Effects of increased swimming costs on foraging behavior and efficiency of captive Steller sea lions: Evidence for behavioral plasticity in the recovery phase of dives

A significant component of foraging energetics is the cost of locomotion, which for marine animals, is the cost of swimming. Increases in the cost of swimming may have significant impacts on foraging efficiency. Minimizing the cost of swimming can contribute to the optimization of foraging strategies by reducing the energetic cost of foraging. Results of several field studies suggest that an increase in the cost of locomotion may have comparable effects on foraging behavior and efficiency to a decrease in prey availability. We tested the hypothesis that an increased cost of swimming, brought on by increased hydrodynamic drag, has the same effect on dive behavior and efficiency as reduced prey availability under standard locomotion. Experiments were performed using two adult female Steller sea lions at the Alaska SeaLife Center in Seward, AK, using the same animals and general experimental design previously used to test the effects of reduced prey encounter rate on dive behavior and efficiency. Animals were fitted with a drag-inducing harness for half of the 500 simulated foraging dives in order to increase the cost of swimming. Individual dive duration and foraging time were significantly reduced in all cost-increased dives, comparable to the effects of reduced prey encounter rate. However, on a bout-by-bout basis, dive and foraging efficiency were only slightly reduced, which is likely due to an average 50% reduction in post-dive surface recovery duration during cost-increased dives. Increased heat flux across the body surface measured in a parallel study confirmed a significant increase in work during drag-increased dives. These results suggest that sea lions are able to compensate for changes in the cost of foraging and maintain their foraging efficiency by altering their dive strategy over an entire bout of dives when operating well within their aerobic scope.     

Structure and Dynamics of Minke Whale Surfacing Patterns in the Gulf of St. Lawrence,Canada

Animal behavioral patterns can help us understand physiological and ecological constraints on animals and its influence on fitness. The surfacing patterns of aquatic air-breathing mammals constitute a behavioral pattern that has evolved as a trade-off between the need to replenish oxygen stores at the surface and the need to conduct other activities underwater. This study aims to better understand the surfacing pattern of a marine top predator, the minke whale (Balaenoptera acutorostrata), by investigating how their dive duration and surfacing pattern changes across their activity range. Activities were classified into resting, traveling, surface feeding and foraging at depth. For each activity, we classified dives into short and long dives and then estimated the temporal dependence between dive types. We found that minke whales modified their surfacing pattern in an activity-specific manner, both by changing the expression of their dives (i.e. density distribution) and the temporal dependence (transition probability) between dive types. As the depth of the prey layer increased between activities, the surfacing pattern of foraging whales became increasingly structured, going from a pattern dominated by long dives, when feeding at the surface, to a pattern where isolated long dives were followed by an increasing number of breaths (i.e. short dives), when the whale was foraging at depth. A similar shift in surfacing pattern occurred when prey handling time (inferred from surface corralling maneuvers) increased for surface feeding whales. The surfacing pattern also differed between feeding and non-feeding whales. Resting whales did not structure their surfacing pattern, while traveling whales did, possibly as a way to minimize cost of transport. Our results also suggest that minke whales might balance their oxygen level over multiple, rather than single, dive cycles.     

The diving behavior of blue and fin whales: is dive duration shorter than expected based on oxygen stores?

Many diving seabirds and marine mammals have been found to regularly exceed their theoretical aerobic dive limit (TADL). No animals have been found to dive for durations that are consistently shorter than their TADL. We attached time-depth recorders to 7 blue whales and 15 fin whales (family Balaenopteridae). The diving behavior of both species was similar, and we distinguished between foraging and traveling dives. Foraging dives in both species were deeper, longer in duration and distinguished by a series of vertical excursions where lunge feeding presumably occurred. Foraging blue whales lunged 2.4 (+/-1.13) times per dive, with a maximum of six times and average vertical excursion of 30.2 (+/-10.04) m. Foraging fin whales lunged 1.7 (+/-0.88) times per dive, with a maximum of eight times and average vertical excursion of 21.2 (+/-4.35) m. The maximum rate of ascent of lunges was higher than the maximum rate of descent in both species, indicating that feeding lunges occurred on ascent. Foraging dives were deeper and longer than non-feeding dives in both species. On average, blue whales dived to 140.0 (+/-46.01) m and 7.8 (+/-1.89) min when foraging, and 67.6 (+/-51.46) m and 4.9 (+/-2.53) min when not foraging. Fin whales dived to 97.9 (+/-32.59) m and 6.3 (+/-1.53) min when foraging and to 59.3 (+/-29.67) m and 4.2 (+/-1.67) min when not foraging. The longest dives recorded for both species, 14.7 min for blue whales and 16.9 min for fin whales, were considerably shorter than the TADL of 31.2 and 28.6 min, respectively. An allometric comparison of seven families diving to an average depth of 80-150 m showed a significant relationship between body mass and dive duration once Balaenopteridae whales, with a mean dive duration of 6.8 min, were excluded from the analysis. Thus, the short dive durations of blue whales and fin whales cannot be explained by the shallow distribution of their prey. We propose instead that short duration diving in large whales results from either: (1) dispersal behavior of prey; or (2) a high energetic cost of foraging.     

