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Aims: Vegetation‐plot sampling usually involves estimating species cover. For classifying plots to vegetation types, covers are often transformed to decrease the effect of dominant species. However, it remains unclear which transformation is optimal. We suggest that for vegetation classification, optimal is such transformation that contributes to creating clusters of plots in an unsupervised classification that are most similar to the widely accepted vegetation types, e.g., phytosociological associations. Here our aim is to find and recommend such optimal transformation by testing a range of transformation options against the national vegetation classifications of three European countries. Location: Czech Republic, The Netherlands, Great Britain. Methods: Three national datasets of vegetation plots with species cover information, classified to associations or community types of the respective national vegetation classification systems, were analysed. From each dataset, multiple subsets of plots were selected randomly, each subset representing a vegetation‐plot table containing several similar associations/community types. Species cover values in these subsets were subjected to various transformations (power transformation, logarithmic transformation and pseudo‐species cut levels). Then each subset was classified by an agglomerative classification method (beta‐flexible clustering with different beta values), and the classification was compared with the units of the national vegetation classification using the adjusted Rand index. Results: Power transformations of percentage covers with an exponent between 0.3 and 0.6 produced the best match between the unsupervised classifications and the national vegetation classifications. This result did not depend on the classification method used. A similar degree of matching was achieved with some cut levels of pseudo‐species and with logarithmic transformation of percentage cover. Conclusions: If an unsupervised classification of vegetation plots aims at defining vegetation types that are close to the phytosociological associations accepted in national vegetation classifications, the best transformation is close to the square‐root of percentage cover (i.e., power transformation with exponent 0.5). [ABSTRACT FROM AUTHOR]

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The launch of gravity-dedicated satellite missions at the beginning of the new millennium led to an accuracy improvement of global Earth gravity field models (GGMs). One of these missions was the Gravity field and steady-state Ocean Circulation Explorer (GOCE) launched in 2009. As the first European Space Agency's Earth Explorer Mission, the satellite carried a novel instrument, a 3-D gradiometer, which allowed measurement of the second-order directional derivatives of the gravitational potential (gravitational gradients) with a uniform quality and a near-global coverage. The main mission goal was to determine the static Earth's gravity field with the ambitious precision of 1-2 cm in terms of geoid heights and 1 mGal in terms of gravity anomalies for spatial resolution of 100 km (half wavelength at the equator). More than three years of the outstanding measurements resulted in three levels of data products (Level 0, Level 1b and Level 2), six releases of GGMs, and several global grids of gravitational gradients. The grids, which represent a step between gravitational gradients measured directly along the GOCE orbit and those represented by GGMs, found their usage mainly in geophysical applications. In this contribution, we validate the official Level 2 product GRD_SPW_2 using height anomalies over two test areas located in central and northern Europe (Czechia/Slovakia and Norway). A mathematical model based on the least-squares spectral weighting is employed with corresponding spectral weights estimated for validation of gravitational gradient grids. This model continues gravitational gradients from the mean orbital altitude of GOCE down to the irregular Earth's surface (not to a sphere) and transforms them to height anomalies in one computational step. Analytical downward continuation errors of the model are estimated using a closed-loop test. Prior to the comparison of height anomalies estimated from gravitational gradients with their reference values derived from Global Navigation Satellite Systems (GNSS)/levelling over the two test areas, the gravitational gradients and reference data are corrected for all systematic effects such as the tide system conversion. Moreover, the high-frequency part of the gravitational signal is estimated and subtracted from reference data as it is attenuated in the gravitational gradients measured by GOCE. A relative improvement between the release 6 and release 2 gradient grids reaches 48 % in terms of height anomalies in Czechia/Slovakia. The relative improvement in Norway is even more significant and reaches 55 % . The release 6 of the official Level 2 product GRD_SPW_2 gained the absolute accuracy with the standard deviation of 8.7 cm over Czechia/Slovakia and 9.3 cm over Norway. Article Highlights: A mathematical model based on the least-squares spectral weighting for validation of the official Level 2 product GRD_SPW_2 is presented Possibilities of the spectral combination method for the downward continuation of gravitational gradients and their transformation into height anomalies are investigated A review of quality of the official Level 2 product GRD_SPW_2 with respect to GNSS/levelling points over two test areas (Czechia/Slovakia and Norway) is provided [ABSTRACT FROM AUTHOR]

• The IUCN Red List of Ecosystems criteria were applied at the national scale. • 157 types of natural and semi-natural habitats of the Czech Republic were assessed. • Two habitats were Collapsed, 14 Critically Endangered, 33 Endangered, 33 Vulnerable. • Natural succession after abandonment, eutrophication and drought are major threats. • IUCN Red List of Ecosystems criteria are applicable in small countries or regions. The Red List of Habitats of the Czech Republic assesses the risk of collapse for 157 types of natural and semi-natural habitats defined in the second edition of the Habitat Catalogue of the Czech Republic. The assessment followed the guidelines for the IUCN Red List of Ecosystems as used in the European Red List of Habitats project, using the criteria of habitat reduction in quantity, restricted geographic distribution, and reduction in abiotic and biotic quality. Quantitative data for the assessment were partly taken from a detailed field habitat mapping at the national scale, and where no quantitative information was available, the values were estimated by summarizing independent judgements of 17 experts. In addition to the criteria involved in the Red List assessment, the experts also assessed various types of threatening factors and their importance for each habitat. Of 157 assessed habitats, 2 were Collapsed (CO), 14 Critically Endangered (CR), 32 Endangered (EN), 33 Vulnerable (VU), 30 Near Threatened (NT) and 46 Least Concern (LC). The largest proportion of CR + EN habitats was in the habitat group of springs and mires and in the group of wetlands. The threatening factors evaluated as the most important were successional changes after cessation of traditional management, eutrophication due to atmospheric nutrient deposition and pollution from agriculture, and increased drought in water-dependent habitats due to climate change or changes in local hydrological regime. The study shows that the IUCN criteria for Red List assessment of habitats, although developed for the global scale, are also applicable within small countries or regions. [ABSTRACT FROM AUTHOR]