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In the marine environment, dynamic physical processes shape biological productivity and predator-prey interactions across multiple scales. Identifying pathways of physical-biological coupling is fundamental to understand the functioning of marine ecosystems yet it is challenging because the interactions are difficult to measure. We examined submesoscale (less than 100 km) surface current features using remote sensing techniques alongside ship-based surveys of krill and baleen whale distributions in the California Current System. We found that aggregative surface current features, represented by Lagrangian coherent structures (LCS) integrated over temporal scales between 2 and 10 days, were associated with increased (a) krill density (up to 2.6 times more dense), (b) baleen whale presence (up to 8.3 times more likely) and (c) subsurface seawater density (at depths up to 10 m). The link between physical oceanography, krill density and krill-predator distributions suggests that LCS are important features that drive the flux of energy and nutrients across trophic levels. Our results may help inform dynamic management strategies aimed at reducing large whales ship strikes and help assess the potential impacts of environmental change on this critical ecosystem.

Despite their enormous size, whales make their living as voracious predators. To catch their much smaller, more maneuverable prey, they have developed several unique locomotor strategies that require high energetic input, high mechanical power output and a surprising degree of agility. To better understand how body size affects maneuverability at the largest scale, we used bio-logging data, aerial photogrammetry and a high-throughput approach to quantify the maneuvering performance of seven species of free-swimming baleen whale. We found that as body size increases, absolute maneuvering performance decreases: larger whales use lower accelerations and perform slower pitch-changes, rolls and turns than smaller species. We also found that baleen whales exhibit positive allometry of maneuvering performance: relative to their body size, larger whales use higher accelerations, and perform faster pitch-changes, rolls and certain types of turns than smaller species. However, not all maneuvers were impacted by body size in the same way, and we found that larger whales behaviorally adjust for their decreased agility by using turns that they can perform more effectively. The positive allometry of maneuvering performance suggests that large whales have compensated for their increased body size by evolving more effective control surfaces and by preferentially selecting maneuvers that play to their strengths., Competing Interests: Competing interests The authors declare no competing or financial interests., (© 2022. Published by The Company of Biologists Ltd.)

Baleen whales influence their ecosystems through immense prey consumption and nutrient recycling 1-3 . It is difficult to accurately gauge the magnitude of their current or historic ecosystem role without measuring feeding rates and prey consumed. To date, prey consumption of the largest species has been estimated using metabolic models 3-9 based on extrapolations that lack empirical validation. Here, we used tags deployed on seven baleen whale (Mysticeti) species (n = 321 tag deployments) in conjunction with acoustic measurements of prey density to calculate prey consumption at daily to annual scales from the Atlantic, Pacific, and Southern Oceans. Our results suggest that previous studies 3-9 have underestimated baleen whale prey consumption by threefold or more in some ecosystems. In the Southern Ocean alone, we calculate that pre-whaling populations of mysticetes annually consumed 430 million tonnes of Antarctic krill (Euphausia superba), twice the current estimated total biomass of E. superba 10 , and more than twice the global catch of marine fisheries today 11 . Larger whale populations may have supported higher productivity in large marine regions through enhanced nutrient recycling: our findings suggest mysticetes recycled 1.2 × 10 4  tonnes iron yr -1 in the Southern Ocean before whaling compared to 1.2 × 10 3  tonnes iron yr -1 recycled by whales today. The recovery of baleen whales and their nutrient recycling services 2,3,7 could augment productivity and restore ecosystem function lost during 20th century whaling 12,13 ., (© 2021. The Author(s), under exclusive licence to Springer Nature Limited.)

In the marine environment, dynamic physical processes shape biological productivity and predator-prey interactions across multiple scales. Identifying pathways of physical-biological coupling is fundamental to understand the functioning of marine ecosystems yet it is challenging because the interactions are difficult to measure. We examined submesoscale (less than 100 km) surface current features using remote sensing techniques alongside ship-based surveys of krill and baleen whale distributions in the California Current System. We found that aggregative surface current features, represented by Lagrangian coherent structures (LCS) integrated over temporal scales between 2 and 10 days, were associated with increased (a) krill density (up to 2.6 times more dense), (b) baleen whale presence (up to 8.3 times more likely) and (c) subsurface seawater density (at depths up to 10 m). The link between physical oceanography, krill density and krill-predator distributions suggests that LCS are important features that drive the flux of energy and nutrients across trophic levels. Our results may help inform dynamic management strategies aimed at reducing large whales ship strikes and help assess the potential impacts of environmental change on this critical ecosystem.

