Effects of vessel traffic and ocean noise on gray whale stress hormones.

Human use of marinescapes is rapidly increasing, especially in populated nearshore regions where recreational vessel traffic can be dense. Marine animals can have a physiological response to such elevated human activity that can impact individual health and population dynamics. To understand the physiological impacts of vessel traffic on baleen whales, we investigated the adrenal stress response of gray whales (Eschrichtius robustus) to variable vessel traffic levels through an assessment of fecal glucocorticoid metabolite (fGC) concentrations. This analysis was conducted at the individual level, at multiple temporal scales (1-7 days), and accounted for factors that may confound fGC: sex, age, nutritional status, and reproductive state. Data were collected in Oregon, USA, from June to October of 2016-2018. Results indicate significant correlations between fGC, month, and vessel counts from the day prior to fecal sample collection. Furthermore, we show a significant positive correlation between vessel traffic and underwater ambient noise levels, which indicates that noise produced by vessel traffic may be a causal factor for the increased fGC. This study increases knowledge of gray whale physiological response to vessel traffic and may inform management decisions regarding regulations of vessel traffic activities and thresholds near critical whale habitats.

Assessment of fecal steroid and thyroid hormone metabolites in eastern North Pacific gray whales.

Baleen whale fecal samples have high potential for endocrine monitoring, which can be used as a non-invasive tool to identify the physiological response to disturbance events and describe population health and vital rates. In this study, we used commercial enzyme-linked immunosorbent assays to validate and quantify fecal steroid (progestins, androgens and glucocorticoids) and thyroid hormone metabolite concentrations in eastern North Pacific gray whales (Eschrichtius robustus) along the Oregon coast, USA, from May to October of 2016-2018. Higher mean progestin metabolite concentrations were observed in postweaning females, followed by pregnant females. Mean androgen, glucocorticoid and thyroid metabolites were higher in mature males. Progestin, glucocorticoids and thyroid fecal metabolites varied significantly by year, with positive correlations between progestin and androgen, and between glucocorticoid and thyroid metabolites. We also present two case studies of a documented injured whale and a mature male displaying reproductive competitive behavior, which provide reference points for physiologically stressed individuals and adult breeding males, respectively. Our methods and findings advance the knowledge of baleen whale physiology, can help guide future research on whale physiology and can inform population management and conservation efforts regarding minimizing the impact of anthropogenic stressors on whales.

Insight into the kinematics of blue whale surface foraging through drone observations and prey data.

To understand how predators optimize foraging strategies, extensive knowledge of predator behavior and prey distribution is needed. Blue whales employ an energetically demanding lunge feeding method that requires the whales to selectively feed where energetic gain exceeds energetic loss, while also balancing oxygen consumption, breath holding capacity, and surface recuperation time. Hence, blue whale foraging behavior is primarily driven by krill patch density and depth, but many studies have not fully considered surface feeding as a significant foraging strategy in energetic models. We collected predator and prey data on a blue whale (Balaenoptera musculus brevicauda) foraging ground in New Zealand in February 2017 to assess the distributional and behavioral response of blue whales to the distribution and density of krill prey aggregations. Krill density across the study region was greater toward the surface (upper 20 m), and blue whales were encountered where prey was relatively shallow and more dense. This relationship was particularly evident where foraging and surface lunge feeding were observed. Furthermore, New Zealand blue whales also had relatively short dive times (2.83 ± 0.27 SE min) as compared to other blue whale populations, which became even shorter at foraging sightings and where surface lunge feeding was observed. Using an unmanned aerial system (UAS; drone) we also captured unique video of a New Zealand blue whale's surface feeding behavior on well-illuminated krill patches. Video analysis illustrates the whale's potential use of vision to target prey, make foraging decisions, and orient body mechanics relative to prey patch characteristics. Kinematic analysis of a surface lunge feeding event revealed biomechanical coordination through speed, acceleration, head inclination, roll, and distance from krill patch to maximize prey engulfment. We compared these lunge kinematics to data previously reported from tagged blue whale lunges at depth to demonstrate strong similarities, and provide rare measurements of gape size, and krill response distance and time. These findings elucidate the predator-prey relationship between blue whales and krill, and provide support for the hypothesis that surface feeding by New Zealand blue whales is an important component to their foraging ecology used to optimize their energetic efficiency. Understanding how blue whales make foraging decisions presents logistical challenges, which may cause incomplete sampling and biased ecological knowledge if portions of their foraging behavior are undocumented. We conclude that surface foraging could be an important strategy for blue whales, and integration of UAS with tag-based studies may expand our understanding of their foraging ecology by examining surface feeding events in conjunction with behaviors at depth.