This web map service provides a 1km resolution gridded coverage of wooded areas in riparian zones (river- or streamsides) across Great Britain. The areas classified as riparian in this dataset are defined by a 50 metre buffer applied to the CEH 1:50000 watercourse network. Wooded areas within this zone are identified as those classified by the Land Cover Map of Great Britain 2007 as either coniferous or deciduous woodland. The data are aggregated to a 1km resolution.

The datasets were collected during experiments undertaken to examine survival rates and larval performance of Speckled Wood butterflies (Pararge aegeria) in different habitats (grassland and woodland). The experiments were carried out between 2008 and 2010 by the University of York, at sites in Yorkshire, Great Britain. Full details about this dataset can be found at https://doi.org/10.5285/ecb17680-da2e-49ae-b250-2d04a6a08d2a

This code: (1) Generates data for the weak-selection mathematical model. This is contained in the "Generate_data_for_island_model_weak_selection" script. (2) Generates data for the agent-based simulation model, which accounts for stronger selection and finite populations. This is contained in the "Generate_data_for_agent_based_simulation" script. (3) Generates data for the version of the agent-based simulation model where there is no tag mutation, in which balancing selection is examined via tag fixation times. This is contained in the "Generate_data_for_balancing_selection_finite_pop" script. Full details about this nonGeographicDataset can be found at https://doi.org/10.5285/aec1e55f-f6ac-4673-9e93-706b44df88f1

This web map service shows the suitability of climate conditions for infection of Phytophthora ramorum and Phytophthora kernoviae across the UK. Suitability is mapped for individual years 2007 to 2011; the average and standard deviations for the whole period are also provided. The model is based on laboratory data of environmental responses of these pathogens and hourly temperature and relative humidity regimes in the period, and describes how many times infection could have been completed within running 48 hour periods through the year. 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).

This code contains scripts for generating data (specifically, these scripts numerically implement our mathematical model). There are three data generating scripts: "Script_for_generating_parameter_sweep_data.m", "Script_for_generating_single_trial_data.m", "Script_for_generating_initial_genotype_frequencies.m". Running the "Script_for_generating_parameter_sweep_data.m" script will generate long-term (equilibrium) results for a range of d (parasite virulence) and lag (parasite evolutionary lag) values, and save these results in matrices. Running the "Script_for_generating_single_trial_data.m" script will generate over-time (dynamical) results for a specific set of parameter values. Both of these scripts call the "Script_for_generating_initial_genotype_frequencies.m" in order to generate the initial genotype frequencies that start off each run. Full details about this nonGeographicDataset can be found at https://doi.org/10.5285/0b78e33c-1f81-4125-9558-c354292bda92

This is a database of all known birds, bryophytes, fungi, invertebrates, lichens and mammals that use Scots Pine (Pinus sylvestris) in the UK. Scots pine is the UK’s only native conifer that is used commercially and is the most common tree in the UK’s native Caledonian pine woods. In total 1589 species are listed in the database. For each species a level of association with Scots pine is provided, ranging from obligate (only found on Scots pine) to cosmopolitan (found on a wide range of other tree species). Data on the ecology of each Scots pine associated species were collated: part of tree used, and use made of tree (feeding, roosting, breeding). Data on use or otherwise of 34 other tree species were also collated for each of the 1589 species. Full details about this dataset can be found at https://doi.org/10.5285/97f8c19b-7451-4809-b011-0f9cf3eb8430

In 2021 and 2022 a total of 60 broadleaved woodland restoration sites from Central Scotland (2021) and English Midlands (2022) and a further six wildcard sites made up of ancient woodlands (2 in Scotland and 2 in England) and rewilding sites (2 in England) were surveyed to calculate metrics of ecological complexity from biodiversity and habitat structure data. In each woodland, we monitored ground flora (surveyed using quadrats), adult trees (within circular plots), tree seedlings and saplings (transects), volume of deadwood (measured within transects), canopy cover estimations, invertebrates on understorey vegetation (surveyed by tray beating) and (mostly) flying invertebrates (surveyed using Malaise traps). Information on site characteristics were collected, including age of the restoration site, former land-use and features of the surrounding landscape. Full details about this dataset can be found at https://doi.org/10.5285/8c997943-1f90-4897-87b3-491eaef534ec

This dataset contains instream dissolved oxygen data collected continuously at one minute intervals for five sites in the Hampshire Avon catchment in the United Kingdom. Data were collected between August 2014 and August 2015 using miniDOT loggers. Full details about this dataset can be found at https://doi.org/10.5285/840228a7-40a1-4db4-aef0-a9fea2079987

The database of chemical composition of Central Asian forage plants contains just under 1000 desert and steppe species with information such as Latin and Russian names and family and related records of chemical composition from various sources including percentages by weight of protein, ash, cellulose and fat. Where available, it also includes data on digestible protein content, metabolisable energy and Soviet Feed Units (SFU). Records also include information on the country, location, season or month and phenological phase at time of collection of each sample. As one of the original uses of the database was for modelling food and energy intake by the saiga antelope, it also includes information identifying saiga food plant species along with sources of this information. Data on the edibility of many species for livestock in different seasons are also available. See the detailed documentation available here for more information on the data types, definitions and sources. NB The database is in text format and must be imported e.g. into relational database software, as Unicode (UTF-8) in order to convert the Cyrillic characters in Russian names. Full details about this dataset can be found at https://doi.org/10.5285/6a5a9a2a-730b-49f7-9e42-2295040aee56

Data are presented showing change in saltmarsh extent along 25 estuaries/embayments in six regions across Great Britain, between 1846 and 2016. Data were captured from maps and aerial photographs. Marsh extent was delineated a scale of 1:7,500 by placing vertices every 5 m along the marsh edge. Error introduced from: (i) inaccuracies in the basemap used to georeference maps and aerial photographs; (ii) the georeferencing procedure itself; (iii) the interpreter when placing vertices on the marsh edge; and (iv) map and photo distortions that occurred prior to digitisation were calculated and used to estimate the root mean square error (RMSE) in areal extent of each marsh complex. Measures of marsh extent were only recorded if maps and aerial photographs were available for the entire estuary/embayment. Data was collected as part of a study on the large-scale, long-term trends and causes of lateral saltmarsh change. The data was used in the analysis for Ladd et al. (2019). C. Ladd and M.F. Duggan-Edwards carried out the collection and processing of the saltmarsh extent data. All authors contributed to the interpretation of the data. The work was carried out under the NERC programme - Carbon Storage in Intertidal Environment (C-SIDE), NERC grant reference NE/R010846/1. Full details about this dataset can be found at https://doi.org/10.5285/03b62fd0-41e2-4355-9a06-1697117f0717