This dataset presents a compendium of field-based earthworm data sources and associated meta-data from across the United Kingdom and Ireland (‘Worm source’). These were compiled up to 2021 and include 257 data sources, the earliest dating back to 1891. Source meta-data covers the type of quantitative earthworm data (i.e. incidence, abundance, biomass, taxa), methodological details (e.g. sampling method/s, location/s, whether sampled plots were natural or experimental, sampling year/s), and environmental information (e.g. habitat/land-use, inclusion of climate data and basic soil properties). Data sources were collected through literature searches on Web of Science and Google Scholar, as well as directly from original authors/data holders where possible. The data sources were compiled with the aim of gathering quantitative data on earthworm species and populations to develop earthworm abundance and niche models, and toward a modelling framework for earthworm impacts on soil processes. This work is part of the Soil Organic Carbon Dynamics (SOC-D) project funded by the NERC UK-SCAPE programme (Grant reference NE/R016429/1). Full details about this dataset can be found at https://doi.org/10.5285/1a1000a8-4e7e-4851-8784-94c7ba3e164f

The dataset contains: (i) estimates of zinc tolerance for 50 populations of Silene uniflora in the UK and Ireland generated between 03/2021 and 09/2021. The data were collected using cuttings from wild collected specimens. Root growth of cuttings in zinc rich media was assessed using deep water culture experiments. The data set contains the zinc tolerance (mean and standard deviations of root growth scores) and the number of cuttings assessed for each population; (ii) GPS positions describing the locations of 56 populations of Silene uniflora in the UK and Ireland which were observed between 2018 and 2021. Basic habitat type (montane, serpentine, mine, coastal) information is also included. The work was supported by the Natural Environment Research Council NE/R001081/1. Full details about this dataset can be found at https://doi.org/10.5285/af4735e3-b5ba-4e0b-8a41-503eeff89a82

The dataset contains annual abundance indices and trends in abundance for 477 species of moths (mostly macro-moths) estimated using the data collected by Rothamsted Insect Survey (RIS) from their light-trap network between the years 1968 and 2021. The abundance indices are trends calculated using Generalized Abundance Index (GAI) models. The trends are presented as Annual Growth Rates (AGR), and the total percentage changes over the time series for each species are also provided. The indices and trends include 95% confidence limits estimated via bootstrapping. Abundance indices and trends are presented for the entire network of traps across Britain, Ireland, and the Channel Islands, as well as country level analyses for England, Scotland, and Wales. Full details about this dataset can be found at https://doi.org/10.5285/75161449-1382-42a4-bb91-58835740cc75

The dataset contains a current inventory of vascular plant species and their attributes present in the flora of Britain and Ireland. The species list is based on the most recent key to the flora of Britain and Ireland, with taxon names linked to unique Kew taxon identifiers and the World Checklist of Vascular Plants, and includes both native and non-native species. Attribute data stem from a variety of sources to give an overview of the current state of the vascular flora. Attributes include functional traits, distribution and ecologically relevant data (e.g. genome size, chromosome numbers, spatial distribution, growth form, hybridization metrics and native/non-native status). The data include previously unpublished genome size measurements, chromosome counts and CSR life strategy assessments. The database aims to provide an up-to-date starting point for flora-wide analyses. Full details about this dataset can be found at https://doi.org/10.5285/9f097d82-7560-4ed2-af13-604a9110cf6d

Uncertainties in future sea level projections are dominated by our limited understanding of the dynamical processes that control instabilities of marine ice sheets. A valuable case to examine these processes is the last deglaciation of the British-Irish Ice Sheet. The Minch Ice Stream, which drained a large proportion of ice from the northwest sector of the British-Irish Ice Sheet during the last deglaciation, is well constrained, with abundant empirical data which could be used to inform, validate and analyse numerical ice sheet simulations. We use BISICLES, a higher-order ice sheet model, to examine the dynamical processes that controlled the retreat of the Minch Ice Stream. We simulate retreat from the shelf edge under constant "warm" surface mass balance and subshelf melt, to isolate the role of internal ice dynamics from external forcings. The model simulates a slowdown of retreat as the ice stream becomes laterally confined at a "pinning-point" between mainland Scotland and the Isle of Lewis. At this stage, the presence of ice shelves became a major control on deglaciation, providing buttressing to upstream ice. Subsequently, the presence of a reverse slope inside the Minch Strait produces an acceleration in retreat, leading to a "collapsed" state, even when the climate returns to the initial "cold" conditions. Our simulations demonstrate the importance of the Marine Ice Sheet Instability and ice shelf buttressing during the deglaciation of parts of the British-Irish Ice Sheet. Thus, geological data could be used to constrain these processes in ice sheet models used for projecting the future of our contemporary ice sheets. Funding was provided by the Natural Environment Research Council (NERC) SPHERES Doctoral Training Partnership (NE/L002574/1) with CASE support from the British Geological Survey.