Using dive behavior and active acoustics to assess prey use and partitioning by fin and humpback whales near Kodiak Island,Alaska

Near the Kodiak Archipelago, fin (Balaenoptera physalus) and humpback (Megaptera novaeangliae) whales frequently overlap spatially and temporally. The Gulf Apex Predator‐prey study (GAP) investigated the prey use and potential prey partitioning between these sympatric species by combining concurrent analysis of vertical whale distribution with acoustic assessment of pelagic prey. Acoustic backscatter was classified as consistent with either fish or zooplankton. Whale dive depths were determined through suction cup tags. Tagged humpback whales (n = 10) were most often associated with distribution of fish, except when zooplankton density was very high. Associations between the dive depths of tagged fin whales (n = 4) and the vertical distribution of either prey type were less conclusive. However, prey assessment methods did not adequately describe the distribution of copepods, a potentially significant resource for fin whales. Mean dive parameters showed no significant difference between species when compared across all surveys. However, fin whales spent a greater proportion of dive time in the foraging phase than humpbacks, suggesting a possible difference in foraging efficiency between the two. These results suggest that humpback and fin whales may target different prey, with the greatest potential for diet overlap occurring when the density of zooplankton is very high.     

Cheetahs of the deep sea: deep foraging sprints in short-finned pilot whales off Tenerife (Canary Islands)

1. Empirical testing of optimal foraging models for breath-hold divers has been difficult. Here we report data from sound and movement recording DTags placed on 23 short-finned pilot whales off Tenerife to study the foraging strategies used to catch deep-water prey. 2. Day and night foraging dives had a maximum depth and duration of 1018 m and 21 min. Vocal behaviour during dives was consistent with biosonar-based foraging, with long series of echolocation clicks interspersed with buzzes. Similar buzzes have been associated with prey capture attempts in other echolocating species. 3. Foraging dives seemed to adapt to circadian rhythms. Deep dives during the day were deeper, but contained fewer buzzes (median 1), than night-time deep dives (median 5 buzzes). 4. In most deep (540-1019 m) daytime dives with buzzes, a downward directed sprint reaching up to 9 m s(-1) occurred just prior to a buzz and coincided with the deepest point in the dive, suggestive of a chase after escaping prey. 5. A large percentage (10-36%) of the drag-related locomotion cost of these dives (15 min long) is spent in sprinting (19-79 s). This energetic foraging tactic focused on a single or few prey items has not been observed previously in deep-diving mammals but resembles the high-risk/high-gain strategy of some terrestrial hunters such as cheetahs. 6. Deep sprints contrast with the expectation that deep-diving mammals will swim at moderate speeds optimized to reduce oxygen consumption and maximize foraging time at depth. Pilot whales may have developed this tactic to target a deep-water niche formed by large/calorific/fast moving prey such as giant squid.     

Shallow food for deep divers: Dynamic foraging behavior of male sperm whales in a high latitude habitat

Groups of female and immature sperm whales live at low latitudes and show a stereotypical diving and foraging behavior with dives lasting about 45 min to depths of between 400 and 1200 m. In comparison, physically mature male sperm whales migrate to high latitudes where little is known about their foraging behavior and ecology. Here we use acoustic recording tags to study the diving and acoustic behavior of male sperm whales foraging off northern Norway. Sixty-five hours of tag data provide detailed information about the movements and sound repertoire of four male sperm whales performing 83 dives lasting between 6 and 60 min. Dives ranged in depth between 14 and 1860 m, with a median depth of 175 m, and 92% of the surfacings lasted less than 15 min. The four whales clicked for an average 91% (SD = 10) of the dive duration, where the first usual click was produced at depths ranging between 4 and 218 m and the last usual click at depths ranging between 1 and 1114 m. Echolocation buzzes, which are used as an indication of prey capture attempts, were emitted at depths between 17 and 1860 m, during both the descent and ascent phase of deep dives. The foraging behavior varied markedly with depth, with the timing and duration of prey capture attempts during shallow dives suggesting that the whales target more sparsely distributed prey. In contrast, deep dives involve frequent prey capture attempts and seem to target more dense food layers. The evidence of exploitation of different food layers, including epipelagic prey, is consistent with the hypothesis that male sperm whales may migrate to high latitudes to access a productive, multi-layered foraging habitat.     

