Ancillary data from animal-borne cameras as an ecological survey tool for marine communities

Author:

Chapple T. K.,Tickler D.,Roche R. C.,Bayley D. T. I.,Gleiss A. C.,Kanive P. E.,Jewell O. J. D.,Jorgensen S. J.,Schallert R.,Carlisle A. B.,Pilly J. Sannassy,Andrzejaczek S.,Wikelski M.,Hussey N. E.,Block B. A.

Abstract

AbstractUnderwater visual surveys represent an essential component of coastal marine research and play a crucial role in supporting the management of marine systems. However, logistical and financial considerations can limit the availability of survey data in some systems. While biologging camera tag devices are being attached to an increasing diversity of marine animals to collect behavioral information about the focal species, the ancillary imagery collected can also be used in analytical techniques developed for diver-based surveys. We illustrate this approach by extracting ancillary data from shark-borne camera tag deployments focused on the behavior of a White shark (Carcharodon carcharias) off Gansbaai, South Africa, and a Grey Reef shark (Carcharhinus amblyrhynchos) within the Chagos Archipelago. Within the giant kelp forest environment of Gansbaai we could determine the spatial density of kelp thali and underlying substrate composition. Within the coral reef environment, the animal-borne video allowed us to determine the approximate percent and type of benthic cover, as well as growth form and genus of corals down to the upper mesophotic zone. We also enumerated fish species-level abundance over reef flat and wall environments. We used established dive-survey methods to analyze video data and found the results to be broadly comparable in the two systems studied. Our work illustrates the broad applicability of ancillary animal-borne video data, which is analogous in type and quality to diver-based video data, for analysis in established marine community survey frameworks. As camera tags and associated biologging technologies continue to develop and are adapted to new environments, utilising these data could have wide-ranging applications and could maximise the overall cost–benefit ratio within biologging deployments.

Funder

Fondation Bertarelli

Stanford University

National Geographic Society

Publisher

Springer Science and Business Media LLC

Subject

Ecology,Aquatic Science,Ecology, Evolution, Behavior and Systematics

Reference51 articles.

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