nonCciKeyword

Scotland

93 record(s)

 

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From 1 - 10 / 93
  • The dataset collates the relative concentration of nearly 300 antimicrobial resistance (AMR) genes found in soil locations across Scotland. Soils were obtained from the National Soils Inventory of Scotland (NSIS2), from which the total community DNA were extracted and provided to assess AMR gene content. Sampling of the NSIS2 was conducted between 2007-2010 at 183 soil locations representing intersections of a 20km grid across all of Scotland. For each sample, nearly 300 AMR genes were assessed representing major antibiotic classes, and included many resistance traits: aminoglycosides, beta-lactams, FCA (fluoroquinolone, quinolone, chloramphenicol, florfenicol and amphenicol resistance genes), MLSB (macrolide, lincosamide, streptogramin B), tetracycline, vancomycin, sulphonamide, efflux pumps and integron genes. The data represent relative gene abundance, i.e., the amount of genes per “total bacteria.” Full details about this dataset can be found at https://doi.org/10.5285/d3498e93-4ac5-4eab-bc1a-eb2328771d24

  • These spatial layers contain risk factors and overall risk scores, representing relative risk of Phytophthora infection (Phytophthora ramorum and P. kernoviae), for heathland fragments across Scotland. Risk factors include climate suitability, proximity to road and river networks and suitability of habitat for key hosts of Phytophthora and were broadly concurrent with the period between 2007 and 2013. This research was funded by the Scottish Government under research contract CR/2008/55, 'Study of the epidemiology of Phytophthora ramorum and Phytophthora kernoviae in managed gardens and heathlands in Scotland' and involved collaborators from St Andrews University, Science and Advice for Scottish Agriculture (SASA), Scottish Natural Heritage (SNH), Forestry Commission, the Food and Environment Research Agency (FERA) and the Centre for Ecology & Hydrology (CEH). Full details about this dataset can be found at https://doi.org/10.5285/8f09b7e6-6daa-4823-b338-4edad8de1461

  • These spatial layers quantify the predicted habitat suitability for Rhododendron ponticum across Scotland. These layers were developed with reference to this species role as reservoir host for Phytophthora plant pathogens, but should have value for management of Rhododendron ponticum as a problematic invasive species. The models were developed by combining biological records of R. ponticum with climate, soil, elevation and woodland cover data. The dataset contains averaged estimates for R. ponticum presence, associated standard deviation for each estimate and locations where environmental conditions in the study region strayed too far from the training set data. This research was funded by the Scottish Government under research contract CR/2008/55, 'Study of the epidemiology of Phytophthora ramorum and Phytophthora kernoviae in managed gardens and heathlands in Scotland' and involved collaborators from St Andrews University, Science and Advice for Scottish Agriculture (SASA), Scottish Natural Heritage (SNH), Forest Research, Forestry Commission and Centre for Ecology & Hydrology (CEH). Full details about this dataset can be found at https://doi.org/10.5285/b984a173-8d80-4781-8a53-bef7bcb0d198

  • This dataset consists of Particle Size Distribution (PSD) measurements made on 419 archived topsoil samples and derived aggregate stability metrics from arable and grassland habitats across Great Britain in 2007. Laser granulometry was used to measure PSD of 1–2 mm aggregates before and after sonication and the difference in their Mean Weight Diameter (MWD) used to indicate aggregate stability. The samples were collected as part of the Countryside Survey monitoring programme, a unique study or ‘audit’ of the natural resources of the UK’s countryside. The analyses were conducted as part of study aiming to quantify how soil quality indicators change across a gradient of agricultural land management and to identify conditions that determine the ability of different soils to resist and recover from perturbations. Full details about this dataset can be found at https://doi.org/10.5285/be3793b6-90fb-4e4c-9515-220cc33223b9

