woodland as part of the heterogeneous landscape (CG). Incorporation of these into the spatial scenario building was not feasible because it is not yet known if or where woodland may develop.

35

Table 12. Area of habitat types under alternative scenarios and change in area between the scenarios. PP is Pre-Project, LS is Landscape-Scale scenario and shaded cells accentuate increases in habitat area.

Area (ha) in case study site

Difference in area (ha)

Habitat type PP LS LS - PP

Acid grassland 33 0 -33

Arable and horticultural 3063 0 -3063

Bog 18 0 -18

Broadleaved woodland 437 0 -437

Calcareous grassland 10 0 -10

Fen, marsh, swamp 174 1145 971

Improved grassland 67 0 -67

Neutral grassland 0 2657 2657

Standing water/canals 9 9 0 .

36

Figure 3. Differences in land cover for each scenario in the Great Fen.

37

5.2.2 Evaluating costs and benefits for Great Fen

5.2.2.1 Ecosystem Services Food - Crops In the pre-project scenario, the only food production is of arable crops but under the Great Fen landscape scenario there will be no food crop production, so there is a 100% decrease in this service. Local gross margin per hectare values, after variable costs, of the main produce of the project area (potatoes, onions, sugar beet, winter wheat and peas) were made available along with expert opinion on the proportions of each that should be estimated (CG, Great Fen Socio Economic Study (PACEC 2004)). An overall crop gross margin value per hectare was determined by calculating a weighted average by proportion of each crop. ‘Standard values’ were calculated using the Nix (2009) gross margins per hectare for each of the crops in place of the local values, and an overall gross margin value per hectare was determined by calculating a weighted average (by proportion of each crop, as for the local values). An average of feed wheat and milling wheat was used for winter wheat, and spring and winter oilseed rape values were combined. A total value of crops for the project area was obtained by multiplying the total area of arable land under the pre-project scenario, by the overall per hectare values. Food - Beef There is no beef production under a pre-project scenario, only under the landscape scenario, where cattle are expected to be grazed in grassland and fen habitats MG8, MG5, S24, and M24 (CG). An estimate of the total number of cattle expected to occur under the landscape scenario was provided by CG and it was assumed that all would be sold for meat. No local monetary values were available, so standard values for grass-finished cattle were used (Nix 2009). A total monetary value for beef production in the study area under the landscape-scale scenario was obtained by multiplying the total number of cattle by the standard net price per animal. A value per hectare was calculated by dividing this value by the number of hectares in which cattle grazing is expected. Food - Lamb There is no lamb production under a pre-project scenario, only under the landscape scenario, where sheep graze in grassland and fen habitats MG8, MG5, S24, and M24 (CG). An estimate of the total number of sheep was provided by CG and all are expected to be sold for meat. No local monetary values were available so standard values for lowland spring lambs were used (Nix 2009). A total monetary value for lamb production was obtained by multiplying the number of sheep by the standard net price per animal. A value per hectare was calculated by dividing this value by the number of hectares in which sheep grazing is expected. Food - Venison The site partners concluded that there was too much uncertainty about changes in deer populations in relation to development of the Great Fen project so it would not be helpful to attempt a valuation. Deer are currently controlled as part of the conservation management, so in the future they may be sold to offset some of the culling costs, but this is not formally planned (CG).

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Fibre - Reed The production of reed would be an added benefit of the Great Fen project as it is only sold under this scenario. The size of the harvest is currently unknown but all S4 reed bed could potentially be used (CG). Reed production was therefore mapped to S4 habitat in the landscape-scale scenario. Total potential yield was calculated based on the assumption that British average reed productivity is about 623 bundles/ha/year (Sanderson & Prendergast 2002). A total monetary value of reed for the project area was calculated by multiplying the market price per bundle of reed (I. Lonsdale, pers. comm., in PACEC 2004) by the total number of bundles produced per year. Future production costs were unknown and estimation not possible (CG) so these were not subtracted resulting in an overestimation of value. Grass and hay Grass and hay is only sold under the landscape-scale scenario. Again, it is not known how much grass and hay will be harvested in the future, or where it will be harvested from. It could potentially be produced anywhere within the fen and grassland (S24, M24, MG8, MG5). Expert opinion suggested that approximately 70% of this area could potentially produce hay (CG). Grass and hay production was mapped to the total area of the four habitats in which it may be produced. Then, to calculate the total value for the project area reflecting the expert opinion, a value of 70% of this total area was used. No local yield or monetary values were available, so ‘standard’ yield values for grazed grass/silage and an average market price per tonne for meadow hay were used (Nix 2009). Again, it is not known what the production costs will be (CG). The market price per hectare was calculated by multiplying the market price per tonne of hay by the yield per hectare, from which a total monetary value of grass and hay production for the project area was calculated by multiplying by the number of hectares in which it is expected to be produced. Coppice Although coppicing is currently carried out within the project area, the produce is used internally rather than being sold. Coppice will only be sold under the landscape-scale scenario (CG). It could potentially be produced in most of the habitat types as woodlands develop as part of a heterogeneous landscape so there any estimate is very approximate: expert opinion suggests 40 hectares of coppice in the landscape-scale scenario (CG). No local values were available, so yield and market price per oven dried tonne were obtained for short rotation coppice (Nix 2009). The total potential yield of coppice was calculated by multiplying the yield per hectare by the expected number of coppice-producing hectares. This was then multiplied by the market price per tonne to obtain an overall monetary value of coppice production for the project area. Firewood and fen litter biofuel At this stage it is not known what quantity of these products will be produced in the landscape-scale scenario, so this was not included. It is also expected that saw-sedge production/selling is unlikely to be significant by 2060 (CG).

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Carbon There is a substantial increase in carbon storage under the Great Fen project landscape-scale scenario compared to the pre-project scenario. This is largely due to the replacement of arable land cover with fen, marsh, swamp, and neutral grassland, which have higher carbon storage values. There is a difference of over £29 million between the upper and lower values for carbon when calculating the difference between the landscape and pre-project scenarios. The substantial increase in carbon value is covered in considerably more detail by the study of carbon balance and offset potential for the Great Fen project, which concludes that the project would convert the area into a carbon sink with an annual avoided loss of 325,000 tonnes of CO2 equivalents (Gauci 2008). Flood mitigation The main difference in the Great Fen project area between the landscape scenario and the pre-project scenario is replacement of arable and horticultural land with neutral grassland and fen, marsh and swamp. Although the landscape scenario shows a loss of broadleaved woodland, the new habitat types may also potentially support areas of woodland as part of the heterogeneous landscape, but these have not been mapped separately as it is not yet know where these will develop (CG). Therefore, change in overall woodland cover, and any impact it may have on flood risk are likely to be negligible. The Great Fen project area currently requires constant draining in order for farming to be possible. Much of the Cambridgeshire Fens area is below sea level because the peat has shrunk so dramatically, meaning that the area (which includes some settlements) is under constant threat of flood (Great Fen Project 2005). When required, water is pumped out of the area by a number of pumping stations to prevent flooding and waterlogging (Environment Agency et al. 2010). Woodwalton Fen is currently used to store floodwater, protecting surrounding land and property. This is having detrimental effects on the nature reserve, which is likely to be too small to provide adequate flood risk management in the future (Environment Agency et al. 2010). The Great Fen project partners are currently investigating opportunities for enhancing the flood risk management role of the project by providing better alternatives in the project area. Whilst plans for the Great Fen involve different water levels in the future, some form of pumping regime will need to be maintained, to control water. However, there is potential to minimise the amount of pumping required in an around the Great Fen, with appropriate wetland management (Environment Agency et al. 2010). The restoration of fenland habitats from arable land will be the key difference in enhancing flood protection. Natural vegetations are typically much less susceptible to high rates of runoff than crops where agricultural practices can have significant impacts on soil structure and infiltration rates (O'Connell et al. 2004). Research on rewetting and other restoration of peat landscapes has shown that such work has the potential to contribute significantly to flood risk management through optimising retention of rainfall (Penny Anderson Associates Ltd 2010). Early responses from the SCaMP project have, for example, demonstrated establishment of a higher water table in the peat body, with reduced variations in seasonal water table levels, and a significant shift in streamflow regime, with discharge levels being reduced post land management works. Any increase in storage within the catchment, such as through the restoration of the natural storage capacity of the soil, like at Great Fen, would be expected to reduce flood generation and flood hazard. However, the extent of the reduction would be dependent on the amount of storage provided (O'Connell et al. 2004). Nonetheless, it is expected that the Great Fen project

40

will provide for enhanced flood storage, protecting surrounding land and property (Environment Agency et al. 2010). Recreation Willing-To-Pay values were calculated using literature values (Table 13) and annual visitor numbers were provided by CG. A figure of 10,000 was provided for the current (pre-project) number of visitors to the nature reserves within the project area and an estimate of the future visitor numbers as a result of the Great Fen Project scenario was based on figures from similar sites at 250,000 (CG). Hunting was not considered significant enough to be included in this area. Table 13. Calculation of WTP values for the Great Fen scenarios. Significance values provided by C. Gerrard. References are given in the main report.

Recreational activity

Literature WTP (£) -converted to current values

WTP value reference

Business-as-usual significance value

Adjusted WTP value business-as-usual scenario (£)

Landscape significance value

Adjusted WTP value landscape scenario (£)

Walking 1.74 Bennett et al. (2003)

3 1.04 5 1.74

Horse riding 15.89 Christie et al. (2006)

2 6.36 4 12.71

Cycling 16.75 Christie et al. (2006)

0 0.00 4 13.40

Climbing 0 0

Nature-watching

8.84 Christie et al. (2006)

4 7.07 5 8.84

Boating, water sports

68.07 Hynes and Hanley (2006)

2 27.23 3 40.82

Fishing 8.80 Peirson et al. (2001)

3 5.28 3 5.28

Swimming Not available

0 1

Picnicking Not available

0 2

Pleasure driving

0 0

Air sports Not available

0 1

Camping Not available

0 2

Average overall WTP value (£):

Pre-project scenario:

7.83 Landscape scenario:

13.80

Hunting 0 0

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There is a very high increase (4,306%) in recreation value under the Great Fen project scenario compared to the pre-project scenario due to a substantial increase in estimated visitor numbers and an increase in significance value of all but one of the recreational activities. Aesthetic The aesthetic value of the Great Fen project scenario is considerably higher than the pre-project scenario largely due to the replacement of arable land cover (which has the lowest aesthetic score of all the habitat types occurring in the project area), mostly with fen, marsh and swamp (which has one of the highest aesthetic scores) and neutral grassland (which also has a higher score). Summary: contrasting the ecosystem services for the two scenarios The Great Fen Project scenario results in significant increases in all ecosystem services apart from arable crops – which are removed from the system (Tables 14 and 15). Many new services are also provided by the project. Although a simple arithmetic comparison of the monetary gains and losses would not be meaningful as not all services can be assessed in money, it is interesting that the monetary loss from arable crops is vastly compensated for by the added and increased services.

Table 14. Difference in overall value of ecosystem services in the Great Fen project area using local values for ecosystem services where available.

Difference in overall value for project area – local values

Landscape minus Pre-project

Ecosystem service Monetary (£) % difference

Crops -3,333,494 -100.0

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Table 15. Difference in overall value of ecosystem services in the Great Fen project area using ‘standard’ values. Note that the values for reed, grass/hay and coppice are market, not net, value. The + symbol indicates that the pre-project value was zero and so a % increase was not appropriate.

Difference in overall value for project area – standard values

Landscape minus Pre-project

Ecosystem service Monetary19 (£) % difference

Crops -3,621,998 -100.0

Beef 264,000 +

Lamb 2,104 +

Reed 505,876 +

Grass/Hay 1,782,900 +

Coppice 60,000 +

Carbon – Lower 14,781,333 43.2

Carbon - Central 29,562,666 43.2

Carbon - Upper 44,343,998 43.2

Aesthetic 2.05 37.0

Recreation 3,371,700 4,306 5.2.2.2 Ecological Impact Assessment For the Great Fen EcIA, some regional resource data were located for the east of England (Land Use Consultants 2009). However, data for several BAP habitats occurring in the case study were missing and further enquiries confirmed that there were no other locally available data to supplement the report 20. The solution was to use Natural England GIS data to derive the missing data, and this was consistent with the derivation of regional resource used in Land Use Consultants (2009). Natural England GIS polygon layers21 were clipped to the east of England boundary and the total area of the polygons calculated. There is a slight increase in the overall EcIA score under the Great Fen landscape scenario compared to the pre-project scenario. This is the result of a substantial increase in area (and EcIA score) or lowland meadows, fens, and reedbeds, as well as non-BAP neutral grassland. The EcIA score does not increase as much as might be expected from the overall increase in area of BAP habitats (from 602 ha to 3635 ha). This is because there is a ‘loss’ of several BAP habitats, which although generally small in area under the pre-project scenario, are missing under the landscape scenario. This includes BAP woodland, for example, which although is likely to occur in the landscape scenario as part of a heterogeneous landscape, has not been mapped as a separate habitat. It should also be borne in mind that the scores were calculated based on relatively inaccurate regional resource data and the pre-project score for reedbeds in particular should possibly have been higher.

19

The values are monetary except for aesthetic, which are scores. 20

(C. Weightman, Regional Biodiversity Coordinator, East of England Biodiversity Forum, pers. comm., 16 September, 2010). 21 21 Downloaded from http://www.gis.naturalengland.org.uk/pubs/gis/GIS_register.asp (Accessed 14 June, 2010; 13 July, 2010).

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5.2.2.3 Costs Rough estimates of the Great Fen set-up and average annual running costs were provided by CG (Table 16). The estimates were approximate as they will inevitably be affected by numerous factors, such as land prices. The set-up cost also assumes that all land within the project area is purchased, but this cost would be slightly lower if the project does not need to buy all of the land and is instead able to manage some areas through landowners. The other set-up costs include habitat restoration costs, engineering costs for water management and provision of visitor and education facilities. The average annual running costs of the Great Fen project are mainly composed of BAP habitat management costs, as well as capital and revenue costs (including staffing costs and people/education related activities). Estimated costs of UK BAP habitat management were provided in Mountford et al. (2002) but in reality are approximate because they depend on unknown factors such as amount and type of management (such as extensive grazing compared to mowing). The pre-project average annual running costs included the costs of running the two nature reserves (Woodwalton Fen and Holme Fen) within the Great Fen project area. These were provided by A. Bowley (Senior Reserves Manager). In addition, the total costs of agri-environment schemes in the project area were obtained from the Natural England Environmental Stewardship GIS data22. The value of Entry Level Stewardship agreements was divided by 5 (the usual length of these agreements (Natural England 2010b)) to obtain an average annual value, and the value of Higher Level Stewardship agreements was divided by 10 to obtain an annual cost. It should be noted that this figure may be slightly higher than the actual figure as some agreements may be only partly within the project area.

