Dataset comprising data on the lifetime reproductive success (LRS) of 879 individually marked long-tailed tits Aegithalos caudatus, a cooperatively breeding passerine. LRS is measured in terms of the number of local recruits into the breeding population in the study area, controlling for fledgling sex and extra-pair paternity. LRS data are then partitioned into direct and indirect fitness components, quantified as genetic equivalents. Partitioning of fitness follows Hamilton’s definition of inclusive fitness: (a) direct fitness is measured as the production of offspring, stripped of the social effect of helpers on productivity; (b) indirect fitness is calculated from the mean marginal effect of a helper on productivity, adjusted for helper relatedness. Inclusive fitness is calculated by summing direct and indirect fitness. Full details about this dataset can be found at https://doi.org/10.5285/0e55f507-e5bd-4678-a5ea-8c3ffb62d3ac

This dataset records the Saiga antelope die-off and calving sites in Kazakhstan. It represents the locations (and where available dates) of (i) die-offs and (ii) normal calving events in the Betpak-dala population of the saiga antelope, in which three major mass mortality events have been recorded since 1988. In total, the data contains 214 saiga die-off and calving sites obtained from field visits, aerial surveys, telemetry and literature. Locations derived from field data, aerial surveys or telemetry are polygons representing the actual size and shape of the die-off or calving sites; locations sourced from the literature are point data around which buffers of 6km were created, representing the average size of calving aggregations. Of the 214 locations listed, 135 sites for which environmental data were available were used to model the probability of a die-off event. The collection and use of these data are written up in more detail in papers which are currently under review (when published links will be added to this record). Saiga antelope are susceptible to mass mortality events, the most severe of which tend to be caused by haemorrhagic septicaemia following infection by the bacteria Pasteurella multocida. These die-off events tend to occur in May during calving, when saigas gather in dense aggregations which can be represented spatially as relatively small sites. The Betpak-dala population is one of three in Kazakhstan, located in the central provinces of the country (see map). Full details about this dataset can be found at https://doi.org/10.5285/8ad12782-e939-4834-830a-c89e503a298b

This dataset provides linear trends, over varying time periods, for the Collated Indices of individual butterfly species across the UK. The main statistical values derived from a linear regression (slope, standard error, P-value) are presented for the entire time series for each species (1976# to the present year), for the last 20 years, and for the last decade. In addition, trends are classified based on the direction and significance of a linear slope together with an estimated percentage change for that time period. These trend data are provided for all UK butterfly species for which we have sufficient data (58 species). Trends are calculated by performing a linear regression on the annual Collated indices for each species. Collated indices are calculated using a log-linear model incorporating individual site indices from all monitored sites across the UK for a given species in a given year. This dataset provides linear trends, over varying time periods, for the Collated Indices of individual butterfly species across the UK. The main statistical values derived from a linear regression (slope, standard error, P-value) are presented for the entire time series for each species (1976# to the present year), for the last 20 years, and for the last decade. In addition, trends are classified based on the direction and significance of a linear slope together with an estimated percentage change for that time period. These trend data are provided for all UK butterfly species for which we have sufficient data (58 species). Trends are calculated by performing a linear regression on the annual Collated indices for each species. Collated indices are calculated using a log-linear model incorporating individual site indices from all monitored sites across the UK for a given species in a given year. Trends across different time series allow us to determine the long and short-term status of individual species. This is enables us to focus conservation and research and also to assess species responses to conservation already in place. The UK Butterfly Monitoring Scheme is organized and funded by Butterfly Conservation (BC), the UK Centre for Ecology & Hydrology (UKCEH), 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. #Because the Collated indices are only calculated for each species in years in which it was recorded on five or more sites, the starting year for the series is later than 1976 for a number of rarer species. Full details about this dataset can be found at https://doi.org/10.5285/236ee6bd-2330-4f84-a871-5a8ebe1925b5

This dataset comprises individual site indices for UK butterfly species calculated from data from the UK Butterfly Monitoring Scheme (UKBMS). Site indices are a relative rather than an absolute measure of the size of a population, and have been shown to relate closely to other, more intensive, measures of population size such as mark, release, recapture (MRR) methods. The site index can be thought of as a relative measure of the population size, being a more or less constant proportion of the number of butterflies present. The proportion seen is likely to vary according to species; some butterfly species are more conspicuous and thus more easily detected, whereas others are much less easy to see. Site indices are only calculated at sites with sufficient monitoring visits throughout the season, or for targeted reduced effort surveys (timed observations, larval web counts and egg counts) where counts are generally obtained as close to the peak of the flight period as possible and are subsequently adjusted for the time of year and size of the site (area of suitable habitat type for a given species). Wider Countryside Butterfly Survey (WCBS) sites are thus excluded because they are based on very few visits from which indices of abundance are not calculated. For transect sites, a statistical model (a General Additive Model, 'GAM') is used to impute missing values and to calculate a site index. Each year most transect sites (over 90%) produce an index for at least one species and in recent years site indices have been calculated for over 2,000 sites across the UK. Site indices are subsequently collated to contribute to the overall 'Collated Index' for each species, which are relative measures of the abundance of each species across a geographical area, for example, across the whole UK or at country level for England, Scotland, Wales or Northern Ireland. Individual site indices are important in informing conservation management as not all sites show the same patterns for each species and likely reflect a combination of local climate and habitat management at the site. 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/10.5285/180a1c76-bceb-4264-872b-deddfe67b3de

