The Retrospective Analysis of Antarctic Tracking (Standardised) Data from the Scientific Committee on Antarctic Research

サンプリング イベント
最新バージョン SCAR - AntOBIS により出版 9 30, 2020 SCAR - AntOBIS
公開日:
2020/09/30
公開者:
SCAR - AntOBIS
ライセンス:
CC-BY 4.0

DwC-A形式のリソース データまたは EML / RTF 形式のリソース メタデータの最新バージョンをダウンロード:

DwC ファイルとしてのデータ ダウンロード 4,060 レコード English で (81 MB) - 更新頻度: as needed
EML ファイルとしてのメタデータ ダウンロード English で (53 KB)
RTF ファイルとしてのメタデータ ダウンロード English で (43 KB)

説明

The Southern Ocean is a remote, hostile environment where conducting marine biology is challenging, so we know relatively little about this important region, which is critical as a habitat for breeding and foraging of many marine endotherms. Scientists from around the world have been tracking seals, penguins, petrels, whales and albatrosses for more than two decades to learn how they spend their time at sea. The Retrospective Analysis of Antarctic Tracking Data (RAATD), was initiated by the SCAR Expert Group on Marine Mammals (EG-BAMM) in 2010. This team has assembled tracking data shared by 38 biologists from 11 different countries to accumulate the largest animal tracking database in the world, containing information from 15 species, containing over 3,400 individual animals and almost 2.5 million at-sea locations. Analysing a dataset of this size brings its own challenges and the team is developing new and innovative statistical approaches to integrate these complex data. When complete RAATD will provide a greater understanding of fundamental ecosystem processes in the Southern Ocean, help predict the future of top predator distribution and help with spatial management planning.

データ レコード

この sampling event リソース内のデータは、1 つまたは複数のデータ テーブルとして生物多様性データを共有するための標準化された形式であるダーウィン コア アーカイブ (DwC-A) として公開されています。 コア データ テーブルには、4,060 レコードが含まれています。

拡張データ テーブルは1 件存在しています。拡張レコードは、コアのレコードについての追加情報を提供するものです。 各拡張データ テーブル内のレコード数を以下に示します。

Event (コア)
4060
Occurrence 
2331595

この IPT はデータをアーカイブし、データ リポジトリとして機能します。データとリソースのメタデータは、 ダウンロード セクションからダウンロードできます。 バージョン テーブルから公開可能な他のバージョンを閲覧でき、リソースに加えられた変更を知ることができます。

バージョン

次の表は、公にアクセス可能な公開バージョンのリソースのみ表示しています。

引用方法

研究者はこの研究内容を以下のように引用する必要があります。:

Ropert-Coudert Y, Van de Putte A P, Bornemann H, Charrassin J, Costa D P, Danis B, Hückstädt L A, Jonsen I D, Lea M, Reisinger R R, Thompson D, Torres L G, Trathan P N, Wotherspoon S, Ainley D G, Alderman R, Andrews-Goff V, Arthur B, Ballard G, Bengtson J, Bester M N, Boehme L, Bost C, Boveng P, Cleeland J, Constantine R, Crawford R J M, Dalla Rosa L, de Bruyn P N, Delord K, Descamps S, Double M, Emmerson L, Fedak M, Friedlander A, Gales N, Goebel M, Goetz K T, Guinet C, Goldsworthy S D, Harcourt R, Hinke J, Jerosch K, Kato A, Kerry K R, Kirkwood R, Kooyma G L, Kovacs K M, Lawton K, Lowther A D, Lydersen C, Lyver P O, Makhado A B, Márquez M E I, McDonald B, McMahon C, Muelbert M, Nachtsheim D, Nicholls K W, Nordøy E S, Olmastroni S, Phillips R A, Pistorius P, Plötz J, Pütz K, Ratcliffe N, Ryan P G, Santos M, Schytte Blix A, Southwell C, Staniland I, Takahashi A, Tarroux A, Trivelpiece W, Wakefield E, Weimerskirch H, Wienecke B, Xavier J C, Raymond B, Hindell M A (2020): The Retrospective Analysis of Antarctic Tracking (Standardised) Data from the Scientific Committee on Antarctic Research. v1.3. SCAR - AntOBIS. Dataset/Metadata. https://ipt.biodiversity.aq/resource?r=raatd_scar_trackingdata&v=1.3

権利

研究者は権利に関する下記ステートメントを尊重する必要があります。:

パブリッシャーとライセンス保持者権利者は SCAR - AntOBIS。 This work is licensed under a Creative Commons Attribution (CC-BY 4.0) License.