Table 16. Set up and running costs for conservation work in the the Great Fen project area. Total costs are indicated in bold, with composition costs listed below these. Set-up costs are only applicable to the landscape-scale scenario. Costs Landscape project (£) Pre-project (£) Set-up 50,000,000 (mainly land acquisition and habitat restoration)

N/A

Average annual running 470,000 + 315,083 BAP habitat management 270,000 - Revenue and capital costs 200,000 - Woodwalton Fen and Holme Fen NNR running costs

- 128,000

Agri-environment schemes Currently unknown 187,083

Funding for the Great Fen project mainly comes from the Heritage Lottery Fund, Interreg, landfill tax, charitable trusts and corporate funding. It is also expected that the Great Fen project will receive some agri-environment scheme funding, but it is not yet known how much (CG). Under the pre-project scenario, there are over 3000 hectares of land within agri-environment scheme agreements (Entry Level Stewardship and Higher Level Stewardship), although it should

22 http://www.gis.naturalengland.org.uk/pubs/gis/gis_register.asp (Accessed 3 June, 2010) - tile 'TL'.

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be noted that the total annual cost figure calculated here may be slightly higher than the actual figure, as some agreements may be only partly within the project area. The average annual running costs are much greater under the Great Fen project compared to the pre-project scenario, but there will be a much larger area of priority habitats and land under conservation management.

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5.3 Heather and Hillforts project

5.3.1 Creating scenario maps

The scenarios for this case study were developed in consultation with the Heather and Hillforts project team using a project team meeting in March 2010 to discuss and approve the land cover for each scenario. Helen Mrowiec (HM) the project manager provided expert opinion and a link to the project team. The scenario mapping was limited to the patches of land of conservation importance within the larger area which delineates the project areas as these are the areas of planned active management. Within these patches under the different scenarios there is relatively little change in land cover, apart from a decrease in areas of bracken replaced by heathland under the landscape-scale scenario. All three scenarios are based on a Moorland Condition Survey of broad habitats carried out in 2005 at the outset of the project (The Heather and Hillforts Partnership Board 2005). Only minor modifications, such as adding missing land cover data, were required and were completed in consultation with HM. To create the 2060 scenarios, modifications to this base map were made using the expert opinion provided by HM and the Heather and Hillforts project team Pre-project scenario This scenario was represented by the 2005 survey data and abutting conifer plantation.

Business-as-usual scenario Future projections were based on knowledge of changes to moorland areas in response to different management approaches. If no management was to take place, as is assumed under the business-as-usual scenario, the moorland vegetation would become degenerate with more trees, such as mountain ash becoming established. The bracken dominated area would increase in area as it would not be managed. An area of recently felled coniferous plantation was not included in the survey. The assumption was that this would be allowed to regenerate to heathland (HM).

Landscape-scale scenario Future projections for this scenario were based on the assumption of achievement of the management goals of the Heather and Hillforts project by 2060. Under this scenario, management would be undertaken by landowners, graziers and the Heather and Hillforts project which would result in a diverse heather structure of pioneering, building and mature heather. Further bracken management would be undertaken, thus reducing its area. No change would occur in the presence of trees in comparison to the pre-project scenario (HM). The area of recently felled coniferous plantation not included in the survey was classified as heathland as for the business-as-usual scenario.

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Characteristics of the Heather and Hillforts scenarios Of the six habitat types occurring in the Heather and Hillforts scenarios, only three (heath, bracken and conifer) change in cover between the scenarios. The main changes are an increase in dwarf shrub heath under the landscape scenario, replacing bracken in the pre-project and business-as-usual scenarios, and coniferous woodland in the pre-project scenario. (Table 17, Figure 5). Table 17. The area of habitat types in the Heather and Hillforts project area under alternative scenarios and change in area between the scenarios. PP is Pre-Project, BAU is Business-as-Usual, LS is Landscape-Scale scenario and shaded cells accentuate increases in habitat area

Area (ha) in case study site Difference in area (ha)

Habitat type PP BAU LS LS - PP

LS - BAU

BAU - PP

Acid grassland 167 167 167 0 0 0

Bracken 838 866 827 -11 -39 28

Coniferous woodland 79 0 0 -79 0 -79

Dwarf shrub heath 1812 1863 1902 90 39 51

Improved grassland 74 74 74 0 0 0

Inland rock 12 12 12 0 0 0

.

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Figure 5. Differences in land cover for each scenario in the Heather and Hillforts project.

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5.3.3 Evaluating costs and benefits for Heather and Hillforts

Valuation of the scenarios in this site involved collaboration with the Project Officer, Helen Mrowiec (HM) and through her, consultation with the project team.

5.3.3.1 Ecosystem Services Food - Lamb Food production in this case study was limited to lamb which was produced in all scenarios. Lamb production was mapped to the whole of the study area excluding cells classified as bracken and quarry areas. For the pre-project scenario, coniferous woodland was also excluded. Figures on the total number of sheep present in the project area were not available, but HM provided a stocking density value of 0.225 livestock units per hectare, which she suggested could be multiplied by the total area in which sheep occur in the site under each scenario to obtain an estimate of the total number of sheep under each scenario. Although future sheep numbers are not known, these numbers would likely remain similar under either scenario, as over-grazing is not an issue in the project area (HM). The proportion of sheep to be sold annually meat was unknown, so the total stock was used for the valuation. It is not ideal as an over-estimate but will be the same for all scenarios. Local net monetary values were not available, so a standard value for the gross margin per ewe for upland flocks, after forage costs was used with the value of wool subtracted (Nix 2009). Wool was not valued due to the low market price compared to the production costs. A total monetary value for lamb production in the study area under each scenario was obtained by multiplying the total number of sheep by the standard net price per animal. This total value for the study area was then divided by the total number of hectares in which sheep occur under each scenario, to obtain a value per hectare. There is an increase in lamb production under both the landscape-scale and business-as-usual scenario compared to the pre-project scenario due to replacement of conifer with heath in both of these scenarios. The highest value was for the landscape-scale scenario because bracken increased in the business-as-usual future whereas it decreased in the alternative future, giving heath instead, and hence more suitable habitat for sheep grazing.

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Carbon It was necessary to align the broad habitats from the survey data supplied for this case study with the CEH LCM2000 classifications in order to enable valuation of carbon (Table 18). Table 18. Equivalent classifications for the Heather and Hillforts habitat survey and the CEH LCM2000. Original classifications LCM 2000 classifications Heathland Dwarf shrub heath Acid Grassland Acid grassland Improved Improved grassland Heathland/Acid Grassland Mosaic Dwarf shrub heath Bracken / Grassland Bracken Grassland/Heathland/Bracken Dwarf shrub heath Bracken Bracken Heathland, Bracken Dwarf shrub heath Heathland / Bracken Dwarf shrub heath Heathland/Bracken Mosaic Dwarf shrub heath Quarry Inland bare ground Bilberry / Acid Grassland / Gorse Acid grassland Coniferous woodland Coniferous woodland There is a small decrease in carbon value under the business-as-usual and landscape scenarios compared to the pre-project scenario, due to the increase in dwarf shrub heath under the two future scenarios, which has a lower carbon storage value than either bracken or coniferous woodland, which it replaces. The landscape scenario therefore has the lowest carbon value. There is a difference of almost £900,000 between the upper and lower values for carbon when calculating the difference between the landscape and pre-project scenarios. Flood mitigation The main landcover type in the Heather and Hillforts project area is heathland. The only change in land cover under the Heather and Hillforts landscape scenario compared to the business-as-usual scenario is the replacement of bracken with dwarf shrub heath, although this is only an area of 39ha. Therefore, this is unlikely to have any effect on flood mitigation. Under both the business-as-usual and landscape scenarios there is replacement of an area of coniferous woodland with dwarf shrub heath. Heathland generally intercepts less rainfall than coniferous woodland (Calder et al. 2002; Gilman 2002), but the area replaced is relatively small in terms of having a significant impact in the wider catchment. Although the project area is grazed by sheep, which can have impacts on surface run-off through soil compaction (O'Connell et al. 2004), numbers are not expected to change significantly under the alternative scenarios as overstocking is not a problem in the project area (H. Mrowiec, pers. comm., 9 July, 2010). There is no flood risk within the project area, or settlements, but the area is an upland area, so could potentially have impacts down slope, although the evidence that local scale changes in runoff generation propagate downstream to create impacts at the larger catchment scale is lacking (O'Connell et al. 2004; Wheater et al. 2008). The main impact of the Heather and Hillforts project is an improvement of heathland condition through better management, and impacts on flooding are not mentioned in the case study literature as an objective of the project.

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Further, the project area is a relatively small proportion of the total catchment and it is therefore likely that the impacts on flood risk of the project will be negligible. Recreation Willing-To-Pay values were calculated using literature values and estimates of visitor numbers (Table 19). The visitor numbers were estimated at 500,000 per year under all scenarios and were thought to be the same with or without the project (HM). Table 19. Calculation of WTP values for Heather and Hillforts. Significance values provided by H. Mrowiec.

Recreational activity

Literature WTP (£) -converted to current values

WTP value reference

Pre-project / business-as-usual significance value

Adjusted WTP value business-as-usual scenario (£)

Landscape significance value

Adjusted WTP value landscape scenario (£)

Walking 1.74 Bennett et al. (2003)

5 1.74 5 1.74

Horse riding 15.89 Christie et al. (2006)

2 6.36 2 6.36

Cycling 16.75 Christie et al. (2006)

2 6.70 2 6.70

Climbing 0 0

Nature-watching

8.84 Christie et al. (2006)

3 5.30 5 8.84

Boating, water sports

0 0

Fishing 0 0

Swimming 0 0

Picnicking Not available

4 4

Pleasure driving

0.97 Hanley (1989)

5 0.97 5 0.97

Air sports Not available

4 4

Camping 0 0

Average overall WTP value (£):

Pre-project/business-as-usual scenario:

4.21 Landscape scenario:

4.92

Hunting 0 0

Although the number of recreational visitors is the same under each of the scenarios, there is an increase in importance of nature-watching under the landscape scenario, meaning that this scenario receives a higher overall willingness-to-pay value, and therefore a higher recreation value.

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Aesthetic The lowest aesthetic value is for the pre-project scenario, due to the presence of coniferous woodland which, of the three habitats that change in cover under the different scenarios, has the lowest aesthetic index value. The business-as-usual scenario achieves a higher aesthetic score than the landscape scenario because it has a greater area of bracken compared to dwarf shrub heath, and bracken has a higher aesthetic index value. Summary: contrasting the ecosystem services for the two scenarios There were relatively minor differences in ecosystem service delivery between the different scenarios for this case study, reflecting the small changes in land cover (Table 20).

Table 20. Difference in overall value of ecosystem services in the Heather and Hillforts project area. LS is the Heather and Hillforts project landscape scenario; BAU is business-as-usual scenario. All values are standard values, as no local values were available for this case study.

Difference in overall value for project area – standard values

LS minus BAU LS minus Pre-project BAU minus Pre-project Ecosystem service

Monetary23 (£)

% difference

Monetary3 (£)

% difference

Monetary3

(£) % difference

Lamb 84 1.9 194 4.4 110 2.5 Carbon – Lower -52,285 -0.2 -437,262 -1.3 -384,977 -1.2 Carbon - Central -104,570 -0.2 -874,524 -1.3 -769,954 -1.2 Carbon - Upper -156,856 -0.2 -1,311,786 -1.3 -1,154,930 -1.2

Aesthetic -0.02 -0.2 0.02 0.3 0.04 0.4

Recreation 355,000 16.9 355,000 16.9 0 0.0 5.3.2.2 Ecological Impact Assessment The overall scores (4) for Heather and Hillforts remain the same under each of the three scenarios, as there is only one BAP habitat type present in the project area (‘upland heathland’) and although the area increases (by 51 ha) under the business-as usual scenario compared to the pre-project scenario, and the area under the landscape scenario increases (by 39 ha) compared to the business-as-usual scenario, the increase is not large enough to change the score. Another factor, that is not taken account of in the EcIA, is that under the pre-project and business-as-usual scenarios the heathland will be in unfavourable condition, whereas under the landscape scenario the condition will become favourable. So although there is not a great increase in the area of this BAP habitat, there is an increase in the area of this BAP habitat in favourable condition under the landscape scenario.

5.3.2.3 Costs The set-up and average annual running costs of the Heather and Hillforts project were provided by HH (Table 21). The only substantial set-up costs of the project were the costs of producing plans to obtain lottery funding. The other set-up cost was obtaining equipment for bracken management. As the total cost of this involved 3 other themes of the project that were not

23

The values are monetary except for aesthetic, which are scores.

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directly related to the biodiversity aspect, an assumption that the biodiversity aspect involved 25% of the total costs was used (HM). The greatest running costs of the Heather and Hillforts project are funded by the Heritage Lottery. These include staff costs, habitat management (heather cutting and burning, bracken management and tree removal), restoration of areas damaged by off-road vehicles, and access work (HM). The other additional costs are associated with Tir Gofal payments which will help to deliver the heathland maintenance work (HM). There were no Tir Gofal agreements within the project area before the Heather and Hillforts project and the project has helped to facilitate the uptake of these agri-environment payments. Therefore, it was assumed that there would be no Tir Gofal agreements under the pre-project or business-as-usual scenarios. Section 15 agreements (in the Llantysilio Mountains SSSI area) also apply for delivery of maintenance work (HM). These section 15 agreements were in place before the Heather and Hillforts project (HM) so the same costs were used in all scenarios The area under each of the Tir Gofal payment rates was obtained from the Welsh Assembly (G. Aeron, Tir Gofal Senior Project Officer), the rates for mandatory habitats and public access obtained from WAG(2006), and the rates for capital works obtained from WAG(2005a). Annual Tir Gofal costs were calculated and the annual mandatory habitats payments and permissive access payments added to this. Other agri-environment schemes, Tir Cynnal and Tir Mynydd, do not have a role in the Heather and Hillforts project (HM). The area under each scheme and payment rates were also obtained from WAG (Welsh Assembly Government 2005b, 2010), and Section 15 costs were obtained from CCW (H. Jones, Conservation Officer). It should be noted that the current Welsh agri-environment schemes are due to be replaced by a new scheme, Glastir. However, as it is not known what agreements will be in place under this scheme, the annual running costs were based on the current schemes only.

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Table 21. Set-up and conservation running costs for the Heather and Hillforts project area. Total costs are indicated in bold, with composition costs listed below these. Costs Landscape project (£) Pre-project/business-as-

usual (£) Set-up 26,883 Obtainment of Heritage lottery funding

20,883

Purchase of equipment for bracken management

60,00

N/A

Average annual running 205,312 23,751 Heather and Hillforts/Heritage lottery biodiversity running costs

113,200 0

Tir Gofal 68,361 0 Other agri-environment schemes

22,651 22,651

Section 15 agreements 1,100 1,100 The average annual running costs are substantially greater under the Heather and Hillforts project scenario compared to the pre-project and business-as-usual scenarios, as a result of money being spent specifically on biodiversity and heathland management, which would otherwise not have occurred.

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5.4 The Knepp Wildland Project

5.4.1 Creating scenario maps

Two scenarios were created for the Knepp castle estate to compare pre-project and landscape-scale scenarios. The scenarios were built using existing habitat survey maps and expert knowledge provided by the estate owner, C. Burrell (CB). For all scenarios some general edits were performed guided by CB: two additional areas of land owned by A. Burrell were added as they fall within the project boundary. CB indicated the habitat type of these additional areas. Other edits included removal of areas outside of the project boundary and also tenanted and urban land.

