Spatial relationships between site hydrology and the ... - Science Direct

Journal of Environmental Management (1998) 54, 189–203 Article No. ev980227

Spatial relationships between site hydrology and the occurrence of grassland of conservation importance: a risk assessment with GIS R. D. Swetnam†∗, J. O. Mountford†, A. C. Armstrong‡, D. J. G. Gowing§, N. J. Brown†, S. J. Manchester† and J. R. Treweek† The UK’s Environmentally Sensitive Area (ESA) scheme provides financial incentives for farmers to undertake management which is compatible with the conservation of landscapes and wildlife species. Lowland wet grassland is an important component of a number of these ESAs. Management prescriptions relate to farming practices like grazing and weed management. For lowland wet grasslands, they may also include options to raise water levels for the benefit of species, many of which have declined following widespread drainage of agricultural land. This paper focuses on Southlake Moor in Somerset, south-west England, where raised water-level prescriptions have operated since 1992 and where an increased incidence of late spring flooding appears to be threatening important areas of nationally scarce Cynosurus cristatus–Caltha palustris grassland. A methodology is presented which makes use of a GIS to quantify the distribution of the nature conservation resource and link this to a hydrological model and a database of plant water-regime requirements. The model predicts water-tables on a field-by-field basis for each 10 day period throughout the year, allowing flood maps to be constructed. The database quantifies the water regime requirements for individual species on Southlake Moor. Using individual fields as the unit of study, these two are linked within the GIS to permit the extent of spring flooding to be identified and its potential impact assessed in terms of suitability for key species/communities. The paper describes how this approach could be used to determine whether deliberate management to raise water levels might be placing characteristic and scarce vegetation communities at risk.  1998 Academic Press

Keywords: Environmentally Sensitive Areas, Geographic Information Systems, hydrological modelling, National Vegetation Classification, Cynosurus cristatus–Caltha palustris (MG8), spatial patterns.

Introduction By the middle of the 1980s, certain undesirable economic and environmental consequences of the European Union’s (EU) Common Agricultural Policy (CAP) were becoming apparent. The negative impacts of agricultural intensification on the wildlife of farmed landscapes in the UK have been well Nomenclature follows Stace (1997) 0301–4797/98/030189+15 $30.00/0

documented (Fuller, 1987; Baldock, 1990; Adams, 1996). Escalating storage costs for surpluses of agricultural produce finally prompted reform of the CAP. The 1986 Agriculture Act attempted to redress the balance between increased productivity and associated environmental degradation. For the first time Agriculture Ministers had a statutory obligation to balance conservation against the support of a stable and efficient agricultural industry (Whitby, 1994). One of the most important provisions of Europe’s

†Institute of Terrestrial Ecology, Monks Wood, Abbots Ripton, Huntingdon, Cambridgeshire PE17 2LS, UK ‡ADAS, Gleadthorpe Land Research Centre, Meden Vale, Mansfield, Nottinghamshire NG20 9PF, UK §Silsoe College, Cranfield University, Silsoe, Bedfordshire MK45 4DT, UK Received 13 August 1997; accepted 6 April 1998

 1998 Academic Press

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first agri-environment policy was the designation of Environmentally Sensitive Areas (ESAs).

Environmentally Sensitive Areas In the UK, the ESA scheme is administered by the Ministry of Agriculture, Fisheries and Food (MAFF). The first round of ESAs were designated in 1987, with further rounds in 1988 and 1994. Included within the designations are a diverse selection of farmed landscapes, from the upland moors of Loch Lomond in Scotland to the chalk grasslands of the South Downs in southern England. MAFF have defined an ESA as: ‘. . . an area where traditional farming methods have helped create a distinctive landscape, wildlife habitats or historic features. The purpose of the scheme is to support the continuation of these farming practices and to encourage measures that will enhance the environment’. (MAFF, 1993)

The scheme is voluntary, consisting of a series of management agreements between MAFF and the landowner which last for 10 years. Usually an ESA will have a number of ‘tiers’ or levels of entry, which determine the amount of commitment involved. Higher tiers are more prescriptive in terms of the management required with the aim of greater environmental benefit. In return the landowner receives larger payments (MAFF, 1996). The nature and number of tiers vary between ESAs. Typically the tier prescriptions control fertilizer and pesticide use, the timing and nature of grazing, cutting and the drainage status of the land. The specific nature of the prescriptions will depend on the site and the environmental objectives of the ESA.

