Long-Term Assessment of Spatio-Temporal Association Patterns of Dusky Dolphins (Lagenorhynchus obscurus) off Kaikoura, New Zealand

Orbach, Dara N.; Pearson, Heidi C.; Beier-Engelhaupt, Amy; Deutsch, Sierra; Srinivasan, Mridula; Weir, Jody S.; Yin, Suzanne; Würsig, Bernd

doi:10.1578/am.44.6.2018.608

Cited by 10 publications

(8 citation statements)

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“…While boat-based observations off Kaikoura have provided important new insights into dusky dolphin mating behaviors (Markowitz et al, 2010;Orbach et al, 2014Orbach et al, , 2015a, fission-fusion societies (Markowitz, 2004;Orbach et al, 2018), and nursery group habitat use (Weir, Deutsch, & Pearson, 2010;Weir, Duprey, & Würsig, 2008), the platform of observation has inherent limitations. For example, the low angle of view from a small (6 m long) boat can prevent observations of dolphin behaviors slightly below the surface of the water that are visible from a higher vantage point (Smultea et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

“…The Kaikoura population consists of ∼2,000 dusky dolphins present at any given time, from a national New Zealand population estimate of ∼12,000 dolphins (Markowitz, 2004); however, recent data suggest that the Kaikoura population may be larger (Orbach et al, 2018). Dusky dolphins are gregarious animals with a highly fluid fission‐fusion social structure and group sizes ranging from 2 to over 1,000 animals (Orbach et al, 2018; Würsig et al, 1997). The mating patterns of male and female dusky dolphins have been described using boat‐based videos and photographs (Markowitz, Markowitz, & Morton, 2010; Orbach, Packard, Kirchner, & Würsig, 2015a).…”

Section: Introductionmentioning

confidence: 99%

“…Males are inverted during much of mating chases and are consistently inverted during copulation attempts (Orbach et al, 2015a), and only 52% of the population has distinguishable natural markings on their dorsal fins (Kügler & Orbach, 2014). Consequently, it is typically not possible to track individual males in situ or by photo‐identification based on dorsal fin markings, the common technique used for distinguishing individual dusky dolphins (Orbach et al, 2018; Würsig & Jefferson, 1990). However, unmanned aerial vehicles (UAVs) provide a platform of observation that circumvents these limitations and can procure high quality video data for post hoc analyses.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Mating patterns of dusky dolphins (Lagenorhynchus obscurus) explored using an unmanned aerial vehicle

Orbach

Eaton

Fiori

et al. 2020

Marine Mammal Science

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Mating patterns of dusky dolphins (Lagenorhynchus obscurus) explored using an unmanned aerial vehicle

Orbach

Eaton

Fiori

et al. 2020

Marine Mammal Science

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“…This mirrors the social patterns of several other dolphin species living in sub-tropical, temperate and cold waters (e.g. bottlenose dolphins, Augusto et al 2012;Louis et al 2015;Dinis et al 2017;Papale et al 2017;Pleslić et al 2019;Commerson's dolphins, Coscarella et al 2011;dusky dolphins, Pearson et al 2017;Orbach et al 2018;snubfin dolphins, Parra et al 2011). This may suggest some universality to the drivers of social patterns across latitude, particularly the trade-off in relation to group size, predation risk, and prey availability (Wrangham & Rubenstein 1986;Connor et al 1998;Gowans et al 2007).…”

Section: Discussionmentioning

confidence: 56%

Fission–fusion dynamics of a pelagic delphinid in the arctic: the white‐beaked dolphin (Lagenorhynchus albirostris)

2021

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Delphinids exhibit great variability in their social structures. It is therefore important to document lesser known species, in extreme changing habitats, to compare and contrast mechanisms driving sociality. Here, we describe the first long-term assessment of social structure of white-beaked dolphins (Lagenorhynchus albirostris) using a compiled version of SOCPROG 2.8 and an 11-year photo-identification dataset (2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013) collected from whalewatching vessels at 2 sites (Faxaflói and Skjálfandi bays) off Iceland. We identified a total of 487 dolphins which are suggested to be part of an open population as shown by the discovery curve obtained analyzing photo-id data. The social analyses were restricted to 35 adults which were sighted on ≥5 different days. The mean residency time of white-beaked dolphins in our 2 study areas was of 95 days (SE = 35.63; 95% CI: 23-171), with the "migration-full interchange" model best describing movements of dolphins in and out of our 2 study sites. Social differentiation in this population was high (Likelihood: S = 0.87, SE = 0.04; r = 0.31, SE = 0.03) indicating diverse, non-random social relationships. Temporal associations best fit the model of "casual acquaintances" against the standardized lagged association rates with the majority of white-beaked dolphin associations being short-term, but with a few long-term across years. Testing for preferred companionship, long-term associations are favored over short-term. In this study, associations among white-beaked dolphins are short-term but with desirably long-term associations fitting into a society with fission-fusion dynamics. This information expands the latitudinal range for which social structure has been described for oceanic dolphin species.

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“…This concept is relevant because odontocetes are at the top of the food chain, and their presence indicates resilient ecosystems and highquality habitats. Strictly related to site fidelity, the concept of residency patterns analyses the temporal variation in habitat use by marine mammal species [31], [36], [41]- [45], [49]. Finally, photo identification can be efficiently applied to provide a baseline on species population abundance.…”

Section: A Field Of Application Of Automated and Semiautomated Photo ...mentioning

confidence: 99%

Machine Learning and Image Processing Methods for Cetacean Photo Identification: A Systematic Review

Maglietta

Carlucci

Fanizza³

et al. 2022

IEEE Access

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Photo identification is an essential method to identify cetaceans, by using natural marks over their body, and allows experts to acquire straightforward information on these animals. The importance of cetaceans lies in te fact that they play a crucial role in maintaining the healthiness of marine ecosystems, however they are exposed to several anthropogenic stressors, under which they could collapse with extreme consequences on the marine ecosystem functioning. Hence, obtaining new knowledge on their status is extremely urgent for the marine biodiversity conservation. The smart use of technology to automate the individual recognition can speed up the photo identification process, opening the door to large-scale studies that are manually unfeasible. We performed a systematic review on systems based on machine learning and statistical methods for cetacean photo identification, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement. This review highlights that interest has been increasing in recent years and several intelligent systems have been presented. However, there are still some open questions, and further efforts to develop more effective automated systems for cetacean photo identification are recommended.INDEX TERMS machine learning algorithms, Convolutional Neural Networks, feature extraction, reviews, oceanic engineering and marine technology, image processing

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Long-Term Assessment of Spatio-Temporal Association Patterns of Dusky Dolphins (Lagenorhynchus obscurus) off Kaikoura, New Zealand

Cited by 10 publications

References 0 publications

Mating patterns of dusky dolphins (Lagenorhynchus obscurus) explored using an unmanned aerial vehicle

Mating patterns of dusky dolphins (Lagenorhynchus obscurus) explored using an unmanned aerial vehicle

Fission–fusion dynamics of a pelagic delphinid in the arctic: the white‐beaked dolphin (Lagenorhynchus albirostris)

Machine Learning and Image Processing Methods for Cetacean Photo Identification: A Systematic Review

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