Pre-project scenario This scenario was developed to represent the estate just prior to the start of the project in 2000. The Estate was managed as an arable and livestock farm, with three dairies. The River Adur restoration project (Janes et al. 2006) was seen as part of the rewilding project and any land cover change associated with this was therefore excluded. The basis for the scenario map was a 2005 habitat survey using Higher Level Stewardship Farm Environment Plan survey categories (Natural England 2010a), with a additional categories assigned by recorders (see Greenaway 2006). This was supplied by Sussex Records Centre. As this survey occurred 5 years into the rewilding project, the map required editing to represent the pre-project condition. . Expert opinion was used to indicate what changes should be made (CB): i. Arable reversion and arable reversion/semi-improved grassland to arable. ii. Some areas of semi-improved grassland to arable. iii. Areas of wood pasture and parkland to arable, semi-improved grassland, or improved

grassland. iv. Some areas of arable to improved grassland, in the dairy areas. Landscape-scale scenario The Knepp rewilding vision is to cease running the Estate as a farm, to enclose the Estate with secure deer-proof fencing and to remove as many internal barriers as possible (Kernon Countryside Consultants and Land Use Consultants 2007). Herds of deer, cattle, pigs and horses would graze across the majority of the Estate to allow the vegetation to establish as it may have done in the past, under the influence of large herbivores. The eastern block of the estate will be fenced and managed in a different way, as it will be used to hold cattle in the spring/summer, so although it is part of the project it is not a rewilding area (CB). This scenario also included the River Adur restoration project (Janes et al. 2006; Kernon Countryside Consultants and Land Use Consultants 2007). This river restoration was associated with projected increase in wetland habitat along the river channel. The landscape-scale scenario aimed to use expert knowledge to project the possible land cover in 2060 assuming the successful implementation of the vision. On our request, CB provided annotated maps of how the estate might look in 2060 under the rewilding scenario, based on his knowledge of the estate and observations of what has happened so far (10 years into the project). These expectations are unavoidably based on numerous assumptions as the future vegetation is largely unknown, due to the nature of the project.

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The following habitat classifications were used in the sketch map by CB. These were aligned as closely as possible to classifications used in the vegetation map for the pre-project scenario: i. High canopy trees (predominantly oak); this was classified as broadleaved woodland; ii. Scrub (hawthorn, blackthorn, bramble); iii. Sallow scrub (dense thickets); iv. Wetland (standing water to seasonally wet areas); this was classified as fen vegetation, to

align with the ‘business-as-usual’ map; v. Gorse. vi. Unimproved (neutral) grassland An additional classification of ‘scrub and broadleaved’ trees was used where these two occurred together in a feature. The sketch map provided by C. Burrell was digitised using the Sussex Records Centre (SRC) 2005 habitat map as a base. The following rules were adhered to:

i. A minimum mappable unit of 0.25 ha was used, as this captured the essence of the sketched changes, and was of comparable detail to the SRC habitat map. It is also the recommended resolution for type features in the Higher Level Stewardship Farm Environment Plan (Natural England 2010a).

ii. Existing woodland was not modified, except where CB had indicated patches of ‘open’ or ‘woodland glade’, in which case ‘wood pasture and parkland’ was assigned.

iii. Scattered trees were mapped where there were three or more small patches of trees (< 0.25ha) in a polygon.

Characteristics of the scenarios for Knepp Under the Wildlands scenario in Knepp, the main change is replacement of arable and horticultural land and semi-improved neutral grassland, with unimproved neutral grassland and scrub, as well as scattered trees over unimproved neutral grassland. There are also smaller increases in broadleaved woodland and fen, marsh and swamp (Table 22, Figure 6).

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Table 22. Area of habitat types in Knepp under alternative scenarios and change in area between the scenarios. PP is Pre-Project, LS is Landscape-Scale scenario, and shaded cells accentuate increases in habitat area.

Area (ha) in case study site

Difference in area (ha)

Habitat type PP LS LS - PP

Arable and horticultural 724 2 -722

Broadleaved woodland 104 128 24

Coniferous woodland 28 24 -4

Fen, marsh, swamp 8 35 27

Fen, marsh, swamp and scrub 0 8 8

Gorse 0 4 4

Improved grassland 205 172 -33

Mixed woodland 70 68 -2

Scattered trees over unimproved neutral grassland 0 85 85

Scrub 11 192 181

Semi-improved neutral grassland 121 13 -108

Standing water/canals 15 15 0

Unimproved neutral grassland 1 538 537

Wood pasture and parkland 0 3 3

Figure 6. Differences in land cover for each scenario in the Knepp Wildland project.

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Figure 6. Differences in land cover for each scenario in the Knepp Wildland project

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5.4.2 Evaluating costs and benefits for the Knepp Wildland Project

The valuation for this case study was achieved through the collaboration of Charlie Burrell (CB), the site owner and manager and colleagues. Values were based on the detailed workings of a project feasibility report, adjusted in the light of the development of the site since the production of the report. The main changes between the pre-project and landscape scenarios at Knepp are the replacement of arable land with neutral grassland and scrub and broadleaved trees. It was assumed that the pre-project scenario would not have any costs associated with conservation work. The deer park restoration, funded by the agri-environment payments of the Countryside Stewardship scheme and the River Ardur restoration were included in the Wildland project.

5.4.2.1 Ecosystem Services Crops and Dairy Crops and dairy values were combined as the local values were only available in this format. Under the Knepp rewilding landscape scenario there will be no crop or dairy production, so there is a 100% decrease in value of this service compared to the pre-project scenario. The standard and local values are of a similar magnitude. Crop production would only occur under the pre-project scenario. All land classified as ‘arable’ in the pre-project map was mapped as producing crops. CB provided a list of the crops grown on the estate (winter wheat, winter barley, spring barley, oats, oilseed rape, beans, peas and maize for silage) and the approximate proportions of each. To calculate values per hectare, Nix (2009) gross margins were used. These were an average of the feed wheat and milling wheat for winter wheat, an average of the feed barley and malting barley values for winter barley and an average of spring and winter values was used for oats, oilseed rape and beans. Average annual sales (1990 – 2000) from crops and dairy) for the Knepp farm was provided by CB. A figure for total payments was also provided, but this was for crops and the dairy combined. The ‘payments’ were equivalent to the ‘variable costs’ used in the Nix pocket book (Nix 2009), so subtracting the payments from the total sales provided an equivalent gross margin. However, as separate values for the payments for crops and dairy were not available, the gross margin value for these was combined. Dairy production would only occur under the pre-project scenario. The fields in which cows were kept were identified by CB and a figure provided for the total number of cows. The Nix (2009) gross margin per cow for Holstein Fresians, producing an average milk yield was used as a standard value. Local values were provided by CB as the average annual sales (1990 – 2000) from dairy production. A figure for total payments was also provided, but this was for dairy and crops combined, so the gross margin value for these was combined, as described for crops.

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Fish Under both scenarios, every 4 to 5 years, Knepp Mill Pond would be drained and approximately £10,000 worth of carp sold. There are no costs involved, as the fish are caught as part of periodic lake draining work (CB). Livestock Meat (beef, pork and venison) is only sold under the Knepp landscape scenario. The local value is higher than the standard value, but it should be noted that the local values were based on figures from a feasibility assessment published in 2007. In terms of food production as a whole, the value of meat under the landscape scenario is much less than the value of crops and dairy under the pre-project scenario. Livestock were mapped for the landscape scenario, guided by CB:

(i) Pigs were mapped everywhere, excluding fenced areas, polo grounds, and a cattle ‘holding area’ (ii) Deer were mapped everywhere, excluding fenced areas and the ‘holding area’, but including polo grounds. (iii) Cattle were mapped everywhere, excluding fenced areas and the polo grounds. They were additionally mapped to the ‘holding area’.

The ‘holding area’ was included for the cattle (but not the pigs and deer), as although it will not be managed as a rewilding area, it is part of the project because it will be used to hold cattle in the spring/summer. This is so that they can be readily available for local abbatoirs for welfare reasons. This is important because Knepp Estate want to be able to sell their beef locally under the Knepp brand. Within the ‘holding area’ cattle will be kept in fenced groups of fields, but excluded from woodland (CB). Local livestock values were obtained from ‘Budget B’ in the Knepp Feasibility Assessment (Kernon Countryside Consultants and Land Use Consultants 2007). The sales for cattle for 2020/21 were used, as the numbers are expected to have reached a plateau by this time (CB). For pigs, the figure was adjusted downwards by using the sales figure for 2012/13. This was because monitoring of the site has indicated that pig production was overestimated in the feasibility study. The deer numbers were also too high in the feasibility assessment, partly because the area of land now included is smaller than predicted (CB). Therefore the 2009/10 figures were used for fallow deer and the 2013/14 figures for red deer, as these were the closest to the expected numbers suggested by CB. A total value of livestock for the project area was calculated. Payments (equivalent to Nix (2009) variable costs) were only available for all livestock combined. The 2015/16 figure was used, as it was in this year that the total livestock sales value was closest to the calculated total value, based on the adjusted livestock figures. It is also recognised that this value may be slightly higher than the true value, because it included costs for Exmoor ponies, which are not sold for food. The total payment value was subtracted from the total livestock sales to provide an overall net value for livestock in the project area. Per hectare values for meat production were calculated by dividing the total monetary value by the number of hectares in which livestock graze. Standard values were obtained from Nix (2009). The gross margin per head for average performance level grass finishing cows was used as a value for cattle. For pigs, an average of the gross margin per pig for pork, cutter and bacon at an average performance level. Nix values were

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only available for red deer, so values of half this were used for fallow deer, as suggested by the market values in the Feasibility Assessment. The gross margin per 300 hinds for a deer park was divided by 300 to obtain a value per animal. These values per animal were multiplied by the total number of animals (obtained from the Knepp Feasibility Assessment (Kernon Countryside Consultants and Land Use Consultants 2007) and CB to obtain a total value for the project area. It should be noted that these standard values are likely to be under-estimate, particularly for beef, as the beef sold at Knepp will likely achieve a higher value as it will be sold as a premium local brand. Per hectare values for meat production were calculated by dividing the total monetary value by the number of hectares in which livestock graze. Fibre and fuel There is no profit in timber production on Knepp Estate, under either scenario, due to high extraction costs, so timber was not valued (CB). Under the landscape scenario, it may be possible to sell animals skins and antlers, but sales are likely to be negligible, so this was not valued. Carbon The 55.1% increase in carbon value in the landscape scenario compared to the pre-project scenario is due to the increased carbon storage capacity of neutral grassland, and even more so of broadleaved woodland (which both increase in area), compared to arable habitat type. There is a difference of over £14 million between the upper and lower values for carbon when calculating the difference between the landscape and pre-project scenarios. Flood mitigation Under the landscape scenario in Knepp the main change in landcover is replacement of arable and horticultural land and semi-improved neutral grassland, with unimproved neutral grassland and scrub, as well as scattered trees over unimproved neutral grassland. There are also smaller increases in broadleaved woodland and fen, marsh and swamp. Under the Knepp landscape scenario the landscape will become more ‘natural’ and it is known that natural vegetation such as woodland are typically much less susceptible to high rates of runoff than crops, due to the degree of protective coverage the foliage provides, the impacts of agricultural practices on soil structure and infiltration rates, the time at which machinery is required on the land, and the effects of agricultural practices on the concentration of flow (O'Connell et al. 2004). In general, taller vegetation will increase interception losses and lead to reduced flood runoff (Gilman 2002). The increase in scrub and scattered trees may act like shelterbelts, which have been shown to generally increase interception losses, available water storage within the soil, and the rate at which water can move from the ground surface into the subsurface (Wheater et al. 2008). Although at an upland site, it has been shown that tree shelter belts and buffer strips can significantly reduce the magnitude of peak runoff at the field and small catchment scale (Wheater et al. 2008). The Knepp project area is a flat lowland landscape, so there may be less effect, but it does form part of the River Adur floodplain, of which there are plans to restore. This restoration will involve re-naturalising up to 8km of the River Adur running through the Estate, including relocation of meanders and wetland and floodplain habitats. The plans to re-introduce meanders to a section of the River Adur, which has been straightened over the centuries, will result in both a slower flow and areas of damp, wet or occasionally flooded

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surrounding land (Janes et al. 2006; Kernon Countryside Consultants and Land Use Consultants 2007). Some properties on the estate might experience some increase in flooding, but flood protection would be given and all properties under risk of flooding are owned by the estate (Janes et al. 2006). It is also specified in the pre-feasibility study for the project (Janes et al. 2006) that hydraulics and engineering works will ensure that the flooding extent and duration upstream and downstream of the site is not adversely affected. Another factor to consider at the Knepp site, is that the landscape scenario will include livestock grazing. However, the stocking densities will not be as high as agricultural stocking densities, so any negative effects of compaction are unlikely to be greater than the positive impact of less compaction from conversion of the land from arable and dairy use to the rewilding landscape scenario. Overall, although there may be some impact of increased tree cover at a site level, it is unlikely that changes in landcover and management on the estate will have wider impacts on flooding beyond the site, in particular as evidence of such wider impacts in general is lacking (O'Connell et al. 2004; Wheater et al. 2008). Recreation The total number of recreational users for the two Knepp scenarios was not known. There are no relevant data for footpath use on the site and no surveys of footpath usage in the county have been carried out (J. Perks, Principal Rights of Way Officer, West Sussex County Council). Therefore, it was not possible to provide any figures for the number of recreational users under the pre-project scenario. However, CB was able to provide an estimate of the expected annual number of the number of recreational visitors to the project area under the future landscape scenario for certain activities (but excluding those using the public footpaths). This was based on an assumption of approximately 600 visitors for training days and guided walks, at least 700 visitors using the proposed tented safari camps and approximately 40 people using the site as part of a riding group. This total was used to calculate the number of recreational users under the landscape scenario and could be seen as the difference in the number of users between the two scenarios. However, this may be an underestimate, as users of the public footpaths are expected to increase. For example, CB reported approximately 5-6 fold increase in the number of walkers near the castle since the rewilding project began. The WTP value increases under the landscape scenario as there is an increase in the significance score of several of the recreational activities in the landscape scenario compared to the pre-project scenario. Several of these activities will also generate income under the landscape scenario.

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Table 23. Calculation of WTP values for Knepp. Significance value provided by T. Greenaway (12 February, 2010) and adjusted hunting significance values provided by C. Burrell (12 May, 2010).

Recreational activity

Literature WTP (£) -converted to current values

WTP value reference

Pre-project significance value

Adjusted WTP value business-as-usual scenario (£)

Landscape significance value

Adjusted WTP value landscape scenario (£)

Walking 1.74 Bennett et al. (2003)

2 0.70 5 1.74

Horse riding 15.89 Christie et al. (2006)

2 6.36 5 15.89

Cycling 16.75 Christie et al. (2006)

1 3.35 4 13.40

Climbing 0 0

Nature-watching

8.84 Christie et al. (2006)

1 7.07 5 8.84

Boating, water sports

68.07 Hynes and Hanley (2006)

1 13.61 1 13.61

Fishing 8.80 Peirson et al. (2001)

1 1.76 1 1.76

Swimming Not available

1 1

Picnicking Not available

0 1

Pleasure driving

0 0

Air sports 0 0

Camping Not available

0 4

Average overall WTP value (£):

Pre-project scenario:

4.30 Landscape scenario:

9.21

Hunting 0 0

Aesthetic The aesthetic value increases by 21.6% under the landscape scenario compared to the pre-project scenario, mainly as a result of the increase in area of neutral grassland and broadleaved woodland, which both receive a higher aesthetic score than arable.