Measurement of success Having set up the scheme, MAFF made a commitment to assess its success and to ensure that the original management guidelines were appropriate. Value for money was important to the policy makers who were required to deliver a reasonable return on the investment of public money. The questions

MAFF were interested in answering included, whether the investment delivered the expected environmental improvements, were the guidelines appropriate, and were there problems within the management prescriptions? Changes in management prescribed under the ESA scheme are intended to promote specific environmental benefits. However, it is not always easy to predict the actual effects of altered management on ecosystems with different management histories or on sites with different physical characteristics (Treweek et al., 1993). As ESA management prescriptions are not tailored to match site-specific circumstances, they cannot be expected to be uniformly effective. Where management prescriptions are implemented on sites with acknowledged existing wildlife of value, some form of risk assessment may be required to ensure that damage to valued communities or species is avoided. Wet grasslands, in particular, depend on the maintenance of a careful balance between hydrology and land use (Treweek et al., 1996). The implementation of a raised water-level scheme to reinstate the hydrological conditions generally (or historically) associated with high wildlife value may represent a dramatic change on sites which have been intensively managed for some years. Ideally, management prescriptions would be tailored to reflect the relationship between current site conditions, current wildlife status and intended environmental benefits.

Objectives and approach The objective of this project was to integrate botanical data with hydrological data, to predict the impact of the ESA prescriptions on a typical lowland wet grassland community. Hydrological modelling was applied to the site and linked to field surveyed data, providing a valuable opportunity to identify ‘risk’. This risk could be to agricultural viability, to the survival of an individual species, or to the survival of a community. Geographic Information Systems (GIS) offer appropriate tools to combine spatial data, field survey data and models within one graphic environment. The research benefits of a GIS approach are illustrated by many successful ecological examples (Coleman et al., 1994; Carver et al., 1995; Cowen et al.,

GIS risk assessment in wet grasslands

Somerset Levels and Moors

Figure 1. Location of the Somerset Levels and Moors Environmentally Sensitive Area within the county of Somerset, UK.

1995; Mallawaarachchi et al., 1996). The integration of hydrological modelling within GIS in particular has become increasingly common and examples exist for open wetland systems such as the Venice lagoon (Bettinetti et al., 1996), mountainous snow-covered regions (Baumgartner and Apfl 1994; Coughlan and Running, 1997) and tundra wetland sites (Ostendorf and Reynolds, 1993). As the technology becomes more common in Government agencies, the use of GIS as a tool to assist policy formulation is becoming more widespread, both for inventory purposes (Peccol et al., 1996) and to address wider strategic issues (Haines-Young et al., 1994). Examples are now available from a range of scales, regional to national, notably that built for the NERC/ESRC Land Use Programme (Watson and Wadsworth, 1996) and the Countryside Information System funded by the UK Department of the Environment (Howard and Bunce, 1996). Although decisions will largely be made at these scales, the impacts of such decisions will be apparent at the local scale. It is therefore, essential to assess the impacts of policy at the site-level. A risk-assessment methodology will be illustrated with a case study, examining the impact of the raised water-level prescriptions

on a valued plant community found on Southlake Moor: Cynosurus cristatus–Caltha palustris (MG8) grassland (Rodwell, 1992), and in particular the impact of late spring flooding on this community.

The study site—Southlake Moor Southlake Moor was chosen as a site for a case study for three reasons: it has been identified as an area of botanical interest under threat (Leach and Cox, 1995); second it forms a self-contained hydrological management unit ideal for catchment studies; thirdly it has been the location of ongoing monitoring and so has an historical data resource (ADAS, 1996a, 1996b). It is situated on the south-western part of the ESA immediately adjacent to the river Parrett and about 9 km south-east of Bridgwater in Somerset, UK, centred on 51°4′4N, 2°54′59E (Figure 1). It is generally level and low lying and is almost entirely situated on Midelney series soils, characterized by deposits of alluvial clay up to 90 cm deep overlying peat (Avery, 1955). Drainage is assisted by a pumped

