The SCAR Retrospective Analysis of Antarctic Tracking Data

The SCAR Retrospective Analysis of Antarctic Tracking Data project is a multi-species synthesis of movement data of Antarctic predators intended to identify Areas of Ecological Significance. These areas are defined as being used by multiple air-breathing predator species and therefore indicative of...

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Bibliographic Details
Main Authors: Hindell, Mark A., Ropert-Coudert, Yan, van de Putte, Anton P., Bornemann, Horst, Charrassin, Jean-Benoît, Danis, Bruno, Hückstädt, Luis A., Jonsen, Ian D., Lea, Mary-Anne, Raymond, Ben, Reisinger, Ryan R., Torres, Leigh G., Trathan, Phil N., Wotherspoon, Simon
Format: Conference Object
Language:unknown
Published: 2017
Subjects:
Online Access:https://epic.awi.de/id/eprint/45900/
https://hdl.handle.net/10013/epic.51987
Description
Summary:The SCAR Retrospective Analysis of Antarctic Tracking Data project is a multi-species synthesis of movement data of Antarctic predators intended to identify Areas of Ecological Significance. These areas are defined as being used by multiple air-breathing predator species and therefore indicative of high biodiversity and abundance of lower trophic organisms. The study therefore aims to provide: (i) a greater understanding of fundamental ecosystem processes in the Southern Ocean, (ii) facilitate future projections of predator distributions under varying climate regimes, and (iii) provide input into spatial planning decisions for management and conservation authorities. Since April 1 2016, RAATD has accumulated almost 3 million at-sea locations from 17 species of seabirds and marine mammals, using GPS, light level geolocation, and ARGOS satellite tracking devices. Importantly, these data come from 49 separate data contributors from 10 countries, who have agreed to share their hard won data with the Antarctic tracking community. The analytical framework of RAATD consists of (i) developing a habitat utilization model for each species, (ii) application of this model towards global predictions of important habitat based on colony locations (where appropriate) for that species, and then (iii) compilation of these species-specific predictions to identify Areas of Ecological Significance. We will present an overview of the dataset and highlight some of the analytical challenges and successes involved in our multi-species synthesis.