Search paths of swans foraging on spatially autocorrelated tubers

Abstract

Summary1. Tundra swans forage on below-ground pondweed tubers that are heterogeneously distributed in space. The swans have no visual cues to delineate patches. It was tested whether swans employ an area-restricted search tactic. Theory predicts that swans should alternate between an intensive (low-speed, sinuous) search mode in high tuber density areas and an extensive (high-speed, directed) search mode between these areas. 2. A quantitative analysis of movement paths recorded over short time frames (15 min) revealed that the sequential step lengths were strongly autocorrelated. After partitioning the data in low-speed paths and high-speed paths, this autocorrelation was very much reduced. 3. Movement paths with low speed were non-directional and could well be described as random walks. In contrast, high-speed paths were directed forward, and were better described as correlated (i.e. directional) random walks. 4. Movement paths recorded over longer time frames (1-4 h) provided empirical evidence that an alternation of low-speed, sinuous and high-speed, directed searches occurred. 5. There was a spatial autocorrelation in tuber biomass density, being significantly positively correlated until c. 10 m distance. The scale of the food clump size and step length of high-speed paths matched, suggesting that they were causally linked. 6. Computer simulations confirmed that swans using the observed search tactic achieved a higher energy gain than swans using only an intensive search mode, provided that the tuber biomass density occurred in clumps. They also achieved a higher gain than swans that alternated between intensive and extensive search mode, but always moved in a random direction.

When the going gets tough: behavioural type-dependent space use in the sleepy lizard changes as the season dries

“…Resource availability at the neighbourhood spatial-scale was a consistently better predictor of lizard space use than at the local scale, implying spatial decisions are influenced by a larger scale than our single quadrats. This finding is consistent with scale-dependent foraging, where movements of animals that use patchy or spatially autocorrelated resources match intermediate spatial scales [52][53][54]. Lizards may obtain relevant information on resource distributions through direct detection [46] or through familiarity with their multi-year stable HR [34,55].…”

A movement ecology paradigm for unifying organismal movement research

“…Navigational information can be goal-and/or sensory-system-specific. Flying swans, for example, use visual cues to detect a lake, kilometers away, but use tactile cues to detect tubers in the mud, millimeters away (31).…”

Foraging movements of emperor penguins at Pointe Géologie, Antarctica

“…Indeed, observations at emperor penguin colonies have shown that foraging trips vary in duration as the breeding season goes on (Kirkwood and Robertson 1997a), with the suggestion being that this is brought about by changes in the environment. The complexity of environmental conditions, both biotic and abiotic, with which emperor penguins have to contend ultimately distil out into two major behavioural patterns which are expressed during foraging: (1) travelling behaviour, where birds move quickly and directly through regions inappropriate for foraging, and (2) searching behaviour, where a reduced rate of overall travel results from greater track tortuosity in regions where prey is most likely to be located (Wilson 1995;Leopold et al 1996;Jaquet and Whitehead 1999;Nolet and Mooij 2002;Wilson 2002;Markman et al 2004;Austin et al 2006). The time allocated to each of these two behaviours results in a total foraging trip duration, which modulates the rate at which chicks can acquire food and thus grow appropriately.…”