This data set comprises plant species, habitat and land cover types, and major biota present, collected during an ecological survey of marginal uplands in the English county of Cumbria, using standardised survey methods. The survey was undertaken by the Institute of Terrestrial Ecology (a forerunner of the Centre for Ecology & Hydrology) in 1978 within a stratified random set of sites. In total, up to 262 plots were surveyed from within 52 x 1km squares. Full details about this dataset can be found at https://doi.org/10.5285/a4f2d52b-1515-434e-bfc3-83b3a53be1c5

A set of data arising from a detailed ecological survey of the native Scots Pine woodland habitats within Scotland. In all, 27 woods from throughout Scotland were identified as the major remaining native pinewoods, and within each wood 16 randomly selected 200m2 plots were surveyed (26 of the woods were surveyed in 1971, with 1 extra wood surveyed in 1972). Details about the trees, ground flora, soil, habitat types as well as general plot information were collected for each plot using standardized procedures and coding systems. The survey was carried out by the Nature Conservancy, a forerunner of the Centre for Ecology & Hydrology. Full details about this dataset can be found at https://doi.org/10.5285/56a48373-771c-4d4a-8b5a-45ef496c6e55

This dataset contains ecosystem function and vegetation survey data from soils collected from Salisbury Plain, UK. The sites were selected to reflect the four main grassland management types on Salisbury Plain ranging from arable cropland to species rich grassland, with six representative grassland plots for each type (24 sites in total). Each site had four replicates for each variable measured. The data collected was intended to illustrate a gradient of ecosystem functioning and vegetation change as the grassland becomes more extensively managed. The field sampling was conducted by the University of Manchester and the Centre for Ecology & Hydrology at Wallingford. Soils were extracted for nutrients and analysed by the University of Manchester. The data includes vegetation surveys, where the cover of each plant species present was assessed, and diversity indices were calculated. Furthermore, greenhouse gas fluxes were measured in situ, and soil nutrients and microbial biomass were also determined. Full details about this dataset can be found at https://doi.org/10.5285/0e0a89e1-21f9-413e-8d7e-764b0b714dd6

A set of data arising from a detailed ecological re-survey of the native Scots Pine woodland habitats within Scotland. In all, 27 woods from throughout Scotland were identified as the major remaining native pinewoods, and within each wood sixteen randomly selected 200m2 plots were surveyed between 2018 and 2022. Details about the trees, ground flora, soil, habitat types as well as general plot information were collected for each plot using standardized procedures and coding systems. The survey was a repeat of an identical survey carried out in 1971, and thus allows an assessment of change in the woodlands since that time. The survey was funded by a consortium led by the Woodland Trust, and carried out by staff employed by the UK Centre for Ecology & Hydrology. Full details about this dataset can be found at https://doi.org/10.5285/5e268e86-4a4f-4112-bf2d-c3b0179c915c

Bird species data from the UK Environmental Change Network (ECN) lowland terrestrial sites. These data were collected, using the British Trust for Ornithology (BTO)'s Common Bird Census methodology (CBC), at ECN's lowland terrestrial sites using a standard protocol. This protocol was abandoned in favour of the Breeding Bird Survey (Rennie et al (2017) UK Environmental Change Network (ECN) bird data: 1995-2015 https://doi.org/10.5285/5886c3ba-1fa5-49c0-8da8-40e69a10d2b5 ) in 1999. However, some sites continued to follow this protocol for a number of years after 1999 to allow comparison with the Breeding Bird Survey data. The CBC uses a mapping method in which a series of visits are made to all parts of a defined plot during the breeding season and contacts with birds by sight or sound are recorded on large-scale maps. Information from the series of visits is combined to estimate the number of territories found. Annual data are recorded but the date ranges available are variable for each site. ECN is the UK's long-term environmental monitoring programme. It is a multi-agency programme sponsored by a consortium of fourteen government departments and agencies. These organisations contribute to the programme through funding either site monitoring and/or network co-ordination activities. These organisations are: Agri-Food and Biosciences Institute, Biotechnology and Biological Sciences Research Council, Cyfoeth Naturiol Cymru - Natural Resources Wales, Defence Science & Technology Laboratory, Department for Environment, Food and Rural Affairs, Environment Agency, Forestry Commission, Llywodraeth Cymru - Welsh Government, Natural England, Natural Environment Research Council, Northern Ireland Environment Agency, Scottish Environment Protection Agency, Scottish Government and Scottish Natural Heritage. Full details about this dataset can be found at https://doi.org/10.5285/8582a02c-b28c-45d2-afa1-c1e85fba023d

This dataset summarises cetacean sightings made during January and February 2019 by an experienced team of cetacean researchers doing regular small-scale surveys in coastal waters close to Cumberland Bay, South Georgia. Some surveys were just within Cumberland Bay, and others include locations to the west and east of Cumberland Bay, as far as Stromness Bay (west) and St Andrews Bay (east). The dataset includes survey tracks, survey effort periods, species sighted and numbers of animals encountered. Over the survey period, Cumberland Bay alone was surveyed six times. Cumberland Bay plus adjoining waters were surveyed nine times, a total of 25:12 hr of search effort for all surveys. Nine expeditions were carried out in January (13:39 hr effort, with whales sighted on six surveys) and six in February (11:33 hr effort, with whales sighted on three surveys). A total of 43 whales (41 humpback whales) were observed during 26 sighting events, nine of which were within Cumberland Bay; a further 10 humpback whales were sighted at the entrance to the Bay (Right Whale Rocks), making a total of 19 humpback whale sightings within or at the entrance to Cumberland Bay. EU BEST 2.0 Medium Grant 1594, DARWIN PLUS award DPLUS057 and funding from the South Georgia Heritage Trust and Friends of South Georgia Island.

