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This repo goes through: importing IMOS acoustic telemetry data, curating and generating residency / non-residencey movements, fetching oceanographic data from IMOS thredds servers directly, connecting movement to oceanographic predictors, utilising both linear and non-linear mixed models to uncover signficant drivers and then visualising data.

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ecologistpablo/C.-taurus-capture-movement-eastern-Aus

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GNS Carharias taurus G Smith flat

Grey nurse shark (Carcharias taurus) capture and movement in eastern Australia

This repository was created by Pablo Fuenzalida, as a part of an honours thesis completed in 2024. All code was written by me (unless otherwise stated) with the heavy assistance from my fantastic supervisory team: Dr. Ross Dwyer, Associate Professor Kylie Scales and Professor David Schoeman.

#This paper is yet to be published and analysis yet to be finalised.

Our research focuses on utilising acoustic telemetry detection data from IMOS (imos.org.au) as well as Queensland department of agriculture and fisheries (DAF) and NSW department of primary industries (DPI) shark control program bycatch data for grey nurse sharks (Carcharias taurus) to connect the migratory movements on a continent scale between certain key aggregation sites with bycatch occurences in the shark control programs. We also model what drives this movement using generalised linear and additive mixed models.

DISCLAIMER

No shark control program analyses or data will be shared before a manuscript has been published.

So this repo will just contain the analysis of openly available data, C. taurus detections accessed from the AODN portal (https://animaltracking.aodn.org.au/), you can replicate this for any species however.

For any questions or concerns regarding this repository, code or any analysis, please email [email protected] tiled workflow GitHub

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This repo goes through: importing IMOS acoustic telemetry data, curating and generating residency / non-residencey movements, fetching oceanographic data from IMOS thredds servers directly, connecting movement to oceanographic predictors, utilising both linear and non-linear mixed models to uncover signficant drivers and then visualising data.

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