Identification Of Dolphins Research Articles

Fine-scale spatial variability of marine acoustic environment corresponds with habitat utilization of Indo-Pacific humpback dolphins in Hong Kong waters

Acoustic properties of the underwater environment are important in maintaining biological processes of various marine organisms. However, with the increasing level of underwater noise in the global ocean, there is a growing need to better understand how marine animals use soundscape cues in their habitat selection. Indo-Pacific humpback dolphins (Sousa chinensis) inhabiting the Pearl River Estuary, southeast China, live in one of world’s most developed and noisiest coastal environment and are subjected to many sources of anthropogenic noise. To investigate whether spatial variability of underwater soundscape corresponds with their habitat utilization, we collected daytime underwater recordings in western Hong Kong waters from mid-2016 to mid-2018, and quantified the spatial pattern of marine acoustic environment and its differing characteristics in a fine spatial scale. We developed a framework of soundscape information retrieval to investigate spectral features that may facilitate identification of dolphins’ core habitats. Our findings reveal that a spectral feature, which peaks at 2 kHz, is a reliable predictor of humpback dolphin core habitat. Further modelling of spatial and seasonal variations of underwater soundscape demonstrates that the relative strength of this spectral feature is positively correlated with the sighting rates of humpback dolphins throughout the year. Although the source of the 2 kHz feature remains unknown, it is likely associated with humpback dolphins’ prey. We suggest that underwater acoustic environment represents an important component in evaluating the quality and suitability of coastal habitats for the daily needs of this threatened dolphin species. Local and regional conservation authorities should include habitat-specific baseline soundscape data when developing conservation management strategies.

ARIANNA: A novel deep learning-based system for fin contours analysis in individual recognition of dolphins

Starting from a digital image that represents the dolphin's body, distinctive features are extracted and used to find the identity of the unknown dolphin in a set of known individuals. This process is called photo identification, used by experts to monitor dolphins, providing relevant data to preserve the environment and its biodiversity. In this work, we show how semantic segmentation can be used to automatically extract a dolphin's fin contour starting from a cropped photo of the fin, and how this contour can be used for individual identification. A novel contour-based system, called ARIANNA, for the automated cetacean photo identification was designed, developed and tested. The novelty of this system is the adoption of two original modules. The first one, which takes as input a new cropped fin image of unknown dolphin, is devoted to the extraction of a mask that depicts the outline of the unknown fin; the core of this module is a trained neural network, specialized in semantic segmentation of images. The second module is designed to compare the outline of the unknown fin with the outlines of all known dolphins, collected in a referring catalogue, returning a ranked list of the best matches where to search the dolphin identity. The experiments were conducted on images collected between 2013 and 2020 in the Northern Ionian Sea (Central-eastern Mediterranean Sea), which presented cropped fins of Risso's dolphin Grampus griseus, one of the least-known cetacean species on a global and Mediterranean scale. The results suggest that ARIANNA provides advances over the state-of-the-art methods, can efficiently assist researchers in the photo identification of dolphins and can be a starting point for further studies on the photo identification of different species based on semantic segmentation.

Indo‐Pacific humpback dolphins (Sousa chinensis) in the Moyang River Estuary: The western part of the world's largest population of humpback dolphins