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Summary: contrasting the ecosystem services for the two scenarios A loss of output from crops and dairy is balanced by commercial meat production in the Knepp Wildlands project and the introduction of the holding area for cattle since the original feasibility plans indicates the importance of this service to the viability of the estate. Monetary comparisons using the local and standard value are reasonably similar for crops. Increases in the delivery of other ecosystem services are also indicated: carbon storage, aesthetic value and recreational use (Tables 24 and 25).

Table 24. Difference in overall value of ecosystem services in the Knepp scenarios using local data where available. The + symbol indicates that the pre-project value was zero and so a % increase was not appropriate.

Difference in overall value for project area – local values

Landscape minus Pre-project

Ecosystem service Monetary (£) % difference

Crops

Dairy -807,624 -100.0

Fish 0 0.0

Livestock - meat 46,000 +

Table 25. Difference in overall value of ecosystem services in the Knepp project scenarios using standard values. The + symbol indicates that the pre-project value was zero and so a % increase was not appropriate.

Difference in overall value for project area – standard values

Landscape minus Pre-project

Ecosystem service Monetary24 (£) % difference

Crops

Dairy -757,783 -100.0

Fish No standard values available

Livestock - meat 30,403 +

Carbon – Lower 7,278,273 55.1

Carbon - Central 14,556,546 55.1

Carbon - Upper 21,834,819 55.1

Aesthetic 1.28 21.5

Recreation 12,341 + 5.4.2.2 Ecological Impact Assessment There is an increase in the overall EcIA score for Knepp, from 2.7 in the pre-project scenario, to 4.0 in the landscape scenario. This is a result of the increase in the individual score for ‘lowland meadows’ which increases from 2 (parish importance) to 6 (national importance), as a result of an increase in area 537 ha. Although there is an increase in area (of 110 ha) of BAP woodland under the landscape scenario, it is not enough to increase the score. Including scrub as BAP woodland also did not affect the score and neither did the different definitions of national

24

The values are monetary except for aesthetic, which are scores.

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resource have an effect. The overall area of BAP habitat increases by 647 ha in the landscape scenario compared to the pre-project scenario.

5.4.2.3 Costs Details on costs for the two Knepp scenarios and agri-environment schemes payments were provided by CB. Annual running costs of the landscape project were determined by taking an average of the running costs from 2010 – 2020. Livestock payments were included in the livestock net value so were not included separately in the costs calculations. However, labour costs were not included in any meat costs, as they were not included in the standard values, so these were included in the annual running costs for the project. Livestock purchase was also included.

Table 26. Set up and running costs for conservation work in the Knepp scenarios. Total costs are indicated in bold, with composition costs listed below these. Costs Landscape project (£) Pre-project (£) Set-up 1,242,000 Capital set-up costs (fencing etc.)

752,000

Livestock purchase 63,000 Surveys 42,000 River Adur restoration 385,000

N/A

Average annual running 84,975 0 Livestock purchase and management

7,800 -

Surveys 10,400 - Signage and deer park equipment

6,000 -

Overheads 55,000 Agri-environment scheme payments

209,047 -

The rewilding landscape project set-up costs are largely composed of fencing and equipment costs. The deer park restoration is included in the rewilding set-up costs, as this was a project that preceded and then became incorporated by the Wildlands scheme. The River Adur floodplain restoration costs are also included within the landscape scenario. Costs are gross amounts rather than net costs to the estate. Funding for the set-up costs of the rewilding project has largely come from the Countryside Stewardship Scheme and from Knepp Estate. The River Adur restoration project also received funding through the Environment Agency. The running costs of the rewilding project are funded through HLS payments (from January 2010). The total agri-environment payments are indicated (composed of HLS, ELS and OELS), but the costs should not be double counted, as the running costs of the rewilding project are funded by agri-environment schemes.

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Under the pre-project scenario no money was being spent specifically on conservation work and no agri-environment payments were received – therefore, running costs for conservation were zero. The pre-project scenario describes the estate as a commercial farm and details of the cash flow for this was supplied by CB. For three years 1997-9 prior to the start of the rewilding project, the overheads averaged £525,000 and the total margins (sales minus payments) were £606,000. These values would clearly differ enormously between years – their utility here is to illustrate the large reduction in overheads made possible through the rewilding project.

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5.5 Pumlumon project

5.5.1 Creating scenario maps

The three scenarios for this case study were created in collaboration with C. Faulkner (CF), Living Landscapes Manager of the Montgomeryshire Wildlife Trust (MWT) with reference to existing vegetation survey maps, project plans and contribution from other members of the MWT team. Edits, such as reclassifying small mapping errors were made to the base vegetation map in consultation with CF. Pre-project scenario This scenario map was created for the Pumlumon project area using a recent Phase 1 survey (carried out by CCW, updated in 2010 by Montgomeryshire Wildlife Trust). Business-as-usual scenario This scenario was based on the Phase 1 map and modified using expert opinion (CF) to project possible changes by 2060 assuming business continues as usual. It was assumed that habitat types would remain the same under a business-as-usual scenario, except dry modified bog (E1.8) was assumed to become unimproved acid grassland (B2.1). Landscape-scale scenario This scenario represented the projected landscape in 2060 assuming the successful implementation of the Pumlumon project. In this case study, maps of target and opportunities had already been created and so these were used, in consultation with CF, to develop the scenario map. Three main sources were provided: i. A ‘target habitat’ map. This map represented a target ‘end point’ for the project, which is

expected to take approximately 20 years. It was noted that this was probably an optimistic projection so is suitable for a 2060 scenario (CF). This map was developed by Montgomeryshire Wildlife Trust and the methodology drawn from the CCW Upland Strategy mapping methodology (Jones 2007).

ii. A grassland opportunity map (created by Jim Latham, CCW, using BEETLE25), which provides polygons of grassland of most likely ecological significance based on the BEETLE output.

iii. A woodland/scrub opportunity map, which is to be implemented with the Forestry Commission, such as through development of scrub on riparian corridors. It also identifies areas to target for tree planting and natural regeneration.

To develop the scenario, the grassland and woodland opportunity maps were used to modify the target habitat map. These two habitats were extended in the target map to reflect the potential for increased habitat connectivity that these opportunity maps are designed to model. These modifications were made in consultation with MWT to reflect their management aspirations. So the grassland map was applied to convert improved to semi-improved grassland and the woodland map was used to modify any habitat underlying the network into woodland.

25 See Latham & Gillespie (09) Applying connectivity mapping to spatial planning in Wales Ecological Networks: Science and Practice. Proceedings of the Sixteenth Annual IALE(UK) Conference. Held at Edinburgh University, 1st - 3rd September 2009. Edited by Roger Catchpole, et.al. ( http://www.bsg-ecology.com/News/Images/Latham%20Gillespie%202009.pdf)

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Characteristics of the scenarios at Pumlumon Under the Pumlumon business-as-usual scenario, compared to the pre-project scenario, the only difference is a replacement of dry modified bog with unimproved acid grassland reflecting a projected change due to continued loss of habitat condition. In the landscape-scale scenario, compared to the other two scenarios, large areas of coniferous woodland are replaced with scrub. The area of broadleaved woodland also increases, replacing improved grassland, which substantially decreases under the landscape-scale scenario, and also replacing bracken. The scenario was built to reflect the management for connectivity using hedgerow and riparian planting to encourage scrub and woodland (Bailey et al., 2010). Under the landscape-scale scenario, a significant amount of fen, marsh and swamp is replaced with blanket bog, and large areas of unimproved acid grassland are replaced with dwarf shrub heath. There is also an increase in semi-improved neutral grassland, which replaces improved grassland (Table 27, Figure 7).

Table 27. Area of habitat types in Pumlumon under alternative scenarios and change in area between the scenarios. PP is Pre-Project, BAU is Business-as-Usual, LS is Landscape-Scale scenario and shaded cells accentuate increases in habitat area.

Area (ha) in case study site Difference in area (ha)

Habitat type PP BAU LS LS - PP

LS - BAU

BAU - PP

Arable and horticultural 76 76 63 -13 -13 0

Blanket bog 862 862 2000 1138 1138 0

Bracken 1160 1160 366 -794 -794 0

Broadleaved woodland 1226 1226 6200 4974 4974 0

Built up areas, gardens 196 196 191 -5 -5 0

Coniferous woodland 7752 7752 5086 -2666 -2666 0

Dry modified bog 270 0 255 -15 255 -270

Dwarf shrub heath 3256 3256 4649 1393 1393 0

Fen, marsh, swamp 2236 2236 1251 -985 -985 0

Improved grassland 12849 12849 6032 -6817 -6817 0

Inland rock 187 187 159 -28 -28 0

Mixed woodland 77 77 2 -75 -75 0

Scrub 47 47 2457 2410 2410 0

Semi-improved acid grassland 329 329 4563 4234 4234 0 Semi-improved neutral grassland 51 51 17 -34 -34 0

Standing water/canals 587 587 558 -29 -29 0

Unimproved acid grassland 7634 7904 4964 -2670 -2940 270

Wet modified bog 242 242 224 -18 -18 0

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Figure 7. Differences in land cover for each scenario in Pumlumon.

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5.5.2 Evaluating costs and benefits for Pumlumon

Valuation of this case study was achieved by collaboration with Clive Faulkner (CF) Liz Lewis-Reddy (ELR) Agricultural Ecologist, Steve Hughes (SH), Estelle Bailey (EB) (Pumlumon project manager) of the Montgomeryshire Wildlife Trust, information was also provided by staff from the Forestry Commission, water and hydroelectric companies, WAG and CCW. The difference between the business-as-usual and pre-project scenarios is the replacement of bog with acid grassland under the business-as-usual scenario. Under the Pumlumon project landscape-scale scenario the main differences compared to the business-as-usual and pre-project scenarios are an increase in acid grassland, bog, dwarf shrub heath and broadleaved woodland, with a decrease in improved grassland, fen, marsh and swamp, and coniferous woodland. 5.5.2.1 Ecosystem services Crops Although some crops are grown on improved grassland, these are used to feed livestock, rather than being sold. The only crops that are sold are a small amount of oilseed rape, which is mapped as arable under each of the three scenarios (ELR). No local values were available, so standard per hectare gross margin values for oilseed rape (an average of the values for winter and spring rape) were obtained (Nix 2009). A total value of crops for the project area under each scenario was obtained by multiplying the total number of hectares of arable land under each scenario, by the standard per hectare value. There is a decrease of 17.1% in crop production under the landscape scenario compared to the business-as-usual and pre-project scenarios due to a relatively small decrease in arable land, which is mostly replaced by broadleaved woodland under the landscape scenario. The total area in which crops are grown is not very large, so a small loss produces a relatively large percentage decrease. Beef For the pre-project and business-as-usual scenarios, beef cattle occur only in improved grassland (ELR). They were mapped to all improved grassland, as the exact locations were not known. Under the Pumlumon project scenario beef cattle were mapped to acid grassland and dry heath habitats, as well as improved grassland (CF). An estimate of the total number of cattle under each of the scenarios was provided by ELR, with an increase in cattle numbers under the Pumlumon project scenario. An assumption was made that approximately 25% of the total number of cattle would be sold for meat (ELR). Local net values (equivalent to Nix gross margin) for beef production were provided by ELR and it was assumed that production costs would be the same under each scenario. Standard values were taken as the average of the gross margins per cow for average performance level for spring and autumn calving single suckling upland/hill cow (Nix 2009). A total monetary value for beef production in the study area under each scenario was obtained by multiplying the total number of cattle by the standard net price per animal. This total value for the study area was then divided by the total number of hectares in which cattle occur under each scenario, to obtain a value per hectare. Beef production is the same under the pre-project and business-as-usual scenarios, but increases by 400% under the landscape scenario due to encouragement of cattle grazing and introduction

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of grazing into areas other than improved grassland as part of the Pumlumon project. The local value is higher than the standard value. Lamb Lamb distribution under all three scenarios was aligned to all habitat types except forestry, inland rock and urban classifications (CF). An estimate of the total number of sheep under each of the scenarios was provided by ELR with the assumption that approximately half would be sold for meat. It was assumed that sheep farming would remain the under each scenario, but the Pumlumon project would increase the number of cattle (ELR). Local net values (equivalent to Nix gross margin) for lamb production were provided and it was assumed that production costs would be the same under each scenario (ELR). To calculate standard values, the gross margin per ewe for upland flocks, after forage costs and with (Nix 2009) and the value of wool was subtracted as it has zero value (CF). A total monetary value for lamb production in the study area under each scenario was obtained by multiplying the total number of sheep by the standard net price per animal. This total value for the study area was then divided by the total number of hectares in which sheep occur under each scenario, to obtain a value per hectare. Although different habitat types support different densities of livestock, it was decided to simplify the value per hectare by providing an average value across all habitat types (ELR). Lamb production stays the same under each of the scenarios, so there is no change in value of this service. Timber The majority of timber production in the Pumlumon project area is from Forestry Commission coniferous woodland, with a small amount from privately owned conifer woodland (CF). Very little broadleaved timber is harvested in the project area, so this was excluded from the valuation (J. Pritchard, Head of Harvesting Wales, Forestry Commission Wales). Under the landscape-scale scenario, a significant amount of these conifer plantations will be replaced by scrub, as part of a long-term plan to develop corridors along water courses and eventually moving towards more broadleaved trees. However, by 2060 these areas are still expected to be scrub, although further into the future it is hoped that broadleaved trees will be present (CF). Under the landscape scenario, there is a substantial increase in broadleaved woodland in the improved grassland areas. This is largely small-scale farm planting to help improve flood water management, carbon storage and stock quality (to be encouraged by the new Glastir agreements), and may be used for producing timber by farmers. However, the extent of this is not currently known and would not be possible to value (CF). The local net value (after harvesting costs) per hectare of coniferous timber per 60 year cycle of the crop was provided by J. Pritchard. This value was divided by the length of the cycle (60) in order to calculate an annual per hectare net value. This value was applied to all coniferous woodland, including non-Forestry Commission woodland, as the timber would likely have a similar value and it was not possible to obtain values from the privately owned woodlands (C.F). It was not possible to determine future costs (J. Pritchard), so the current values were used for all scenarios.