GBIF登録

このリソースをはGBIF と登録されており GBIF UUID: b86fe411-8e62-4cd0-aab2-914d75401598が割り当てられています。   Ocean Biodiversity Information System によって承認されたデータ パブリッシャーとして GBIF に登録されているSCAR - AntOBIS が、このリソースをパブリッシュしました。

キーワード

Occurrence; ANIMAL ECOLOGY AND BEHAVIOR BIRDS ALBATROSSES/PETRELS AND ALLIES PENGUINS MAMMALS SEALS/SEA LIONS/WALRUSES BALEEN WHALES

外部データ

リソース データは他の形式で入手可能です。

連絡先

Yan Ropert-Coudert
  • 論文著者
  • 最初のデータ採集者
  • 連絡先
Centre d’Etudes Biologiques de Chizé, Station d’Écologie de Chizé-Université de La Rochelle
CNRS UMR7372
79360 Villiers-en-Bois
FR
Anton P. Van de Putte
  • 最初のデータ採集者
  • 連絡先
BEDIC, OD Nature, Royal Belgian Institute for Natural Sciences
Rue Vautierstraat 29
B-1000 Brussels
BE
Horst Bornemann
  • 論文著者
  • 最初のデータ採集者
Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung
Am Handelshafen 12
27570 Bremerhaven
Jean-Benoît Charrassin
  • 論文著者
  • 最初のデータ採集者
Sorbonne Universités, UPMC University, Paris 06
FR
Daniel P. Costa
  • 論文著者
  • 最初のデータ採集者
Department of Ecology and Evolutionary Biology, University of California Santa Cruz
US
Bruno Danis
  • 論文著者
  • 最初のデータ採集者
Université Libre de Bruxelles, Marine Biology Lab
Luis A. Hückstädt
  • 最初のデータ採集者
Department of Ecology and Evolutionary Biology, University of California Santa Cruz
US
Ian D. Jonsen
  • 最初のデータ採集者
Department of Biological Sciences, Macquarie University
Mary-Anne Lea
  • 論文著者
  • 最初のデータ採集者
Institute for Marine and Antarctic Studies, University of Tasmania
Ryan R. Reisinger
  • 論文著者
  • 最初のデータ採集者
Centre d’Etudes Biologiques de Chizé, Station d’Écologie de Chizé-Université de La Rochelle
David Thompson
  • 論文著者
  • 最初のデータ採集者
National Institute of Water and Atmospheric Research Ltd
Leigh G. Torres
  • 論文著者
  • 最初のデータ採集者
Hatfield Marine Science Center
Philip N. Trathan
  • 論文著者
  • 最初のデータ採集者
British Antarctic Survey, Natural Environment Research Council
Simon Wotherspoon
  • 論文著者
  • 最初のデータ採集者
Institute for Marine and Antarctic Studies, University of Tasmania
David G Ainley
  • 最初のデータ採集者
Rachael Alderman
  • 最初のデータ採集者
Virginia Andrews-Goff
  • 最初のデータ採集者
Ben Arthur
  • 最初のデータ採集者
Grant Ballard
  • 最初のデータ採集者
John Bengtson
  • 最初のデータ採集者
Marthán N. Bester
  • 最初のデータ採集者
Lars Boehme
  • 最初のデータ採集者
Charles-André Bost
  • 最初のデータ採集者
Peter Boveng
  • 最初のデータ採集者
Jaimie Cleeland
  • 最初のデータ採集者
Rochelle Constantine
  • 最初のデータ採集者
Robert J. M. Crawford
  • 最初のデータ採集者
Luciano Dalla Rosa
  • 最初のデータ採集者
P.J. Nico de Bruyn
  • 最初のデータ採集者
Karine Delord
  • 最初のデータ採集者
Sébastien Descamps
  • 最初のデータ採集者
Mike Double
