Identifying seabird interactions with fisheries from GPS tracks: Automatic classification validated using bird-borne video recordings

• Main Authors: 3rd World Seabird Conference 2021, Gremillet, David
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: Underline Science Inc. 2021
• Subjects: Animal Science; Computer-Aided Technologies; Amélie; National Institute of Polar Research
• Online Access: https://dx.doi.org/10.48448/2nqk-7j80; https://underline.io/lecture/34569-identifying-seabird-interactions-with-fisheries-from-gps-tracks-automatic-classification-validated-using-bird-borne-video-recordings

Abstract: The world seabird community is declining globally, and seabird-fishery interactions have been identified as a significant cause of this general trend. It is therefore important and urgent to better understand the spatio-temporal determinants of such interactions. Historically, those have been extensively studied using at-sea observations and dietary studies. More recently, bird-borne devices allowed tracking seabird behaviour over time, but it is challenging to identify seabird-fisheries interactions exclusively from those movement data. Fortunately, bird-borne videos have brought invaluable information on the subject, enabling to directly observe the surroundings of ocean wanderers. Yet, the analysis of video data is extremely time-consuming. Using combined deployments of GPS and video cameras, we aimed at identifying specific movement patterns (GPS data) associated with seabird-fisheries interactions (as observed from video). If such patterns can be automatically identified, the routine can then be widely applied to similar datasets comprising only movement data. We deployed GPS recorders and cameras on 37 northern gannets (Morus bassanus) foraging in the English Channel from 2011 to 2015. In addition, 185 gannets from the same breeding colony were equipped with GPS only across 2005-2019. Using statistical and modelling procedures, we analysed the fine scale foraging movements of gannets interacting with fisheries to identify specific movement patterns associated with seabird-fisheries interactions. The classification model was then applied to all GPS-tracked Northern gannets to detect and map the spatio-temporal dynamics of gannet-fishery interactions in the English Channel across 2005-2019. Overall, our analysis provides a long-term perspective on seabird-fishery interactions in one of the most anthropized seas of the planet, and we propose a general methodology to help reach a better understanding of seabirds/fisheries interactions worldwide. Authors: David Grémillet¹, Amélie Lescroël¹, Andréa Thiebault², Jérôme Fort¹, Pascal Provost³, Akinori Takahashi⁴, Clara Péron⁵ ¹CNRS, ²NMMU, ³LPO, ⁴National Institute of Polar Research, ⁵MNHN