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The Woodland Survey of Great Britain is a unique data set, consisting of a detailed range of ecological measurements at a national scale, covering a time span of 30 years. A set of 103 woods spread across Britain were first surveyed in 1971, which were again surveyed in 2000-2003 (for convenience referred to subsequently as the "2001 survey"). Standardised methods of describing the trees, shrubs, ground flora, soils and general habitats present were used for both sets of surveys. The sample of 1648 plots spread through 103 woodland sites located across Britain makes it probably the most extensive quantitative ecological woodland survey undertaken in Britain; it is also notable for the range of sites that have been revisited after such a long interval. The data set provides a unique opportunity to explore the effects of a range of potential drivers of woodland change that operated between 1971 and 2001. The data set is available in four discrete parts, which have been assigned the following DOIs: doi:10.5285/4d93f9ac-68e3-49cf-8a41-4d02a7ead81a (Kirby et al., 2013b), doi:10.5285/d6409d40-58fe-4fa7-b7c8-71a105b965b4 (Kirby et al., 2013d), doi:10.5285/fb1e474d-456b-42a9- 9a10-a02c35af10d2 (Kirby et al., 2013c), doi:10.5285/2d023ce9-6dbe-4b4f-a0cd-34768e1455ae (Kirby et al., 2013a). [ABSTRACT FROM AUTHOR]

1 Simulation models of forest stand dynamics have increased understanding of over-storey vegetation functioning, and have facilitated the development of tools capable of assessing possible successional trajectories. However, few models incorporate the response of the field layer vegetation despite it being another key component of forest ecosystems. 2 Our main objective was to assess the degree to which field-layer vegetation composition in forests is determined by variables operating at different scales, from regional (e.g. climate, location) to local factors (e.g. basal area of canopy trees, management). 3 We used data gathered during a nationwide forest survey to assess the relative effects of a broad spectrum of environmental variables on species composition. Variation partitioning was used to examine the relative contribution of subsets of environmental variables such as site spatial variation, boundary type and presence of herbivores. 4 Ordination confirmed hypotheses that field layer vegetation is primarily structured by two composite geo-climatic gradients. However, variation partitioning demonstrated that site- and plot-scale management factors also strongly influence the floristic composition of forest patches. 5 Disturbance variables (site boundary type/regional presence of deer) accounted for considerable species variation, exceeding that due to either site spatial variation or forest structure. 6 This is the first time variation attributable to such a comprehensive range of environmental variables has been quantified for forests surveyed at a national scale. We thus provide a context within which regional studies, or analyses considering a more limited range of factors, can be viewed, and a framework from which robust models of floristic response to gradual and episodic natural and anthropogenic disturbances may be developed. 7 The methodology we present, including a novel technique for the identification and removal of outliers in large data sets, provides a unique and standardized means of assessing the relative importance of diverse environmental drivers across a range of habitat types at the landscape scale, and is readily applicable elsewhere. [ABSTRACT FROM AUTHOR]

Habitat surveillance and subsequent monitoring at a national level is usually carried out by recording data from in situ sample sites located according to predefined strata. This paper describes the application of remote sensing to the extension of such field data recorded in 1-km squares to adjacent squares, in order to increase sample number without further field visits. Habitats were mapped in eight central squares in northeast Estonia in 2010 using a standardized recording procedure. Around one of the squares, a special study site was established which consisted of the central square and eight surrounding squares. A Landsat-7 Enhanced Thematic Mapper Plus (ETM+) image was used for correlation with in situ data. An airborne light detection and ranging (lidar) vegetation height map was also included in the classification. A series of tests were carried out by including the lidar data and contrasting analytical techniques, which are described in detail in the paper. Training accuracy in the central square varied from 75 to 100 %. In the extrapolation procedure to the surrounding squares, accuracy varied from 53.1 to 63.1 %, which improved by 10 % with the inclusion of lidar data. The reasons for this relatively low classification accuracy were mainly inherent variability in the spectral signatures of habitats but also differences between the dates of imagery acquisition and field sampling. Improvements could therefore be made by better synchronization of the field survey and image acquisition as well as by dividing general habitat categories (GHCs) into units which are more likely to have similar spectral signatures. However, the increase in the number of sample kilometre squares compensates for the loss of accuracy in the measurements of individual squares. The methodology can be applied in other studies as the procedures used are readily available.

Integration of European long term ecosystem research (LTER) would provide important support for the management of the pan-European environment and ecosystems, as well as international policy commitments. This does require appropriate coverage of Europe and standardised frameworks and research methods between countries. Emerging interest in socio-ecological systems prompted the present assessment of the distribution of LTER activities across European socio-ecological gradients. This paper presents a European stratification with a 1 km(2) resolution, delineating 48 broad socio-ecological regions. The dataset is based on an existing biogeophysical stratification constructed using multivariate clustering of mainly climatic variables and a newly developed socio-economic stratification based on an economic density indicator. The coverage of European LTER facilities across the socio-ecological gradients is tested using this dataset. The analysis shows two strong biases in the present LTER effort. Firstly, urban and disturbed regions are consistently under-represented, illustrating a bias for traditional ecological research away from human activity. Secondly, the Mediterranean, for which some of the most extreme global change impacts are projected, is receiving comparatively little attention. Both findings can help guide future investment in the European LTER network - and especially in a Long Term Socio-Ecological Research (LTSER) component- to provide a more balanced coverage. This will provide better scientific understanding of pan-European environmental concerns and support the management of natural resources and international policy commitments in the European Union., ((c) 2010 Elsevier Ltd. All rights reserved.)

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.

Various biogeographical and bioclimatic classifications of a number of regions, countries and continents have been created to meet different objectives. A policy maker might ask the question 'why is there no single accepted classification and how do the different classifications compare with one another?' In order to answer these two questions three classifications created by different methods for Great Britain and two for Spain are compared using the Kappa statistic. All of the classifications were created from data on cellular grids with a set window size. Further non-statistical comparisons are made with other classifications. The biogeographic classifications studied in this paper produced three different types of zone: those that were always identified whatever the method; those that were broadly similar but where the boundaries differed; and those that were unique to a particular classification. These different types of zone are likely to exist for any comparison between classifications of a particular region. The extent of the geographic window from which data were obtained had a major effect on the classification of grid cells at the edges of the window. For example, the few grid cells in the south of England, with characteristics of continental Europe, are not detected if data from Great Britain alone are used for the classification. We conclude that the data window should always be larger than the area for which the classification is being made. The objective Kappa statistic, although useful, was not capable of discerning similarities and dissimilarities that appear obvious to the subjective human eye. Although the details of the classifications differed there were broad similarities between the classifications and these differences reflect important divisions along major environmental axes that have been inferred by earlier biogeographers. As the divisions are real there is a sound basis for their use in future land use or environmental policy.