As populations of large whales recover from whaling, species that forage and breed in coastal waters, including the humpback whale (Megaptera novaeangliae), increasingly overlap with human activities. This represents a potential hazard in locations worldwide subject to intensive vessel traffic, including New York, Panama City and Brisbane.Historically, humpback whales were not considered part of San Francisco Bay's fauna, except for a few 'lost' whales that wandered into the estuary.An unprecedented influx of humpback whales into highly urbanized San Francisco Bay began in 2016. Research efforts in 2016–2018 from vessels and shore resulted in 496 photo‐identification records plus 319 visual sightings. Sixty‐one individuals were photo‐identified, of which 80% (n = 49) used the bay on multiple days (range = 2 to 39), and 34% (n = 21) were resighted in successive years.Whales photographed in San Francisco Bay were found to belong to distinct population segments listed as endangered and threatened under the U.S. Endangered Species Act.Whales moved in and out of the bay seasonally (April–November). Habitat use patterns indicated movements farther into San Francisco Bay correlated positively with high tides.Humpback whales were visually observed lunge feeding on northern anchovy (Engraulis mordax) at the surface. Analysis of dive patterns by three tagged whales confirmed subsurface feeding when surface feeding was not apparent.The use of San Francisco Bay and adjacent waters by recovering populations of humpback whales exacerbates the potential for collisions with vessels, entanglement in fishing gear, and harassment by recreational vessels. The most pressing conservation concern is the risk of ship strikes, observed where humpback whales occur near active seaports. [ABSTRACT FROM AUTHOR]

Large groups of animals aggregate around resource hotspots, with group size often influenced by the heterogeneity of the environment. In most cases, the foraging success of individuals within groups is interdependent, scaling either constructively or destructively with group size. Here we used biologging tags, acoustic prey mapping, passive acoustic recording of social cues and remote sensing of surface currents to investigate an alternative scenario in which large, dense aggregations of southeast Atlantic humpback whales, Megaptera novaeangliae , and northeast Pacific blue whales, Balaenoptera musculus , were each associated with ephemeral krill aggregations large enough such that their availability to predators appeared to be influenced more by environmental features than by consumption, implying independence of group size and consumption rates. We found that the temporal scale and spatial extent of oceanographic drivers were consistent with the temporal scale and locations of predator aggregations, and additionally found that groups formed above bathymetric features known to promote zooplankton concentration. Additionally, we found calling behaviour counter-indicative of competition: blue whale foraging calls were anomalously high during observed aggregation time periods, suggesting signalling behaviour that could alert conspecifics to the location of high-quality resources. Modelled results suggest that the use of social information reduces the time required for individuals to discover and exploit high-quality resources, allowing for more efficient foraging without apparent costs to the caller. Thus, rorqual whales foraging in these environments appear to exhibit a social foraging strategy whereby a behaviour with negligible individual costs (signalling) provides information that enhances group foraging efficiency. The population density dependence of this social foraging strategy may help explain why some rorqual species were at first slow to recover from human exploitation, but have since increased more rapidly. • Large, dense prey patches were found near supergroups of rorqual whales. • Ephemeral patches formed when surface features intersected with bathymetry. • Blue whales increased social call production during observed aggregation events. • Rorqual whale foraging appears to be enhanced when social information is utilized. [ABSTRACT FROM AUTHOR]

Animals are distributed relative to the resources they rely upon, often scaling in abundance relative to available resources. Yet, in heterogeneously distributed environments, describing resource availability at relevant spatial scales remains a challenge in ecology, inhibiting understanding of predator distribution and foraging decisions.We investigated the foraging behaviour of two species of rorqual whales within spatially limited and numerically extraordinary super‐aggregations in two oceans. We additionally described the lognormal distribution of prey data at species‐specific spatial scales that matched the predator's unique lunge‐feeding strategy.Here we show that both humpback whales off South Africa's west coast and blue whales off the US west coast perform more lunges per unit time within these aggregations than when foraging individually, and that the biomass within gulp‐sized parcels was on average higher and more tightly distributed within super‐group‐associated prey patches, facilitating greater energy intake per feeding event as well as increased feeding rates.Prey analysis at predator‐specific spatial scales revealed a stronger association of super‐groups with patches containing relatively high geometric mean biomass and low geometric standard deviations than with arithmetic mean biomass, suggesting that the foraging decisions of rorqual whales may be more influenced by the distribution of high‐biomass portions of a patch than total biomass. The hierarchical distribution of prey in spatially restricted, temporally transient, super‐group‐associated patches demonstrated high biomass and less variable distributions that facilitated what are likely near‐minimum intervals between feeding events.Combining increased biomass with increased foraging rates implied that overall intake rates of whales foraging within super‐groups were approximately double those of whales foraging in other environments. Locating large, high‐quality prey patches via the detection of aggregation hotspots may be an important aspect of rorqual whale foraging, one that may have been suppressed when population sizes were anthropogenically reduced in the 20th century to critical lows. A free Plain Language Summary can be found within the Supporting Information of this article. [ABSTRACT FROM AUTHOR]

