This dataset captures annual measurements of body mass for Adelie penguin chicks at Signy Island, from 1997 until 2020. Between 50 and 100 chicks are measured on beaches immediately prior to their departure, with 3-5 weighing sessions carried out annually per species in the period before fledging is complete. This monitoring contributes to the CCAMLR Ecosystem Monitoring Program (CEMP) and is part of the annual seabird Long Term Monitoring Science carried out by the British Antarctic Survey at Signy Island. This work was funded by Natural Environment Research Council (UK) core funding to the British Antarctic Survey.

This datasets captures the annual measurements of body mass for chinstrap penguin chicks at Signy Island, from 1997 to 2020. Between 50 to 100 chicks are measured, with 3-5 weighing sessions carried out in the period before fledging is complete. This monitoring contributes to the CCAMLR Ecosystem Monitoring Program (CEMP) and is part of annual monitoring carried out by the British Antarctic Survey. This work was funded by Natural Environment Research Council (UK) core funding to the British Antarctic Survey.

This dataset pertains to Adelie penguin breeding success at selected colonies on Signy island from 1978 to 2020. It comprises annual ground counts of occupied and incubating nests, eggs (proxy for breeding pairs), chicks hatched, and chicks expected to fledge. The GPS locations for surveyed sites are also included. From the 1996-1997 season onwards, this dataset conforms to CCAMLR data collection standards and contributes to the CCAMLR Ecosystem Monitoring Program (CEMP). Ecosystems component of BAS Polar Science for Planet Earth Programme, funded by NERC.

This dataset pertains to gentoo penguin breeding success at selected colonies on Signy island from 1978 to 2020. It comprises annual ground counts of occupied and incubating nests, eggs (proxy for breeding pairs), chicks hatched, and chicks expected to fledge. The GPS locations for surveyed sites are also included. From the 1996-1997 season onwards, this dataset conforms to CCAMLR data collection standards and contributes to the CCAMLR Ecosystem Monitoring Program (CEMP). Ecosystems component of BAS Polar Science for Planet Earth Programme, funded by NERC.

This dataset pertains to chinstrap penguin breeding success at selected colonies on Signy island from 1978 to 2020. It comprises annual ground counts of occupied and incubating nests, eggs (proxy for breeding pairs), chicks hatched, and chicks expected to fledge. The GPS locations for surveyed sites are also included. From the 1996-1997 season onwards, this dataset conforms to CCAMLR data collection standards and contributes to the CCAMLR Ecosystem Monitoring Program (CEMP). Ecosystems component of BAS Polar Science for Planet Earth Programme, funded by NERC.

This dataset comprises Argos PTT data for Adelie penguins, Pygoscelid adeliae, at Signy, Powell and Laurie Islands, part of the South Orkney Islands, between December and January 1999-2014. Tags were deployed across the South Orkney Islands (Signy Island, Powell Island and Laurie Island) between December and January (austral summer). The tracking data encompasses the breeding and post-breeding migratory dispersal of chinstrap penguins. The data includes coordinates for satellite uplinks for each tag and respective trip, along with error values for each satellite uplink. Metadata includes additional information about nesting and morphology, when available. PTT tags were deployed by British Antarctic Survey (BAS) personnel and supported by Natural Environment Research Council (UK) core funding and WWF grant GB095701

This annotated dataset comprises locational data of grey whales in lagoons San Ignacio and Ojo de Liebre in Baja California Sur as detected from Very High Resolution (VHR) satellite imagery in January 2009, 2013 and 2015. Images were manually scanned and whales detected through the use of grids. Additional metadata includes information on image type and model, and whale distinctive characteristics (e.g., fluke or blow). This work supports the '' training'' of machine learning algorithms for automatic detection of whales from satellite imagery. This study formed part of the Ecosystems component of the British Antarctic Survey Polar Science for Planet Earth Programme, funded by The Natural Environment Research Council. The work was supported by the UKRI Centre for Doctoral Training in Application of Artificial Intelligence to the study of Environmental Risks (reference EP/S022961/1).

This dataset contains model input and output data on emperor penguin population dynamics for a Bayesian analysis carried out on multivariate classification results. Model input data comprises multivariate classification analysis results derived from very-high resolution (VHR) satellite imagery pertaining to 16 emperor penguin colonies, spanning the Bellingshausen Sea to the Weddell Sea between 2009 to 2023. Model output data comprises population estimates for each year for each colony, global trends per year, global change for the dataset overall, global abundance pertaining to individual colonies, as well as statistical parameter estimates provided by the model. Data collection was carried out by personnel at BAS. Funding from WWF UK (GB095701), project NE/Y00115X/1 "Understanding emperor penguin populations in the Weddell Sea and Antarctic Peninsula" and previous WWF funding over the 15 year period.

This dataset comprises Platform Terminal Transmitter (PTT) data for chinstrap penguins at Signy, Laurie and Monroe Islands, part of the South Orkney Islands, between December and February 2000-2016 (austral summer). The tracking data encompasses the breeding and post-breeding migratory dispersal of chinstrap penguins. The data includes coordinates for satellite uplinks for each tag and respective trip, along with error values for each satellite uplink. Metadata includes additional information about nesting and morphology, when available. PTT tags were deployed by British Antarctic Survey (BAS) personnel supported by Natural Environment Research Council (UK) core funding, WWF Grant (GB095701), Darwin Plus grant DPLUS054 and CCAMLR special fund.