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The standard per hectare value obtained from the Forestry Commission for conifer trees was also applied. This standard value was calculated by multiplying average cumulative production values for conifers and broadleaves (provided by E. Mackie, Forestry Commission) by the average standing sale prices for conifers (provided by C. Winbow, Forestry Commission, 24 May, 2010).This value was then divided by the length of the cycle in order to obtain an annual/snapshot value. A total value for the project area for each scenario was calculated by multiplying the total area of coniferous woodland by the local and standard monetary values per hectare. Timber production is the same under the pre-project and business-as-usual scenarios, but decreases by 34.4% under the landscape scenario, due to the decrease in area of coniferous woodland, replaced by scrub. It is anticipated that these areas of scrub will eventually be areas of broadleaved woodland, producing timber, but this will not be the case by 2060 (CF). Although under the landscape-scale scenario there is an increase in habitat classified as broadleaved woodland under the Land Cover Map (LCM) classification, a significant proportion of this is scrub, which is not included in the timber calculations. The standard timber values produce a higher overall value than the local timber values. Hydroelectric energy Within the Pumlumon project area, hydroelectric energy is produced at the Nant-y-Moch reservoir. Values for the quantity of electricity produced annually were obtained from P. Miller (production engineer, Statkraft Energy Ltd., pers. comm., 15 June, 2010). It was not possible to obtained monetary values for this as such information was considered commercially sensitive (P. Miller). Although the ‘sponge effect’ of bog improvement may slow down water runoff and maintain a higher sustained flow to the generators during dry periods (P. Miller), it is difficult to quantitatively estimate how the Pumlumon project will effect hydroelectricity generation at this stage. P. Miller, suggested that provided the water is not diverted out of the catchment, it is unlikely to produce a significant change. Therefore, the same value was used for each scenario. Fresh water provision There are two reservoirs within the Pumlumon project area from which fresh water is extracted; Craig-y-Pistyll and Llyn Llygad Rheidol. A GIS layer of the locations of these was created and values for the total amount of water extracted annually from the reservoirs and the market price (per m3) to the consumer were obtained from West Wales Water (D. Webb, water quality scientist). It was not possible to obtain net values as this information was considered commercially sensitive. However, no significant changes in production costs would be expected under different land cover scenarios because the water in that area is very clean already, and although they may expect bigger changes in water quality from river abstraction, they would not for reservoirs (D. Webb). Carbon There is a slight decrease of 2.1% in carbon value in the business-as-usual scenario compared to the pre-project scenario as a result of the replacement of some areas of bog (which has the highest carbon storage value) with acid grassland (which has a much lower carbon storage value). There is a more substantial increase in carbon value in the landscape scenario compared to the pre-project and business-as-usual scenarios, largely due to an increase in bog and broadleaved woodland in place of a decrease in coniferous woodland and fen, marsh and swamp, which have lower carbon storage values. There is a difference of over £200 million between the upper and

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lower values for carbon when calculating the difference between the landscape and pre-project scenarios. Flood mitigation The Pumlumon Project area is the largest watershed in Wales, being the head waters of 8 rivers (the Severn, Wye, Rheidol, Ystwyth, Elan, Teifi, Tywi, and Irfon), so there is much scope for the project to make a significant contribution to mitigating against flooding events (Anon. 2007). With a substantial area of upland landscape within the project area, this is a significant source area for runoff generation (Wheater et al. 2008). Under the landscape scenario compared to the pre-project and business-as-usual scenarios, a significant amount of fen, marsh and swamp is replaced with blanket bog. The rewetting of upland bogs is a key aspect of the Pumlumon landscape project that is likely to have an influence on flood mitigation. The project involves a substantial amount of ditch blocking and rewetting of upland bogs, with expected restoration of over 1000ha of blanket bog in the landscape scenario compared to the pre-project and business-as-usual scenarios. Early results from the SCaMP project Goyt catchment site have demonstrated promising responses to similar management of moorland and blanket bog restoration through grip blocking and other associated land management changes (Penny Anderson Associates Ltd 2010). Although the programme has only been running for a few years, responses have included the establishment of a higher water table in the peat body, with reduced variations in seasonal water table levels; and a significant shift in the streamflow regime, with discharge levels being reduced post land management works. Optimising the retention of rainfall on the catchment in this way may have a significant contribution to make to flood risk management (O'Connell et al. 2004; Penny Anderson Associates Ltd 2010). As part of the LIFE-Nature Active Blanket Bogs in Wales project, Wilson et al. (2010) report that drain blocking restoration work of a degraded Welsh upland blanket bog has led to increases in water storage, producing lower discharge rates observable at the level of both drains and hill streams; as well as greater water table stability, reduction in peak flows and increases in water residency after rainfall. Similar results could be expected for Pumlumon although the authors do note that further research is needed on the landscape scale and over longer time periods as there are strong local and large scale topographic effects on the response to the restoration. Another significant habitat change under the landscape scenario compared to the pre-project and business-as-usual scenarios is that the area of broadleaved woodland increases, replacing improved grassland, which substantially decreases under the landscape scenario, and bracken. This could potentially decrease surface run-off. For example, results from research undertaken at Pontbren (Wheater et al. 2008) have shown that, compared to grazed grassland, there is significantly less overland flow within tree planted areas where sheep are excluded. This is the result of an increased ability (compared to soils under improved grassland) of the soil under these tree planted areas to store and conduct incoming rain water or potentially, overland flow from the hillslope above. Although the treatments are not long established and time is required to see whether these reductions are significant, there is also evidence that tree shelterbelts strategically positioned across a hillslope may act as runoff peak mitigation features at the hillslope scale, reducing surface runoff and having a positive effect on flooding (Carroll et al. 2004a; Marshall et al. 2009; Wheater et al. 2008). O’ Connell et al (2004) also note that conversion of arable or intensively used grassland to woodland has significant potential to reduce total runoff in the long term.

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Related to this aspect, there is also the possibility of the Pumlumon project helping to mitigate flooding events through reduction of sheep stocking density in upland areas. Soil compaction (and consequent decreased rainwater infiltration) through sheep grazing is considered to be a significant issue in the Cambrian Mountains (Anon. 2007; Carroll et al. 2004b). Decreases in stocking density have been shown to increase infiltration rates (Gilman 2002). Further support that an increase in woodland cover may have a positive effect on flood mitigation comes from comparisons of a grassland catchment with a forested (67%) catchment at Pumlumon, which have demonstrated the grassland catchment to exhibit a greater level of flow variability, especially in summer, and shorter hydrograph duration, especially in winter (Archer 2007). In the landscape scenario compared to the pre-project and business-as-usual scenarios, large areas of coniferous woodland are replaced with scrub. Scrub is likely to intercept less rainfall than coniferous woodland (Calder et al. 2002), but the overall effect of this is likely to be minimal. Large areas of unimproved acid grassland are replaced with dwarf shrub heath under the landscape scenario, which may have a positive effect on flood mitigation. This is because heathland vegetation is likely to be taller and tall vegetation generally intercepts more rainfall, leading to less rapid surface runoff (Calder et al. 2002; Gilman 2002; Orr & Carling 2006). Overall, there are several aspects of the Pumlumon project scenario that may help to mitigate flooding, in particular the bog rewetting. There are some built-up areas within the project boundary, some of which fall within flood risk zones. Evidence is limited on the extent of the impacts of local scale changes in runoff generation on downstream and the wider catchment, and the outcome will depend on a complex mosaic of different landscape elements (different topographies, soils, vegetation etc), only some of which will be impacted by changes in land management practices (O'Connell et al. 2004). However, results from research carried out within the Pumlumon project area, suggest that the benefits of well placed tree strips extend to at least the small (ca 12 km2) catchment scale (Jackson et al. 2008a) and differences in flow variability between dominant grassland and woodland land uses can also be seen at this scale (Archer 2007). Further, the area of habitat change and/or management change that is to take place under the Pumlumon project is substantial (the project area covers over 30,000 ha), so it is likely that there will be effects on flood mitigation, but it is not possible to determine the significance of this at this stage. Recreation Estimation of recreational value was limited in Pumlumon by two main factors: lack of data of visitor numbers and the possible unsuitability of visitor numbers as a method for estimating value (Table 28). No accurate figures for total trips to the Pumlumon project area were available, so an estimate based on supply side data (visitor accommodation) from 2002-2004 was used, giving a total of 180,000 (Montgomeryshire Wildlife Trust 2006; S. Hughes, pers. comm., 27 May, 2010). In the absence of more complete data this figure has been used for the pre-project and business-as-usual scenarios, although it is an underestimate because it does not account for all recreation trips. An increase in number of tourism trips to the project area of 5% over 5 years may be a reasonable estimate for the purposes of the scenario (Montgomeryshire Wildlife Trust 2006). As

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no other figures are available, this figure (189,000) was used for the Pumlumon project scenario, but is again likely to be an underestimate. Notably, our consultation with project representatives made it clear that the Pumlumon project aims to increase visitor spend rather than increase visitor numbers (SH) so our method would potentially also underestimate potential recreational values for that reason as well. Table 28. Calculation of WTP values for Pumlumon. Significance values provided by I. Thomas (Montgomeryshire Wildlife Trust) and adjusted hunting values provided by S. Hughes

Recreational activity

Literature WTP (£) -converted to current values

WTP value reference

Pre-project / business-as-usual significance value

Adjusted WTP value business-as-usual scenario (£)

Landscape significance value

Adjusted WTP value landscape scenario (£)

Walking 1.74 Bennett et al. (2003)

4 1.39 4 1.39

Horse riding 15.89 Christie et al. (2006)

3 9.53 3 9.53

Cycling 16.75 Christie et al. (2006)

3 10.05 3 10.05

Climbing 30.55 Hanley et al. (2002)

3 18.33 3 18.33

Nature-watching

8.84 Christie et al. (2006)

5 8.84 5 8.84

Boating, water sports

68.07 Hynes and Hanley (2006)

1 13.61 1 13.61

Fishing 8.80 Peirson et al. (2001)

3 5.28 4 7.04

Swimming Not available

1 1

Picnicking Not available

2 3

Pleasure driving

0 0

Air sports Not available

1 1

Camping Not available

3 3

Average overall WTP value (£):

Pre-project/ business-as-usual scenario:

9.58 Landscape-scale scenario:

9.83

Hunting 0 0

The recreation value increases under the landscape-scale scenario to £1,857,870 compared to the other scenarios (£1,724,440) as there is an expected increase in visitor numbers and the WTP value was slightly higher under the landscape scenario, due to an increase in significance rating of two of the recreational activities under this scenario. However, it should be noted, that the

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recreation numbers are likely to be underestimates due to the lack of available data on current and expected future numbers. Aesthetic There is a slight decrease in aesthetic value in the business-as-usual scenario compared to the pre-project scenario due to some areas of bog being replaced by acid grassland (which receives a lower aesthetic score). Under the landscape scenario there is an increase in aesthetic value of 1.5% compared to the business-as-usual scenario, mostly the result of an increase in dwarf shrub heath and broadleaved woodland (which both receive a higher aesthetic scores) compared to coniferous woodland, improved grassland and acid grassland. Summary: contrasting the ecosystem services for the scenarios

Table 29. Difference in overall value of ecosystem services in the Pumlumon project area. LS = Pumlumon project landscape scenario; BAU = business-as-usual scenario. The values are local values, for ecosystem services for which such values were available.

Difference in overall value for project area – local values

LS minus BAU LS minus Pre-project BAU minus Pre-

project Ecosystem service

Monetary (£)

% difference

Monetary (£)

% difference

Monetary

(£) % difference

Lamb 0 0.0 0 0.0 0 0

Beef 52,000 400.0 52,000 400.0 0 0

Timber -191,063 -34.4 -191,063 -34.4 0 0

Fresh water 0 0.0 0 0.0 0 0 Hydro-electricity 0 0.0 0 0.0 0 0

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Table 30. Difference in overall value of ecosystem services in the Pumlumon project area. LS = Pumlumon project landscape scenario; BAU = business-as-usual scenario. The values are standard values.

Difference in overall value for project area – standard values

LS minus BAU LS minus Pre-project BAU minus Pre-project Ecosystem service

Monetary26 (£)

% difference

Monetary5 (£)

% difference

Monetary5

(£) % difference

Crops -4947 -17.1 -4947 -17.1 0 0.0

Lamb 0 0.0 0 0.0 0 0.0 Beef 15,990 400.0 15,990 400.0 0 0.0

Timber -290,288 -34.4 -290,288 -34.4 0 0.0

Fresh water Standard values not available Hydro-electricity Standard values not available Carbon – Lower 123,800,610 22.6 111,973,922 20.0 -11,826,689 -2.1 Carbon - Central 247,601,221 22.6 223,947,843 20.0 -23,653,378 -2.1 Carbon - Upper 371,401,831 22.6 335,921,765 20.0 -35,480,066 -2.1

Aesthetic 0.11 1.5 0.10 1.3 -0.01 -0.2

Recreation 133,470 7.7 133,470 7.7 0 0.0

The business-as-usual (BaU) scenario assumes that replacement of bog with acid grassland will occur, and it is this change that is reflected in the substantial reduction in carbon when BaU is compared to the pre-project scenario. Projection of a business as usual future is more challenging than the landscape-scale future, because in addition to the uncertainties inherent in any future vision, in the BaU case there are no project visions or strategies to guide the scenario creation. The output for Pumlumon does however demonstrate that it is useful to explore these alternative scenarios, as the benefits, especially in the case of carbon, are more pronounced when the landscape vision scenario is compared to the alternative business-as-usual future due to likely degradation of habitat should land management continue as usual (Tables 29 and 30). For the Pumlumon landscape-scale scenario acid grassland, bog, heath, and broadleaved woodland are more prevalent than in the other two scenarios. There is also a decrease in improved grassland, fen, marsh and swamp, and coniferous woodland. The effects of this landscape change, aside from increases in carbon sequestration, are large increases in revenue from recreational use when comparing this scenario to the other two and a loss of revenue from timber. Due largely to the disproportionate effect of the valuation of carbon, the overall effect is for much higher values for ecosystem services in the landscape-scale compared to the other scenarios. Some big differences were evident in the valuation of some services such as food and timber when local and ‘standard’ values are used. The local values for cattle were much higher reflecting local market forces and premium meat from extensively grazed stock. 5.5.2.2 Ecological Impact Assessment

26 The values are monetary except for aesthetic, which are scores.

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The overall scores for the Pumlumon pre-project and business-as-usual scenarios are the same, as the only real difference between these two scenarios is a decrease in area of ‘blanket bog’ (by 270 ha) under the business-as-usual scenario compared to the pre-project scenario, but this is not enough to affect the score for this habitat type. The overall scores for the pre-project and business-as-usual scenarios are slightly higher (4.8 compared to 4.7) when England and Wales are used as the national resource rather than the UK. There is no difference in the score for BAP woodland whether scrub is included or not, as the area of scrub is too small to affect the score. Under the landscape scenario, there is a decrease in overall score compared to the pre-project and business-as-usual scenarios. This is because there are decreases in the area of ‘fens’ and ‘lowland dry acid grassland’ which have a large influence of the individual scores for these habitat types: the ‘fens’ score drops from 6 to 4 (-640 ha), and the ‘lowland dry acid grassland’ drops from 6 to 3 (-900 ha). Although there are also substantial increases in several BAP habitats under the landscape scenario, including ‘blanket bog’ (which replaces much of the ‘fens’ habitat), ‘upland heathland’ (which replaces much of the ‘lowland acid grassland’ habitat) and ‘BAP woodland’ the increases in scores are not as great as the decrease in scores. For example, although the area of ‘upland heathland’ increases by 1434 ha in the landscape-scale scenario compared to the pre-project and business-as-usual scenarios, the increase in score is only from 4 to 5 if the UK is used as the national resource, or 6 if England and Wales is used as the national resource. Further, although the area of ‘blanket bog’ substantially increases (1,375 ha in the landscape scenario compared to the business-as-usual scenario), this does not have any effect on the individual score, which remains as 4 under each of the scenarios. The area of BAP woodland also shows a large increase (4,982 ha) in the landscape scenario compared to the pre-project and business-as-usual scenario. However, if scrub is excluded, the score only increases from 4 to 5, or if scrub is included, from 4 to 6. There is also a slightly bigger difference in the overall scores for the landscape scenario depending on whether the UK or England and Wales are used as the national resource. Although there is a decrease in EcIA score in the landscape scenario compared to the pre-project and business-as-usual scenarios for Pumlumon, there is a substantial increase in the area of BAP habitat by 5,867 ha in the landscape scenario compared to the business-as-usual scenario (from 9,053 ha to 14,937 ha). The condition of many of the habitats is also likely to improve under the landscape scenario compared to the other scenarios.

