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  • This dataset consists of change data for areas of Broad Habitats across Great Britain between 1990 and 1998, between 1990 and 2007, and between 1998 and 2007. The data are national estimates generated by analysing the sample data from up to 591 1km squares and scaling up to a national level. The data are summarized as change in habitat area per Land Class (areas of similar environmental characteristics). The sample sites are chosen from a stratified random sample, based on a 15 by 15 km grid of GB and using the 'ITE Land Classification' as a method of stratification. The data were collected as part of Countryside Survey, a unique study or 'audit' of the natural resources of the UK's countryside. The Survey has been carried out at regular intervals since 1978 by the Centre for Ecology & Hydrology. The countryside is sampled and surveyed using rigorous scientific methods, allowing us to compare new results with those from previous surveys. In this way we can detect the gradual and subtle changes that occur in the UK's countryside over time. Surveys have been carried out in 1978, 1984, 1990, 1998 and 2007 with repeated visits to the majority of squares. In addition to habitat areas, vegetation species data, soil data, linear habitat data, and freshwater habitat data are also gathered by Countryside Survey. Full details about this dataset can be found at https://doi.org/10.5285/7e2981e7-bd4c-4992-b7b0-1b1253bfd20d

  • The dataset consists of a distribution map of ash trees (Fraxinus excelsior) within woody linear features across Great Britain. The data is derived from Countryside Survey 2007 and includes trees recorded in lines of trees of a natural shape and lines of trees of an unnatural shape. Trees were mapped in 569 1km sample squares across Britain, and this national estimate dataset was derived from the sample data using ITE Land Classes. Full details about this dataset can be found at https://doi.org/10.5285/05e5d538-6be7-476d-9141-76d9328738a4

  • This dataset models positive plant habitat condition indicators across Great Britain (GB). This data provides a metric of plant diversity weighted by the species that you would expect and desire to have in a particular habitat type so indicates habitat condition. In each Countryside Survey 2007 area vegetation plot the number of positive plant habitat indicators (taken from a list created from Common Standards Monitoring Guidance and consultation with the Botanical society of the British Isles (BSBI)) for the habitat type in which the plot is located are counted. This count is then divided by the possible indicators for that habitat type (and multiplied by 100) to get a percentage value. This is extrapolated to 1km squares across GB using a generalised additive mixed model. Co-variables used in the model are Broad Habitat (the dominant broad habitat of the 1km square), air temperature, nitrogen deposition, sulphur deposition, precipitation and whether the plot is located in a Site of Special Scientific Interest (SSSI) (presence or absence data). Full details about this dataset can be found at https://doi.org/10.5285/cc5ae9b1-43a0-475e-9157-a9b7fccb24e7

  • Topsoil moisture data - gravimetric moisture content (%). Data is representative of 0 - 15 cm soil depth. Cores from 1098 plots within 256 1km by 1km squares were measured in 1998 and 2614 plots within 591 1km x 1km squares were analysed in 2007 across Great Britain. See Emmett et al. 2010 for further details of sampling and methods (http://nora.nerc.ac.uk/id/eprint/5201/1/CS_UK_2007_TR3%5B1%5D.pdf). Estimates of mean values within selected habitats and parent material characteristics across GB were made using Countryside Survey (CS) data from 1998 and 2007 using a mixed model approach. The estimated means of habitat/parent material combinations are modelled on dominant habitat and parent material characteristics derived from the Land Cover Map 2007 and Parent Material Model 2009, respectively. The parent material characteristics used were those which minimised AIC in the model (see Data documentation). Please see Scott, 2008 for further details of similar statistical analysis (http://nora.nerc.ac.uk/id/eprint/5202/1/CS_UK_2007_TR4%5B1%5D.pdf). Areas, such as urban and littoral rock, are not sampled by CS and therefore have no associated data. Also, in some circumstances sample sizes for particular habitat / parent material combinations were insufficient to estimate mean values. Full details about this dataset can be found at https://doi.org/10.5285/8db84900-5fdb-43be-a607-e56c843d9b87

  • Countryside Survey topsoil pH and bulk density (g cm-3) data is representative of 0 - 15 cm soil depth. Topsoil pH was measured using 10g of field moist soil with 25ml de-ionised water giving a ratio of soil to water of 1:2.5 by weight; bulk density was estimated by making detailed weight measurements throughout the soil processing procedure. For topsoil pH and bulk density data, a total of 2614 cores from 591 1km x 1km squares across Great Britain were collected and analysed in 2007. Please see Emmett et al. 2010 for further details of sampling and methods (http://nora.nerc.ac.uk/id/eprint/5201/1/CS_UK_2007_TR3%5B1%5D.pdf). Estimates of mean values within selected habitats and parent material characteristics across GB were made using CS data from 1978, 1998 and 2007 using a mixed model approach. Please see Scott, 2008 for further details of similar statistical analysis (http://nora.nerc.ac.uk/id/eprint/5202/1/CS_UK_2007_TR4%5B1%5D.pdf). The estimated means of habitat /parent material combinations using 2007 data are modelled on dominant habitat and parent material characteristics derived from the Land Cover Map 2007 and Parent Material Model 2009, respectively. The parent material characteristic used was that which minimised AIC in each model (see Dataset Documentation). The Countryside Survey looks at a range of physical, chemical and biological properties of the topsoil from a representative sample of habitats across the UK. Countryside Survey soils data are freely available under licence from the Environmental Information Data Centre catalogue. Full details about this dataset can be found at https://doi.org/10.5285/5dd624a9-55c9-4cc0-b366-d335991073c7

