Search

A method of environmental classification has been applied twice to surveys of the whole of England, Scotland and Wales (the United Kingdom). Such experience is now being extended to the European continent. The paper draws on the unpublished working-papers of the relevant scientists and institutions in reconstructing both the motives and circumstances in which a methodology was developed in the UK for the assessment of the ecological resources of the wider countryside. The principles of strategic classification and subsequent sampling from defined strata were initially devised for broadleaved woodland, and first tested at a regional level. They drew on classical regression theory, with the environmental classification being the independent, and the vegetation or habitat the dependent, variable. The approach was linked to the development of efficient algorithms for analysis and classification, and more recently remote sensing and geographical information systems. Successive Countryside Surveys of the UK, carried out since 1978, have provided an objective measurement of the decline in the quality of vegetation and habitats. Such a statistically robust approach can be used to measure the rates of vegetation and habitat change at the strategic European level, and as an aid to devising appropriate rural-resources policies.

An inventory describing the fluxes of the volatile organic compound (VOC), isoprene, and the class of VOCs, the monoterpenes, from the biosphere to the atmosphere has been constructed for Great Britain (GB). The controlling parameters were emission potentials from individual plant species, plant species distribution, biomass distribution, temperature, and light intensity. Species distribution and cover data from a national survey of vegetation in 1990 were used. A database of monthly biomass factors was compiled and a qualitative database of VOC emission potentials from vegetation species was updated to a quantitative form. This was used in conjunction with a taxonomic methodology to assign isoprene and monoterpene emission potentials to each plant species extant in GB. Hourly meteorological data for 1998 were calculated using a three-dimensional nonhydrostatic meteorological mesoscale model (MM5) and these were used to predict the isoprene and monoterpene fluxes in GB in 1998 on a spatial scale of 12 × 12 km and with an hourly temporal resolution. Estimates of annual biogenic isoprene and monoterpene fluxes were 8 and 83 kt, respectively, for the model year. Picea sitchensis (Sitka spruce) is the dominant emitting species in GB, emitting approximately 40% of the annual isoprene and monoterpene fluxes. The dominant emitting regions in GB are coniferous forests in Scotland (isoprene and monoterpenes) and a Populus spp. (poplar) rich area in eastern England (isoprene). Overall uncertainty in the estimates is a maximum of a factor of 4. A sensitivity analysis of the model was used to study the impact of changes in vegetation cover and climate on VOC emission.

Countryside Survey 2000 (CS2000) is the latest in a series of surveys designed to measure and evaluate stock and change of land cover, landscape features, freshwaters, habitats and the vegetation of Great Britain. The ideas behind CS2000 developed during the 1960s and 1970s and culminated in the first survey of vegetation and land cover in 1978. One kilometer sample squares were selected at random using an environmental stratification. Subsequent surveys took place in 1984, 1990 and 1998, revisiting the original sample locations, whilst progressively expanding in scope and sample size; CS2000 included soils, breeding birds, remotely sensed imagery, freshwater biota and hydromorphology. Countryside Survey data may be interpreted using the pressure–state–response model, by selecting indicators of process and quality, and by identifying models of expected responses to different pressures. Thus, results showing losses of hedgerows between 1984 and 1990 stimulated new protection for these features. Ideally, CS2000 data should be used to stimulate experiments to distinguish between different pressures, in order to ensure that policy and management responses are both appropriate and achievable. The experience from CS2000 may prove helpful for the design and management of other large scale monitoring programmes of ecosystems. In particular, the scope of the survey, and the use to which the data are applied, have evolved through time, and yet continuity was essential for change to be detected efficiently. These objectives were reconciled by collecting the data in a disaggregated form, allowing a high degree of flexibility in both analysis and reporting.