5.5.2.3 Costs Set-up and average annual running costs of the Pumlumon project were provided by EB including extracts from a revised Business Plan (Bailey et al. 2010) (Table 31). Notably, during the consultation, EB stressed that a key benefit of the landscape-scale approach is to consolidate effort which should prevent lack of coherence and continuity in funding. Past lack of continuity has had a negative feedback effect, discouraging confidence in funding for specific works (EB). Sources of information and interpretation Annual running costs were provided separately for the first 5 years (2006-2010) as these were lower than the projected costs for the following 5 years. The annual running costs for 2011-2015 are based on a ‘Rolls Royce’ version of the project aspirations (EB). Details on funding were

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obtained from Bailey et al. (2010) and from discussions with case study representatives (5 May, 2010). It is difficult to estimate the future agri-environment scheme costs in Pumlumon as the current Welsh schemes are to be replaced by a new scheme, Glastir, in 2012. Without the Pumlumon project it is assumed that there would be roughly the same enrolment to Glastir as there currently is for Tir Gofal (approximately 25% of farms). However, the Pumlumon project will incentivise farmers to take up Glastir, and it is expected that uptake may increase to approximately 50%. As a rough estimate, it is assumed that this doubling will include some farms previously in schemes other than Tir Gofal, and the remaining farms will not be part of an agri-environment scheme (ELR). The area under each of the Tir Gofal payment rates was obtained from the Welsh Assembly (G. Aeron, Tir Gofal Senior Project Officer), the rates for mandatory habitats and public access obtained from the Welsh Assembly Government (2006) and the rates for capital works obtained from the Welsh Assembly Government (2005a). Total annual Tir Gofal costs were calculated by dividing the capital works payments by 5 to obtain an approximate annual figure, based on an average 5-year agreement. The annual mandatory habitats payments and permissive access payments were added to this. The area under each of the other agri-environment schemes (Tir Cynnal, Tir Mynydd, Organic Farming Scheme and Organic Maintenance Scheme) occurring in the project area were obtained from WAG (G. Aeron) and payment rates were also obtained from the WAG (Organic Centre Wales 2004; Welsh Assembly Government 2005b, 2009, 2010). The total value for agri-environment schemes was used for the pre-project and business-as usual scenarios. For the landscape-scale scenario, as Glastir payments are currently unknown, the value was estimated by doubling current Tir Gofal payments and excluding payments from other schemes (ELR). Hence, this is a very approximate figure27. Section 15 costs were obtained from C. Fielding (Countryside Council for Wales). These are relatively insignificant as a large proportion of the Pumlumon SSSI land is under Tir Gofal agreements, rather than section 15. It was assumed that Section 15 payments would be the same under the alternative scenarios (EB).

Table 31. Set up and running costs for conservation work in the Pumlumon project area. Total costs are indicated in bold, with composition costs listed below these. Costs Landscape-scale project (£) Pre-project/business-as-

usual (£) Set-up 253,000 Staff time to develop/scope project

48,000

Habitat restoration pilot project

10,000

Works on the ground 180,000 Fundraising 15,000

N/A

27Since estimation of the costs details of the Glastir scheme became available, but interpretation of the payments for this scheme, especially in the overlap period between Tir Gofal and Glastir are complex and not yet fully resolved (Ashbridge, Mangement matters: Glastir scheme leaves more questions than answers.August 2010 Framers Weekly).

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Average annual running 2006-2010 / 2011-2015

1,506,199 / 2,264,034 1,449,319

Pumlumon project costs – 2006-2010 / 2011-2015

76,000 / 833,836

-

Glaslyn Nature Reserve costs 0 (included in Pumlumon project costs)

1,000

Agri-environment schemes 1,429,129 1,447,249 Section 15 agreements 1,070 1,070

Landscape-scale set-up costs The Pumlumon project set-up costs are composed of staff time to develop the project, including investigating the feasibility, demonstrating the need, and producing a scoping report. This also involved running a habitat restoration pilot project and other works on the ground (such as ditch blocking and cattle grazing), as well as initial fundraising for the project. Landscape-scale running costs The Pumlumon project running costs are shown for the initial 5 years (up to 2010) as well as the expected average annual running costs from 2011-2015, which are much higher. The initial costs included administration costs/costs of hosting the project, plus employment of a Social Economist, Grazing Ecologist and People and Wildlife Officer from 2008 and additionally the employment of a Project Manager from 2009. From 2011, the Pumlumon project running costs are mainly composed of staff costs, administration and financial management, marketing and fundraising, habitat restoration and creation and flood water management. Pre-project and Business-As-Usual running costs Under a pre-project/BAU scenario, the running costs in the project area are the agri-environment scheme and Section 15 payments as well as minimal maintenance costs for the Montgomeryshire Wildlife Trust Glaslyn Nature Reserve (EB). Sources of funding for the landscape-scale initiative Funding for the Pumlumon project comes from numerous sources (Bailey et al. 2010):

• Waterloo Foundation charitable trust: for staff time, habitat management / restoration work - ditch blocking for carbon safeguard (£30,000 per year for 5 years)

• JP Getty: employment of a Social Economist to plan and test the valuation of new markets and engage with local businesses (£30,000 per year for 3 years).

• Biffa Award: for habitat works for flood amelioration and landowner liaison (£45,000 per year for 3 years).

• Varying levels of year on year financial support from Countryside Council for Wales and Environment Agency for capital works: habitat restoration, ditch blocking and staff time.

• In kind support from the Forestry Commission.

• Rural Development Plan (RDP) funding from Glasu (Powys County Council) for 1 year projects for hydrology monitoring, Audio Trail / e-trail and Low Carbon Bus feasibility study.

• Strategic Development Fund (SDF), The Wildlife Trusts (2010) for 1 year to employ a Project Manager.

• Communities and Nature (CAN) programme (Welsh European Funding Office) for the Dyfi Osprey Project: 4 year project worth £240,000 includes match funding from other sources, i.e. SDF - £22,000.

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Running costs (excluding employment) for 2006-2010 were also given as match funding by Montgomeryshire Wildlife Trust (EB).

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5.6 Frome catchment

5.6.1 Creating scenario maps

The scenarios for this case study were developed in collaboration with an EU research project Transactional Environmental Support Systems (TESS28) which includes a case study focussed on the River Frome catchment. This part of the TESS project aims to explore perception of ecosystem benefits across local communities and determine whether these benefits are delivered through implementation of an existing regional strategy, the South West Nature Map which was developed from the Rebuilding Biodiversity methodology (Brenman 2005). Rebuilding Biodiversity was developed by the Wildlife Trusts and “is an innovative approach to defining a set of ecologically functional units at a landscape-scale, called Strategic Nature Areas, which together can provide the minimum space needed to conserve key habitats and species across the South West region in the long term. The methodology combines a robust regional framework with the expertise of local people, and provides a means for selecting and prioritising Strategic Nature Areas where habitat restoration should happen in the future, to achieve the best environmental return for the optimum investment of resources.”(Brenman 2005). For the purposes of the study, it was assumed that the objectives for restoration of priority habitats, expressed in the nature map strategy, were realised in the future scenarios. Although locally implemented nature conservation actions were guided by the nature map strategy, there was no source of information that could be used to map a future landscape in relation to these local schemes. Instead, the strategy document (Brenman 2005) was used to guide development of future scenarios based on expanding existing priority habitats. Four scenarios were developed for this case study, pre-project and three landscape-scale scenarios based on interpretations of the Nature Map. There was a large number of existing conservation projects in the area, some of which are well established and long-running, and which also have a landscape-scale component. It was therefore, inappropriate to attempt to visualise a future ‘business-as-usual’ scenario. Pre-project scenario This was based on current land cover, as determined by the remotely sensed CEH Land Cover Map 2000 using the Level 3 land cover classifications (LCM2000). Landscape-scale scenarios (LS_30; LS_60; LS_30-60) The LCM2000 map was modified to reflect the biodiversity restoration targets of the Strategic Nature Areas (SNAs) of the South West Nature Map. The SNAs had associated targets of a minimum area of restoration of target habitat to increase the overall area and produce a viable and less fragmented landscape (Brenman 2005). There were 23 SNAs in the Frome catchment area and the target habitats and number of SNAs for each were: grassland (11), lowland heath (4), woodland (4), coastal and floodplain grazing marsh (2), neutral grassland, woodland, purple moor grass and rush pasture (1) and woodland, neutral grassland, fen (1) (Brenman 2005). Land cover conversions were simulated by extending existing habitat patches in a GIS buffering process. In this process, it was assumed that any land cover in the SNAs could potentially be

28

http://www.tess-project.eu/

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converted into the Nature Map priority habitats calcareous grassland, heathland or woodland, with the exception of inland marsh and saltmarsh (due to the high hydrological costs). The process also excluded a number of habitats that would be unsuitable for conversion: continuous urban, littoral sediment, suburban / rural developed and inland water. The assumption was made that the SNAs were from the strategic map were placed in areas with suitable abiotic conditions for conversion to the target habitats. Three scenarios were modelled in GIS by extending buffers from existing habitat patches until specified increases in habitat were achieved. These increases in area were set to reflect the aspirations of the SW Nature Map. In this, habitats are differentiated into matrices and patch forming. Matrices have a target of 60% priority habitat in each SNA and patch-forming habitats have a target of 30% plus 30% of other priority habitats (see Brenman 2005, p.43 and Appendix 2). These targets were reflected in the modelling using the following rules:

i) 30% of the area of each SNA encompassing the target habitat; (LS_30)

ii) 60% of the area of each SNA encompassing the target habitat; (LS_60)

iii) a combination of 30% and 60% based on the Rebuilding Biodiversity manual (p.43)

(Broad-leaved / mixed woodland, 30%; Fen, marsh, swamp, 60%; Neutral grassland,

30%; Calcareous grassland, 60%; and Dwarf shrub heath, 60%). LS_30-60

Prior to the buffering, it was necessary to align the LCM 2000 types to the Nature Map habitats types in each SNA (Table 32). Table 32. Alignment table between LCM 2000 types and Nature Map habitats used in the modelling process of the SNAs. N/A denotes land cover types excluded from the buffering process. LCM 2000 types Nature Map habitats Acid grassland Acid grassland Arable cereals Arable land Arable horticulture Arable land Arable non-rotational Arable land Broad-leaved / mixed woodland Woodland Calcareous grassland Chalk grassland Coniferous woodland Coniferous Continuous urban N/A Dense dwarf shrub heath Lowland heath Fen, marsh, swamp Purple Moor Grass and Rush Pasture/Inland marsh Improved grassland Improved grassland Inland bare ground Bare-ground Littoral sediment N/A Neutral grassland Neutral grassland Open dwarf shrub heath Lowland heath Saltmarsh Saltmarsh Set-aside grassland Set-aside grassland Suburban / rural developed N/A

Water (inland) N/A

In order to reach the 30% and 60% targets within each SNA, new areas of the target habitat were created by buffering around the existing target habitat areas. For example, in chalk

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grassland SNAs, the existing calcareous grassland areas were buffered until the area covered by calcareous grassland was 30% or 60% of the total SNA area. The process was iterative; using increasing buffer distances and dividing the difference between the simulated target area and the expected target area each time until the percentage increase in are was within 0.1% of the target. In the case of an SNA with a mosaic of target habitats, the targets of 30% and 60% were equally split between the habitats. For example, in a SNA with three target habitats (Woodland, Neutral Grassland and Fen) the target of 30% was achieved by extending each of these three habitats by 10%. Modelling SNAs with a mosaic of habitats was more complex and involved buffering the minority habitat before the others to avoid its fragmentation. The modelling was necessarily a simplification of any practical implementation of the SNA goals, and interestingly, the research demonstrated a lack of locally applicable spatial data of sufficient completeness to fine-tune the model. There were also issues of spatial compatibility of existing data sets from different sources. For instance, the possibility was considered of avoiding the conversion of any existing BAP priority habitats not included in the SNA target by excluding these from the buffering process. However, the spatial data on BAP habitats available from Natural England was incomplete and did not align with the LCM2000 map. Other possibilities for fine-tuning included plans for local implementations, such as the RSPB Habitat Re-creation Opportunity Mapping (RSPB, 2004). These were considered for incorporation into the modelling but they were found covering only a small part of the SNA with a mosaic of habitats. So their inclusion was not feasible. The Wareham managed realignment case study (Eftec, 2007) was also considered to inform the modelling of saltmarsh expansion. However, the scenarios in this document where new saltmarshes were proposed (i.e. ‘Do Nothing’ and ‘Do Minimum’ scenarios) suggested the erosion of the existing saltmarshes. Therefore, no net saltmarshes expansion was foreseen. Based on this consideration, and also taking into account that saltmarshes cover only 0.026 % of the catchment area, it was agreed to exclude saltmarshes from the scenarios modelling. Characteristics of the scenarios for the Frome catchment As the modelling of the target habitat restoration in the Strategic Nature Areas was based on the buffering and increase of target habitats, these increases are inevitably expressed in the scenarios produced. So there are several substantial changes in areas of the different habitats under the landscape-scale scenarios compared to the pre-project scenario. There are large increases in calcareous grassland, heath, fen marsh and swamp and neutral grassland, which largely replace the arable, horticultural and improved grassland habitats (Table 33 Figure 8).

The main difference between the three landscape scenarios compared to the pre-project is a significant decrease in the amount of arable land and improved grassland with some decline also seen in acid grassland, coniferous, broadleaved and mixed woodland. This is contrasted by an increase in calcareous grassland, dense dwarf shrub heath and fen, marsh and swamp. There is a slight increase in broadleaved woodland in the 60% scenario compared to the pre-project scenario, mainly replacing improved grassland.

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Table 33. Area of habitat types in the Frome catchment under alternative scenarios and change in area between the scenarios. PP is Pre-Project, BAU is Business-as-Usual, LS is Landscape-Scale scenario and shaded cells accentuate increases in habitat area.

