“…Marine predators whose foraging cannot be observed directly, such as turtles (Fossette et al, 2008;Hochscheid et al, 2005;Myers and Hays, 2006), cetaceans (RopertCoudert et al, 2002), pinnipeds (Liebsch et al, 2007) and diving birds (Shepard et al, 2010;Simeone and Wilson, 2003;Takahashi et al, 2004;Wilson et al, 2002) are represented in most of these studies (but see Ropert-Coudert et al, 2004), the data from which provided valuable information on prey captures. Of the two penguin species that have been fitted with Hall sensors at sea, the Magellanic penguin Spheniscus magellanicus (Simeone and Wilson, 2003;Wilson et al, 2002) and the chinstrap penguin Pygoscelis antarctica (Takahashi et al, 2004), both dived to moderate depths (<100m) and remained for less than 24h at sea each trip, in contrast with king penguins.…”
SUMMARYQuantification of prey consumption by marine predators is key to understanding the organisation of ecosystems. This especially concerns penguins, which are major consumers of southern food webs. As direct observation of their feeding activity is not possible, several indirect methods have been developed that take advantage of miniaturised data logging technology, most commonly: detection of (i) anomalies in diving profiles (wiggles), (ii) drops in oesophageal temperature and (iii) the opening of mouth parts (recorded with a Hall sensor). In the present study, we used these three techniques to compare their validity and obtain information about the feeding activity of two free-ranging king penguins (Aptenodytes patagonicus). Crucially, and for the first time, two types of beak-opening events were identified. Type A was believed to correspond to failed prey-capture attempts and type B to successful attempts, because, in nearly all cases, only type B was followed by a drop in oesophageal temperature. The number of beak-opening events, oesophageal temperature drops and wiggles per dive were all correlated. However, for a given dive, the number of wiggles and oesophageal temperature drops were lower than the number of beak-opening events. Our results suggest that recording beak opening is a very accurate method for detecting prey ingestions by diving seabirds at a fine scale. However, these advantages are counterbalanced by the difficulty, and hence potential adverse effects, of instrumenting birds with the necessary sensor/magnet, which is in contrast to the less accurate but more practicable methods of measuring dive profiles or, to a lesser extent, oesophageal temperature.
“…Marine predators whose foraging cannot be observed directly, such as turtles (Fossette et al, 2008;Hochscheid et al, 2005;Myers and Hays, 2006), cetaceans (RopertCoudert et al, 2002), pinnipeds (Liebsch et al, 2007) and diving birds (Shepard et al, 2010;Simeone and Wilson, 2003;Takahashi et al, 2004;Wilson et al, 2002) are represented in most of these studies (but see Ropert-Coudert et al, 2004), the data from which provided valuable information on prey captures. Of the two penguin species that have been fitted with Hall sensors at sea, the Magellanic penguin Spheniscus magellanicus (Simeone and Wilson, 2003;Wilson et al, 2002) and the chinstrap penguin Pygoscelis antarctica (Takahashi et al, 2004), both dived to moderate depths (<100m) and remained for less than 24h at sea each trip, in contrast with king penguins.…”
SUMMARYQuantification of prey consumption by marine predators is key to understanding the organisation of ecosystems. This especially concerns penguins, which are major consumers of southern food webs. As direct observation of their feeding activity is not possible, several indirect methods have been developed that take advantage of miniaturised data logging technology, most commonly: detection of (i) anomalies in diving profiles (wiggles), (ii) drops in oesophageal temperature and (iii) the opening of mouth parts (recorded with a Hall sensor). In the present study, we used these three techniques to compare their validity and obtain information about the feeding activity of two free-ranging king penguins (Aptenodytes patagonicus). Crucially, and for the first time, two types of beak-opening events were identified. Type A was believed to correspond to failed prey-capture attempts and type B to successful attempts, because, in nearly all cases, only type B was followed by a drop in oesophageal temperature. The number of beak-opening events, oesophageal temperature drops and wiggles per dive were all correlated. However, for a given dive, the number of wiggles and oesophageal temperature drops were lower than the number of beak-opening events. Our results suggest that recording beak opening is a very accurate method for detecting prey ingestions by diving seabirds at a fine scale. However, these advantages are counterbalanced by the difficulty, and hence potential adverse effects, of instrumenting birds with the necessary sensor/magnet, which is in contrast to the less accurate but more practicable methods of measuring dive profiles or, to a lesser extent, oesophageal temperature.
