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

Cetacean sightings in South Georgia and South Sandwich Islands waters, made by a team of four professional marine mammal observers during the British Antarctic Survey CCAMLR synoptic krill survey on the RRS Discovery (DY098), January and February 2019. The latitude and longitude of each sighting, the identified species, bearing and distance from the vessel, and estimated group size are provided. These data have been used by BAS to estimate (i) humpback whale and (ii) baleen whale abundance in South Georgia and South Sandwich Islands waters in 2019. Funding was provided by the Foreign, Commonwealth and Development Office, as part of the Overseas Territories Blue Belt programme, as well as the South Georgia Heritage Trust, Friends of South Georgia Island and Darwin PLUS award DPLUS057.

This dataset includes taxonomic and abundance data at the of benthic macroinvertebrates in ten rivers within the glacial valleys of Parón, Huaytapallana and Llanganuco in the Cordillera Blanca, Ancash, Peru. This data was created to analyse the response of aquatic biodiversity to glacial retreat, studying rivers in a gradient of glacial coverage. The sampling work was carried out from October 14 to 30, 2019 and from October 7 to 16, 2020. The study was funded by NERC, Newton‐Paulet Fund and Fondo Nacional de Desarrollo Científico, Tecnológico y de Innovación Tecnológica-Perú Full details about this dataset can be found at https://doi.org/10.5285/db604b78-c616-471b-9028-2d0826a6f50c