Area (ha) in case study site Difference in area (ha)

Habitat type PP LS 30%

LS 60%

LS 30/60%

LS 30 - PP

LS 60 - PP

LS 30/60 - PP

Acid grassland 460 397 218 220 -63 -242 -240 Arable and horticultural 20396 18028 14545 15110 -2369 -5852 -5286

Broadleaved woodland 3831 3756 3985 3058 -75 154 -773

Calcareous grassland 1219 4512 8363 8401 3293 7144 7182

Coniferous woodland 1726 1397 735 821 -329 -990 -905

Built-up areas, gardens 1830 1830 1830 1830 0 0 0

Dwarf shrub heath 2073 2779 4757 4760 706 2685 2687

Fen, marsh, swamp 103 1239 2432 2432 1136 2329 2329

Improved grassland 15674 13063 9807 10588 -2611 -5867 -5086

Inland rock 592 425 246 250 -167 -346 -342

Littoral sediment 59 59 59 59 0 0 0

Neutral grassland 295 773 1281 730 478 986 435

Standing water/canals 38 38 38 38 0 0 0

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5.6.2 Evaluating the costs and benefits for the Frome catchment

As the scenario building process for this case study was based on a regional strategy, rather than project plan, the valuation was more reliant on published ‘standard’ values than the other case studies. Some local consultation was used where possible, for instance, to inform the timber valuation and for the adjustment of recreational values. 5.6.2.1 Ecosystem services Crops and livestock Recorded or predicted crop and livestock products (meat and dairy) were sourced from the ‘Nix pocketbook’ (Nix 2010). Ideally, locally available prices and production costs of these services would have been used but it was not possible to get comprehensive local data for all the necessary parameters. The method therefore uses the net standard values in the Nix pocketbook, giving a generalised estimate, which has reduced accuracy, but retains relevance for comparisons of relative values between scenarios. The net values (after costs) were used to convert production to monetary value as this provides the most up to date and comprehensive values currently available for this purpose. The proportion of land given over to each crop or livestock type was obtained for the area using Agricultural Census data for the selected relevant catchments in Dorset, supplied by the Farming Statistics Branch, York. An overall crop net value per hectare was determined by calculating a weighted average (by proportion of each crop). A total value of crops for the project area was obtained by multiplying the total number of hectares of arable land (all LCM 2000 arable classifications) under the pre-project scenario, by the overall per hectare values. Arable crops in the scenarios were assumed to be present in the same proportion as in the current pre-project so that value was only altered by land cover change. The feasibility of calculating crop values in future scenarios relies on a number of simplifications, mainly being the assumption that everything else in the scenario remain the same as in the original state, except for the land cover change. Crop value was mapped in GIS by applying the weighted average value per unit of arable land for three types of arable land: cereals, horticulture, fallow. This is a simplification of the distribution of crop value, which in reality would vary across the landscape depending on which crops were planted where. However, as crops are often planted on rotation and no information was obtained from local farmers giving details of what crops were planted where, an average value was used based on the proportion of each crop (using Agricultural census data) and standard Nix values. The proportion of land in the pre-project state dedicated to livestock production was calculated by dividing the total number of individuals of each livestock type (adjusted from the numbers given in the Agricultural Census data in order to fit the study area boundary) by the standard stocking densities given in the Nix pocketbook. A total monetary value for livestock production in the study area under each scenario was obtained by multiplying the total number of each livestock type by the standard net price per animal. This total value for the study area was then divided by the total number of hectares in which the livestock occur under each scenario, as calculated from the Census data, to obtain a value per hectare. It was assumed that the same proportion of available land would be used for livestock production in each of the future landscape scenarios. As future livestock numbers are not known for certain, the stocking density was multiplied by the adjusted proportion of land available to determine the number of individuals and the total value for each future scenario.

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Since no data was available on the actual location of the farms (due to data protection restrictions) it was not possible to accurately pinpoint the likely locations of each livestock type. It was therefore assumed that livestock are able to roam freely within the farmland and therefore, the amount of land actually available to livestock could be represented by the total area of improved grassland for each scenario land cover. Values per hectare were calculated by dividing the total value of each livestock type by the area of improved grassland and summing these values to give a total value per hectare. This was distributed evenly across the improved grassland to generate a GIS map of livestock value. Food value estimated for the landscape scenarios was discounted at 0, 0.5, 3 and 10% for comparative purposes (Table 34). Table 34. Standard annual harvest values for food at 0% discount rate.

Overall value for project area – standard values (£)

Ecosystem service PP LS_30 LS_60 LS_30-60

Arable crops 8,734,874 7,720,518 6,228,820 6,471,001

Livestock production 9,061,469 7,560,639 5,681,442 6,131,706 Arable crops Due to the conversion of arable land to other land cover types, the production of crops was greatly reduced in all landscape scenarios, with significant declines from 12%-29%. This loss of value from crop production represents an opportunity cost of the landscape scenarios as the landowners would suffer the cost of loss of income from this landscape change. Livestock production There is a decrease in production of dairy products and beef, lamb and pork under both all the landscape scenarios compared to the pre-project scenario due to a decrease in available grazing land. Significant declines of 17%-37% are estimated suggesting a high opportunity cost to landowners in this area. Timber For timber, the Forestry Commission29 provided cumulative yield per hectare (m3) values for generalised broadleaved and conifer production using their 'Forest Yield' software, which is based on 'Yield models for forest management' (Edwards & Christie 1981). Oak and birch were used to model the broadleaf yields and Sitka spruce for conifer. The cumulative yield approach is more realistic than using volume at clearfell, because it takes account of overall extraction throughout the rotation, including the value of timber removed through thinning. The average standing sale price for broadleaves and conifers, provided by the Forestry Commission30, was then used to calculate a monetary value per hectare. It can be interpreted as a net value; although the planting costs are not included, this is offset by the sale as a standing crop. Values for current timber harvest are £108.89/ha/yr for coniferous, £51.04/ha/yr for broadleaved forest and £77.74/ha/yr for mixed forest based on cutting cycles of 60, 70, 65 years respectively. Local yield data was supplied by Dr Michael Mdeze of the Forestry Commission office in Lyndhurst, Hampshire (MM). Conifer plantations in the catchment provide an average volume per hectare of 500 m3 yielding 12 m3 per annum under cumulative felling. A standard thin will

29

Ewan Mackie, Centre for Forest Resources and Management, pers. comm., 27 May, 2010 30 Charene Winbow, Sustainable Forestry and Land Management Team, pers. comm., 24 May, 2010

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remove 70% of the annual increment (8.4 m3) at 5 year intervals. Assuming an area of woodland is thinned 5 times before final clearfelling this would give a total volume of 710 m3 (MM). The current average price for conifers is £11.00 per m3 (MM). Broadleaves yield about 3 m3 per annum, on a 10 year cycle (MM). Assuming thinning occurs over a period of 50 years, this would give a total volume of 120 m3. The average price for Broadleaves is £9.50 / m3 (MM). Values for current timber harvest using this local data are £92.40/ha/yr for coniferous, £28.50/ha/yr for broadleaved forest and £58.43/ha/yr for mixed forest based on cutting cycles of 5 and 10 years respectively. Timber yield varies widely due to extraction or production variation between years and between sites. A more comprehensive survey of woodland data would be needed for a more accurate representation. However, for the purposes of this study, the information provided is sufficient to estimate an average value for the study area. The location of Forestry Commission land was provided in GIS format by the Forestry Commission so that values could be applied spatially. The type of forest (broadleaved, conifer or mixed) was determined by overlaying the LCM 2000 land cover layer. Values per hectare were calculated for the three categories. Timber value did not vary between scenarios because the area of Forestry Commission land remained unchanged and there was no significant change in the forest types under each FC land parcel (Table 35). Table 35. Annual value of timber harvest based on average cutting cycles for broadleaved, mixed and coniferous woodland.

Overall value for project area – local values (£)

Ecosystem service BAU LS_30 LS_60 LS_30-60

Timber 91,449 91,449 91,449 91,449

Overall value for project area – standard values (£)

Ecosystem service BAU LS_30 LS_60 LS_30-60

Timber 113,669 113,669 113,669 113,669 Carbon The land cover categories in each scenario were reclassified where necessary to align with carbon values for above and below ground carbon storage capacity for different land-cover types assessed in Cantarello, Newton & Hill, in press. There is an increase in carbon value under all of the landscape scenarios compared to the pre-project scenario, mainly due to the significant replacement of arable land (which has a relatively low carbon storage capacity of 66.3 Mg/ha) by natural grasslands, heath land and fen/marsh/swamp (in this case purple moor grass and rush pasture) with storage capacities of 123.9 Mg/ha, 110.0 Mg/ha and 160.5 Mg/ha respectively. There is a substantial difference between the monetary value of carbon depending on whether the upper, central or lower value is used. For example, there is a difference of over £31 million between the upper and lower values when calculating the difference between the 30% landscape scenario and the pre-project scenario, demonstrating the effect that using different monetary values can have (Table 36).

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Table 36. Values for carbon in the Frome catchment scenarios.

Overall value for project area

Ecosystem service PP LS_30 LS_60 LS_30-60

Carbon storage (Mg) 4,920,848 5,146,330 5,383,623 5,249,236 Carbon storage - Lower (£) 475,436,596 491,363,940 514,009,308 501,200,181 Carbon storage - Central (£) 950,873,191 982,727,879 1,028,018,616 1,002,400,362 Carbon storage - Upper (£) 1,426,309,787 1,474,091,819 1,542,027,924 1,503,600,542 Marginal value – Lower (£) 15,927,344 38,572,712 25,763,585 Marginal value – Central (£) 31,854,688 77,145,425 51,527,171 Marginal value – Upper (£) 47,782,032 115,718,137 77,290,756 Flood mitigation The Frome case study site is the catchment of the River Frome. It contains several built up areas, parts of which fall within flood risk zones. There are several substantial changes in areas of the different habitat types in Frome under the landscape scenarios compared to the pre-project scenario. There are large increases (greatest in the 60% scenario) in calcareous grassland, dwarf shrub heath, fen marsh and swamp and neutral grassland, which largely replace the arable and horticultural and improved grassland habitat types. These more ‘natural’ habitats are typically much less susceptible to high rates of runoff than crops, due to the degree of protective coverage the foliage provides, the impacts of agricultural practices on soil structure and infiltration rates, the time at which machinery is required on the land, and the effects of agricultural practices on the concentration of flow (O'Connell et al. 2004). Restoration of the natural storage capacity of these soils should mitigate surface runoff and any increase in storage within the catchment would be expected to reduce flood generation and flood hazard. However, the extent of the reduction would be dependent on the amount of storage provided (O'Connell et al. 2004), and it is not yet known the extent to which the Frome landscape scenarios will be realised. Another factor, related to these habitat changes, is potential reduction in compaction by grazing livestock under the landscape scenarios. The stocking levels for the alternative scenarios are not known, but treading by livestock is known to cause soil compaction which can lead to increased surface runoff (O'Connell et al. 2004). Another difference in landcover between the scenarios is loss of acid grassland under each of the landscape scenarios, which is largely replaced by dwarf shrub heath. This may have a positive effect on flood mitigation, as heathland vegetation is likely to be taller and tall vegetation generally intercepts more rainfall and there is therefore likely to be less rapid surface runoff (Calder et al. 2002; Gilman 2002; Orr & Carling 2006).

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There are also large losses of coniferous woodland, which is generally replaced by dwarf shrub heath and some broadleaved woodland under the 60% scenario. However, there is loss of broadleaved woodland under the 30% and 30/60% scenarios, where it is partly replaced by dwarf shrub heath. Peak flows are generally reduced under mature forests compared to heathland, due to increased evaporation losses and the increased water storage capacity of soils under trees (Calder et al. 2002; Gilman 2002). However, it is likely that any negative impacts of this would be offset by the larger changes in the replacement of arable land with more ‘natural’ habitat types described above. Recreation The recreational value increases by 74% under the landscape scenarios compared to the pre-project scenario due to a significantly higher willingness-to-pay value for this scenario as a result of the improvements to the aesthetic value of the area (Table 37). No change in visitor numbers was predicted under the landscape scenarios as data provided could not be used with confidence to estimate what this might be. This value is therefore likely to be an underestimate of the true value of tourism and recreation in the landscape scenarios as visitor numbers are likely to increase up to a threshold level at which point they may stabilise.

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Table 37. Significance values provided by (A. Pollard, Mid Dorset Area Manager, Dorset Wildlife Trust, 10 March, 2010). Recreational activity

Literature WTP (£) -converted to current values

WTP value reference

Business-as-usual significance value

Adjusted WTP value business-as-usual scenario (£)

Landscape significance value

Adjusted WTP value landscape scenarios (£)

Walking 1.74 Bennett et al. (2003)

2 0.70 5 1.74

Horse riding 15.89 Christie et al. (2006)

3 9.59 5 15.89

Cycling 16.75 Christie et al. (2006)

3 10.05 5 16.75

Climbing 0 0

Nature-watching

8.84 Christie et al. (2006)

3 5.30 5 8.84

Boating, water sports

68.07 Hynes and Hanley (2006)

2 27.23 4 54.46

Fishing 8.80 Peirson et al. (2001)

4 7.04 4 7.04

Swimming Not available

1 1

Picnicking Not available

3 4

Pleasure driving

0.97 Hanley (1989)

3 0.58 3 0.58

Air sports Not available

1 1

Camping Not available

2 4

Average overall WTP value (£):

Business-as-usual scenario:

8.64 Landscape-scale scenario:

15.04

Hunting Bullock et al. (1998)

4 £329.65 4 £329.65

An estimate of the annual visitor numbers to the project area were made based on the State of Tourism 2001 report (South West Tourism, 2001). Data on the total number of staying visitor nights and day visits were available for each district within Dorset. Data was extrapolated from the West Dorset and Purbeck districts as the Frome catchment boundary incorporates these districts. On average, staying visitors spent 4.4 nights. An assumption was made that they spent one day doing one of the recreation activities listed in Table 37, so only the total number of visits were counted, rather than visitor nights. This is likely to provide an underestimate of staying visitor numbers for recreation. In addition, all the day visits that were attributable to ‘countryside’ visits were counted. Visitor numbers for the business-as-usual scenario were estimated at 2,167,588 per year. As no reliable data was available to predict tourist numbers

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under the three scenarios, tourist numbers were assumed to be the same with or without the project. Hunting (shooting of deer and birds) was valued separately, because the average value obtained from the literature for hunting was £329.65 per trip, which was significantly greater than the values obtained for any of the other activities (£1.74 - £68.07). Data for annual hunting visits was not available at the close of the project. This may be of little importance as no change in the significance value of hunting between the pre-project and landscape scenarios was predicted (A. Pollard, pers comm. 10 March, 2010). The overall recreational value for each scenario was obtained by multiplying the number of visits by the WTP value per trip, and summing for general recreation (Table 39). Table 39. Recreation values for the Frome catchment

Overall value for project area – standard values (£)

Ecosystem service Pre-project Landscape scenarios31

General recreation 9,829,970 17,111,429 All landscape scenarios had higher scores that the pre-project scenario. The highest aesthetic score is obtained for 60% landscape scenario. This is largely due to the replacement of improved grassland with broadleaved woodland, which has a slightly higher aesthetic score and the greatest area of neutral grassland in this scenario (Table 40). Table 40. Aesthetic values for the Frome catchment

Overall value for project area – standard values (£)

Ecosystem service PP LS_30 LS_60 LS_30-60

Aesthetic 6.09 6.25 6.49 6.46

31 This value is the same for all three landscape scenarios (LS_30, LS_60), LS_30-60) as the scoping study did not provide data based on the different targets.

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Summary: contrasting the ecosystem services for the scenarios Table 41. Difference in overall value of ecosystem services in the Frome catchment project area. LS = landscape scenario; PP = pre-project/current scenario. The values are standard values at 0% discount rate.

