Demographic characteristics of Australian humpback dolphins reveal important habitat toward the southwestern limit of their range

Open Access under Creative Commons by Attribution Licence. Use, distribution and reproduction are un-restricted. Authors and original publication must be credited.ABSTRACT: The paucity of information on the recently described Australian humpback dolphin Sousa sahulensis has hindered assessment of its conservation status. Here, we applied capture-recapture models to photo-identification data collected during boat-based surveys between 2013 and 2015 to estimate the abundance, site fidelity and residence patterns of Australian humpback dolphins around the North West Cape (NWC), Western Australia. Using Pollock’s closed robust design, abundance estimates varied from 65 to 102 individuals, and POPAN open modelling yielded a super-population size of 129 individuals in the 130 km2 study area. At approximately 1 humpback dolphin per km2, this density is the highest recorded for this species. Temporary emigration was Markovian, suggesting seasonal movement in and out of the study area. Hierarchical clustering showed that 63% of individuals identified exhibited high levels of site fidelity. Analysis of lagged identification rates indicated dolphins use the study area regularly, following a movement model characterised by emigration and re-immigration. These density, site fidelity and residence patterns indicate that the NWC is an important habitat toward the southwestern limit of this species’ range. Much of the NWC study area lies within a Marine Protected Area, offering a regulatory framework on which to base the management of human activities with the potential to impact this threatened species. Our methods provide a methodological framework to be used in future environmental impact assessments, and our findings represent a baseline from which to develop long-term studies to gain a more complete understanding of Australian humpback dolphin population dynamics

Automated photo-identification of cetaceans : An integrated software solution

This study investigates current techniques used for automated photo-identification of cetaceans (i.e. dolphins and whales). The primary focus constitutes various techniques that can be applied to identify and extract dorsal fins from digital photographs. A comprehensive analysis of these techniques demonstrates the most effective software solution. To further support this analysis, four prototypes are developed to demonstrate the effectiveness of each technique in a practical environment. The analysis bases its final conclusions on test results generated from these prototype software examples. Final conclusions provide recommendations for an effective, accurate, and practical software solution. This software solution allows dorsal fins to be easily extracted from digital photographs and identified through the use of computer automated methods

Assessment of a non-invasive approach to pregnancy diagnosis in gray whales through drone-based photogrammetry and faecal hormone analysis

This project was supported by the NOAA National Marine Fisheries Service Office of Science and Technology, the Office of Naval Research Marine Mammals and Biology Program (no. N00014-20-1-2760), the Oregon State University Marine Mammal Institute and Oregon Sea Grant.Knowledge of baleen whales’ reproductive physiology is limited and requires long-term individual-based studies and innovative tools. We used 6 years of individual-level data on the Pacific Coast Feeding Group gray whales to evaluate the utility of faecal progesterone immunoassays and drone-based photogrammetry for pregnancy diagnosis. We explored the variability in faecal progesterone metabolites and body morphology relative to observed reproductive status and estimated the pregnancy probability for mature females of unknown reproductive status using normal mixture models. Individual females had higher faecal progesterone concentrations when pregnant than when presumed nonpregnant. Yet, at the population level, high overlap and variability in progesterone metabolite concentrations occurred between pregnant and non-pregnant groups, limiting this metric for accurate pregnancy diagnosis in gray whales. Alternatively, body width at 50% of the total body length (W50) correctly discriminated pregnant from non-pregnant females at individual and population levels, with high accuracy. Application of the model using W50 metric to mature females of unknown pregnancy status identified eight additional pregnancies with high confidence. Our findings highlight the utility of drone-based photogrammetry to non-invasively diagnose pregnancy in this group of gray whales, and the potential for improved data on reproductive rates for population management of baleen whales generally.Publisher PDFPeer reviewe