  • 最初のデータ採集者
Louise Emmerson
  • 最初のデータ採集者
Mike Fedak
  • 最初のデータ採集者
Ari Friedlander
  • 最初のデータ採集者
Nick Gales
  • 最初のデータ採集者
Mike Goebel
  • 最初のデータ採集者
Kimberly T. Goetz
  • 最初のデータ採集者
Christophe Guinet
  • 最初のデータ採集者
Simon D. Goldsworthy
  • 最初のデータ採集者
Rob Harcourt
  • 最初のデータ採集者
Jefferson Hinke
  • 最初のデータ採集者
Kerstin Jerosch
  • 最初のデータ採集者
Akiko Kato
  • 最初のデータ採集者
Knowles R. Kerry
  • 最初のデータ採集者
Roger Kirkwood
  • 最初のデータ採集者
Gerald L. Kooyma
  • 最初のデータ採集者
Kit M. Kovacs
  • 最初のデータ採集者
Kieran Lawton
  • 最初のデータ採集者
Andrew D. Lowther
  • 最初のデータ採集者
Christian Lydersen
  • 最初のデータ採集者
Phil O'B. Lyver
  • 最初のデータ採集者
Azwianewi B. Makhado
  • 最初のデータ採集者
Maria E. I. Márquez
  • 最初のデータ採集者
Birgitte McDonald
  • 最初のデータ採集者
Clive McMahon
  • 最初のデータ採集者
Monica Muelbert
  • 最初のデータ採集者
Dominik Nachtsheim
  • 最初のデータ採集者
Keith W. Nicholls
  • 最初のデータ採集者
Erling S. Nordøy
  • 最初のデータ採集者
Silvia Olmastroni
  • 最初のデータ採集者
Richard A. Phillips
  • 最初のデータ採集者
Pierre Pistorius
  • 最初のデータ採集者
Joachim Plötz
  • 最初のデータ採集者
Klemens Pütz
  • 最初のデータ採集者
Norman Ratcliffe
  • 最初のデータ採集者
Peter G. Ryan
  • 最初のデータ採集者
Mercedes Santos
  • 最初のデータ採集者
Arnoldus Schytte Blix
  • 最初のデータ採集者
Colin Southwell
  • 最初のデータ採集者
Iain Staniland
  • 最初のデータ採集者
Akinori Takahashi
  • 最初のデータ採集者
Arnaud Tarroux
  • 最初のデータ採集者
Wayne Trivelpiece
  • 最初のデータ採集者
Ewan Wakefield
  • 最初のデータ採集者
Henri Weimerskirch
  • 最初のデータ採集者
Barbara Wienecke
  • 最初のデータ採集者
José C. Xavier
  • 最初のデータ採集者
Ben Raymond
  • 論文著者
  • 最初のデータ採集者
Mark A. Hindell
  • 最初のデータ採集者
Anton Van de Putte
  • メタデータ提供者
  • 論文著者
BEDIC, OD Nature, Royal Belgian Institute for Natural Sciences
Rue Vautierstraat 29
B-1000 Brussels
BE
Mark Hindell
  • 論文著者
Professor
Antarctic Climate and Ecosystems Cooperative Research Centre, University of Tasmania,
Hobart
AU
Luis Huckstadt
  • 論文著者
Researcher
Department of Ecology and Evolutionary Biology, University of California Santa Cruz, Long Marine Lab
115 McAllister Way
CA 95060 Santa Cruz
California
US
Ian D Jonsen
  • 論文著者
Professor
Department of Biological Sciences, Macquarie University
Sydney, NSW 2109 Sydney
AU
David G. Ainley
  • データ提供者
H.T. Harvey & Associates
983 University Avenue
CA 95032 Los Gatos
California
US

地理的範囲

The dataset is restricted to the Southern Ocean, in a broad sense. All species considered in this dataset have circumpolar distributions with a longitudinal range spanning 180°W to 180°E. The species breed either on the coast of the Antarctic continent or on the sub-Antarctic islands to the north

座標(緯度経度) 南 西 [-90, -180], 北 東 [-40, 180]