AbstractInformation gaps from uninvestigated habitats can hinder population assessments and the efficacy of conservation actions for marine mammals, particularly for populations of widely distributed species. The full extent of occurrence of the world's largest (putative) population of Indo‐Pacific humpback dolphins (Sousa chinensis) in the Pearl River estuary (PRE) is not known due to a poor understanding of the western boundary of the population's range. This information gap is the basis of the most critical obstacle for assessing the population's status.To determine the distribution and abundance of the PRE humpback dolphins in the far western portion of its range, systematic line‐transect vessel surveys were conducted in the Moyang River estuary (MRE) during 2013–2015. Photo identification of dolphins and cross‐matching of individual dolphins between different regions were also undertaken to examine individual movement patterns.The abundance of humpback dolphins in the MRE was estimated to be 528 individuals (coefficient of variation: 28.7–50.2%).Cross‐matching of individually identified dolphins from the MRE (present survey area) with those from other survey areas of the PRE showed that dolphins moved frequently across different regions of the PRE, indicating dolphins from both PRE and MRE comprise a single population (which is renamed to be the PRE–MRE population). The western boundary of this population appears to be in the waters on the eastern side of Hailing Island, as dolphins were never observed further west.Supporting around one‐fifth of the PRE–MRE population and providing a quarter of the habitat of the entire PRE–MRE population, the MRE clearly also deserves consideration for greater conservation measures. Strengthening the management with stringent controls over fishing activities in the MRE and establishing a marine protected area in the core habitat are recommended to facilitate better conservation for the entire PRE–MRE humpback dolphin population.

Digital Photography Improves Efficiency Of Individual Dolphin Identification: A Reply to Markowitz et al.

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Digital Photography Improves Efficiency Of Individual Dolphin Identification: A Reply To Mizroch

Marine Mammal ScienceVolume 19, Issue 3 p. 608-612 Digital Photography Improves Efficiency Of Individual Dolphin Identification: A Reply To Mizroch T. M. Markowitz, T. M. Markowitz Marine Mammal Research Program, Department of Wildlife and Fisheries Sciences, Texas A&M University, 4700 Avenue U, Building 303, Galveston, Texas 77551, U.S.A.; e-mail: tim_markowitz@yahoo.comSearch for more papers by this authorA. D. Harlin, A. D. Harlin Marine Mammal Research Program, Department of Wildlife and Fisheries Sciences, Texas A&M University, 4700 Avenue U, Building 303, Galveston, Texas 77551, U.S.A.; e-mail: tim_markowitz@yahoo.comSearch for more papers by this authorB. Würsig, B. Würsig Marine Mammal Research Program, Department of Wildlife and Fisheries Sciences, Texas A&M University, 4700 Avenue U, Building 303, Galveston, Texas 77551, U.S.A.; e-mail: tim_markowitz@yahoo.comSearch for more papers by this author T. M. Markowitz, T. M. Markowitz Marine Mammal Research Program, Department of Wildlife and Fisheries Sciences, Texas A&M University, 4700 Avenue U, Building 303, Galveston, Texas 77551, U.S.A.; e-mail: tim_markowitz@yahoo.comSearch for more papers by this authorA. D. Harlin, A. D. Harlin Marine Mammal Research Program, Department of Wildlife and Fisheries Sciences, Texas A&M University, 4700 Avenue U, Building 303, Galveston, Texas 77551, U.S.A.; e-mail: tim_markowitz@yahoo.comSearch for more papers by this authorB. Würsig, B. Würsig Marine Mammal Research Program, Department of Wildlife and Fisheries Sciences, Texas A&M University, 4700 Avenue U, Building 303, Galveston, Texas 77551, U.S.A.; e-mail: tim_markowitz@yahoo.comSearch for more papers by this author First published: 26 August 2006 https://doi.org/10.1111/j.1748-7692.2003.tb01326.xCitations: 4AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Citing Literature Volume19, Issue3July 2003Pages 608-612 RelatedInformation