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drainage scheme administered by an Internal Drainage Board (IDB), these cover a number of contiguous farms and are required to maintain specific summer and winter levels. The moor is almost entirely managed as permanent grassland, with a summer haycut and aftermath grazing. It has been designated as a Site of Special Scientific Interest (SSSI) by English Nature. Many of the grassland communities found on the moor are nationally scarce (Leach, 1995). Existing surveys suggest a varied composition with several communities of the National Vegetation Classification represented (Rodwell, 1992). These include swards which developed under agricultural improvement (MG7: Lolium perenne leys and related grasslands), and important areas of C. cristatus–C. palustris grassland (MG8) and in higher-lying parts, the C. cristatus–Centaurea nigra grassland (MG5); both of which are the subject of conservation action by English Nature. These plant communities represent types of ‘neutral grassland’ which are nationally scarce. It has been estimated that there are less than 10 000 hectares in total, with the MG8 community in particular being restricted to approximately 500 hectares (Jefferson and Robertson, 1996). This community is particularly well represented on Southlake Moor and forms the focus of this study.

Cynosurus cristatus–Caltha palustris (MG8)—community characteristics Grasslands which were described in the nineteenth century by the functional name ‘water meadows’ were recognized by the NVC as having a characteristic floristic composition (Rodwell, 1992), and to be closely related or identical to those swards described in Continental phytosociology as Senecioni-Brometum racemosi (Tu¨xen and Priesing, 1951). Although field-work for the NVC found only 15 samples clearly belonging to MG8, centred on the chalkland valleys of southern England, further intensive field-work (particularly by English Nature and ADAS) has shown MG8 grassland to be widespread, though local in England with major areas in the Somerset Levels and Moors and the Pennine Dales ESA (Swash, 1997). This grassland type is notably species-rich, with no clear dominant, though

Anthoxanthum odoratum, C. cristatus, Festuca rubra, Holcus lanatus and Poa trivialis are prominent, and important herbs include C. palustris, Cerastium fontanum, Leontodon autumnalis, Ranunculus acris, Rumex acetosa and Trifolium repens. This community is clearly related to certain poor-fen grasslands, as well as the more typical mesotrophic swards. Both predictive modelling (Gowing, 1996) and field monitoring (Leach and Cox, 1995) have suggested that prolonged flooding into late March and April reduces the extent of MG8, and its replacement by more speciespoor inundation grasslands and swamp communities. This perceived risk of damage to the C. cristatus–C. palustris resource led ADAS, Silsoe College and the Institute of Terrestrial Ecology (ITE) to assess the scope of the potential problem in one study area—the Southlake Moor SSSI.

Methods A GIS was an integral part of the study. This ‘Wetlands GIS’ was developed specifically to address spatial queries at the site level. The system was based on workstation Arc/Info (ESRI, 1992). All of the information is organized around a unique identifier, the field number. A field represents the minimum geographic unit that could be represented on the map with accuracy. Within each field numerous quadrats were collected, however, their location was not recorded to a sufficient level of accuracy to allow them to be displayed as points, so they were geographically referenced to the field within which they were located. Botanical data and model output were reported at this field level, but results can be aggregated to the block or compartment level. The methodology presented in this paper links a hydrological model to a database of plant requirements. The model, DITCH, predicted the hydrological regime of individual fields throughout the catchment, so providing an overview of conditions (Armstrong, 1993). The output from DITCH was spatially referenced by the Wetlands GIS and linked to maps showing the distribution of plant communities in relation to flood duration. Shifting from the field-scale to the plant-scale


Access quadrat database (200+ quadrats) No Is TABLEFIT choice MG8 and >=60%? Yes Link to map via fieldnumber

Draw selection

Select data from ITE field survey No Is MG8 present in the field? Yes Link to map via fieldnumber

Add in second selection

Access English Nature field survey No Is MG8 present in the field? Yes Discard

Link to map via fieldnumber

Draw the final map of MG8

Figure 2. Identifying the MG8 fields on Southlake Moor. ITE, Institute of Terrestrial Ecology.

required a second element, a database which contained the plant-water requirements of some of the individual species which comprise the MG8 community (Gowing et al., 1994). This database contained information derived from detailed modelling at similar sites and gave an indication of how tolerant particular species were to drought stress and how well each could survive in waterlogged conditions. The areas under threat from spring flooding (located using DITCH) were then examined from the point of view of individual species. Where the flood regimes in these fields were apparently not suitable for these species, support may be given to the argument that spring flooding is detrimental to the community, since key elements of the MG8 are likely to decline if the regime is maintained. Each stage will now be discussed in more detail.

