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Ian D. Jonsen

Researcher at Macquarie University

Publications -  96
Citations -  7189

Ian D. Jonsen is an academic researcher from Macquarie University. The author has contributed to research in topics: Foraging & Population. The author has an hindex of 37, co-authored 87 publications receiving 6093 citations. Previous affiliations of Ian D. Jonsen include Bedford Institute of Oceanography & Dalhousie University.

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Transmitting species-interaction data from animal-borne transceivers through Service Argos using Bluetooth communication

TL;DR: In this article, a Bluetooth link was integrated into the VMT and GPS satellite-linked transmitter to collect data on species interactions in otherwise inaccessible environments and without the need to recover instruments.
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Abundance estimates and habitat preferences of bottlenose dolphins reveal the importance of two gulfs in South Australia

TL;DR: The high densities of bottlenose dolphins in the two gulfs highlight the importance of these gulfs as a habitat for the species and should inform management strategies, marine park planning and environmental assessments of potential anthropogenic threats to this protected species.
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A Water Mass Classification Approach to Tracking Variability in the East Australian Current

TL;DR: In this paper, a machine-learning classification approach was developed to quantify variability in coastal EAC dynamics along a latitudinal gradient within the EAC extension zone in southeastern Australia, showing significant decadal-scale changes to EAC's dynamics in the region.
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Inter- and intrasex habitat partitioning in the highly dimorphic southern elephant seal

TL;DR: In the case of the southern elephant seal, the authors of as mentioned in this paper found that the intersexual differences in habitat use existed before the divergence in body size and that the amount of energy gained was the same in all of the major habitats.
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Putting the behavior into animal movement modeling: Improved activity budgets from use of ancillary tag information

TL;DR: Two state‐space models adapted to incorporate ancillary data to inform three discrete movement states: directed, resident, and an activity state are presented, reinforcing previously raised contentions about the drawbacks of behavioral states inferred solely from horizontal movements.