Content uploaded by Rolf Åke Norberg
Author content
All content in this area was uploaded by Rolf Åke Norberg on Jun 09, 2015
Content may be subject to copyright.
Hunting Technique of Tengmalm's Owl Aegolius funereus (L.)
Abstract
Hunting by Aegolius funereus (L.) was studied by direct observation, and various phases of the prey capture were photographed. The owls hunted in forest land and frequented dense parts of the forest where they flew skilfully. They searched for prey from low perches, mean height 1.7 m, and waited a short time at each perch, mean 1 4/5 min. Mean distance between perches was ca. 17 m. Strikes occurred from close range, ca. 4.5 m. The owl's eyes were closed for protection just before impact. At impact the talons of both feet combined covered an area approximately 4 by 6 1/2 cm. The prey was usually killed by bites in the head or back of the neck. Due to its choice of low perches and strike from close range, the owl can make good use of auditory clues.
... Saw-whet owls tend to hunt from low perches and scan the ground for prey (Rasmussen Tengmalm's owl (Aegolius funereus) is a close relative of the saw-whet owl (Wink et al. 2009). It too is a small search-and-pounce predator (Norberg 1970), and has remarkably similar skull morphology to the saw-whet owl, exhibiting bony asymmetry of the external ears (Norberg 1977). Close observation of Tengmalm's owls reveals that foraging owls on a perch exhibit numerous head turns before either focusing on prey or moving to another perch (Norberg 1970). ...
... It too is a small search-and-pounce predator (Norberg 1970), and has remarkably similar skull morphology to the saw-whet owl, exhibiting bony asymmetry of the external ears (Norberg 1977). Close observation of Tengmalm's owls reveals that foraging owls on a perch exhibit numerous head turns before either focusing on prey or moving to another perch (Norberg 1970). Like a number of owl species, saw-whet owls have nearly immobile eyes (Steinbach and Money 1973;Steinbach et al. 1974;Martin 1982;Frost et al. 1989) and so like Tengmalm's owls, they rely on head movements to focus their eyes on potential prey (Norberg 1970;Johnsgard 1988;Rasmussen et al. 2008). ...
... Close observation of Tengmalm's owls reveals that foraging owls on a perch exhibit numerous head turns before either focusing on prey or moving to another perch (Norberg 1970). Like a number of owl species, saw-whet owls have nearly immobile eyes (Steinbach and Money 1973;Steinbach et al. 1974;Martin 1982;Frost et al. 1989) and so like Tengmalm's owls, they rely on head movements to focus their eyes on potential prey (Norberg 1970;Johnsgard 1988;Rasmussen et al. 2008). When saw-whet owls are perched above the ground with their heads swiveled downward, their area of best sensitivity is directed to the location of prey. ...
Northern saw-whet owls (Aegolius acadicus) are nocturnal predators that are able to acoustically localize prey with great accuracy; an ability that is attributed to their unique asymmetrical ear structure. While a great deal of research has focused on open loop sound localization prior to flight in owls (primarily barn owls), directional sensitivity of the ears may also be important in locating moving prey on the wing. Furthermore, directionally sensitive ears may also reduce the effects of masking noise, either from the owls' wings during flight or environmental noise (e.g. wind, leaf rustling, etc.), by enhancing spatial segregation of target sounds and noise sources. Here, we investigated auditory processing of Northern saw-whet owls in three-dimensional space using auditory evoked potentials (AEPs). We simultaneously evoked auditory responses in two channels (right and left ear) with broadband clicks from a sound source that could be manipulated in space. Responses were evoked from 66 spatial locations, separated by 30° increments in both azimuth and elevation. We found that Northern saw-whet owls had increased sensitivity to sound sources directly in front of and above their beaks and decreased sensitivity to sound sources below and behind their heads. The spatial region of highest sensitivity extends from the lower beak to the crown of the head and 30° left or right of the median plane, dropping off beyond those margins. Directional sensitivity is undoubtedly useful during foraging and predator evasion, and may also reduce the effect of masking noise from the wings during flight due to the spatial segregation of the noise and targets of interest.