Locating the community type The first step was to quantify the resource. Good botanical data are available for Southlake Moor. To ensure as wide a coverage as possible three contemporary sources were accessed: field assessments made by English Nature in 1992–4, a further field survey commissioned by ITE in 1994 and an intensive quadrat survey of seven fields by ITE in the same year. Of the 92 fields on the moor, data were available for 30 fields with even coverage between the different management tiers. Only the eastern edge of the moor was under-represented. These data largely represent the situation in the grassland before the onset of raised water-level management. The rationale behind the selection approach was that the most detailed data were

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R. D. Swetnam et al. Table 1. Summary of the water management imposed at Southlake Moor Date

Timing of control

Pre. 1989

Summer Winter

Summer levels kept high to allow stock watering Winter levels kept low to prevent flooding, apart from periods of warping

Dec. 1989

1 April–31 Oct

Levels maintained at or above the penning level, provided since 1987 by the relevant IDB and never more than 45 cm below the mean field level Levels maintained at or above the winter level provided since 1987 by the relevant IDB, with at least 30cm of water in the bottom of the ditches at all times

1 Nov.–31 Mar.

Dec. 1992

1 May–30 Nov. 1 Dec.–30 Apr.

Type of ditch management

Maintained at no more than 30cm below the mean field level Maintained at no less than mean field level so as to cause surface splashing

IDB, Internal Drainage Board.

accessed first, if unavailable the next best source was accessed (Figure 2). Quadrat data collected by ITE were classified into NVC communities by using TABLEFIT (Hill, 1991). The output from the program represents those five communities with the highest goodness-of-fit to the floristic tables in Rodwell (1992). Where quadrat data were available, the fields were classed as possessing some MG8 when more than two of the quadrats had a goodness of fit >60. The remaining fields had been classified by English Nature into NVC communities based on the field species lists. These fields were included in the selection where the community was recorded as present. Some fields were only covered by one data set, others by all three. In each case the most detailed data set was used to assess community presence.

Modelling the hydrological regime A raised water-level regime was implemented on Southlake Moor in December 1993. However, this is only the latest in a long history of water management at the site (Table 1). ADAS have monitored the hydrological regime of Southlake Moor since June 1989. Six fields were instrumented to measure watertable depth. These data were reviewed in 1995 and it was found that the levels in all the monitored fields followed similar patterns. It was concluded that the water-table level was controlled by the ditch level in the winter months but falls to 1 m below ground level in

summer as evapotranspiration from growing plants exceeded the recharge from the ditches (Armstrong et al., 1996). In conjunction with data from gauge heights, soil strength, type, mean topographic height and ditch spacing the water-level data were fed into the model, DITCH (Armstrong, 1993). DITCH The DITCH model was originally developed to investigate the interactions between ditches, management regimes and in-field soil-water regimes (Armstrong, 1993). It has been used and validated on data from the Broads ESA (Armstrong and Rose, 1998) and for several sites in Somerset (ADAS, 1996b). DITCH calculated the water-table level position and reported it on a daily basis for each field. These results were then summarized by deriving a mean water-table position for each of the 36 10-day periods in the year (with the last period including the extra days at the end of December). For each of these 10-day periods (hydro-periods) the mean water-table depth, the profile water content, and the mean duration of flooding was calculated. These 108 variables give a mean annual picture of the state of each field. In the DITCH model, the water levels in a field were calculated from a consideration of the water balance (1): Mt=Mt−1+(R−ET−Qd )/f

