TY  - STD
AU  - David Grémillet, Damien Chevallier
PY  - 2022//
TI  - Big data approaches to the spatial ecology and conservation of marine megafauna
N2  - Satellite remote-sensing and wildlife tracking allow researchers to record rapidly increasing volumes of information on the spatial ecology of marine megafauna in the context of global change. This field of investigation is thereby entering the realm of big data science: Information technology allows the design of completely new frameworks for acquiring, storing, sharing, analysing, visualizing, and publicizing data. This review aims at framing the importance of big data for the conservation of marine megafauna, through intimate knowledge of the spatial ecology of these threatened, charismatic animals. We first define marine megafauna and big data science, before detailing the technological breakthroughs leading to pioneering “big data” studies. We then describe the workflow from acquiring megafauna tracking data to the identification and the prediction of their critical habitats under global changes, leading to marine spatial planning and political negotiations. Finally, we outline future objectives for big data studies, which should not take the form of a blind technological race forward, but of a coordinated, worldwide approach to megafauna spatial ecology, based on regular gap analyses, with care for ethical and environmental implications. Employing big data science for the efficient conservation of marine megafauna will also require inventing new pathways from research to action.
SN  - 1054-3139
L1  - http://publi.ipev.fr/polar_references/files/yes
UR  - http://dx.doi.org/10.1093/icesjms/fsac059
N1  - exported from refbase (http://publi.ipev.fr/polar_references/show.php?record=8332), last updated on Tue, 30 Nov 1999 00:00:00 +0100
ID  - DavidGremillet2022
ER  -