... The Boreal Owl (Aegolius funereus) is a small, cavitynesting, nocturnal predator which breeds in the boreal forest, including alpine forest further south, and depends heavily on small mammals, i.e., shrews and rodents, as its main prey (Korpimäki and Hakkarainen 2012). It locates small mammals by auditory clues and searches for them by the pause-travel strategy, perching on low branches (Norberg 1970;Bye et al. 1992). By radio-tracking a male Boreal Owl in a low vole year, Sonerud et al. (1986) found that the owl utilized a win-stay strategy on a short time scale: following a prey capture and delivery to the nestlings, the owl returned to the area where the previous prey was captured. ...
... It should be noted that during the night around the time of summer solstice there is sufficient light in our study area to allow navigation without artificial light sources; consequently, our method of radiotracking consisted of homing in on the owls and observing them, and not of triangulation without visual confirmation. This method of radio-tracking did not disturb the owls in their whereabouts, as Boreal Owls are very tolerant to approach by humans (e.g., Norberg 1970;Bye et al. 1992). The time and UTM coordinates obtained from a handheld GPS receiver were noted for each fix, which was assigned to one of three levels of resolution. ...
... Boreal Owls are silent hunters (Norberg 1970) and provide few clues of their whereabouts to potential prey. However, considering that Boreal Owls, like other owls, fail in most of their attempts to capture prey (Nishimura and Abe 1988;Bye et al. 1992;Sonerud 1992b;Schifferman and Eilam 2004), increased prey vigilance can be expected after failed capture attempts. ...
Birds providing prey with a clumped distribution often return to the previous capture site after having delivered a prey item at the nest. However, details of this foraging tactic are still poorly known, in particular for birds of prey, which often travel far from their nest. We radio-tracked four provisioning male Boreal Owls (Aegolius funereus) during the nighttime and simultaneously recorded their prey deliveries by a video camera positioned at the nest in an increase year of the vole cycle. The camera allowed prey identification and made it possible to assign prey deliveries to fixes of the foraging owls, i.e. the last recorded fix before the owl returned to the nest for a prey delivery. Within a single night, the owls returned more often than randomly expected to the area where they had captured the previous prey item. A prey item delivered was more likely than randomly expected to be of the same species as the previous prey item delivered. However, the probability of a prey item delivered being of the same species as the previous prey item delivered was independent of whether the owl had returned to the area where it captured the previous prey and did not decrease with longer time elapsed since the previous delivery. The owls did not shift hunting area from one night to the next to a larger extent than they did over a longer time span, and overall tended to shift their hunting area gradually over more nights. Our study should be replicated in a peak vole year with higher prey abundance as well as in a low vole year, which should improve the study results by enabling a higher spatial and temporal resolution of the data on the owls’ movements.
... The great majority of prey brought to the young throughout the late nestling and postfledging dependence period (hereafter PFDP), in this particular species, is delivered by the male [47,48,50], and during good food years polygyny may occur [43,44]. Tengmalm's owl searches for prey by the pause-travel mode and locates it by sound [51][52][53]. ...
... This reflects the hunting strategy of Tengmalm's owl. The owl searches for prey by the pause-travel mode and depends heavily on sound to localize ground-dwelling prey [51][52][53]. Thus, high wind speed or heavy rain very likely hamper the hunt itself. ...
Animal home ranges typically characterized by their size, shape and a given time interval can be affected by many different biotic and abiotic factors. However, despite the fact that many studies have addressed home ranges, our knowledge of the factors influencing the size of area occupied by different animals is, in many cases, still quite poor, especially among raptors. Using radio-telemetry (VHF; 2.1 g tail-mounted tags) we studied movements of 20 Tengmalm’s owl (Aegolius funereus) males during the breeding season in a mountain area of Central Europe (the Czech Republic, the Ore Mountains: 50° 40’ N, 13° 35’ E) between years 2006–2010, determined their average hunting home range size and explored what factors affected the size of home range utilised. The mean breeding home range size calculated according to 95% fixed kernel density estimator was 190.7 ± 65.7 ha (± SD) with a median value of 187.1 ha. Home range size was affected by prey abundance, presence or absence of polygyny, the number of fledglings, and weather conditions. Home range size increased with decreasing prey abundance. Polygynously mated males had overall larger home range than those mated monogamously, and individuals with more fledged young possessed larger home range compared to those with fewer raised fledglings. Finally, we found that home ranges recorded during harsh weather (nights with strong wind speed and/or heavy rain) were smaller in size than those registered during better weather. Overall, the results provide novel insights into what factors may influence home range size and emphasize the prey abundance as a key factor for breeding dynamics in Tengmalm’s owl.