(1)

where the water elevation in the field on day


t is Mt , R is the rainfall, ET is evapotranspiration, Qd is the discharge through the drainage systems. The specific yield, f, is approximated by the drainable porosity of the soil. Prediction of the soil-water regime required estimates of the flux through the drainage system. These fluxes can be in either direction, and so include both drainage and recharge. The theory of water movement to drains (described for example by Ritzema, 1994), is derived from an understanding of the physics of soil-water flow processes, based on Darcy’s Law for saturated flow, and the Richards’ equation for unsaturated flow (see for example, Childs, 1969; Marshall and Holmes, 1988). For geometrically regular situations such as a soil drained by parallel ditches, this can be calculated from one of the well-known drainage equations. This flux between ditch and field, Qd can be in either direction, and therefore includes both drainage (Qd is positive) and recharge (Qd is negative), to represent both the winter and summer phases of operation. This flux is estimated from the difference in levels between the water-table in the centre of the field and the level in the ditch (the hydraulic head), the hydraulic conductivity of the soil, and the geometry of the drainage system. For Southlake Moor in which a low conductivity topsoil overlies a more permeable subsoil, the drain flow equation for two-layered soils given by Wesseling (1973) using an analysis originally due to Ernst, was used, in which the two soil layers were each characterized by different values of the hydraulic conductivity and drainable porosity. This model has been tested using data from the Southlake Moor site, and has been shown to give good estimates of water-table position (Armstrong et al., 1996). The model predictions were in general very close to observations. In particular, the model predicted the lowest depth to which the water-table fell in the middle of the summer. These results were held within the Wetlands GIS. Detailed temporal shifts in the hydrology could then be represented spatially.

Quantifying the threat to the MG8 communities To determine which fields were flooded and when, a series of database selections were

required. The GIS was used to query the hydrological data tables and to select those where the mean water-table was above ground level. As the key issue was to determine the threat from prolonged flooding (especially in the spring), only those fields flooded after the 1 March were retained in the selection, these data falling within ‘hydroperiod’ 7. The selection was thus refined and mapped. By combining this information with that on the location of MG8 within the catchment, the area of MG8 affected by spring flooding could then be calculated. There was a further need to decide which of those fields affected by spring flooding were persistently flooded and for how long, as intermittent flooding events were considered less likely to pose so great a threat as prolonged and late flooding. This temporal refinement was possible because the model output gives results for every 10 day hydroperiod through the year. All that was required was an extension to the initial query to highlight those fields where the water-table would be above ground surface for consecutive hydro-periods. In this manner a rapid assessment of the flooding risk to any of the botanical communities or even individual species on Southlake Moor could be achieved.

Modelling the plant water requirements The relationship between plants and the prevailing hydrological regime within which they grow is complex. Although the DITCH model provided an overview of field conditions, it is necessarily general, and does not take account of field-scale micro topography. Each individual species has its own physiological requirements and its own particular thresholds for stress, one of the most limiting being the availability of oxygen within the soil. Communities are essentially groups of plants which share similar, though not identical requirements. The field-scale modelling described previously gives an overview of conditions within the spatial unit of a field and the risk to the MG8 community has so far been described at this scale. However, the species which have been grouped into MG8 are many and varied, each with slightly different response to aeration stress (i.e. flooding). Some of the more common species can be

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R. D. Swetnam et al. Ground level

Depth to watertable

Wetness Aeration threshold

Drought threshold

Drought

Time

Figure 3. Calculation of the drought and aeration exceedence values. The Sum Exceedence Value statistic summarizes the area of the hydrograph which falls under (drought) or over (aeration) the threshold value for the soil column.

part of many different communities, whereas others are much more specific or faithful to that vegetation type. However, some of these widespread grassland plants may be particularly frequent in examples of a given community, occurring in >60% of samples. Rodwell (1992) defined them as ‘constant species’ and in the MG8 community these include: A. odoratum, C. palustris, C. fontanum, C. cristatus, F. rubra and L. autumnalis. When these species are lost or reduced in frequency and cover a shift in community type may be suggested. To show how varied this response can be, an exceedence approach to plant stress has been included in this particular risk assessment.