生物分類学的範囲

Seventeen species of meso- and top predators were included in the dataset, five marine mammals (one baleen whale, one otariid and three phocid seals) and twelve seabirds (five penguin, five albatross, and two petrels). The species cover a diverse range of ecological niches and life history traits and include dietary specialists (e.g. crabeater seals), deep divers (e.g. elephant seal Mirounga leonina and emperor penguin Aptenodytes forsteri), wide ranging, highly migratory species (e.g. wandering albatross Diomedea exulans), nearshore foragers (e.g. Adélie penguin Pygoscelis adeliae) and capital (e.g. Weddell seal) versus income (e.g. Antarctic fur seal Arctocephalus gazella) breeders.

Species Pygoscelis adeliae (Adelie penguin), Aptenodytes forsteri (Emperor penguin), Thalassarche melanophris (Black browed albatross), Eudyptes chrysolophus (Macaroni penguin), Aptenodytes patagonicus (King penguin), Thalassarche chrysostoma (Grey headed albatross), Diomedea exulans (Wandering albatross), Phoebetria palpebrata (Light mantled albatross), Phoebetria fusca (Dark mantled sooty albatross), Thalassoica antarctica (Antarctic petrel), Procellaria aequinoctialis (White-chinned petrel), Mirounga leonina (Southern elephant seals), Leptonychotes weddellii (Weddell seals), Lobodon carcinophagus (Crabeater seals), Arctocephalus gazella (Antarctic fur seals), Megaptera novaeangliae (Humpback whales)

時間的範囲

開始日 / 終了日 1991-01-01 / 2015-12-31

プロジェクトデータ

The Retrospective Analysis of Antarctic Tracking Data (RAATD) was initiated in 2010 by the Expert Group on Birds and Marine Mammals (EG-BAMM) and the Expert Group on Antarctic Biodiversity Informatics (EGABI) of the Scientific Committee on Antarctic Research (SCAR). RAATD aims to advance our understanding of both fundamental and applied questions in a data-driven way, matching research priorities already identified by the SCAR Horizon Scanand key questions in animal movement ecology. For these reasons, we worked on the collation, validation and preparation of tracking data collected south of 45° S. Data from over 70 contributors were collated. This database includes information from 17 predator species, including 4,060 individuals and over 2.9 million at-sea locations. To exploit this unique dataset, RAATD undertook a multi-species assessment of habitat use for higher predators in the Southern Ocean (Hindell et al. in prep.).

タイトル Retrospective Analysis of Antarctic Tracking data
識別子 RAATD
ファンデイング Support and funding were provided by supranational committees and organisations including the Scientific Committee on Antarctic Research Life Science Group and BirdLife International, as well as from various national institutions (see also author affiliations) and foundations, including but not limited to Argentina (Dirección Nacional del Antártico), Australia (Australian Antarctic program; Australian Research Council; Sea World Research and Rescue Foundation Inc., IMOS is a national collaborative research infrastructure, supported by the Australian Government and operated by a consortium of institutions as an unincorporated joint venture, with the University of Tasmania as Lead Agent), Belgium (Belgian Science Policy Office), Brazil (Brazilian Antarctic Programme; Brazilian National Research Council (CNPq/MCTI) and CAPES), France (Agence Nationale de la Recherche; Centre National d’Etudes Spatiales; Centre National de la Recherche Scientifique; CESAB-FRB as part of the activities of the RAATD Working Group; Fondation Total; Institut Paul-Emile Victor; Programme Zone Atelier de Recherches sur l’Environnement Antarctique et Subantarctique; Terres Australes et Antarctiques Françaises), Germany (Hanse-Wissenschaftskolleg - Institute for Advanced Study), Italy (Italian National Antarctic Research Program; Ministry for Education University and Research), Japan (Japanese Antarctic Research Expedition; JSPS Kakenhi grant; National Science Foundation), Monaco (Fondation Prince Albert II de Monaco), New Zealand (National Environmental Research Council, Norway (National Environmental Research Council; Norwegian Antarctic Research Expeditions; Norwegian Research Council), Portugal (Foundation for Science and Technology), South Africa (Department of Environmental Affairs; National Research Foundation; South African National Antarctic Programme), UK (Darwin Plus; Ecosystems Programme at the British Antarctic Survey; Natural Environment Research Council; WWF), and USA (U.S. AMLR Program of NOAA Fisheries; US Office of Polar Programs).

