Repeated Vessel Interactions and Climate- or Fishery-Driven Changes in Prey Density Limit Energy Acquisition by Foraging Blue Whales

Abstract

Blue whale survival and fitness are highly contingent on successful food intake during an intense feeding season. Factors affecting time spent at the surface or at depth in a prey patch are likely to alter foraging effort, net energy gain, and fitness. We specifically examined the energetic consequences of a demonstrated reduction in dive duration caused by vessel proximity, and of krill density reductions potentially resulting from krill exploitation or climate change. We estimated net energy gain over a simulated 10h foraging bout under baseline conditions, and three scenarios, reflecting krill density reductions, vessel interactions of different amplitudes, and their combined effects. Generally, the magnitude of the effects increased with that of krill density reductions and duration of vessel proximity. They were also smaller when peak densities were more accessible, i.e., nearer to the surface. Effect size from a reduction in krill density on net energy gain were deemed small to moderate at 5% krill reduction, moderate to large at 10% reduction, and large at 25 and 50% reductions. Vessels reduced cumulated net energy gain by as much as 25% when in proximity for 3 of a 10-h daylight foraging period, and by up to 47-85% when continuously present for 10 h. The impacts of vessel proximity on net energy gain increased with their duration. They were more important when whales were precluded from reaching the most beneficial peak densities, and when these densities were located at deeper depths. When krill densities were decreased by 5% or more, disturbing foraging blue whales for 3 h could reduce their net energy gain by ≥30%. For this endangered western North Atlantic blue whale population, a decrease in net energy gain through an altered krill preyscape or repeated vessel interactions is of particular concern, as this species relies on a relatively short feeding season to accumulate energy reserves and to fuel reproduction. This study highlights the importance of distance limits during whale-watching operations to ensure efficient feeding, as well as the vulnerability of this specialist to fluctuations in krill densities.

Rorqual Lunge-Feeding Energetics Near and Away from the Kinematic Threshold of Optimal Efficiency

“…5 ), which turns out dominated by the duration of the water expulsion and prey retention stage ( T purge ; Goldbogen et al 2011 ; Guilpin et al 2019 , 2020 ; Kahane-Rapport et al 2020 ). Here, and intra-specifically ( Kahane-Rapport et al 2020 ), body size and swim speed appear as secondary factors in determining T lunge , as compared to other, environmentally and behaviorally driven factors ( Goldbogen et al 2013 ; Hazen et al 2015 ; Lesage et al 2017 ; Guilpin et al 2020 ). Thus, two tag-informed bounding values of the lunge duration are used instead in the upcoming expenditure scaling analysis.…”

“…2 ; Doniol-Valcroze et al 2011 ; Goldbogen et al 2011 ; Cade et al 2016 ; Torres et al 2020 ). There might be several reasons behind such dispersion, including duration of the water expulsion/filtration stage, patch size in relation to a whale’s size, oxygen management during a dive ( Hazen et al 2015 ), or limited surface ( Lesage et al 2017 ; Guilpin et al 2020 ) or bottom time ( Goldbogen et al 2013 ). But, other factors may be at play, particularly with regard to the minimal U open .…”

“…One is the patch prey density ( ρ prey ), which, per the results shown here, could constrain lunge feeding speeds ( U open ) to lower values to maintain high efficiency wherever the density is low, as during feeding near the surface. More generally, correlating a whale’s trajectory with actual prey density data obtained from echo sounding ( Goulet et al 2019 ; Cade et al 2021 ) would be preferable to estimation through a geographical average ( Nemoto 1983 ), as done here and elsewhere ( Goldbogen et al 2011 ; Cade et al 2016 ; Guilpin et al 2019 , 2020 ). This would go a long way in not only determining the efficiency on a lunge-to-lunge basis, but also in documenting the minimal patch densities that rorquals are known to avoid ( Hazen et al 2015 ).…”

“…Rorquals are edentulous filter-feeders that forage on large aggregations of small prey, typically plankton (krill; 10–40 mm) or schools of forage fish (e.g., anchovies and capelin; 10–20 cm; Doniol-Valcroze et al 2011 ; Cade et al 2016 , 2020 ; Goldbogen et al 2017 ; Guilpin et al 2020 ). As lunge feeders, they accelerate while approaching the prey, to subsequently engulf it in large numbers along with the water in which it is embedded ( Fig.…”

Confronting assumptions about prey selection by lunge‐feeding whales using a process‐based model

“…At the same time, warm water events in the Gulf of Alaska have caused ecosystem‐wide changes (Bond et al., 2015; Lorenzo & Mantua, 2016) in addition to more typical climate variability (Fleming et al., 2016; Newman et al., 2016). To understand how predators may adapt to increasing environmental change, it will be important to continue to develop tools, such as the process models (Guilpin et al., 2020), that account for and incorporate the fundamental mechanisms underlying ecological processes.…”