For ecological studies, one useful approach to determining conditions of plant water stress is the Sum Exceedence Value method of Siebens (1965) (Gowing, et al., 1998). This quantifies the extent and timing that a given water table threshold is breached and summarizes it into a single statistic [Equation (2), (2a), (2b)]: T

SEV=

]EW

t

(2)

t=1

where EWt=RV−WTt WTtRV

(2b)

Sum exceedence values database Individual plants can suffer two main types of soil-water stress: drought and aeration. The first occurs where there is a soil moisture deficit caused by deep water-tables and inadequate capillary rise. Drought sensitive species may close their stomata and reduce their competitiveness. Conversely, aeration stress is due to a soil oxygen deficit caused by shallow water-tables. Where air-filled porosity in the soil falls below 10%, oxygen diffusion is insufficient to supply the respiratory demands of the root during periods of rapid growth (Wesseling and van Wijk, 1957).

where WTt is the water-table depth at time t, and RV is the reference depth used as the aeration threshold. The summary statistic, SEV, has the units of time ∗ depth, and is effectively the area between the graph of water-table depth and the reference value. This statistic is indicative of stress to the plants from water-logging. A similar statistic can be calculated to define drought stress as the area below the curve (Figure 3). The threshold values for drought and aeration depend purely on physical criteria such as the soil conductivity and evaporative demand, they are not species specific.

GIS risk assessment in wet grasslands Table 2. Distribution of flooded MG8 fields through the management tiers on Southlake Moor Tier

0 1 2 3

Total area in the tier (ha)

Area of MG8 (ha)

Area of MG8 flooded after 1 March (ha)

Percentage of total MG8 area flooded after 1 March 1

33·5 11·1 35·1 42·7

3·6 6·2 0·0 24·8

1·3 3·4 0·0 22·9

37·7 54·1 0·0 92·2

This approach has been developed for peat soils on flat, low-lying land (Youngs et al., 1989; Youngs, 1992; Gowing et al., 1994). SEV tolerance ranges have been calculated for 69 species at Tadham Moor, another peat site in Somerset which is very similar to Southlake Moor. The method can be described with an example species, L. autumnalis. Five-hundred and forty-two positions were randomly selected within a 20 ha area of Tadham Moor and the presence or absence of L. autumnalis in a 1 m2 quadrat was recorded at each. The species was observed in 45% of samples overall. A hydrological model (Youngs et al., 1989) was used to generate weekly water-table depth estimates for a 15-year period at each position, and Sum Exceedence Value (SEV) parameters were derived from these data (cf. Figure 5). The hydrological model was validated by reference to a network of dipwells across the site (Gowing et al., 1994). The sampled positions were then ranked in ascending order of their SEV (drought) value. The frequency of occurrence in the 60 least droughty samples was 0·59. The corresponding frequency for a rolling subset of 60 observations was calculated across the whole data set, until the 60 droughtiest samples were considered and found to have a frequency of 0·27. Taking the null hypothesis that the species is randomly distributed through the site with no regard to drought stress, the binomial distribution was used to calculate the confidence limit below which the proportion of quadrats containing Leontodon was significantly (P10% of the sampled positions. Although the tolerance regimes have been only partially validated at Southlake Moor, the two sites were deemed to be sufficiently similar to illustrate the methodology and to show how the model output from DITCH could provide useful input to a species-scale assessment of plant response to water management. The output of the catchment-scale modelling provided SEV values for each field. These could be examined in relation to the species water regime database to give an indication of the impact on individual constituents of the MG8 community. This quantitative approach to describing the water regime tolerances of plant species does not aim to supersede the published rankings of Ellenberg (1988) and Grime et al. (1988), but to provide an estimate of tolerance which can be compared to the output of hydrological models. Qualitative ranking systems are not applicable to a predictive framework such as the one developed here.

Results Seventeen fields containing some MG8 were identified on Southlake Moor, covering a total area of 34·6 ha. Over 24·5 ha (70%) of the total probable MG8 area were located in fields included in raised water-level areas (Table 2). In 1995, 22·9 ha (92%) of these were found to be flooded after the first of March, and indeed, six of the 17 fields were flooded until

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Figure 4. Fields on Southlake Moor where the survival of MG8 may be at risk through prolonged spring flooding after 1 March with fields flooded until 20 March at low risk, fields flooded until 9 April at medium risk and fields flooded until 19 April at high risk.

after 9 April, well into the growing season. These six fields covered an area of 16·2 ha, (i.e. over 65% of the apparent total community extent of the MG8) on Southlake Moor, and were managed under ‘Tier 3’ management prescriptions. The fields containing MG8 grassland could be classified on the basis of the perceived risk to MG8 from persistent flooding i.e. areas of no risk (not flooded after March 1st); area of low risk (flooded until 20th March); areas of medium risk (flooded until 9th April); and areas of high risk (flooded until 19th of April) (Figure 4).

