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A study was conducted on the biogeography classifications that produced three different types of zones. The different types of zones were likely to exist for any comparison between classifications of particular regions. It was concluded that the data window should always be larger than the area for which the classification is being made.

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.