Patterns of vegetation across Great Britain (GB) between 1990 and 1998 were quantified based on an analysis of plant species data from a total of 9596 fixed plots. Plots were established on a stratified random basis within 501 1 km sample squares located as part of the Countryside Survey of GB. Results are primarily conveyed in terms of a classification of national land-cover into 22 mutually exclusive Broad Habitat types. Each of the fixed vegetation plots could be assigned to the Broad Habitat in which they were located in either year. Two types of analysis are reported, both based on changes in plant species composition within monitoring plots. The first examined turnover and net change between Broad Habitat types. The second quantified more subtle changes that had occurred within each Broad Habitat using a series of condition measures that summarized multivariate plant species data as a single scalar value for each plot at each time. There are major difficulties in using uncontrolled, large-scale surveillance data to unravel causal linkages and no attempt was made to quantitatively partition variation among competing causes. However, it was clear that results were broadly consistent with environmental drivers known to have operated prior to and during the survey interval. Large-scale vegetation changes could be summarized in terms of shifts along gradients of substrate fertility and disturbance. Changes implied increased nutrient availability across upland and lowland ecosystems while, in lowland landscapes, linear features and small biotope fragments saw a marked shift to species compositions associated with greater shade and less disturbance

There is a well-established need to monitor land use and ecological change so that appropriate policies for the maintenance and enhancement of biodiversity can be developed. By building such exercises around sound scientific principles the reliability of the results can be quantified and policy makers can have confidence that they are genuinely independent. This paper describes two case studies of the development of such systems, the Small Biotope project of Denmark and the Countryside Survey project of Great Britain. These systems illustrate the problems involved in studies at the landscape level and the way satisfactory results can be achieved. Monitoring is considered to be effectively repeated surveillance and needs especially strict protocols to separate real change from the artefacts of sampling. The lessons to be learnt from these studies are summarised as a number of guidelines.

The Centre for Ecology and Hydrology, in collaboration with Oxford University, has developed a European environmental classification for the assessment and monitoring of effects of climate change on biodiversity at different spatial scales. The classification was constructed using various multivariate techniques from the database for 5500 half by half degree cells for the wider European window, developed by the University of East Anglia (UEA) for the TIGER programme. A statistical rule set created from the classification allows any cell size down to 1 x 1 km to be allocated to one of the 64 classes from its climate and altitude characteristics. Currently, this procedure has been used at its original resolution of half by half degree cell size across Europe and at a 10 x 10 km cell size across Great Britain. A number of climate change scenarios from different climate models provided by UEA have been assessed using the allocation procedure. By using the outputs from these climate models , the predicated movement of climate classes can be determined throughout Europe and at higher resolution for Great Britain. At the European scale, the greatest predicted changes in environmental diversity occur in Iberia and around the Mediterranean fringe. These areas show substantial decreases in the diversity of the region indicated by a fall in the number of classes present mainly due to the extension of two arid classes. The other major changes are in Northeast Europe where large uniform classes were sensitive to the scenarios but the implications are more difficult to determine. Using the half x half degree resolution, major changes can be seen in Great Britain with areas north and west of the Severn / Wash line becoming more oceanic where as those to the south and east becoming more continental. When the same scenarios are imposed in Great Britain using the 10 x 10 km resolution a new climate class was identified as being present whose distribution is centred in eastern Denmark

For hedgerows to act as corridors for woodland plants they must provide habitat conditions to suit species’ autecological requirements. This supposition was tested by examining differences in the habitat and autecological characteristics of woodland plants according to their relative frequency in hedgerows and woodlands using a novel Habitat Preference Index (HPI). Indicator values for habitat and autecological characteristics of plant species were derived from Ellenberg and other published sources. Analyses were done separately for three main types of landscape in which hedgerows are found in Britain: (1) Lowland Arable; (2) Lowland Pastural; and (3) Marginal Upland. The relative frequency of plant species across all three landscape types was similar and significant differences between HPIs and environmental indicators were found for all three landscape types. Plants more frequently found in hedgerows had significantly higher indicator scores for soil fertility, temperature, continentality together with reduced soil acidity, in comparison to those species more frequent in woodlands. Analyses of autecological indicators failed to show similar consistent trends across landscape types except for the number of woodland types of the National Vegetation Classification (NVC) in which species occur. Plants more frequently found in hedgerows were associated with fewer woodland communities suggesting that hedgerows contain only a narrow range of recognised woodland NVC stand types. Also, a significantly higher proportion of ancient woodland indicators were found in the group of plants that were more frequent in woodlands. Overall, results suggested that the environments of hedgerows are more similar to woodland edges than interiors. Qualitative differences between the environmental characteristics of hedgerows and woodlands are such that certain woodland plant species are highly likely to be limited in their capacity to use hedgerow networks. Implications for conservation of