Single-species response to flooding Figure 4 identified fields containing MG8 which would be at risk from spring flooding. To illustrate how the SEV values can be used, five species were examined individually. These five species were chosen to illustrate the approach because they are constituents of MG8 and their aeration tolerance values derived from Tadham Moor, overlap the range of SEV values for the site (Table 3).

Those MG8 fields where the aeration value exceeded that given for the species were identified. Of the species in Table 3, three (R. acris, R. acetosa and T. repens) had their SEV aeration value exceeded in seven of the fields where MG8 was recorded. Anthoxanthum odoratum and L. autumnalis are two of the constant species of the MG8 community, but their maximum aeration value was exceeded in five and four of the MG8 fields, respectively. Those fields which exceed the aeration range given for each of the five example species are shown in Figure 5. When compared with the original MG8 risk map (Figure 4), it can be seen that all those fields which exceed the aeration values for all five example species fall into the high or medium risk category.

Discussion On Southlake Moor nearly 35 ha containing MG8 grassland were identified and mapped. When this is placed within the national context the implications of any damage to this

GIS risk assessment in wet grasslands Table 3. Species water tolerances for selected species found within MG8 communities, with drought and aeration values calculated using the Sum Exceedence Value approach, where the aeration threshold is 40 cm and the drought threshold is 45 cm (see text for details) Species

Anthoxanthum odoratum Leontodon autumnalis Ranunculus acris Rumex acetosa Trifolium repens

Drought

Aeration

min

max min (m week−1)

max

Ellenberg Moisture 1–12a

0·0 0·0 0·5 2·0 0·0

— 4·1 — — —

3·7 4·0 3·3 3·3 3·4

X 5 6 X 5

0·0 0·0 0·6 0·6 0·0

CPE Class Hydrology A–Fb A (→C) B A→C A→B (→D) A→C

Corresponding water tolerance ranges are given for Ellenberg Moisture Values and for the groups given in the Comparative Plant Ecology of Grime et al. (1988). a Ellenberg moisture classes. Where 1=extreme dryness, 12=submerged aquatic and X=indifferent behaviour. (Ellenberg, 1988). b CPE=Comparative Plant Ecology. Where A→C represents species occurrence throughout hydrological groups A–C, ranges in brackets indicate that the species does occur in this group, but less frequently (Grime et al., 1988).

Exceeded 0 of 5 3 of 5 4 of 5 5 of 5 Other

m 0

200

400

600

800

1000

Figure 5. MG8 fields where the modelled aeration value exceeded that defined for individual species in Table 3. (Maximum value=five species).

community become apparent. If the Jefferson and Robertson (1996) estimate of 500 ha is used, the MG8 found on Southlake Moor may comprise up to 7% of the national resource, all on one very small site. Potential damage to this resource has national implications. Over 70% of the total area of MG8 on Southlake Moor is situated within the higher-level water management agreement and would be

at risk if the ESA guidelines proved to be inappropriate. Landowners may be receiving subsidies which ultimately lead to a decline in species diversity. Using a hydrological model to detail the water regime within 10-day periods allowed the risk of flooding into the growing season to be identified. Many of the Tier 3 fields were shown to be particularly at risk from late