... Foraging pattern. Hunt primarily after dark except in rroi:tliern regions without summer darkness (Norberg 1970, Mikkola 1983. In southern areas exhibit biphasic rhythm with peaks of activity 20:00-22:00 hand 02:00--05:00 h (Mikkola 1983). ...
... Perch heights averaged 4 m (± 0.6 CI, n = 114) and owls watched for prey for less than 5 min on 75% of 150 perches (Hayward 1987, Hayward et al. 1993. Norberg (1970) recorded perch heights averaging 1.7 m (n = 154, range = l DB 0.5-8) and flight distances 17 m (range= 2-128). After detecting prey will wait 10 min or more before attacking if prey not in vulnerable position. ...
... Scenario 3 is a slightly modified version of scenario 2, intended for animals with flying abilities (birds, bats…) and using roads as corridors for long-range displacements; or for hunting because roads "drive" preys in the landscape (Kerth and Melber, 2009;Schwartz et al., 2018). Flying animals often make low-altitude flights to catch a prey or land on the road to feed (Grilo et al., 2014; see also the 'leap and strike' hunting behavior of owls: Norberg and Norberg, 1970;Southern, 1954). To this end, we added a third dimension z a describing the altitude of the animals to their existing (x a , y a ) position on the plane. ...
Road networks have major ecological impacts on living organisms consequent to habitat loss and fragmentation, chemical and acoustic pollution, and direct mortality when wildlife-vehicle collisions are involved (WVC). The many past empirical studies revealed major variables accounting for WVC incidence (e.g., population density). Similarly, spatial locations of WVC hot-spots are associated to landscape features at large spatial scales, and to road characteristics at small spatial scales. Yet, we currently lack a comprehensive theoretical framework for WVC. Animal movement in relation to habitats is likely an essential driver of encounters with roads, but this remains largely ignored in most studies. Movement ecology now provides the necessary tools to investigate the impact of animal movement on WVC. We built a general individual-based model incorporating recent knowledge in movement ecology (movement typology: roaming, migratory route crossing a road, active attraction and active repulsion of roads) to estimate WVC risks. We explored the relative effects of animal and vehicle movement parameters (speed, abundance, road sinuosity and animal movement pattern) on collision probability. We show that animal behavior toward roads has major impacts on the number and risks of WVC, but also modulate the effects of other factors (animal speed, species local abundance, road traffic volume) on WVC. Sensitivity analyses show that the movement and behavior of the animal has more influence on WVC risks than any of the characteristics of roads and vehicles we tested. Our results suggest that empirical studies of WVC should incorporate knowledge about the behavioral habits of the focal species in relation to roads.
... Because Ural Owl males are twice as large as Boreal Owl males by linear body measures (Cramp 1985), the distance between their ears is larger, so they would be able to determine the exact position of a ground-dwelling prey by acoustic cues at a larger distance (cf. Norberg 1970Norberg , 1978. ...
Four breeding Ural Owls (Strix uralensis) (one pair, one female and one male) were radio-tagged at the nest and tracked on foot with portable equipment in Hedmark county in SE Nor-way. The owls´ positions were determined by cross-triangulating or by direct observations. A total of 105 plotted locations were obtained. The mated male and female were located 58 and 22 times on 30 and 17 separate days, respectively, in 1989, while the other female was located 18 times on 15 separate days in 1989, and the other male 7 times on 4 separate days in 1990. From October 1989 on, presumably after the young became independent, the first male moved out of his summer range and eastwards into Sweden. Home range areas were treated as summer areas until this date, and winter areas thereafter. Calculated as 100% minimum convex polygon, the summer (May-September) home range for this male was 11 km 2 , while his winter (October-December) home range was 63 km 2. The corresponding home ranges for his mate were 7 km 2
... El mochuelo boreal es una especie ampliamente distribuida por la franja de bosques boreales del hemisferio norte (Cramp 1984, Mikkola 1983. En Europa, se distribuye también de manera heterogénea por diversas cordilleras montañosas forestales y en el extremo meridional de su distribución se localiza en la Península Ibérica, Grecia y Turquía (Hagemeijer y Blair 1997;Díaz et al. 1999), teniendo el límite de su área de distribución europea en los Pirineos (figura 1). ...