Data comprise results of a soil survey in England, Scotland and Wales carried out during 2013 and 2014 as part of the NERC Macronutrient Cycles project: LTLS : Analysing and simulating long-term and large-scale interactions of carbon nitrogen and phosphorus in UK land, freshwater and atmosphere. The data include bulk density measurements, charcoal and coal determinations, site locations and sampling dates, site vegetation data, soil chemistry and isotope data, soil classifications, information on soil cores collected and soil texture data. Full details about this dataset can be found at https://doi.org/10.5285/17bebd7e-d342-49fd-b631-841ff148ecb0

This data set is a combination of trapping data, tracking data, vegetation/habitat data and data on the gut microbiome composition of wild rodents caught in 4 ha study site in Holly Hill in Wytham Woods, Oxford, UK, from November 2018 to November 2019. Three species of rodents were trapped with Sherman live-traps fortnightly for 12 months: wood mouse (Apodemus sylvaticus), yellow-necked mouse (Apodemus flavicollis) and bank vole (Myodes glareolus). Upon capture, they were measured, weighted, sexed, aged and a faecal sample was collected from all rodent individuals for microbiome analyses. All rodents were released to their location of capture. First time each individual was captured, they were injected with a permanent subcutaneous Radio-Frequency Identification(RFID)-tag (Passive Integrated Transponder-tag). The tagged rodents were subsequently tracked from February to November 2019 with a set of 120 custom-made tracking devices (loggers). Loggers recorded to time-stamped presence of any tagged individual that passed near it, producing occurrence data suitable for inferring spatiotemporal activity patterns of rodents, such as temporal niches, home ranges and social networks. Bacterial DNA extracted from faecal samples were used to profile their gut microbiome composition. The study area was surveyed for vegetation and microhabitat variation by gathering habitat data of each 10 x 10 m grid square across the 4 ha plot. Data included list of plant species (visible in late May), coverage by the main ground cover types, canopy openness and amount of dead wood in each grid square. This work was funded by a NC3Rs Fellowship to Sarah Knowles, and NERC independent Research Fellowship to Sarah Knowles (NE/L011867/1) Full details about this dataset can be found at https://doi.org/10.5285/043513e5-406c-4477-89aa-c96059acb232

This dataset contains information about soil near-surface physical and hydrological properties, vegetation observations and land use & management information across the Thames catchment (UK). It was collected during the ‘Landwise' project's ‘Broad-scale field survey' which sampled 1836 location points across a total of 164 fields/land parcels. The aim of the survey was to quantify the impact of innovative land use and management on soil properties, with implications for natural flood management. The surveyed fields were selected to represent four broad land use and management classes (arable with and without grass in rotation, permanent grassland and broadleaf woodland) and five generalised soil/geology classes. Approximately eight fields were sampled for each of the twenty combinations of land use and soil/geology class. The sampled fields cover a range of traditional and innovative agricultural practices. Within each field/parcel, representative sampling locations were selected to cover the anticipated range of soil variability, including typical infield, untrafficked margins and trafficked headlands/tramlines etc. Sampling was undertaken once during the period 2018-2021. Samples were measured and analysed using a range of field and laboratory techniques (see Data Lineage). Point data include: 1. Survey point location (British National Grid coordinates) 2. Soil quantitative measurements (near-surface: 0 – 50 mm below ground level): dry bulk density, volumetric water content, organic matter, derived porosity, derived porosity accounting for variable organic matter, particle size distribution and texture classification 3. Vegetation quantitative measurements: maximum and minimum height 4. Soil qualitative measurements: hand texture classification, aggregate stability test slaking and dispersion results, hydrochloric acid test for calcareous soil, and for a subset of locations Visual Evaluation of Soil Structure (VESS) score 5. Observations (also classified into groups): soil surface condition (e.g. slaked/unslaked/capped/poached etc.), vegetation type Field contextual data include: 1. Land owner/manager responses to a land use and management questionnaire (primary data) including information on: crop types/rotation, cover crops, herbal leys, organic or conventional, organic amendments, lime additions, tillage, last ploughed, tramlines, buffer strips, field drainage, grass species, livestock, last grazed, stocking density, grazing weeks per year, stock out-wintering, mob or paddock grazing, woodland management, tree species, woodland age, path management, land use history, flooding history, waterlogging, water or sediment runoff 2. Classification of selected questionnaire free text responses into categories (derived secondary data) 3. General field observations (primary data) including: slope gradient and shape, surface form, surface water, surface condition (slaking, capped, ruts, wheelings, poaching etc.), soil erosion or deposition features As agreed with the survey participants, this dataset has been anonymised by removing location specific information, such as farm and field names, along with any other personally identifiable information. As also agreed, point data location coordinates have been degraded to the nearest 1 km grid point. The dataset was co-produced by the UK Centre for Ecology and Hydrology and Landwise Partners as part of the Landwise Natural Flood Management project, supported by the Natural Environment Research Council (Grant NE/R004668/1). The participation and assistance of the land owners and managers is gratefully acknowledged. Full details about this dataset can be found at https://doi.org/10.5285/9ab5285f-e9c4-4588-ba21-476e79e87668