Body mass is a key life‐history trait in animals. Despite being the largest animals on the planet, no method currently exists to estimate body mass of free‐living whales. We combined aerial photographs and historical catch records to estimate the body mass of free‐living right whales (Eubalaena sp.). First, aerial photogrammetry from unmanned aerial vehicles was used to measure the body length, width (lateral distance) and height (dorso‐ventral distance) of free‐living southern right whales (Eubalaena australis; 48 calves, seven juveniles and 31 lactating females). From these data, body volume was estimated by modelling the whales as a series of infinitely small ellipses. The body girth of the whales was next calculated at three measurement sites (across the pectoral fin, the umbilicus and the anus) and a linear model was developed to predict body volume from the body girth and length data. To obtain a volume‐to‐mass conversion factor, this model was then used to estimate the body volume of eight lethally caught North Pacific right whales (Eubalaena japonica), for which body mass was measured. This conversion factor was consequently used to predict the body mass of the free‐living whales. The cross‐sectional body shape (height–width ratio) of the whales was slightly flattened dorso‐ventrally at the anterior end of the body, almost circular in the mid region, and significantly flattened in the lateral plane across the posterior half of the body. Compared to a circular cross‐sectional model, our body mass model incorporating body length, width and height improved mass estimates by up to 23.6% (mean = 6.1%, SD = 5.27). Our model had a mean error of only 1.6% (SD = 0.012), compared to 9.5% (SD = 7.68) for a simpler body length‐to‐mass model. The volume‐to‐mass conversion factor was estimated at 754.63 kg/m3 (SD = 50.03). Predicted body mass estimates were within a close range of existing body mass measurements. We provide a non‐invasive method to accurately estimate body mass of free‐living whales while accounting for both their structural size (body length) and relative body condition (body width). Our approach can be directly applied to other marine mammals by adjusting the model parameters (body mass model script provided).

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At least 626 southern right whale (Eubalaena australis) calves died at the Península Valdés calving ground, Argentina, between 2003 and 2014. Intense gull harassment may have contributed to these deaths. In the 1970s, Kelp Gulls (Larus dominicanus) began feeding on skin and blubber pecked from the backs of living right whales at Valdés. The frequency of gull attacks has increased dramatically over the last three decades and mother-calf pairs are the primary targets. Pairs attacked by gulls spend less time nursing, resting and playing than pairs not under attack. In successive attacks, gulls open new lesions on the whales’ backs or enlarge preexisting ones. Increased wounding could potentially lead to dehydration, impaired thermoregulation, and energy loss to wound healing. The presence, number and total area of gull-inflicted lesions were assessed using aerial survey photographs of living mother-calf pairs in 1974–2011 (n = 2680) and stranding photographs of dead calves (n = 192) in 2003–2011. The percentage of living mothers and calves with gull lesions increased from an average of 2% in the 1970s to 99% in the 2000s. In the 1980s and 1990s, mothers and calves had roughly equal numbers of lesions (one to five), but by the 2000s, calves had more lesions (nine or more) covering a greater area of their backs compared to their mothers. Living mother-calf pairs and dead calves in Golfo Nuevo had more lesions than those in Golfo San José in the 2000s. The number and area of lesions increased with calf age during the calving season. Intensified Kelp Gull harassment at Península Valdés could be compromising calf health and thereby contributing to the high average rate of calf mortality observed in recent years, but it cannot explain the large year-to-year variance in calf deaths since 2000.

). Postmortem examination and pathogen testing were performed on 212 whales; 208 (98.1%) were calvesof-the-year and 48.0% of these were newborns or neonates. A known or probable cause of death was established in only a small number (6.6%) of cases. These included ship strike in a juvenile and blunt trauma or lacerations (n = 5), pneumonia (n = 4), myocarditis (n = 2), meningitis (n = 1), or myocarditis and meningitis (n = 1) in calves. Ante-mortem gull parasitism was the most common gross finding. It was associated with systemic disease in a single 1−2 mo old calf. Immunohistochemical labeling for canine distemper virus, Toxoplasma gondii and Brucella spp., and PCR for cetacean morbillivirus (CeMV), influenza A, and apicomplexan protozoa were negative on formalin-fixed, paraffinembedded lung and brain samples from a subset of whales; PCR for Brucella spp. was positive in a newborn/neonate with pneumonia. Skin samples from whales with gull parasitism were PCR negative for CeMV, poxvirus, and papillomavirus. This is the first long-term study to investigate and summarize notable post-mortem findings in the PV SRW population. Consistent, significant findings within or between years to explain the majority of deaths and those in high-mortality years remain to be identified.

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Baleen from stranded carcasses of five right whale calves (four southern and one North Atlantic) contain cortisol and corticosterone patterns that may represent longitudinal profiles of stress exposure over time. Calves with high wounding from Kelp Gulls had markedly higher glucocorticoids in postnatal baleen than did less wounded and unwounded calves.

Background: This study is part of a larger research program focused on developing objective, scalable tools for digital behavioral phenotyping. We evaluated whether a digital app delivered on a smartphone or tablet using computer vision analysis (CVA) can elicit and accurately measure one of the most common early autism symptoms, namely failure to respond to a name call. Methods: During a pediatric primary care well-child visit, 910 toddlers, 17-37 months old, were administered an app on an iPhone or iPad consisting of brief movies during which the child's name was called three times by an examiner standing behind them. Thirty-seven toddlers were subsequently diagnosed with autism spectrum disorder (ASD). Name calls and children's behavior were recorded by the camera embedded in the device, and children's head turns were coded by both CVA and a human. Results: CVA coding of response to name was found to be comparable to human coding. Based on CVA, children with ASD responded to their name significantly less frequently than children without ASD. CVA also revealed that children with ASD who did orient to their name exhibited a longer latency before turning their head. Combining information about both the frequency and the delay in response to name improved the ability to distinguish toddlers with and without ASD. Conclusions: A digital app delivered on an iPhone or iPad in real-world settings using computer vision analysis to quantify behavior can reliably detect a key early autism symptom-failure to respond to name. Moreover, the higher resolution offered by CVA identified a delay in head turn in toddlers with ASD who did respond to their name. Digital phenotyping is a promising methodology for early assessment of ASD symptoms.

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