Point of no return in diving emperor penguins: is the timing of the decision to return limited by the number of strokes?

Abstract

SUMMARYAt some point in a dive, breath-hold divers must decide to return to the surface to breathe. The issue of when to end a dive has been discussed intensively in terms of foraging ecology and behavioral physiology, using dive duration as a temporal parameter. Inevitably, however, a time lag exists between the decision of animals to start returning to the surface and the end of the dive, especially in deep dives. In the present study, we examined the decision time in emperor penguins under two different conditions: during foraging trips at sea and during dives at an artificial isolated dive hole. It was found that there was an upper limit for the decision-to-return time irrespective of dive depth in birds diving at sea. However, in a large proportion of dives at the isolated dive hole, the decision-to-return time exceeded the upper limit at sea. This difference between the decision times in dives at sea versus the isolated dive hole was accounted for by a difference in stroke rate. The stroke rates were much lower in dives at the isolated hole and were inversely correlated with the upper limit of decision times in individual birds. Unlike the decision time to start returning, the cumulative number of strokes at the decision time fell within a similar range in the two experiments. This finding suggests that the number of strokes, but not elapsed time, constrained the decision of emperor penguins to return to the surface. While the decision to return and to end a dive may be determined by a variety of ecological, behavioral and physiological factors, the upper limit to that decision time may be related to cumulative muscle workload.

Observing the unwatchable through acceleration logging of animal behavior

“…There are several existing methods for locating animals in space and time including radio telemetry [136], satellite or geographic positioning systems [11,137,138] and acoustic arrays [139]. None of these methods works for all species and habitats and, consequently, travel paths are frequently reconstructed by bridging sporadic points and have low spatio-temporal resolution [140,141].…”

“…Furthermore, these errors accumulate over time, making location estimates increasingly worse further from the last known location. Because of these problems, dead-reckoning from accelerometry data has been used infrequently and most researchers interested in movement speed have added separate speed sensors (small external propellers) to the telemetry tags [24,137,[141][142][143][144]. As GPS technology becomes more widely integrated into accelerometer tags, the greatest potential for dead-reckoned animal location comes in recreating the exact travel path between subsequent GPS locations collected at short intervals e.g., <15 min [24,139].…”

“…Generally, the smaller the subject, the faster the movement and the higher the sampling frequency necessary to accurately characterize the pattern of acceleration [98,123,137]. From signal processing theory we have the rule-of-thumb that for adequate reconstruction of a continuous waveform such as acceleration, the sampling frequency ought to be at least twice that of the highest frequency movement being classified [162].…”

Evidence of partial deferment of digestion during diving in Steller sea lions (Eumetopias jubatus)

“…The patterns and underlying physiological controls of foraging dives have been investigated in a number of air-breathing vertebrates, including seabirds (Elliott et al, 2013;Heath et al, 2007;Shoji et al, 2015), penguins (Hanuise et al, 2013;Shiomi et al, 2012), sea snakes (Cook and Brischoux, 2014), sea turtles (Bradshaw et al, 2007;Wallace and Jones, 2008), and a host of marine mammals. Current models of the cost of foraging in these diving animals and the resultant theories of optimal foraging strategies treat the acquisition and digestion of prey as physiological processes that are independent of one another (e.g., Burns et al, 2006;Mori, 1998;Sparling et al, 2007b;Thompson and Fedak, 2001).…”

Testing optimal foraging theory in a penguin–krill system

“…In breath-hold divers, dive duration is basically regulated by physiology, notably via oxygen store management [24]. Therefore, parameters such as inhaled air volume, blood flow and workload of locomotory muscles [24][25][26] might explain some of the observed residuals ( figure 4b,c). According to AIC (table 1) and coefficients in the full model, bout-scale patch quality had a stronger effect than dive-scale patch quality on dive duration.…”