Deep-diving foraging behaviour of sperm whales (Physeter macrocephalus)

1. Digital tags were used to describe diving and vocal behaviour of sperm whales during 198 complete and partial foraging dives made by 37 individual sperm whales in the Atlantic Ocean, the Gulf of Mexico and the Ligurian Sea. 2. The maximum depth of dive averaged by individual differed across the three regions and was 985 m (SD = 124.3), 644 m (123.4) and 827 m (60.3), respectively. An average dive cycle consisted of a 45 min (6.3) dive with a 9 min (3.0) surface interval, with no significant differences among regions. On average, whales spent greater than 72% of their time in foraging dive cycles. 3. Whales produced regular clicks for 81% (4.1) of a dive and 64% (14.6) of the descent phase. The occurrence of buzz vocalizations (also called 'creaks') as an indicator of the foraging phase of a dive showed no difference in mean prey capture attempts per dive between regions [18 buzzes/dive (7.6)]. Sperm whales descended a mean of 392 m (144) from the start of regular clicking to the first buzz, which supports the hypothesis that regular clicks function as a long-range biosonar. 4. There were no significant differences in the duration of the foraging phase [28 min (6.0)] or percentage of the dive duration in the foraging phase [62% (7.3)] between the three regions, with an overall average proportion of time spent actively encountering prey during dive cycles of 0.53 (0.05). Whales maintained their time in the foraging phase by decreasing transit time for deeper foraging dives. 5. Similarity in foraging behaviour in the three regions and high diving efficiencies suggest that the success of sperm whales as mesopelagic predators is due in part to long-range echolocation of deep prey patches, efficient locomotion and a large aerobic capacity during diving.     

When cormorants go fishing: the differing costs of hunting for sedentary and motile prey

Cormorants hunt both benthic (sedentary) and pelagic (motile) prey but it is not known if the energy costs of foraging on these prey differ. We used respirometry to measure the costs of diving in double-crested cormorants (Phalacrocorax auritus) foraging either for sedentary (fish pieces) or motile (juvenile salmon) prey in a deep dive tank. Short dives for sedentary prey were more expensive than dives of similar duration for motile prey (e.g. 20% higher for a 10s dive) whereas the reverse was true for long dives (i.e. long dives for motile prey were more expensive than for sedentary prey). Across dives of all durations, the foraging phase of the dive was more expensive when the birds hunted motile prey, presumably due to pursuit costs. The period of descent in all the dives undertaken appears to have been more expensive when the birds foraged on sedentary prey, probably due to a higher swimming speed during this period.     

Following a foraging fish-finder: diel habitat use of Blainville's beaked whales revealed by echolocation

Simultaneous high resolution sampling of predator behavior and habitat characteristics is often difficult to achieve despite its importance in understanding the foraging decisions and habitat use of predators. Here we tap into the biosonar system of Blainville''s beaked whales, Mesoplodon densirostris, using sound and orientation recording tags to uncover prey-finding cues available to echolocating predators in the deep-sea. Echolocation sounds indicate where whales search and encounter prey, as well as the altitude of whales above the sea-floor and the density of organisms around them, providing a link between foraging activity and the bio-physical environment. Tagged whales (n = 9) hunted exclusively at depth, investing most of their search time either in the lower part of the deep scattering layer (DSL) or near the sea-floor with little diel change. At least 43% (420/974) of recorded prey-capture attempts were performed within the benthic boundary layer despite a wide range of dive depths, and many dives included both meso- and bentho-pelagic foraging. Blainville''s beaked whales only initiate searching when already deep in the descent and encounter prey suitable for capture within 2 min of the start of echolocation, suggesting that these whales are accessing prey in reliable vertical strata. Moreover, these prey resources are sufficiently dense to feed the animals in what is effectively four hours of hunting per day enabling a strategy in which long dives to exploit numerous deep-prey with low nutritional value require protracted recovery periods (average 1.5 h) between dives. This apparent searching efficiency maybe aided by inhabiting steep undersea slopes with access to both the DSL and the sea-floor over small spatial scales. Aggregations of prey in these biotopes are located using biosonar-derived landmarks and represent stable and abundant resources for Blainville''s beaked whales in the otherwise food-limited deep-ocean.     

