Interest features and linked critical load/level values for UK protected sites

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Dataset information

Country of origin
Updated
Created
Available languages
English
Keywords
nitrogen deposition, Protected Sites, natura 2000
Quality scoring

Dataset description

This dataset contains the critical load and level values for designated habitats and species (where there is an appropriate match) at protected sites across the UK. The data is available for designated interest features for the following designations: (i) Special Areas of Conservation (SAC) (ii) Special Protection Areas (SPA) (iii) Sites of Special Scientific Interest (SSSI) - England only. Critical loads and levels are set under the auspices of the United Nations Economic Commission for Europe (UNECE) Convention on Long-Range Transboundary Air Pollution. For nutrient nitrogen critical loads are based on empirical evidence, mainly observations from experiments and targeted gradient studies. These empirical critical loads are assigned to habitat classes of the European Nature Information System (EUNIS) to enable consistency of habitat terminology and understanding across Europe. In order the assign the relevant critical load to Annex I features, SSSI habitat features, or habitats of Annex II/SPA features, habitat correspondence tables are used to determine the relationship between the EUNIS classes for which nitrogen critical loads are set and the interest features. Critical loads of acidity are based on soil and habitat types. They are set for six Broad Habitats; acid grassland, calcareous grassland, dwarf shrub heath, bogs, montane, unmanaged coniferous and broadleaved woodland. Critical Levels for air pollutants are not habitat specific and have been set to cover broad vegetation types (e.g. forest arable, semi-natural), often with critical values set for sensitive lichens and bryophytes. They have been derived from experiments and observation that show varied effects on vegetation including visible injury symptoms of exposure and species composition changes in semi-natural vegetation. Full details about this dataset can be found at https://doi.org/10.5285/0c04050d-ed79-4864-a164-5eb25f8c6ebd
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190K+
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32
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2019
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