プロジェクトに携わる要員:

Mark Hindell
  • 編集者
Yan Ropert-Coudert
  • 編集者
Anton Van de Putte
  • 論文著者

収集方法

Original deployment of tracking devices The RAATD core group (Fig. 1) aggregated data from three types of tracking device used by individual research teams. In increasing order of precision these are light recording Global Location Sensors (GLS loggers or geolocators), satellite-relayed Platform Terminal Transmitters (PTTs), and Global Positioning System devices (GPS). Typically, GLS and GPS devices record data in internal memory, and so must be physically recovered in order to download the data. PTTs transmit a carrier signal to satellites, and so can deliver data remotely and in near-real time. Some modern devices now combine the capabilities of PTT and GPS (or other) devices, relaying data to satellites. A GLS device, which is the smallest thus allowing deployment on the smaller predators, typically records ambient light levels through the day from which relatively coarse estimates of latitude and longitude can be calculated (~100–200 km) using day length and timing of local noon. Some GLS units can also record sea surface temperature, and this can help refine position estimates. GLS locations were estimated by the data contributors using five methods (Phillips et al. 2004, Sumner et al. 2009, Lisovski & Hahn 2012, Bindoff 2017, Wotherspoon 2017) (Supplementary File S2). With very small batteries, the data are usually archived and thus animals must be recaptured to download the data. GPS tags make use of global navigation satellite systems and provide very high resolution (~10 m) location fixes and time information. PTT tags transmit signals to ARGOS satellites which transfer the received signals and their frequencies to a receiving station at the Collecte de Localisation Satellites (CLS) in Toulouse, France, to estimate locations based on Doppler shifts in the received signals to a medium level of accuracy(~1,000 m). Processing by CLS involved a least-squares filtering method up to 2008, thereafter using Kalman filters (Lopez et al. 2014). Different models of GLS, PTT, and GPS devices from different manufactures have been used throughout the years, each of these having specific characteristics (size, operating modes, etc.) that may influence accuracy of the locations, but as device type was not always provided by the data providers, we applied standard corrections (see below). Device attachment to animals was also species-specific. When loggers are small enough, like GLS, they are mounted on leg or flipper bands, while larger data-loggers and transmitters are often attached to the plumage or fur on the back or head of the animal, a position that optimizes data communication with satellites. Modes of attachment on the back varied from using harnesses, glue or marine tape. For whales, transmitters with cutaneous anchors were attached to the back, using poles, cross bows or air guns. Scientists limited handling time and stress as much as possible during attachment and retrieval of devices (e.g. Field et al. 2012), following established animal handling guidelines, and institutional ethical review. However, it should be noted that our dataset contains tracking data that span almost three decades during which time substantial progress has been made in terms of miniaturization and advances in electronic components. Any adverse effects of devices on animals are therefore likely to be less acute in recent years than in the earlier years of tracking. Consideration of adverse reaction on study animals has been reviewed in the past (e.g. Phillips et al. 2003, Vandenabeele et al. 2012, Bannasch et al. 1994).

Study Extent All species considered in this dataset have circumpolar distributions with a longitudinal range spanning 180°W to 180°E. The species breed either on the coast of the Antarctic continent or on the sub-Antarctic islands to the north. Species with geographically limited distributions (such as chinstrap penguins Pygoscelis antarcticus) were not included. In addition, a number of deployments in the Antarctic (crabeater seals Lobodon carcinophagus and Weddell seals Leptonychotes weddellii) were conducted in the pack ice at un-named locations. Similarly, humpback whales Megaptera novaengeliae were instrumented at sea either off the coast of the Antarctic Peninsula or off Australia.

