Towards the integration of animal‐borne instruments into global ocean observing systems. (27th November 2019) - March, David; Boehme, Lars; Tintoré, Joaquín; Vélez‐Belchi, Pedro Joaquín; Godley, Brendan J.
Abstract: Marine animals are increasingly instrumented with environmental sensors that provide large volumes of oceanographic data. Here, we conduct an innovative and comprehensive global analysis to determine the potential contribution of animal‐borne instruments (ABI) into ocean observing systems (OOSs) and provide a foundation to establish future integrated ocean monitoring programmes. We analyse the current gaps of the long‐term Argo observing system (>1.5 million profiles) and assess its spatial overlap with the distribution of marine animals across eight major species groups (tuna and billfishes, sharks and rays, marine turtles, pinnipeds, cetaceans, sirenians, flying seabirds and penguins). We combine distribution ranges of 183 species and satellite tracking observations from >3, 000 animals. Our analyses identify potential areas where ABI could complement OOS. Specifically, ABI have the potential to fill gaps in marginal seas, upwelling areas, the upper 10 m of the water column, shelf regions and polewards of 60° latitude. Our approach provides the global baseline required to plan the integration of ABI into global and regional OOS while integrating conservation and ocean monitoring priorities. Abstract : Marine animals are increasingly instrumented with environmental sensors that provide large volumes of oceanographic data. By linking sampling gaps in ocean monitoring with marine animal distributions, this study provides new insights into using such sensors more efficiently to complement ocean observing systems at global and regional scales. With limited potential to monitor the deep ocean, animal‐borne instruments could fill the gaps in marginal seas, upwelling areas, the upper 10 m of the water column, shelf regions and polewards of 60° latitude. This contribution could benefit ocean research in reducing monitoring biases and improving our understanding of key oceanographic processes.