“…Thus, in cold water, dive costs of up to 20 times the BMR have been estimated in birds (Grémillet et al 2001, Enstipp et al 2006. It has been noted recently (Shepard et al 2009(Shepard et al , 2010 that, due to reduced buoyancy, deep diving is proportionally less expensive metabolically than expected.…”
Section: Introductionmentioning
confidence: 99%
“…Similar differences in maximum dive depth have been observed in other blue-eyed shags, such as Heard Island shags Phalacrocorax nivalis (Green & Williams 1997: males 60 m, females 33 m), Macquarie Island king cormorants P. albiventer (Kato et al 2000: males 109 m, females 62 m), and Crozet shags P. melanogenis (Cook et al 2007: males 145 m, females 55 m), but not in Antarctic shags P. bransfieldensis (Casaux et al 2001: males 110 m, females 113 m). A recent study using acceleration data to estimate dive effort in imperial shag (Shepard et al 2009(Shepard et al , 2010 found that the degree to which time and energy costs diverge with depth will be a function of (1) the buoyancy of the study individual, and (2) the depth range used. But, how these parameters differ between female and male imperial shags needs to be explored in greater detail.…”
Section: Intrinsic Factors: Sex Differencesmentioning
Sex differences in foraging behaviour have been explained by size dimorphism and/or avoidance of inter-sexual competition for depletable resources. To distinguish between these 2 hypotheses, we examined how intrinsic factors (sex-related differences) and extrinsic factors (year differences) shape the foraging behaviour of size-dimorphic imperial shags Phalacrocorax atriceps albiventer breeding at New Island, Falkland Islands/Islas Malvinas. We deployed time-depth and compass loggers to male and female imperial shags over 3 consecutive chick-feeding seasons. Males and females partly overlapped in coastal foraging areas, which were used mainly for benthic diving. Males additionally used offshore areas over deep water for shallow pelagic diving, suggesting that spatial segregation is involved in the avoidance of inter-sexual competition for food. Stable isotope data suggested differences in prey composition between the sexes, with consistently higher trophic levels in males, as expected for their larger size. Males were 27% heavier than females and reached greater maximum dive depths (98.9 ± 5.3 m) than females (54.1 ± 2.9 m). However, contrary to predictions based on body size dimorphism, the median dive depths of males were similar to those of females. While females used mainly benthic diving, males were more flexible in their benthic and pelagic foraging behaviour. Females also carried out more dives per day in all years, and deeper and longer dives than males in one year. As dive parameters differed strongly among the years, our results suggest that body size dimorphism and the avoidance of inter-sexual competition for food are involved in the evolution of sex-related differences in foraging in this species.
“…To investigate patterns of body posture, raw acceleration values were smoothed with adjacent averaging over 3 s to estimate the gravitational acceleration in the three axes [27,45,46]. To control for individual differences in device alignment, smoothed acceleration data in each of the three axes were centred on the individual's in-flight mean.…”
Section: Patterns In Body Posture and Motionmentioning
Background: Accelerometry has been used to identify behaviours through the quantification of body posture and motion for a range of species moving in different media. This technique has not been applied to flight behaviours to the same degree, having only been used to distinguish flapping from soaring flight, even though identifying the type of soaring flight could provide important insights into the factors underlying movement paths in soaring birds. This may be due to the complexities of interpreting acceleration data, as movement in the aerial environment may be influenced by phenomena such as centripetal acceleration (pulling-g). This study used high-resolution movement data on the flight of free-living Andean condors (Vultur gryphus) and a captive Eurasian griffon vulture (Gyps fulvus) to examine the influence of gravitational, dynamic and centripetal acceleration in different flight types. Flight behaviour was categorised as thermal soaring, slope soaring, gliding and flapping, using changes in altitude and heading from magnetometry data. We examined the ability of the k-nearest neighbour (KNN) algorithm to distinguish between these behaviours using acceleration data alone.
Results:Values of the vectorial static body acceleration (VeSBA) suggest that these birds experience relatively little centripetal acceleration in flight, though this varies between flight types. Centripetal acceleration appears to be of most influence during thermal soaring; consequently, it is not possible to derive bank angle from smoothed values of lateral acceleration. In contrast, the smoothed acceleration values in the dorso-ventral axis provide insight into body pitch, which varied linearly with airspeed. Classification of passive flight types via KNN was limited, with low accuracy and precision for soaring and gliding.
Conclusion:The importance of soaring was evident in the high proportion of time each bird spent in this flight mode (52.17-84.00 %). Accelerometry alone was limited in its ability to distinguish between passive flight types, though smoothed values in the dorso-ventral axis did vary with airspeed. Other sensors, in particular the magnetometer, provided powerful methods of identifying flight behaviour and these data may be better suited for automated behavioural identification. This should provide further insight into the type and strength of updraughts available to soaring birds.
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