The following data set describes regional and temporal occurrence of plants foraged upon by managed honey bees (Apis mellifera). This data was derived from DNA meta-barcoding of pollen extracted from honey samples provided by bee keepers archived as part of the UK National Honey Monitoring Scheme (https://honey-monitoring.ac.uk/). All data provided is from the first full year of the scheme in 2019. Working in partnership with UK beekeepers, the National Honey Monitoring Scheme aims to use honeybees to monitor long-term changes in the condition and health of the UK countryside. Data associated with subsequent years will be made available as samples are processed. The Honey Monitoring Scheme is supported by national capability funding from UK Centre for Ecology & Hydrology under the ASSIST programme. Full details about this dataset can be found at https://doi.org/10.5285/e9ec63be-3f2b-4d1b-b9bf-77ca2b96c7f5

This dataset comprises individual site indices for UK butterfly species calculated from data from the UK Butterfly Monitoring Scheme (UKBMS). Site indices are a relative rather than an absolute measure of the size of a population, and have been shown to relate closely to other, more intensive, measures of population size such as mark, release, recapture (MRR) methods. The site index can be thought of as a relative measure of the population size, being a more or less constant proportion of the number of butterflies present. The proportion seen is likely to vary according to species; some butterfly species are more conspicuous and thus more easily detected, whereas others are much less easy to see. Site indices are only calculated at sites with sufficient monitoring visits throughout the season, or for targeted reduced effort surveys (timed observations, larval web counts and egg counts) where counts are generally obtained as close to the peak of the flight period as possible and are subsequently adjusted for the time of year and size of the site (area of suitable habitat type for a given species). Wider Countryside Butterfly Survey (WCBS) sites are thus excluded because they are based on very few visits from which indices of abundance are not calculated. For transect sites, a statistical model (a General Additive Model, 'GAM') is used to impute missing values and to calculate a site index. Each year most transect sites (over 90%) produce an index for at least one species and in recent years site indices have been calculated for over 2,000 sites across the UK. Site indices are subsequently collated to contribute to the overall 'Collated Index' for each species, which are relative measures of the abundance of each species across a geographical area, for example, across the whole UK or at country level for England, Scotland, Wales or Northern Ireland. Individual site indices are important in informing conservation management as not all sites show the same patterns for each species and likely reflect a combination of local climate and habitat management at the site. The UK Butterfly Monitoring Scheme is organized and funded by Butterfly Conservation (BC), the UK Centre for Ecology & Hydrology (UKCEH), 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/10.5285/1286b858-34a7-4ff2-84a1-a55e48d63e86

This dataset provides data on the timing of butterfly flight periods for each UK butterfly species across all monitored sites in the UK Butterfly Monitoring Scheme (UKBMS). Annual data from over 2,500 sites are presented relating to the timing (first appearance, last appearance, date of peak abundance and mean flight date) and the duration (total number of days, standard deviation around the mean flight date) of the flight period for all UK butterfly species from 1976 to 2021. In addition, this data is divided each year for eleven multi-voltine species to provide separate phenology data for distinct flight periods associated with first and subsequent generations. Phenology change is a widely used measure of the biological impacts of climate change because of the close relationship between temperature and the timing of biological events. This dataset provides an invaluable tool for assessing the impacts of climate change both spatially and temporally. The UK Butterfly Monitoring Scheme is organized and funded by Butterfly Conservation (BC), the UK Centre for Ecology & Hydrology (UKCEH), 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/10.5285/0c59eb20-26e3-4066-86f5-418afae18769

[This dataset is embargoed until June 21, 2023]. The dataset comprises of physical and biogeochemical measurements of saltmarsh soils from across 22 UK saltmarshes. Between 2018 and 2021, 462 narrow diameter gouge cores (30 mm in diameter) were collected as part of the Carbon Storage in Intertidal Environments (C-SIDE) project to facilitate the calculation of saltmarsh soil organic carbon stocks. Sites were chosen to represent contrasting habitats types in the UK, in particular sediment types, vegetation and sea level history. The data provides a quantitative measure of soil dry bulk density and organic carbon content across varies substrate and marsh types. 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/d301c5f5-77f5-41ba-934e-a80e1293d4cd

This dataset contains energy expenditure, sea surface temperature, foraging activity, day length, longitude, latitude, distance from the coastline and mass data from 17 common guillemots (Uria aalge) from the Isle of May during the 2016-2017 annual cycle. Full details about this dataset can be found at https://doi.org/10.5285/1cc5dcdb-e894-4973-a5b5-7a38a6cfc770

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