Institutions: British Antarctic Survey, British Antarctic Survey, Polar Data Centre,Natural Environment Research Council,UK Research & Innovation
Last metadata update: 2021-07-30T02:00:00Z
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Abstract:
We tracked 94 common and 50 Brunnich''s guillemots from five colonies around Iceland (Latrabjarg, Grimsey, Langanes, Skrudur and Papey) during late incubation and chick rearing from June to July 2019. We also tracked 5 common and 3 Brunnich''s guillemots from Langanes during chick-rearing in July 2020 (GPS only). Finally, we tracked 4 common and 4 Brunnich''s guillemots from Langanes during late incubation and chick rearing in June 2021. We used Pathtrack nanoFix GPS loggers to record locations every 3min and Cefas G5 TDR loggers to record depth every second. The tags recorded the birds'' behaviour for a few days (typically 2 to 3). The aim was to investigate the foraging behaviour of the two species and the potential competition between them.
Funding was provided by NERC grant NE/R012660/1 (part of the NERC Changing Arctic Ocean programme).
Institutions: British Antarctic Survey, British Antarctic Survey, Polar Data Centre,Natural Environment Research Council,UK Research & Innovation
Last metadata update: 2022-03-01T01:00:00Z
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Abstract:
This dataset contains penguin survey data and imagery from unmanned aerial vehicles (UAV) across the South Sandwich Islands, from December 2019 to February 2020. It comprises orthotiff images (orthotiffs) and digital elevation models (DEMS) of surveyed sites, geographic penguin colony outlines, nest coordinates for individual species, mixed species'' sub-colonies and groups where species-level identification was not possible. Finally, it also includes the total count for these different categories for each individual site, alongside an estimate of the nests that were not counted due to distortion in certain parts of the orthotiffs.
The orthotiff images and DEMS were produced using Structure-from-motion (SfM), a three-dimensional (3D) rendering technology, and were then loaded into QGIS to manually extract nest coordinates for chinstrap, adelie, gentoo and macaroni penguins. Where counting nests was not possible, the estimate of possible nests present was calculated using regions of the site where a count was carried out.
This dataset was collected by researchers at the Polar Ecology and Conservation Group at the University of Oxford with the aim that surveying these sites and updating current population assessments over the South Sandwich Islands will aide conservation policy and advance monitoring technology and capability.
The South Sandwich Islands expedition was supported by the Government of South Georgia and the South Sandwich Islands, and funded by the John Ellerman Foundation and donations from passengers on Quark Expeditions'' ships.
Institutions: British Antarctic Survey, British Antarctic Survey, Polar Data Centre,Natural Environment Research Council,UK Research & Innovation
Last metadata update: 2021-09-17T02:00:00Z
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Abstract:
Quantification of interactive effects of ocean warming and ocean acidification based on near-future climate change projections on morphometrics and oocyte size of benthic invertebrates (the bivalves Astarte crenata and Bathyarca glacialis) from the Western Barents Sea.
Supported by The Changing Arctic Ocean Seafloor (ChAOS) - how changing sea ice conditions impact biological communities, biogeochemical processes and ecosystems project (NE/N015894/1 and NE/P006426/1, 2017-2021), Natural Environment Research Council (NERC) in the UK.
Institutions: British Antarctic Survey, British Antarctic Survey, Polar Data Centre,Natural Environment Research Council,UK Research & Innovation
Last metadata update: 2022-03-22T01:00:00Z
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Abstract:
Images of histological sections of oocytes to quantify the interactive effects of ocean warming and ocean acidification based on near-future climate change projections on oocyte size frequency distributions of benthic invertebrates (the bivalves Astarte crenata and Bathyarca glacialis) from the Western Barents Sea.
Supported by The Changing Arctic Ocean Seafloor (ChAOS) - how changing sea ice conditions impact biological communities, biogeochemical processes and ecosystems project (NE/N015894/1 and NE/P006426/1, 2017-2021), Natural Environment Research Council (NERC) in the UK.