Pursuit plunging by northern gannets (Sula bassana) feeding on capelin (Mallotus villosus)

Northern gannets (Sula bassana) are considered to obtain prey usually by rapid, vertical, shallow plunge dives. In order to test this contention and investigate underwater foraging behaviour, we attached two types of data-logging systems to 11 parental northern gannets at Funk Island in the North-Wiest Atlantic. We documented, for the first time to the authors' knowledge, gannets performing long, flat-bottomed, U-shaped dives that involved underwater wing propulsion as well as rapid, shallow, V-shaped dives. The median and maximum dive depths and durations were 4.6 and 22.0 m and 8 and 38 s, respectively. Short, shallow dives were usually V-shaped and dives deeper than 8 m and longer than 10 s were usually U-shaped, including a period at constant depth (varying between 4 and 28s with median 8s). Diving occurred throughout the daylight period and deepest dives were performed during late morning. On the basis of motion sensors in the loggers and food collections from telemetered birds, we concluded that extended, deep dives were directed at deep schools of capelin, a small pelagic fish, and we hypothesized that V-shaped dives were aimed at larger, pelagic fishes and squids. Furthermore, these V-shaped dives allowed the birds to surprise their pelagic prey and this may be critical because the maximum swimming speeds of the prey species may exceed the maximum dive speeds of the birds.     

Echolocation in Blainville’s beaked whales (Mesoplodon densirostris)

Here we use sound and movement recording tags to study how deep-diving Blainville’s beaked whales (Mesoplodon densirostris) use echolocation to forage in their natural mesopelagic habitat. These whales ensonify thousands of organisms per dive but select only about 25 prey for capture. They negotiate their cluttered environment by radiating sound in a narrow 20° field of view which they sample with 1.5–3 clicks per metre travelled requiring only some 60 clicks to locate, select and approach each prey. Sampling rates do not appear to be defined by the range to individual targets, but rather by the movement of the predator. Whales sample faster when they encounter patches of prey allowing them to search new water volumes while turning rapidly to stay within a patch. This implies that the Griffin search–approach–capture model of biosonar foraging must be expanded to account for sampling behaviours adapted to the overall prey distribution. Beaked whales can classify prey at more than 15 m range adopting stereotyped motor patterns when approaching some prey. This long detection range relative to swimming speed facilitates a deliberate mode of sensory-motor operation in which prey and capture tactics can be selected to optimize energy returns during long breath-hold dives.     

Sperm whale behaviour indicates the use of echolocation click buzzes "creaks" in prey capture

During foraging dives, sperm whales (Physeter macrocephalus) produce long series of regular clicks at 0.5-2 s intervals interspersed with rapid-click buzzes called "creaks". Sound, depth and orientation recording Dtags were attached to 23 whales in the Ligurian Sea and Gulf of Mexico to test whether the behaviour of diving sperm whales supports the hypothesis that creaks are produced during prey capture. Sperm whales spent most of their bottom time within one or two depth bands, apparently feeding in vertically stratified prey layers. Creak rates were highest during the bottom phase: 99.8% of creaks were produced in the deepest 50% of dives, 57% in the deepest 15% of dives. Whales swam actively during the bottom phase, producing a mean of 12.5 depth inflections per dive. A mean of 32% of creaks produced during the bottom phase occurred within 10 s of an inflection (13x more than chance). Sperm whales actively altered their body orientation throughout the bottom phase with significantly increased rates of change during creaks, reflecting increased manoeuvring. Sperm whales increased their bottom foraging time when creak rates were higher. These results all strongly support the hypothesis that creaks are an echolocation signal adapted for foraging, analogous to terminal buzzes in taxonomically diverse echolocating species.     