... Larger owl species hunt primarily in a gliding mode on approach, which ends in a thrust toward the prey at the final instant (see Figure 1). This behavior is consistent in both lighted (Norberg 1970) and darkened (Payne 1962) conditions, where in the latter case, the owl must make continuous flight path adjustments en route to its prey using acoustical cues. These larger owl species favor mammalian prey indigenous to their habitat, which typically include rodents such as voles and mice. ...
The ability of some species of owl to fly in effective silence is unique among birds and provides a distinct hunting advantage, but it remains a mystery as to exactly what aspects of the owl and its flight are responsible for this dramatic noise reduction. Crucially, this mystery extends to how the flow physics may be leveraged to generate noise-reduction strategies for wider technological application. We review current knowledge of aerodynamic noise from owls, ranging from live owl noise measurements to mathematical modeling and experiments focused on how owls may disrupt the standard routes of noise generation. Specialized adaptations and foraging strategies are not uniform across all owl species: Some species may not have need for silent flight, or their evolutionary adaptations may not be effective for useful noise reduction for certain species. This hypothesis is examined using mathematical models and borne out where possible by noise measurements and morphological observations of owl feathers and wings.
Expected final online publication date for the Annual Review of Fluid Mechanics, Volume 52 is January 5, 2020. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
... It is thus likely that increased movement may render bank voles more susceptible to both predation and infection. Tengmalm's owls are perch hunters and rely on auditory cues, e.g., generated by movement, to locate and strike their prey (Norberg 1970). If owls prey disproportionately on the subset of the population that is most likely to be infected, we would expect a higher proportion of PUUVinfected individuals in cached voles compared to that in the population (sensu Ostfeld and Holt 2004). ...
It has been suggested that predators may protect human health through reducing disease-host densities or selectively preying on infected individuals from the population. However, this has not been tested empirically. We hypothesized that Tengmalm's owl (Aegolius funereus) selectively preys on hantavirus-infected individuals of its staple prey, the bank vole (Myodes glareolus). Bank voles are hosts of Puumala hantavirus, which causes a form of hemorrhagic fever in humans. Selective predation by owls on infected voles may reduce human disease risk. We compared the prevalence of anti-Puumala hantavirus antibodies (seroprevalence), in bank voles cached by owls in nest boxes to seroprevalence in voles trapped in closed-canopy forest around each nest box. We found no general difference in seroprevalence. Forest landscape structure could partly account for the observed patterns in seroprevalence. Only in more connected forest patches was seroprevalence in bank voles cached in nest boxes higher than seroprevalence in trapped voles. This effect disappeared with increasing forest patch isolation, as seroprevalence in trapped voles increased with forest patch isolation, but did not in cached voles. Our results suggest a complex relationship between zoonotic disease prevalence in hosts, their predators, and landscape structure. Some mechanisms that may have caused the seroprevalence patterns in our results include higher bank vole density in isolated forest patches. This study offers future research potential to shed further light on the contribution of predators and landscape properties to human health.
Road networks have major ecological impacts on living organisms consequent to habitat loss and fragmentation, chemical and acoustic pollution, and direct mortality when wildlife-vehicle collisions are involved (WVC). The many past empirical studies revealed biological traits shared by species most vulnerable to roadkills (e.g. population density). Similarly, spatial locations of WVC hot-spots are associated to landscape features at large spatial scales, and to road characteristics at small spatial scale. We currently lack a comprehensive theoretical framework for WVC.
Animal movement in relation to habitats is an essential driver of encounters with roads, but this remains largely ignored in studies, even when movement ecology provides the necessary tools to investigate the impact of animal movement on WVC. We built a general individual-based model incorporating recent knowledge in movement ecology (movement typology: roaming, migratory route crossing a road, active attraction and active repulsion of roads) to estimate WVC risks. We explored the relative effects of animal and vehicle movement parameters (speed, abundance, road sinuosity and animal movement pattern) on collision probability;
We show that animal behaviour toward roads has major impacts on the number and risks of WVC, but also modulate the effects of other factors (animal traveling speed, species local abundance, road traffic volume) on WVC. Sensitivity analyses show that the movement and behaviour of the animal has more influence on WVC risks than any of the characteristics of roads and vehicles we tested.
Synthesis and applications . Our results suggest that (1) effective roadkill mitigation should be species-specific and could vary in efficiency depending on the target’s movement pattern (mating and migratory seasons, foraging habits…) and (2) empirical studies of WVC should incorporate knowledge about the behavioural habits of the focal species in relation to roads.
ResearchGate has not been able to resolve any references for this publication.