  • This dataset consists of a 1km resolution raster version of the Land Cover Map 2007 for Great Britain. The raster consists of 23 bands. Within each band, each 1km pixel represents a percentage cover value for one of 23 target classes, broadly representing Broad Habitats (see below). The dataset is part of a series of data products produced by the Centre for Ecology & Hydrology known as LCM2007. LCM2007 is a parcel-based thematic classification of satellite image data covering the entire United Kingdom. The map updates and upgrades the Land Cover Map of Great Britain (LCMGB) 1990 and LCM2000. Like the earlier 1990 and 2000 products, LCM2007 is derived from a computer classification of satellite scenes obtained mainly from Landsat, IRS and SPOT sensors and also incorporates information derived from other ancillary datasets. LCM2007 was classified using a nomenclature corresponding to the Joint Nature Conservation Committee (JNCC) Broad Habitats, which encompasses the entire range of UK habitats. In addition, it recorded further detail where possible. The series of LCM2007 products includes vector and raster formats, with a number of different versions containing varying levels of detail and at different spatial resolutions. Full details about this dataset can be found at https://doi.org/10.5285/fdf8c8d3-5998-45a5-8431-7f5e6302fc32

  • These spatial layers contain risk factors and overall risk scores, representing relative risk of Phytophthora infection (Phytophthora ramorum and P. kernoviae), for Core Native Woodland and known larch fragments across Scotland. Risk factors include climate suitability, proximity to road and river networks and suitability of habitat for key hosts of Phytophthora and were broadly concurrent with the period between 2007 and 2013. This research was funded by the Scottish Government under research contract CR/2008/55, 'Study of the epidemiology of Phytophthora ramorum and Phytophthora kernoviae in managed gardens and heathlands in Scotland' and involved collaborators from St Andrews University, Science and Advice for Scottish Agriculture (SASA), Scottish Natural Heritage (SNH), Forestry Commission, the Food and Environment Research Agency (FERA) and the Centre for Ecology & Hydrology (CEH). Full details about this dataset can be found at https://doi.org/10.5285/29726cda-09f5-4661-8fd4-ddaa5555466a

  • This dataset consists of a 1km resolution raster version of the Land Cover Map 2007 for Great Britain. The raster consists of 10 bands. Within each band, each 1km pixel represents a percentage cover value for one of 10 aggregate classes. The aggregate classes are aggregations of the target classes, broadly representing Broad Habitats (see below). The dataset is part of a series of data products produced by the Centre for Ecology & Hydrology known as LCM2007. LCM2007 is a parcel-based thematic classification of satellite image data covering the entire United Kingdom. The map updates and upgrades the Land Cover Map of Great Britain (LCMGB) 1990 and LCM2000. Like the earlier 1990 and 2000 products, LCM2007 is derived from a computer classification of satellite scenes obtained mainly from Landsat, IRS and SPOT sensors and also incorporates information derived from other ancillary datasets. LCM2007 was classified using a nomenclature corresponding to the Joint Nature Conservation Committee (JNCC) Broad Habitats, which encompasses the entire range of UK habitats. In addition, it recorded further detail where possible. The series of LCM2007 products includes vector and raster formats, with a number of different versions containing varying levels of detail and at different spatial resolutions. Full details about this dataset can be found at https://doi.org/10.5285/289805c2-4be7-4fb5-b6ec-1539ed88c43d

  • This dataset consists of change data for areas of Broad Habitats across Great Britain between 1990 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 percentage increase or decrease in habitat area per Land Class (areas of similar environmental characteristics) and are in a vector format. 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/10.5285/4af5abe4-158a-4736-b318-ec660e09e45a

  • This dataset consists of change data for areas of Broad Habitats across Great Britain between 1990 and 1998. The data are national estimates generated by analysing the sample data from up to 569 1km squares and scaling up to a national level. The data are summarized as percentage increase or decrease in habitat area per Land Class (areas of similar environmental characteristics) and are in a vector format. 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/10.5285/2bfdede9-8008-4ba3-ac8e-af4e6ab9888b

  • This dataset consists of change data for areas of Broad Habitats across Great Britain 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 percentage increase or decrease in habitat area per Land Class (areas of similar environmental characteristics) and are in a vector format. 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/d83a0f9e-00c9-4d2d-9d0a-e92a16dcb334