Difference in overall value for project area – standard values

LS_30 minus PP LS_60 minus PP LS_30-60 minus PP Ecosystem service

Monetary32 (£)

% difference

Monetary1 (£)

% difference

Monetary1

(£) % difference

Carbon – Lower 15,927,344 3.4 38,572,712 8.1 25,763,585 5.4 Carbon - Central 31,854,688 3.4 77,145,425 8.1 51,527,171 5.4 Carbon - Upper 47,782,032 3.4 115,718,137 8.1 77,290,756 5.4

Aesthetic 0.16 2.7 0.40 6.6 0.37 6.0

Recreation 7,281,459 74.1 7,281,459 74.1 7,281,459 74.1

Hunting 0 0 0 0 0 0

Arable crops -1,014,356 -11.6 -2,506,055 -28.7 -2,263,873 -25.9

Livestock -1,500,830 -16.6 -3,380,027 -37.3 -2,929,763 -32.3

Timber 0 0 0 0 0 0 TOTAL (using central carbon value) 36,620,961 3.7 78,540,802 8.0 53,614,994 5.5

5.6.2.2 Ecological Impact Assessment The habitat was classified using the broad habitats of the CEH LCM2000, and some of these incorporated several BAP habitats so conversion to BAP classifications required by this analysis was achieved by using Natural England boundaries of BAP habitats to identify relevant areas by overlay on the LCM 2000 land cover. A number of assumptions were necessary when calculating the EcIA due to differences in the LCM and BAP habitat classifications. For instance, any new broadleaved woodland was classed as BAP deciduous woodland and the LCM habitat ‘fen, marsh and swamp’ incorporated three BAP habitats (‘Fens’, ‘Purple moor grass and rush pasture’, and ‘Reedbeds’). Only ‘Purple moor grass and rush pasture’ was increased in the ‘Rebuilding Biodiversity’ project (see Table 1 in Brenman 2005), so any increase in the future scenarios was allocated to this BAP habitat. The overall score increases in each of the landscape scenarios (where the score ranges from 5.1 to 5.3) compared to the pre-project scenario (which scores 4.3 or 4.4 depending on the definition of national resource). There is a substantial increase in overall area of BAP habitat, of 5475 ha in the 30% landscape scenario compared to the pre-project scenario, and 13055 ha in the 60% landscape scenario. The 60% and average 30/60% scenarios achieve a higher score than the 30% scenario and the scores for all three landscape scenarios are higher when England and Wales are used as the national resource instead of the UK.

32 The values are monetary except for aesthetic, which are scores.

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The increase in overall score under the landscape scenarios is due to an increase in the individual scores, particularly for ‘lowland meadows’ and ‘purple moor grass and rush pastures’ which both increase from 2 (parish importance) to 6 (national importance). Note that this was based on the assumptions that ‘new’ areas of the corresponding Land Cover Map habitat type would be composed of these BAP habitat types. The other increases in individual scores are for ‘lowland calcareous grassland’ and ‘lowland heath’, which increase from 6 (national importance) in the pre-project scenario to 7 (international importance) in the 60% and average 30/60% landscape scenarios. ‘Lowland calcareous grassland’ also shows the greatest increase in extent, of 7182 ha under the 30/60% landscape scenario compared to the pre-project scenario. Different individual scores are obtained for ‘reedbeds’ depending on whether the national resource figures are for the UK or England and Wales, with the latter achieving a higher score (6 compared to 5). 5.6.2.3 Costs Costs for the scenarios include production costs, conservation project implementation and running costs and opportunity costs. The estimation of costs needs to be addressed using a variety of approaches because some are closely associated with services and others apply across the site. Production Costs Production costs have been subtracted from the market price values for benefits which are valued using this approach (e.g. food, timber). All ecosystem service values to which this applies are therefore presented as net values. Implementation and running costs Pre-project scenario In the pre-project scenario, these were estimated using the agri-environment schemes (AES) present in the region. It is recognised that additional work by conservation organisations and local authorities occurs in the region; however, identifying costs attributable to practical conservation work from these grant budgets was too complex, and so this factor had to be excluded from the analysis. Spatial data showing the location of current schemes was obtained from Natural England (downloaded 6 September 2010) and clipped to fit the Frome study area boundary. The total cost of AES in the study area for current schemes (which span 5-15years depending on the scheme type) is £18,160,200, covering 37,170ha. As an average annual cost, this would be £2,095,962 for the catchment, or £63.68 ha-1yr-1. Landscape-scale scenarios For the three landscape scenarios, project implementation and running costs were based on the area of BAP habitat types that were predicted to be restored under a ‘rebuilding biodiversity’ scenario following Brenman 2005. Using GIS, the increase in area of each BAP habitat was calculated between each landscape scenario and the pre-project map (Table 42). Table 42. Increase in area of BAP habitats in each of the landscape-scale scenarios for the Frome catchment. . Increase in area of BAP habitat (ha)

LCM category BAP habitat type LS_30 LS_60 LS_30-60

Broad-leaved / mixed woodland

Native deciduous woodland 154

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Calcareous grassland Lowland calcareous grassland 3,293 7,144 7,182

Dense dwarf shrub heath Lowland heathland 706 2,684 2,687

Fen, marsh, swamp Purple moorgrass and rush pasture 1,136 2,329 2,329

Neutral grassland Lowland meadows 478 986 435 Total 5,613 13,297 12,633 Useful guides exist in the literature to enable estimation of the costs associated with habitat restoration. For instance, the Environment Group (2004) outline the different types of site management costs considered in their economic assessment of the costs and benefits of Natura 2000 sites in Scotland. However, these costs are site-specific. Therefore, details on implementation and running costs for the landscape scenarios would ideally be sourced from projects carried out inside the study area. As this information was not available, a recent BAP document was used as a reference guide: the “UK Biodiversity Action Plan: Preparing Costings for Species and Habitat Action Plans” (Rayment 2006). The costs presented in this document are considered suitable as they refer to the total costs of delivering Habitat Action Plans (HAPs) rather than estimates of additional costs relative to existing expenditures. Costs reported are attributable to the BAP itself, and its targets and actions, rather than other legislative drivers or costs incurred as part of the core duties of the conservation agencies. They also include the costs of land purchase where necessary as well as net costs of actions. The costs summarise information given by the lead partner and country leads for each HAP, supplemented by reviews of published information (including agri-environment and forestry grant schemes and habitat restoration and re-creation projects). The estimated figures may include opportunity costs where these are reflected in grant rates and land purchase costs and values are expressed in 2005/06 prices (Rayment 2006). The per hectare costs derived from Rayment 2006 were applied to the area of each land cover type re-established in each scenario, the method assumes that re-establishing BAP habitats on private farmland under the AES costs the same to implement as re-establishing these habitats outside of AES. This assumption may of course be invalid, as payments for AES often incorporate some compensation for opportunity costs in addition to implementation costs. The estimation of costs found below may therefore be an overestimate. Assuming that the area of current BAP habitats is in good condition, and requires no additional implementation or management costs, costs for restoration in these areas were not considered. Re-establishment and expansion costs along with annual management costs as estimated in Rayment 2006 were used as shown in Table 43. The mean cost for re-establishment of the target habitat types (excluding the one-off capital cost) was estimated as £298 ranging from £275 for native woodland to £450 for heathland. Table 43. Per hectare costs associated with conservation actions on BAP habitats (Rayment 2006).

Unit costs of implementation (£)

BAP habitat type Re-establishment/Expansion

Native deciduous woodland £1500/ha capital grant

plus £200/ha/yr for 10 years

Lowland calcareous grassland £725/ha capital cost

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plus £280/ha/yr

Lowland heathland £350/ha capital cost

plus £450/ha/yr

Purple moorgrass and rush pasture £495 capital costs/ha +

£280/ha/yr

Lowland meadow £561 capital costs/ ha + £280/ha/yr

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Table 44. Costs of conservation actions associated with each of the landscape scenarios in the Frome catchment

Cost for landscape scenario (£)

BAP habitat type LS_30 LS_60 LS_30-60

Native deciduous woodland 30,832

Lowland calcareous grassland 922,039 2,000,348 2,011,009

Lowland heathland 317,700 1,207,800 1,209,150

Purple moorgrass and rush pasture 317,975 652,045 652,045

Lowland meadows 133,951 276,012 121,702

Total annual cost 1,691,664 4,167,037 3,993,907

Capital cost 3,465,036 8,055,843 7,544,090

Sum (annual+capital) 5,156,700 12,222,880 11,537,997 Summary of costs Table 45. Estimated conservation costs for the scenarios for the Frome case study. The costs are based on a single year of implementation. Costs LS_30 (£) LS_60 (£) LS_30-60 (£) Pre-project

(£) Set-up* 3,465,036 8,055,843 7,544,090 N/A Estimated annual running 3,787,626 6,262,999 6,089,869 2,095,962 Management of existing habitat

2,095,962 2,095,962 2,095,962 2,095,962

Restoration 1,691,664 4,167,037 3,993,907 * capital costs including land acquisition and one-off grants under AES

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5.6.2.4 Functional Connectivity in the Frome Catchment The connectivity modelling entailed the use of focal species, following Catchpole (2006), with three estimated dispersal distances and also estimates of landscape permeability. The need for this approach highlights the knowledge gap on species dispersal abilities and the function of the landscape matrix at the species level. Nevertheless, the modelling enables a comparison of the scenarios and particularly of the way in which the relative expansion of one habitat affects the connectivity of the other habitats. Although, in this case, the scenarios were based on a hypothetical interpretation of the SW biodiversity strategy this approach would merit further application to aid priority setting and planning at the landscape level. Maps of the habitat networks created for woodland, grassland and heathland focal species showed a visible difference between the connectivity when comparing the scenarios (Figures 9-11). However, the three dispersal levels that were applied caused little difference between the measures of connectivity. A smaller number of networks indicated greater connectivity. For woodland species, interestingly, although the sum of area of networks was smaller in the restored scenarios, the maximum area was much larger and the number of networks reduced. In other words, connectivity appeared improved. The 30-60 scenario was less favourable for woodlands as this modelling favoured other habitats e.g. chalk grassland (60%) at the expense of woodland (30%). Probably for the same reason, the grassland and heathland species had the lowest number of networks in the combined 30-60 scenario, in other words connectivity was enhanced in these habitats reflecting the modelling method. The metrics of sum of area, and maximum area of networks, also increased in all the future scenarios for these two habitats and was greatest in the 30-60% scenarios.

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Table 46. Metrics of the individual networks generated for woodland species under the present

and the three future scenarios (i.e. 30%, 60% and 30-60%) for three dispersal distances (500m,

1000m and 2000m).

Max dispersal distance 500 m

Current 30% 60% combined 30-60%

Number of networks: 759 712 671 741 Minimum area (ha): 0.01 0.01 0.01 0.01 Maximum area (ha): 106 216 598 162 Sum area (ha): 4589 4419 4471 3190 Mean area (ha): 6.05 6.21 6.66 4.30 Standard Deviation (area): 10.2 13.1 27.3 9.97 Max dispersal distance 1000 m

Current 30% 60% combined 30-60%

Number of networks: 759 712 670 741 Minimum area (ha): 0.01 0.01 0.01 0.01 Maximum area (ha): 106 216 598 162 Sum area (ha): 4590 4420 4471 3190 Mean area (ha): 6.05 6.21 6.67 4.30 Standard Deviation (area): 10.2 13.1 27.3 9.97 Max dispersal distance 2000 m

Current 30% 60% combined 30-60%

Number of networks: 759 712 671 741 Minimum area (ha): 0.01 0.01 0.01 0.01 Maximum area (ha): 106 216 598 162 Sum area (ha): 4589 4419 4471 3190 Mean area (ha): 6.05 6.21 6.66 4.30 Standard Deviation (area): 10.2 13.1 27.3 9.97

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Table 47. Metrics of the individual networks generated for heathland species under the current

situation and the three scenarios (30%, 60% and 30-60%) for three dispersal distances (500m,

1000m and 2000m).

Max dispersal distance 500 m

Current 30% 60% combined 30-60%

Number networks: 110 85 56 48 Minimum area (ha): 0.01 0.03 0.01 0.01 Maximum area (ha): 566 582 1201 1229 Sum area (ha): 2263 3061 4848 4960 Mean area (ha): 20.6 36.0 86.6 103 Standard Deviation (area): 74.9 108 260 285 Max dispersal distance 1000 m

Current 30% 60% combined 30-60%

Number networks: 110 85 56 48 Minimum area (ha): 0.01 0.03 0.01 0.01 Maximum area (ha): 567 583 1201 1231 Sum area (ha): 2265 3068 4848 4969 Mean area (ha): 20.6 36.1 86.6 104 Standard Deviation (area): 74.9 108 260 285 Max dispersal distance 2000m

Current 30% 60% combined 30-60%

Number networks: 110 85 56 48 Minimum area (ha): 0.01 0.03 0.01 0.01 Maximum area (ha): 566 582 1201 1229 Sum area (ha): 2263 3061 4848 4961 Mean area (ha): 20.6 36.0 86.6 103 Standard Deviation (area): 74.9 108 260 285

Table 48. Metrics of the individual networks generated for grassland species under the current

situation and the three scenarios (i.e. 30%, 60% and 30-60%) for three dispersal distances (500m,

1000m and 2000m).

Max dispersal distance 500m

Current 30% 60% combined 30-60%

Number networks: 434 333 254 269 Minimum area (ha): 0.01 0.01 0.01 0.01 Maximum area (ha): 34 298 1137 1137 Sum area (ha): 1281 4752 8628 8668 Mean area (ha): 2.95 14.3 34.0 32.2 Standard Deviation (area): 3.62 31.4 148 144

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Max dispersal distance 1000m

Current 30% 60% combined 30-60%

Number networks: 434 332 253 268 Minimum area (ha): 0.01 0.01 0.01 0.01 Maximum area (ha): 35 298 1138 1138 Sum area (ha): 1284 4759 8636 8676 Mean area (ha): 2.96 14.3 34.1 32.4 Standard Deviation (area): 3.64 31.5 148 144 Max dispersal distance 2000m

Current 30% 60% combined 30-60%

Number networks: 434 332 253 268 Minimum area (ha): 0.01 0.01 0.01 0.01 Maximum area (ha): 34 298 1137 1137 Sum area (ha): 1281 4753 8629 8669 Mean area (ha): 2.95 14.3 34.1 32.3 Standard Deviation (area): 3.62 31.4 148 144

Figure. 9: Potential habitat network for woodland species with max dispersal distance of 500 m under (A) the current situation, (B) the 30% scenario, (C) the 60% scenario and (D)

the 30-60% scenario. The patches with different shades of grey represent the individual networks.

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Figure. 10: Potential habitat network for heathland species with max dispersal distance of 500 m under (A) the current situation, (B) the 30% scenario, (C) the 60%

scenario and (D) the 30-60% scenario. The patches with different shades of grey represent the individual networks.

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Figure 11: Potential habitat network for grassland species with max dispersal distance of 500 m under (A) the current situation, (B) the 30% scenario, (C) the 60%

scenario and (D) the 30-60% scenario. The patches with different shades of grey represent the individual networks.