Institutions: British Antarctic Survey, British Antarctic Survey, Polar Data Centre,Natural Environment Research Council,UK Research & Innovation
Last metadata update: 2021-09-17T02:00:00Z
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Abstract:
Images of histological sections of oocytes to quantify the interactive effects of ocean warming and ocean acidification based on near-future climate change projections on oocyte size frequency distributions of benthic invertebrates (the bivalves Astarte crenata and Bathyarca glacialis) from the Western Barents Sea.
Supported by The Changing Arctic Ocean Seafloor (ChAOS) - how changing sea ice conditions impact biological communities, biogeochemical processes and ecosystems project (NE/N015894/1 and NE/P006426/1, 2017-2021), Natural Environment Research Council (NERC) in the UK.
Institutions: British Antarctic Survey, British Antarctic Survey, Polar Data Centre,Natural Environment Research Council,UK Research & Innovation
Last metadata update: 2020-12-07T01:00:00Z
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Abstract:
Platform Transmitting Terminal (PTT) tags were used to track Gentoo penguins from Maiviken and Ocean Harbour, South Georgia, from June to September 2018. PTT tags were attached to the lower back feathers with tape and glue. PTT tags use the ARGOS satellite system to collect geospatial data. Tags were deployed to provide information on the protection afforded to Gentoo penguins by the 12NM no take zone (part of the South Georgia and South Sandwich Island MPA that is closed to fishing), and the krill fishing grounds.
Effect of snow depth and snowmelt timing on arctic terrestrial ecosystems (SnoEco) (SnoEco)
Institutions: Department of Arctic and Marine Biology, UiT – The Arctic University of Norway
Last metadata update: 2020-12-14T19:01:06Z
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Abstract:
These photos were collected with a time-lapse RGB camera installed on a 2 meter high metal rack to monitor tundra vegetation. The photos have gone through a manual quality check and were automatically adjusted with an algorithm to correct for lateral and rotational movements. Black borders are placed around the photos to provide room for these adjustments. The mask included with this data was used to calculate Green Chromatic Channel (GCC), a vegetation index, to compare with NDVI data recorded in parallel.
Effect of snow depth and snowmelt timing on arctic terrestrial ecosystems (SnoEco) (SnoEco)
Institutions: Department of Arctic and Marine Biology, UiT – The Arctic University of Norway
Last metadata update: 2020-12-14T19:01:06Z
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Abstract:
These photos were collected with a time-lapse RGB camera installed on a 2 meter high metal rack to monitor tundra vegetation. The photos have gone through a manual quality check and were automatically adjusted with an algorithm to correct for lateral and rotational movements. Black borders are placed around the photos to provide room for these adjustments. The mask included with this data was used to calculate Green Chromatic Channel (GCC), a vegetation index, to compare with NDVI data recorded in parallel.
Effect of snow depth and snowmelt timing on arctic terrestrial ecosystems (SnoEco) (SnoEco)
Institutions: Department of Arctic and Marine Biology, UiT – The Arctic University of Norway
Last metadata update: 2020-12-14T19:01:06Z
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Abstract:
These photos were collected with a time-lapse RGB camera installed on a 2 meter high metal rack to monitor tundra vegetation. The photos have gone through a manual quality check and were automatically adjusted with an algorithm to correct for lateral and rotational movements. Black borders are placed around the photos to provide room for these adjustments. The mask included with this data was used to calculate Green Chromatic Channel (GCC), a vegetation index, to compare with NDVI data recorded in parallel.
Effect of snow depth and snowmelt timing on arctic terrestrial ecosystems (SnoEco) (SnoEco)
Institutions: Department of Arctic and Marine Biology, UiT – The Arctic University of Norway
Last metadata update: 2020-12-14T19:01:06Z
Show more...
