Data comprise plot location (latitude, longitude, elevation), taxonomic family and species names and measurements of trees (diameter, height, health). Presence of lianas (vines) and their measurements were also recorded. Funder: NERC - Brazil (CONFAP) Newton Fund: “Dry forest biomes in Brazil: biodiversity and ecosystem services” (NE/N000587/1) Full details about this dataset can be found at https://doi.org/10.5285/aa3babe9-072c-42ce-9ea5-9dbb921a922d

[This dataset is embargoed until March 31, 2024]. This dataset is in vitro validation of a potassium sensor that will be inserted into a plant stem. The dataset shows the sensitivity and selectivity of the fabricated potassium sensor. The data was obtained by measuring changes in electrical current with an increase in concentrations of the primary ion (K+) and interfering ion (Na+) to extract the sensitivity and selectivity, respectively using a semiconductor parameter analyser. K+ ion sensing data, measured directly inside a plant stem, are absent as the in vivo experiment should be optimised further. Full details about this dataset can be found at https://doi.org/10.5285/89998967-a974-4136-b650-b9af9f9d6969

This dataset contains modelled ammonia recapture by shelterbelts downwind of an ammonia source. The runs were located in the UK with ten years of averaged meteorological data for the different seasons of the year. Several tree species and tree heights were also taken into consideration and predictions of recapture were made for the year 5, 15, 25 and 50 after planting . Two models were coupled to obtain this dataset; Open-source Field Operation And Manipulation (OpenFOAM) and MOdel of Dispersion and Deposition of Ammonia over the Short-range in two dimensions (MODDAS-2D). This dataset was created by the Modelling Uncertainty for Decision Making on Ammonia mitigation with Trees in the landscape (MUDMAT) project funded by NERC. Full details about this dataset can be found at https://doi.org/10.5285/83a2a25c-dbb7-4760-ae3d-21904f3dd278

KRILLBASE is a data rescue and compilation project which aims to improve the availability of information on two of the Southern Ocean''s most important zooplankton taxa: Antarctic krill (Euphausia superba) and salps (Family Salpidae). In 2016, the project released a database of information from 15,194 scientific net hauls, collected between 1926 and 2016 by scientists from ten countries. These data, on the density of Antarctic krill and salps, provide a resource for analysing the distribution and abundance of these taxa throughout the Southern Ocean, to support ecological and biogeochemical research as well as fisheries management and conservation. The data are available as a downloadable csv files and via a seachable web interface. Each row of the main data table represents either a net haul or a composite of several net hauls. The columns describe searchable and filterable sampling and environmental information as well as the krill and salp density. The krill data are presented as both the observed density (NUMBER_OF_KRILL_UNDER_1M2, no.m-2) and the density standardised to a single, relatively efficient sampling method (STANDARDISED_KRILL_UNDER_1M2, no.m-2). The salp data are presented as observed density for all species combined, where an individual can be either a solitary oozoid or a member of an aggregate chain (NUMBER_OF_SALPS_UNDER_1M2, no.m-2). 12,758 of the net hauls in the database include krill data, 9,726 include salp data. 7,295 of the net hauls include both krill and salp data. For hauls where data for either salps or krill were not available the relevant field is blank. The RECORD_TYPE column distinguishes between four types of record and we emphasise that every analysis of the data should first screen on this field to avoid using the same data twice. Most records are labelled "haul", and these result from a single net sampling the water column at a specific station. Others, labelled "stratified pooled haul", are the combined result of several (typically three) stratified hauls (labelled "stratified haul") sampling different parts of the water column. A small number of records, labelled "survey mean" represent the arithmetic mean densities from multiple stations as this was the only recoverable information from the relevant surveys, which were mainly conducted in the 1980s. The dataset is fully described in the following publication which should be cited in published analyses of these data: Atkinson A, Hill SL, Pakhomov E, Siegel V, Anadon R, Chiba S, Daly KL, Downie R, Fielding S, Fretwell P, Gerrish L, Hosie GW, Jessopp MJ, Kawaguchi S, Krafft BA, Loeb V, Nishikawa J, Peat HJ, Reiss CS, Ross RM, Langdon B Quetin, Schmidt K, Steinberg DK, Subramaniam RC, Tarling GA, Ward P (2017) KRILLBASE: a circumpolar database of Antarctic krill and salp numerical densities, 1926-2016. Earth Syst. Sci. Data, 9: 193-210 (doi:10.5194/essd-9-193-2017)

This dataset is part of the study of mimetic host shifts in an endangered social parasite of ants, which is a joint study of the NERC's Centre for Ecology & Hydrology(UK), the University of Oxford(UK), University of Bialystok(Poland), Polish Academy of Sciences(Poland) and UFZ Helmholtz Centre for Environmental Research(Germany). Combined with datasets collected from previous study, they compare the proportions of caterpillars of Maculinea rebeli being adopted by resident Myrmica ant species near Przemysl, Poland in autumn with proportions of successful survivors the following summer to establish host specificity of the socially parasitic butterfly species. The data comprise: the study year, the ant species, total number of ant nest, the number of caterpillar survivors found in the nest of each ant species, number of nests with caterpillar presence and total number of nests without caterpillar presence. They were obtained from one population for 4 years(Y2001, Y2003, Y2004, Y2005). Detailed research method can be found in Thomas et al. (2013) Mimetic host shifts in an endangered social parasite of ants. Proc. R. Soc. B vol. 280 no.1751. (doi: 10.1098/rspb.2012.2336) Full details about this nonGeographicDataset can be found at https://doi.org/10.5285/b472d635-d8fa-4c39-acfe-2b285ca0b9a8