  • This dataset presents modelled estimates of soil pH at 1km2 resolution across Great Britain. A Generalized Additive Model approach was used with Countryside Survey soil pH data from 2007 and including climate, atmospheric deposition, habitat, soil and spatial predictors. The model is based on soil pH data from 2446 locations across Great Britain and is representative of 0-15 cm soil depth. Soil pH was measured using 10g of field moist soil with 25ml de-ionised water giving a ratio of soil to water of 1:2.5 by weight. The Countryside Survey looks at a range of physical, chemical and biological properties of the topsoil from a representative sample of habitats across the UK. This work was supported by the Natural Environment Research Council award number NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability. Full details about this dataset can be found at https://doi.org/10.5285/4b0e364d-61e6-48fb-8973-5eb18fb454cd

  • This dataset consists of landscape point feature information for points across Great Britain, surveyed in 1998. Data are presented as rows of information recorded as point features (for example individual trees, water bodies or structures), with associated plant species where relevant, within a set of 569 1km squares across Great Britain, surveyed during the Countryside Survey long term monitoring project (note: not all surveyed squares contained point features). The Countryside Survey is a unique study or 'audit' of the natural resources of the UK's countryside. The sample sites are chosen from a stratified random sample, based on a 15 by 15 km grid of GB. Surveys have been carried out in 1978, 1984, 1990, 1998 and 2007 by the Centre for Ecology & Hydrology, with repeated visits to the majority of squares. The countryside is sampled and surveyed using rigorous scientific methods, allowing us to compare new results with those from previous surveys. In this way we can detect the gradual and subtle changes that occur in the UK's countryside over time. In addition to point features, habitat areas, vegetation species data, soil data, linear habitat data, and freshwater habitat data are also gathered by Countryside Survey. Full details about this dataset can be found at https://doi.org/10.5285/ed10944f-40c8-4913-b3f5-13c8e844e153

  • Data consist of modelled estimates of observed/expected Biological Monitoring Working Party (an index for measuring the biological quality of rivers using selected families of macroinvertebrates as biological indicators) scores for freshwater streams across Great Britain (GB). The BMWP scores (1-10) are based on the principle that macroinvertebrates differ in their perceived sensitivity or tolerance to organic pollution (i.e. nutrient enrichment). Values greater than 1 indicate high water quality. Data pooled across two survey years (1998 and 2007) was used to model the relationships between headwater stream quality and catchment/stream characteristics for headwater streams across GB based on known relationships for headwater streams in Countryside Survey squares. Modelled estimates of stream water quality were based on a Boosted Regression Tree modelling approach . Full details about this dataset can be found at https://doi.org/10.5285/85e7beb6-e031-4397-a090-841b8c907d1b

  • This dataset presents the mean topsoil (0-15 cm) organic carbon concentration (g kg-1) and measures of its variability at 1 km resolution across Great Britain. The mean and variability metrics were calculated from an ensemble of eight previously published digital soil maps applied to all 1 km grid cells across GB where data were available from all eight maps. Four of the maps were generated from the 2007 UKCEH Countryside Survey topsoil data, two of which are available online to use. Two maps are from the International Soil Reference and Information Centre, ISRIC: SoilGrids250m v.1 (2017) and v.2 (2020) which are free to download. Two maps are from the EU’s Joint Research Centre (JRC): the OCTOP map of 2004 and LUCAS map of 2014 which are both free to download. The dataset comes in the form of a 7-band raster tiff file, with each band representing the following: 1. Mean predicted soil organic carbon concentration (g kg-1) of all 8 maps at each 1 km grid cell 2. Standard deviation (g kg-1) of all 8 maps at each 1 km grid cell 3. Coefficient of variation (unitless; the standard deviation divided by the mean) at each 1 km grid cell 4. Signal to noise ratio (unitless; the mean divided by the standard deviation) at each 1 km grid cell 5. Name of the map that deviates the most from the ensemble mean at each 1 km grid cell 6. Relative size (%) of the largest difference from the ensemble mean at each 1 km grid cell 7. Relative size of the largest difference from the ensemble mean expressed as the number of standard deviations exceeded at each 1 km grid cell This work was supported by the Natural Environment Research Council award number NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability. Full details about this dataset can be found at https://doi.org/10.5285/c3b400ea-f603-4bc2-9225-5f1abfa9fe65

  • This dataset presents modelled estimates of soil nitrogen concentration (% dry weight soil) at 1km2 resolution across Great Britain. A Generalized Additive Model approach was used with Countryside Survey soil nitrogen data from 2007 and including climate, atmospheric deposition, habitat, soil and spatial predictors. The model is based on soil nitrogen data from 913 locations across Great Britain and is representative of 0-15 cm soil depth. Soil N concentration was determined using a total elemental analyser. The Countryside Survey looks at a range of physical, chemical and biological properties of the topsoil from a representative sample of habitats across the UK. This work was supported by the Natural Environment Research Council award number NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability. Full details about this dataset can be found at https://doi.org/10.5285/8ec2d5ae-5d19-4b58-8cf6-aafdad485bb2