Method step description:

  1. Data Collection Starting from 2010, the core group of RAATD compiled a catalogue of existing (both published and unpublished) tracking data by contacting international experts and asking them to contribute data. The data collection phase ended in 2016. Besides directly contacting researchers, the team also harvested data from existing repositories, including the Australian Antarctic Data Center (https://data.aad.gov.au/), the Integrated Marine Observing System (http://imos.org.au/), PANGAEA (https://www.pangaea.de/), BirdLife International (http://www.seabirdtracking.org/), the Antarctic Biodiversity Portal (http://www.biodiversity.aq/), Ocean Biogeographic Information System (http://www.iobis.org/), and the Global Biodiversity Information Facility (http://www.gbif.org/).
  2. Associated metadata Where available, information on the deployment site and relevant characteristics of the animal at the time of deployment was standardized by the data editors. Where age class and sex were known, these were included in the metadata
  3. Data standardization Location dates and times were converted to UTC (Coordinated Universal Time). Records with missing latitude or longitude values were removed, and all longitudes were transformed to lie between 180° W and 180° E. Data files were row-ordered by individual, with rows within an individual in their correct temporal sequence. Near-duplicate positions were removed, those positions defined as having occurred 3 seconds or less after an existing position fix from the same animal, and which had identical longitude and latitude values (for GPS devices) or longitude and latitude values that differed by less than 1e-05 and which had the same location quality value (for PTT devices). Entries in the age class, breeding stage, device type, location quality, scientific, common, and abbreviated name, sex, and deployment site columns were validated against controlled vocabularies. Mandatory entries (e.g. deployment date, device type, individual animal identifier) were checked for missing values. Deployment locations were recorded by the original field team either at the individual animal level (using e.g. a hand-held GPS device) or at the deployment-site level (i.e. one deployment location per group of animals). The latter was common for deployments at colonies, whereas the former was most common for non-colony deployments (e.g. on seals and whales). Where deployment locations were not recorded by the field team, the first location estimate(s) in the tracking data were used. Deployment site names were standardized to colony granularity wherever possible (e.g. to the beach-on-island level). Periods at the start or end of deployments were identified and discarded if there was evidence that location data during these periods did not represent the animals’ at-sea movement. For example, tags may have been turned on early (thereby recording locations prior to their deployment on animals) or animals may have remained at the deployment site, e.g. the breeding colony, for an extended period at the start or end of the tag deployment. Some tracks also showed a marked deterioration in the frequency and quality (for PTTs) of location estimates near the end of a track. Such locations were visually identified based on maps of each track in conjunction with plots of location distance from deployment site against time. This information is captured in the location_to_keep column appended to each species’ raw data file (1 = keep, 0 = discard).
  4. Data filtering The trimmed data were subjected to a number of automated quality control checks to remove individual deployments that: 1) were flagged for removal by the Data Editor Group (using the keepornot column in the metadata file); 2) had fewer than 20 location records; and 3) had deployments lasting less than 1 day. Additionally, individual deployments were checked to ensure that: 1) duplicate records in PTTs (locations occurring within 2 min of each other) were removed; 2) PTT Argos Z-class locations were reclassified as B-class locations (the least precise Argos location quality class that has an associated error variance; Jonsen et al. 2005); and 3) locations implying unrealistic travel rates (> 10 m s-1 for penguins and marine mammals and > 30 m s-1 for flying seabirds) were removed. Note that the definition of “duplicate locations” in this filtering context is more aggressive than that used during data standardization: for standardization purposes, the intention was to keep the data as close to original as possible, whereas for filtering the presence of multiple positions in a short period of time (< 2 min) has a negative effect on the filter performance. A state-space model (SSM) was used to estimate locations at regular time intervals (1 h for GPS data; 2 h for Argos data; 12 h for GLS data) and account for measurement error in the original observations (Jonsen et al. 2005, Block et al. 2011). The data were SSM-filtered and subject to a final quality control where tracks that failed to converge, as judged by nlminb convergence criteria (Nash 2014), were re-fit using different initial values. If re-fit tracks continually failed to converge they were removed from the final filtered dataset. For converged tracks, longitude and latitude residuals were examined for systematic trends indicative of lack of fit. Tracks that failed this inspection were removed from the final filtered dataset.
  5. Data publication The core working team of RAATD established a data sharing and publication agreement with all data providers in 2017. The standardized (trimmed) data are held here. The filtered data are published in international repositories (see details below, in the ‘Filtered Data’ section).