DIGITAL PHOTOGRAPHY IMPROVES EFFICIENCY OF INDIVIDUAL DOLPHIN IDENTIFICATION

Marine Mammal ScienceVolume 19, Issue 1 p. 217-223 DIGITAL PHOTOGRAPHY IMPROVES EFFICIENCY OF INDIVIDUAL DOLPHIN IDENTIFICATION Tim M. Markowitz, Tim M. Markowitz Marine Mammal Research Program, Department of Wildlife and Fisheries Sciences, Texas A&M University, 4700 Avenue U, Building 303, Galveston, Texas 77551, U.S.A. E-mail: tim_markowitz@yahoo.comSearch for more papers by this authorAprilD. Harlin, AprilD. Harlin Marine Mammal Research Program, Department of Wildlife and Fisheries Sciences, Texas A&M University, 4700 Avenue U, Building 303, Galveston, Texas 77551, U.S.A. E-mail: tim_markowitz@yahoo.comSearch for more papers by this authorBernd Würsig, Bernd Würsig Marine Mammal Research Program, Department of Wildlife and Fisheries Sciences, Texas A&M University, 4700 Avenue U, Building 303, Galveston, Texas 77551, U.S.A. E-mail: tim_markowitz@yahoo.comSearch for more papers by this author Tim M. Markowitz, Tim M. Markowitz Marine Mammal Research Program, Department of Wildlife and Fisheries Sciences, Texas A&M University, 4700 Avenue U, Building 303, Galveston, Texas 77551, U.S.A. E-mail: tim_markowitz@yahoo.comSearch for more papers by this authorAprilD. Harlin, AprilD. Harlin Marine Mammal Research Program, Department of Wildlife and Fisheries Sciences, Texas A&M University, 4700 Avenue U, Building 303, Galveston, Texas 77551, U.S.A. E-mail: tim_markowitz@yahoo.comSearch for more papers by this authorBernd Würsig, Bernd Würsig Marine Mammal Research Program, Department of Wildlife and Fisheries Sciences, Texas A&M University, 4700 Avenue U, Building 303, Galveston, Texas 77551, U.S.A. E-mail: tim_markowitz@yahoo.comSearch for more papers by this author First published: 26 August 2006 https://doi.org/10.1111/j.1748-7692.2003.tb01103.xCitations: 36AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Citing Literature Volume19, Issue1January 2003Pages 217-223 RelatedInformation

A string matching computer-assisted system for dolphin photoidentification.

This paper presents a syntactic/semantic string representation scheme as well as a string matching method as part of a computer-assisted system to identify dolphins from photographs of their dorsal fins. A low-level string representation is constructed from the curvature function of a dolphin's fin trailing edge, consisting of positive and negative curvature primitives. A high-level string representation is then built over the low-level string via merging appropriate groupings of primitives in order to have a less sensitive representation to curvature fluctuations or noise. A family of syntactic/semantic distance measures between two strings is introduced. A composite distance measure is then defined and used as a dissimilarity measure for database search, highlighting both the syntax (structure or sequence) and semantic (attribute or feature) differences. The syntax consists of an ordered sequence of significant protrusions and intrusions on the edge, while the semantics consist of seven attributes extracted from the edge and its curvature function. The matching results are reported for a database of 624 images corresponding to 164 individual dolphins. The identification results indicate that the developed string matching method performs better than the previous matching methods including dorsal ratio, curvature, and curve matching. The developed computer-assisted system can help marine mammalogists in their identification of dolphins, since it allows them to examine only a handful of candidate images instead of the currently used manual searching of the entire database.

Assisting manual dolphin identification by computer extraction of dorsal ratio.

Marine biologists use a measurement called the "Dorsal Ratio" in the process of manual identification of bottlenose dolphins. The dorsal ratio denotes the relative distances of the two largest notches from the tip on the dorsal fin. The manual computation of this ratio is time consuming, labor intensive, and user dependent. This paper presents a computer-assisted system to extract the dorsal ratio for use in identification of individual animals. The first component of the system consists of active contour modeling where the trailing edge of the dorsal fin is detected. This is followed by a curvature module to find the characteristic fin points: tip and two most prominent notches. Curvature smoothing is performed at various smoothing scales, and wavelet coefficients are utilized to select an appropriate smoothing scale. The dorsal ratio is then computed from the curvature function at the appropriate smoothing scale. The system was tested using 296 digitized images of dolphins, representing 94 individual dolphins. The results obtained indicate that the computer extracted dorsal ratio can be used in place of the manually extracted dorsal ratio as part of the manual identification process.