Investigation of foraging habits and prey selection by humpback whales (Megaptera novaeangliae) using acoustic tags and concurrent fish surveys

Tags containing acoustic time-depth transmitters (ATDT) were attached to four humpback whales near Kodiak, Alaska. Tags allowed for whale dive depths to be recorded in real time. Acoustic and mid-water trawl surveys were conducted concurrent with tagging efforts within the study area to quantify available fish resources and describe potential prey selection by humpback whales. Recorded dives were grouped through visual assessment and t -tests. Dives that indicated likely foraging occurred at a mean maximum depth of 106.2 m with 62% of dives occurring between 92 m and 120 m. Acoustic backscatter from fish surveys was attributed to potential humpback prey based on known target strength values and 10 net tows. Capelin comprised 84% of the total potential prey abundance in the region followed by age 0 (12%) and juvenile pollock (2%), and eulachon (<1%). Although horizontally segregated in the region, both capelin and age 0 pollock were distributed at depths exceeding 92 m with maximum abundance between 107 m and 120 m. The four-tagged humpbacks were found to forage in areas with greatest capelin densities but bypassed areas of high age 0 pollock abundance. The location and diving behavior of tagged whales suggested that whales were favoring capelin over pollock as a prey source.     

Scaling of swim speed and stroke frequency in geometrically similar penguins: they swim optimally to minimize cost of transport

It has been predicted that geometrically similar animals would swim at the same speed with stroke frequency scaling with mass^−1/3. In the present study, morphological and behavioural data obtained from free-ranging penguins (seven species) were compared. Morphological measurements support the geometrical similarity. However, cruising speeds of 1.8–2.3 m s⁻¹ were significantly related to mass^0.08 and stroke frequencies were proportional to mass^−0.29. These scaling relationships do not agree with the previous predictions for geometrically similar animals. We propose a theoretical model, considering metabolic cost, work against mechanical forces (drag and buoyancy), pitch angle and dive depth. This new model predicts that: (i) the optimal swim speed, which minimizes the energy cost of transport, is proportional to (basal metabolic rate/drag)^1/3 independent of buoyancy, pitch angle and dive depth; (ii) the optimal speed is related to mass^0.05; and (iii) stroke frequency is proportional to mass^−0.28. The observed scaling relationships of penguins support these predictions, which suggest that breath-hold divers swam optimally to minimize the cost of transport, including mechanical and metabolic energy during dive.     

The Influence of Structural Complexity on Fish–zooplankton Interactions: A Study Using Artificial Submerged Macrophytes

Aquatic macrophytes produce considerable structural variation within the littoral zone and as a result the vegetation provides refuge to prey communities by hindering predator foraging activities. The behavior of planktivorous fish Pseudorasbora parva (Cyprinidae) and their zooplankton prey Daphnia pulex were quantified in a series of laboratory experiments with artificial vegetation at densities of 0, 350, 700, 1400, 2100 and 2800 stemsm^–2. Swimming speeds and foraging rates of the fish were recorded at different prey densities for all stem densities. The foraging efficiency of P. parva decreased significantly with increasing habitat complexity. This decline in feeding efficiency was related to two factors: submerged vegetation impeded swimming behavior and obstructed sight while foraging. This study separated the effects of swimming speed variation and of visual impairment, both due to stems, that led to reduced prey–predator encounters and examined how the reduction of the visual field volume may be predicted using a random encounter model.     

Deep-diving beaked whales dive together but forage apart

Echolocating animals that forage in social groups can potentially benefit from eavesdropping on other group members, cooperative foraging or social defence, but may also face problems of acoustic interference and intra-group competition for prey. Here, we investigate these potential trade-offs of sociality for extreme deep-diving Blainville′s and Cuvier''s beaked whales. These species perform highly synchronous group dives as a presumed predator-avoidance behaviour, but the benefits and costs of this on foraging have not been investigated. We show that group members could hear their companions for a median of at least 91% of the vocal foraging phase of their dives. This enables whales to coordinate their mean travel direction despite differing individual headings as they pursue prey on a minute-by-minute basis. While beaked whales coordinate their echolocation-based foraging periods tightly, individual click and buzz rates are both independent of the number of whales in the group. Thus, their foraging performance is not affected by intra-group competition or interference from group members, and they do not seem to capitalize directly on eavesdropping on the echoes produced by the echolocation clicks of their companions. We conclude that the close diving and vocal synchronization of beaked whale groups that quantitatively reduces predation risk has little impact on foraging performance.     