1. Ellenberg's indicator values scale the flora of a region along gradients reflecting light, temperature, continentality, moisture, soil pH, fertility and salinity. They can be used to monitor environmental change. 2. Ellenberg values can be extended from central Europe, for which they were defined, to nearby parts of Europe. Given a database of quadrat samples, they can be repredicted by a simple algorithm consisting of two-way weighted averaging, followed by local regression. 3. A database of British samples was assembled from two large surveys. Ellenberg values were repredicted. 4. Except for the indicator of continentality, the correlation of repredicted and original values was in the range 0·72 (light) to 0·91 (moisture). The continentality indicator could not be adequately repredicted by the algorithm, and is unusable in Britain. 5. Discrepancies between original and repredicted values can be attributed to various causes, including wrong original values, differing ecological requirements in Britain and central Europe, biased sampling of the British range of habitats, and the occurrence of small plants in shaded or basic microhabitats within well illuminated or predominantly acid quadrats. 6. The repredicted values were generally reliable, but a small proportion was clearly wrong. Wrong values were due to either inadequate sampling of species' realized niches in Britain or sampling with quadrats that were too large and included species that were not close associates.

The Institute of Terrestrial Ecology (ITE) has monitored ecological change in Great Britain (GB) since 1978. The task has been undertaken using a stratified sampling scheme working with a 1 km square as the sample unit. In more recent years, scientific researchers at ITE have been working closely with the policy-makers of the United Kingdom Department of the Environment. The presentation of information to policy advisors and planners was a component within a large project investigating the ecological consequences of land-use change. A simple PC-based decision support system was developed during the project and subsequently has been expanded to produce a marketable product. The system, called the Countryside Information System (CIS), presents and links information at national, regional and thematic levels along with qualifying data describing accuracy and appropriateness of use (i.e., metadata). An integral part of the CIS is the ITE Land Classification, which divides GB into 32 environmental land classes; all 250 000 squares have been classified. The classification allows sampled data to be presented and, as the co-ordinate system is widely used in GB, it allows census datasets to be linked and compared. CIS has been described as a Geographical Information System, but the classification, data held within the system, and the use of metadata to assist in interpretation of results make the system much more decision-support oriented. Indeed, government departments have been involved in directing the development and are now starting to use the system to answer parliamentary questions and formulate, assess and monitor environmental policy. The CIS is an open system, running on a standard PC in Microsoft Windows. Tools for loading and editing new datasets (both sample and census) are incorporated in the suite of programs. The Windows environment and users comments during development have produced a system with an intuitive feel, removing some of the overhead of acquiring s

The Institute of Terrestrial Ecology (ITE) has classified the 1 km squares in Great Britain (GB) into thirty-two environmental strata, termed land classes, as a basis for ecological survey. The classes have been used in biogeographical studies of the distribution of individual species and species assemblages. The concept behind the technique is that there is an association between the environmental character of land and ecological parameters. The initial classification was based on a sample of squares drawn from a regular grid. The data for the 12121 km squares classified were drawn from published maps; the number of squares was limited by the available computing power. Subsequently the availability of more powerful computers and the need to improve geographical definition have led to the allocation of every 1 km square to its appropriate class. This paper has been written to summarise the principles involved in the development of the system and indicate the range of projects for which it has been used. The extension of the classification from a sample to the complete coverage of GB revealed the importance of the structure and style of data used to produce the classification. The significance of these conclusions for future work is discussed, with particular reference to automated methods of data capture.

Traditionally, ecological survey relies upon the intuitive interpretation of habitat patterns in the held. The statistical stratification developed for regional survey by the Institute of Terrestrial Ecology (ITE) is designed to minimise personal judgement in sample site location. The environmental strata within the classification are recognisable and give confidence to users from a variety of backgrounds. The methodology originated in the 1960s when multivariate statistics were developed and applied to ecological data. Initially, Great Britain (GB) was classified from environmental data recorded from 1200 out of the 240 000 km(2) of the National Grid. Logistic discrimination and discriminant functions were used to assign the remaining squares to original classes and to reassign the original squares. The final classes differed slightly from the initial divisions because the allocations use different data sets and different techniques. Field surveys of ecological parameters have been used to provide independent data for testing the classification, to characterise the classes and to provide national estimates of land coverage. The statistical rationale behind the methodology is described and the relevance of the experience gained during the development is discussed in relation to future work. Finally, applications of the classification are described demonstrating its use as a framework in a variety of ecological studies.