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spring flooding. Data provided by the plantwater model added further weight to this argument. The impact on individual constituents of the community was assessed and it was found that certain constant species of MG8, notably A. odoratum and L. autumnalis were expected to suffer stress from waterlogging. The ability to focus on an individual species is important because the changes which may result from the water management on the moor may first become apparent with their loss or from marked changes in their cover and frequency. A shift to a more inundated grassland could be suggested by a decline in their abundance. The situation is complicated by the fact that some of the objectives of the ESA have the potential to be in at least partial conflict. The management agreements operating in the Somerset Levels ESA are trying to meet a number of objectives, not all of which are botanical. Wet grasslands have been identified as a priority habitat for birds in an English Nature review (Brown and Grice, 1993). Many Red Data Book Species such as the Golden Plover and the Snipe are dependent on lowland wet grasslands (Fuller, 1982). One of the reasons for increasing the water-table height on Southlake Moor was to encourage nesting by these wading birds. However, the success in attracting wading birds may well occur at the same time as a deterioration in the grasslands for which the site is also designated. Quantifying subtle changes in the floristic nature of the moor is more difficult than estimating success at attracting wading birds—the results are less apparent. A potential conflict is highlighted by the results of this analysis of MG8. Classification of samples may be achieved through conventional phytosociological tablework, through the keys of the NVC, or using the TABLEFIT procedure (Hill, 1991). There are inherent problems in attempting to classify as separate, communities which are continuous with one another (Whittaker, 1980). Such difficulties are especially pronounced within mesotrophic grasslands, where the number of faithful species (i.e. those restricted to a single community) are very few, and most vegetation types are distinguished on the basis of the composition of the dominant grasses and forbs. However, in the light of both the continuum problem, and the marked within-community variation, it is not

surprising that some vegetation stands cannot be readily ascribed to a single type. In the context of the present study, an attempt was made to use only those vegetation data with a high goodness-of-fit to a particular community. Nevertheless, within any given field, micro-topographic variation can produce a mosaic of vegetation types, and samples which fit well with MG8 may fit almost as well with a closely-related community. However, by combining the best available data-sources, and comparing them one with another, a high degree of consistency in vegetation classification was achieved. The methodology has been illustrated using a particular community type, however, it is not limited in that respect. The same approach could be used to investigate hydrological relationships between any of the communities on the moor. The hydrological model produced output which related to the centre of each field. The centre is usually the driest place within the field and as such represented an extreme value. Even on flat sites such as Southlake Moor the micro-topography within fields will vary; the model output provides a summary of conditions. Likewise, the SEV values derived for the field, are summarized at this central point. In reality, the ranges given in Table 3 may be exceeded only in part of the field. It is recognized that the figures used for plant water database are derived from Tadham Moor, however, this site is very similar to Southlake Moor both in terms of topography and management history. As such, it was deemed reasonable to apply the values to the study site to illustrate the approach. Direct determination of SEV tolerance ranges for a subset of species was undertaken on Southlake Moor and found to be in agreement with the estimates for Tadham (Gowing, 1997). In light of this, Figure 5 should not be interpreted as a definitive picture of where species are declining on Southlake but it does suggest some general trends. The similarity to the risk map given in Figure 4 is striking, highlighting these areas as requiring particular attention.

Conclusions Management of botanically rich wet grasslands is a very fine balancing act, if man-


agement is inappropriate, recovery or re-instatement is difficult and expensive. Predictive modelling cannot replace monitoring, but it can provide an early warning of species decline. Such an assessment can be tested in the field through further monitoring, allowing field survey to be targeted on areas of concern. Perhaps more importantly, such assessments highlight areas at risk which may not have received as much scrutiny as others. The methodology described has allowed investigation of specific concerns expressed by botanists about the Somerset Levels and Moors ESA. It has shown that these concerns can be translated into something more concrete: what is happening, where is it happening and when is it happening? On Southlake Moor a slight change in management prescriptions—a lowering of the water-table after 1 March could help alleviate the risk (Gowing, 1996). The Wetlands GIS can help to explore a particular issue of relevance to this and other sites and has shown how it can be expressed in terms which are meaningful to the site managers and advisors. Feedback of this nature should lead to a gradual refinement of the management prescriptions in operation and help identify conflicts and balance the needs of different ESA objectives.

Acknowledgements This study was funded by the Ministry of Agriculture, Fisheries and Food. The views expressed in this paper are those of the authors and should not be attributed to the Ministry. The authors thank colleagues from all three of the collaborating organizations for their input into the research including: Deborah Solomon and Steve Rose (ADAS), Gordon Spoor and Jo Gilbert (Silsoe College), Richard Caldow, Trem Stamp and Neil Veitch (ITE). Richard Bradford at English Nature provided species data for Southlake Moor. Particular thanks go to Wendy Cox, whose efforts with field-survey and archive research accounted for a large part of the botanical database for this site.

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