This dataset consists of plant species presence and abundance in different sizes and types of plots from 591 1km x 1km square sites surveyed across Great Britain in 2007. Many of the plots are repeated from surveys in 1978, 1990 and 1998. General information about the plot was recorded including plot number and type as well as species presence and (usually) cover. Data were collected under the Countryside Survey long term monitoring project managed by the Centre for Ecology & Hydrology. Full details about this dataset can be found at https://doi.org/10.5285/57f97915-8ff1-473b-8c77-2564cbd747bc

This dataset comprises summary data for a literature search on invasive alien species (IAS) control efficacy and their outcomes. It contains article title, authors, journal, year of publication, taxa investigated, type of control method, and whether the paper evaluated outcomes. Overall, 373 publications were assessed. The literature search on Web of Science and the subsequent screening were conducted between May and July 2020. Full details about this dataset can be found at https://doi.org/10.5285/7b274f84-0d93-416d-a5b3-54f3387cebd5

This dataset gives axiophyte score for plants in Great Britain, based on Botanical Society of Britain and Ireland (BSBI) published lists of axiophytes for 24 counties in Great Britain. Axiophytes have been defined as 'worthy plants', that is, species that are indicative of high quality habitat within a particular region. This information product takes the county lists that were available in May 2016, and summarises the data in order to produce national (i.e. Great Britain) level scores of 'axiophyte-ness'; that is, the extent to which a species has been selected as a good indicator of high quality habitat where it occurs. This meta-list of axiophytes will be updated in the future as more county-level lists become available. 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/af2ac4af-12c6-4152-8ed7-e886ed19622b

Collated indices are a relative measure of butterfly abundance across sites monitored as part of the UK Butterfly Monitoring Scheme. Data from all survey sites (standard UKBMS transects, Wider Countryside Survey transects and targeted species surveys such as timed, larval web and egg counts) are used in the calculation of these indices. The statistics are presented as log10 values. These values are centred round an arbitrary value of 2 as a mean for the time series in order to help show which years are below or above average. Collated indices are calculated annually for each individual butterfly species that has been recorded on five or more sites in that year. Indices are calculated at UK level and at individual country level for England, Scotland, Wales and Northern Ireland where sufficient data are available. Based on this criterion, collated indices have been calculated for the entire time series from 1976 (UK, England and Wales), 1979 (Scotland) and 2004 (Northern Ireland) to the current year for the majority of species, but for some rarer species this has not been possible in some years, particular those in the first part of the time series. Collated indices are calculated using a log-linear model incorporating individual site indices from all monitored sites across the UK or country for a given species in a given year. The number of sites for each species ranges from 5 to several hundred or more and fluctuates from year to year. By 2010 almost 2,000 sites were monitored in total across the UK, with this number rising to more than 3,000 over the next decade. Collated indices are calculated so that we can determine how butterfly populations are changing over time across the UK. This data can be used, for example, to determine where to target conservation efforts and more generally the condition of the UK countryside. Butterflies are recognised as important indicators of biodiversity and environmental change, for example in UK and country Biodiversity Indicators, and have been used in numerous studies of the impacts of climate and habitat change on biodiversity. The UK Butterfly Monitoring Scheme is organized and funded by Butterfly Conservation (BC), the Centre for Ecology & Hydrology (CEH), the British Trust for Ornithology (BTO), and the Joint Nature Conservation Committee (JNCC). The UKBMS is indebted to all volunteers who contribute data to the scheme. 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/10.5285/657a64b2-8c34-43d2-a0f0-662ddf73c720

Data comprises of the uptake of the plant nutrient phosphorus (P) by seven common and often co-occurring herbaceous plants grown in limestone grassland soil in pots. P uptake is from one of three different sources of P that were injected into the soil, with the P sources being labelled with radio-isotope 33P, such that uptake of this could be quantified by assessing the radioactivity of the plant tissue. The plant species were grown in pots as monocultures, and as mixed communities containing all seven species. The 33P labelled P sources that were injected into the soil were orthophosphate, DNA and calcium phosphate. Assessment of the amount of 33P taken up was undertaken by harvesting and analysing plant shoots six days after the 33P source was injected into the soil. The datasets contain biomass of the harvested plant material, its radioactivity as assessed by scintillation counting, and the calculated proportion of the 33P supplied that was taken up into plant shoots. The data also contains % cover abundance values of the plant species from surveys undertaken at Wardlow Hay Cop, the limestone grassland from where the soil was sourced on which the plants were grown for the 33P addition study. Full details about this dataset can be found at https://doi.org/10.5285/87cdc267-a8c7-4f59-83b4-1bceaae837ad