Assessing the long-term consequences of sub-lethal anthropogenic disturbance on wildlife populations requires integrating data on fine-scale individual behavior and physiology into spatially and temporally broader, population-level inference. A typical behavioral response to disturbance is the cessation of foraging, which can be translated into a common metric of energetic cost. However, this necessitates detailed empirical information on baseline movements, activity budgets, feeding rates and energy intake, as well as the probability of an individual responding to the disturbance-inducing stressor within different exposure contexts. Here, we integrated data from blue whales (Balaenoptera musculus) experimentally exposed to military active sonar signals with fine-scale measurements of baseline behavior over multiple days or weeks obtained from accelerometry loggers, telemetry tracking and prey sampling. Specifically, we developed daily simulations of movement, feeding behavior and exposure to localized sonar events of increasing duration and intensity and predicted the effects of this disturbance source on the daily energy intake of an individual. Activity budgets and movements were highly variable in space and time and among individuals, resulting in large variability in predicted energetic intake and costs. In half of our simulations, an individual's energy intake was unaffected by the simulated source. However, some individuals lost their entire daily energy intake under brief or weak exposure scenarios. Given this large variation, population-level models will have to assess the consequences of the entire distribution of energetic costs, rather than only consider single summary statistics. The shape of the exposure-response functions also strongly influenced predictions, reinforcing the need for contextually explicit experiments and improved mechanistic understanding of the processes driving behavioral and physiological responses to disturbance. This study presents a robust approach for integrating different types of empirical information to assess the effects of disturbance at spatio-temporal and ecological scales that are relevant to management and conservation. [ABSTRACT FROM AUTHOR]

How predators maximize energetic gains while minimizing the costs associated with exploiting heterogeneous prey remains a difficult ecological principle to test in natural systems.Deep‐diving, air‐breathing predators face conflicting demands of oxygen conservation to extend dive time and oxygen usage from the exercise required to find and capture prey. How predators balance these opposing factors is additionally complicated by prey patches that are heterogeneous spatially, temporally and in quality.Tags deployed on foraging fin whales revealed that deeper dives consisted of higher feeding rates (lunges/hr), as generally predicted by optimal foraging theory. By simultaneously measuring prey density and distribution in the local environment, we show that whales increased their dive depths in order to forage on the densest prey patches.Despite the increased travel time needed to find deeper prey during a breath‐hold dive, the increase in feeding rates of fin whales and modelled prey consumption quadrupled compared to shallow foraging. Because the cost of transport is low at this extreme in body size, we posit that feeding on the deep prey patches significantly increases the energetic efficiency of foraging.Given the increasing recognition that anthropogenic disturbance can curtail deep foraging dives in many cetacean species, endangered fin whales may be susceptible to significant energetic losses that may impact individual fitness and population health in some areas. A free Plain Language Summary can be found within the Supporting Information of this article. [ABSTRACT FROM AUTHOR]

Linking individual and population scales is fundamental to many concepts in ecology [ 1 ], including migration [ 2 , 3 ]. This behavior is a critical [ 4 ] yet increasingly threatened [ 5 ] part of the life history of diverse organisms. Research on migratory behavior is constrained by observational scale [ 2 ], limiting ecological understanding and precise management of migratory populations in expansive, inaccessible marine ecosystems [ 6 ]. This knowledge gap is magnified for dispersed oceanic predators such as endangered blue whales (Balaenoptera musculus). As capital breeders, blue whales migrate vast distances annually between foraging and breeding grounds, and their population fitness depends on synchrony of migration with phenology of prey populations [ 7 , 8 ]. Despite previous studies of individual-level blue whale vocal behavior via bio-logging [ 9 , 10 ] and population-level acoustic presence via passive acoustic monitoring [ 11 ], detection of the life history transition from foraging to migration remains challenging. Here, we integrate direct high-resolution measures of individual behavior and continuous broad-scale acoustic monitoring of regional song production (Figure 1 A) to identify an acoustic signature of the transition from foraging to migration in the Northeast Pacific population. We find that foraging blue whales sing primarily at night, whereas migratory whales sing primarily during the day. The ability to acoustically detect population-level transitions in behavior provides a tool to more comprehensively study the life history, fitness, and plasticity of population behavior in a dispersed, capital breeding population. Real-time detection of this behavioral signal can also inform dynamic management efforts [ 12 ] to mitigate anthropogenic threats to this endangered population [ 13 , 14 ]). • Acoustic monitoring reveals patterns in population-level blue whale song production • Tag-derived metrics provide behavioral context for distinct diel patterns in song • When integrated, tag and acoustic metrics reveal an acoustic signature of migration • Key to discerning timing, plasticity, and drivers of a dispersed migration Oestreich et al. integrate long-term acoustic monitoring and tag-derived metrics to identify an acoustic signature of blue whales' transition from foraging to migration. This finding links individual and population-level behavior in a highly dispersed population and is central to discerning timing, plasticity, and drivers of blue whale migration. [ABSTRACT FROM AUTHOR]