Abstract:
These photos were collected with a time-lapse RGB camera installed on a 2 meter high metal rack to monitor tundra vegetation. The photos have gone through a manual quality check and were automatically adjusted with an algorithm to correct for lateral and rotational movements. Black borders are placed around the photos to provide room for these adjustments. The mask included with this data was used to calculate Green Chromatic Channel (GCC), a vegetation index, to compare with NDVI data recorded in parallel.
Effect of snow depth and snowmelt timing on arctic terrestrial ecosystems (SnoEco) (SnoEco)
Institutions: Department of Arctic and Marine Biology, UiT – The Arctic University of Norway
Last metadata update: 2020-12-14T19:01:06Z
Show more...
Abstract:
These photos were collected with a time-lapse RGB camera installed on a 2 meter high metal rack to monitor tundra vegetation. The photos have gone through a manual quality check and were automatically adjusted with an algorithm to correct for lateral and rotational movements. Black borders are placed around the photos to provide room for these adjustments. The mask included with this data was used to calculate Green Chromatic Channel (GCC), a vegetation index, to compare with NDVI data recorded in parallel.
Effect of snow depth and snowmelt timing on arctic terrestrial ecosystems (SnoEco) (SnoEco)
Institutions: Department of Arctic and Marine Biology, UiT – The Arctic University of Norway
Last metadata update: 2020-12-14T19:01:06Z
Show more...
Abstract:
These photos were collected with a time-lapse RGB camera installed on a 2 meter high metal rack to monitor tundra vegetation. The photos have gone through a manual quality check and were automatically adjusted with an algorithm to correct for lateral and rotational movements. Black borders are placed around the photos to provide room for these adjustments. The mask included with this data was used to calculate Green Chromatic Channel (GCC), a vegetation index, to compare with NDVI data recorded in parallel.
Effect of snow depth and snowmelt timing on arctic terrestrial ecosystems (SnoEco) (SnoEco)
Institutions: Department of Arctic and Marine Biology, UiT – The Arctic University of Norway
Last metadata update: 2020-12-14T19:01:06Z
Show more...
Abstract:
These photos were collected with a time-lapse RGB camera installed on a 2 meter high metal rack to monitor tundra vegetation. The photos have gone through a manual quality check and were automatically adjusted with an algorithm to correct for lateral and rotational movements. Black borders are placed around the photos to provide room for these adjustments. The mask included with this data was used to calculate Green Chromatic Channel (GCC), a vegetation index, to compare with NDVI data recorded in parallel.
Effect of snow depth and snowmelt timing on arctic terrestrial ecosystems (SnoEco) (SnoEco)
Institutions: Department of Arctic and Marine Biology, UiT – The Arctic University of Norway
Last metadata update: 2020-12-14T19:01:06Z
Show more...
Abstract:
These photos were collected with a time-lapse RGB camera installed on a 2 meter high metal rack to monitor tundra vegetation. The photos have gone through a manual quality check and were automatically adjusted with an algorithm to correct for lateral and rotational movements. Black borders are placed around the photos to provide room for these adjustments. The mask included with this data was used to calculate Green Chromatic Channel (GCC), a vegetation index, to compare with NDVI data recorded in parallel.
Effect of snow depth and snowmelt timing on arctic terrestrial ecosystems (SnoEco) (SnoEco)
Institutions: Department of Arctic and Marine Biology, UiT – The Arctic University of Norway
Last metadata update: 2020-12-14T19:01:06Z
Show more...
Abstract:
These photos were collected with a time-lapse RGB camera installed on a 2 meter high metal rack to monitor tundra vegetation. The photos have gone through a manual quality check and were automatically adjusted with an algorithm to correct for lateral and rotational movements. Black borders are placed around the photos to provide room for these adjustments. The mask included with this data was used to calculate Green Chromatic Channel (GCC), a vegetation index, to compare with NDVI data recorded in parallel.