Sperm whale dive behavior characteristics derived from intermediate‐duration archival tag data

Here, we describe the diving behavior of sperm whales (Physeter macrocephalus) using the Advanced Dive Behavior (ADB) tag, which records depth data at 1‐Hz resolution and GPS‐quality locations for over 1 month, before releasing from the whale for recovery. A total of 27 ADB tags were deployed on sperm whales in the central Gulf of California, Mexico, during spring 2007 and 2008, of which 10 were recovered for data download. Tracking durations of all tags ranged from 0 to 34.5 days (median = 2.3 days), and 0.6 to 26.6 days (median = 5.0 days) for recovered tags. Recovered tags recorded a median of 50.8 GPS‐quality locations and 42.6 dives per day. Dive summary metrics were generated for archived dives and were subsequently classified into six categories using hierarchical cluster analysis. A mean of 77% of archived dives per individual were one of four dive categories with median Maximum Dive Depth >290 m (V‐shaped, Mid‐water, Benthic, or Variable), likely associated with foraging. Median Maximum Dive Depth was <30 m for the other two categories (Short‐ and Long‐duration shallow dives), likely representing socializing or resting behavior. Most tagged whales remained near the tagging area during the tracking period, but one moved north of Isla Tiburón, where it appeared to regularly dive to, and travel along the seafloor. Three whales were tagged on the same day in 2007 and subsequently traveled in close proximity (<1 km) for 2 days. During this period, the depth and timing of their dives were not coordinated, suggesting they were foraging on a vertically heterogeneous prey field. The multiweek dive records produced by ADB tags enabled us to generate a robust characterization of the diving behavior, activity budget, and individual variation for an important predator of the mesopelagos over temporal and spatial scales not previously possible.     

Locomotion in diving elephant seals: physical and physiological constraints

To better understand how elephant seals (Mirounga angustirostris) use negative buoyancy to reduce energy metabolism and prolong dive duration, we modelled the energetic cost of transit and deep foraging dives in an elephant seal. A numerical integration technique was used to model the effects of swim speed, descent and ascent angles, and modes of locomotion (i.e. stroking and gliding) on diving metabolic rate, aerobic dive limit, vertical displacement (maximum dive depth) and horizontal displacement (maximum horizontal distance along a straight line between the beginning and end locations of the dive) for aerobic transit and foraging dives. Realistic values of the various parameters were taken from previous experimental data. Our results indicate that there is little energetic advantage to transit dives with gliding descent compared with horizontal swimming beneath the surface. Other factors such as feeding and predator avoidance may favour diving to depth during migration. Gliding descent showed variable energy savings for foraging dives. Deep mid-water foraging dives showed the greatest energy savings (approx. 18%) as a result of gliding during descent. In contrast, flat-bottom foraging dives with horizontal swimming at a depth of 400m showed less of an energetic advantage with gliding descent, primarily because more of the dive involved stroking. Additional data are needed before the advantages of gliding descent can be fully understood for male and female elephant seals of different age and body composition. This type of data will require animal-borne instruments that can record the behaviour, three-dimensional movements and locomotory performance of free-ranging animals at depth.     

Development of net energy intake models for drift-feeding juvenile coho salmon and steelhead

We developed models to predict the effect of water velocity on prey capture rates and on optimal foraging velocities of two sympatric juvenile salmonids, coho salmon and steelhead. Mean fish size was ~80 mm, the size of age I+ coho and steelhead during their second summer in Southeast Alaska streams, when size overlap suggests that competition might be strongest. We used experimentally determined prey capture probabilities to estimate the effect of water velocity on gross energy intake rates, and we modeled prey capture costs using experimental data for search and handling times and published models of swimming costs. We used the difference between gross energy intake and prey capture costs to predict velocities at which each species maximized net energy intake rate. Predicted prey capture rates for both species declined from ~75 to 30–40 prey/h with a velocity increase from 0.30 to 0.60 m·s⁻¹. We found little difference between coho and steelhead in predicted optimum foraging velocities (0.29 m·s⁻¹ for coho and 0.30 m·s⁻¹ for steelhead). Although prey capture ability appears to be more important than are prey capture costs in determining optimum foraging velocities, capture costs may be important for models that predict fish growth. Because coho are assumed to pay a greater swimming cost due to a less hydrodynamic body form, we also modeled 10 and 25% increases in hydrodynamic drag to assess the effect of increased prey capture costs. This reduced optimum velocity by 0 and 0.01 m∙s⁻¹, respectively. Habitat segregation among equal-sized coho and steelhead does not appear to be related to the effects of water velocity on their respective foraging abilities.