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

• Published in: Royal Society Open Science
• Main Authors: Fernandez Ajó, Alejandro, Pirotta, Enrico, Bierlich, K. C., Hildebrand, Lisa, Bird, Clara N., Hunt, Kathleen E., Buck, C. Loren, New, Leslie, Dillon, Danielle, Torres, Leigh G.
• Format: Article in Journal/Newspaper
• Language: English
• Published: 2023
• Subjects: Gray whale; Progesterone; Drone-based photogrammetry; Enzyme immunoassay; Pregnancy; Pacific; baleen whales
• Online Access: https://research-portal.st-andrews.ac.uk/en/publications/cb70c056-f611-432d-9cc5-ff67b7b843bc; https://doi.org/10.1098/rsos.230452; https://research-repository.st-andrews.ac.uk/bitstream/10023/28000/1/Fernandez_2023_RSOS_Assesment_non_invasive_CC.pdf

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.