Abstract:We describe a method for tracking the path of animals in the field, based on stereo videography and aiming-angle measurements, combined in a single, rotational device. In open environments, this technique has the potential to extract multiple 3D positions per second, with a spatial uncertainty of <1 m (rms) within 300 m of the observer, and <0.1 m (rms) within 100 m of the observer, in all directions. The tracking device is transportable and operated by a single observer, and does not involve any animal taggin… Show more
“…In this respect, the increased availability of unmanned aerial vehicles offers ecologists an unprecedented opportunity to obtain LiDAR data at a user‐defined scale and point density (Anderson & Gaston, ; Strandburg‐Peshkin et al., ). In addition, technical advances in animal tracking (Cagnacci, Boitani, Powell, & Boyce, ; De Margerie, Simonneau, Caudal, Houdelier, & Lumineau, ; Kays, Crofoot, Jetz, & Wikelski, ; Shipley, Kapoor, Dreelin, & Winkler, ) has drastically increased the spatial resolution (also in 3D) of location data which means that the spatial precision offered by LiDAR can increasingly be utilized to its full potential for viewshed ecology.…”
There has been rapid increase of interest in the role that information acquisition plays in ecological process and in shaping life histories and their evolution. Compared to auditory and olfactory cues, the range at which visual cues are likely to be informative to animals is particularly sensitive to the spatial structure of the environment. However, quantification of and accounting for availability of visual information in fundamental and applied ecological research remains extremely limited.
We argue that a comprehensive understanding of animal behaviour in a spatial context would greatly benefit from objective quantification of the area an animal can potentially obtain visual information from and therefore draw broad attention to viewshed analysis. This analysis identifies all cells of a gridded surface that are connected by lines‐of‐sight to a viewpoint, hence, providing information on how much of the environment surrounding a location can be seen. Although heavily used in non‐ecological disciplines including civil planning and archaeology, viewshed analysis has seldom been applied in an ecological context.
Here, we highlight the opportunity to make use of viewshed approaches in conjunction with three‐dimensional remote sensing data and data from animal tracking to make major progress in understanding how visual information influences animal spatial behaviour, ecology and evolution.
“…In this respect, the increased availability of unmanned aerial vehicles offers ecologists an unprecedented opportunity to obtain LiDAR data at a user‐defined scale and point density (Anderson & Gaston, ; Strandburg‐Peshkin et al., ). In addition, technical advances in animal tracking (Cagnacci, Boitani, Powell, & Boyce, ; De Margerie, Simonneau, Caudal, Houdelier, & Lumineau, ; Kays, Crofoot, Jetz, & Wikelski, ; Shipley, Kapoor, Dreelin, & Winkler, ) has drastically increased the spatial resolution (also in 3D) of location data which means that the spatial precision offered by LiDAR can increasingly be utilized to its full potential for viewshed ecology.…”
There has been rapid increase of interest in the role that information acquisition plays in ecological process and in shaping life histories and their evolution. Compared to auditory and olfactory cues, the range at which visual cues are likely to be informative to animals is particularly sensitive to the spatial structure of the environment. However, quantification of and accounting for availability of visual information in fundamental and applied ecological research remains extremely limited.
We argue that a comprehensive understanding of animal behaviour in a spatial context would greatly benefit from objective quantification of the area an animal can potentially obtain visual information from and therefore draw broad attention to viewshed analysis. This analysis identifies all cells of a gridded surface that are connected by lines‐of‐sight to a viewpoint, hence, providing information on how much of the environment surrounding a location can be seen. Although heavily used in non‐ecological disciplines including civil planning and archaeology, viewshed analysis has seldom been applied in an ecological context.
Here, we highlight the opportunity to make use of viewshed approaches in conjunction with three‐dimensional remote sensing data and data from animal tracking to make major progress in understanding how visual information influences animal spatial behaviour, ecology and evolution.
“…The RSV method natively produces position measurements in a spherical coordinate system Θ, Φ, Ρ (i.e. azimuthal angle, elevation angle and radius), with a measurement uncertainty for Ρ that increases proportional to Ρ 2 and is a fixed property of the device for Θ and Φ (de Margerie et al, 2015). The cumulative outcome of these uncertainties in 3D Cartesian space is a random position uncertainty attaining 0.2, 0.8 and 1.8 m at 100, 200 and 300 m, respectively.…”
Section: Smoothingmentioning
confidence: 99%
“…Here, we quantified swift flight trajectories by rotational stereo videography (RSV), which uses a camera and telephoto lens with a set of mirrors to combine views from two vantage points into one image, all mounted on an instrumented pivot to track individual birds during flight (de Margerie et al, 2015). Application of this and other videographic methods enables measurement of field flight biomechanics with high spatial (centimetre-metre scale) and temporal (5-100 Hz) resolution, even for species where use of an on-board satellite-based positioning package is currently infeasible because of weight or other restrictions.…”
Although the biomechanics of animal flight have been well studied in laboratory apparatus such as wind tunnels for many years, the applicability of these data to natural flight behaviour has been examined in few instances and mostly in the context of long-distance migration. Here, we used rotational stereo-videography to record the free-flight trajectories of foraging common swifts. We found that, despite their exquisite manoeuvring capabilities, the swifts only rarely performed high-acceleration turns. More surprisingly, we also found that despite feeding on tiny insects probably moving with ambient flow, the birds adjust their air speed to optimize cost of transport over distance. Finally, swifts spent only 25% of their time flapping; the majority of their time (71%) was spent in extended wing gliding, during which the average power expended for changes in speed or elevation was 0.84 W kg −1 and not significantly different from 0. Thus, gliding swifts extracted sufficient environmental energy to pay the cost of flight during foraging. Kinematic power P (W kg −1 ) (mean±s.d.) 6.85±5.71 P<0.0001 −0.84±4.00 P=0.0775 P<0.0001 Number of tracks with relevant data, out of 73 72 73 -P-values in columns are the result of t-tests for that cell only compared with the null hypothesis; the paired t-test column is a comparison of flapping and gliding results. 6
“…One application of this technology is the ability to track the movements and paths of animals in 3D, based on the view of multiple calibrated cameras. Although thus far the use of this technology in animal behavior research has mostly been restricted to the laboratory (but see Clark, ; de Margerie et al, ; Thierault et al, ), it has been used recently to track the flight paths of hummingbirds as they searched for a previously visited flower (Pritchard et al, 2016b, Fig. ).…”
An animal's behavior is affected by its cognitive abilities, which are, in turn, a consequence of the environment in which an animal has evolved and developed. Although behavioral ecologists have been studying animals in their natural environment for several decades, over much the same period animal cognition has been studied almost exclusively in the laboratory. Traditionally, the study of animal cognition has been based on well-established paradigms used to investigate well-defined cognitive processes. This allows identification of what animals can do, but may not, however, always reflect what animals actually do in the wild. As both ecologists and some psychologists increasingly try to explain behaviors observable only in wild animals, we review the different motivations and methodologies used to study cognition in the wild and identify some of the challenges that accompany the combination of a naturalistic approach together with typical psychological testing paradigms. We think that studying animal cognition in the wild is likely to be most productive when the questions addressed correspond to the species' ecology and when laboratory cognitive tests are appropriately adapted for use in the field. Furthermore, recent methodological and technological advances will likely allow significant expansion of the species and questions that can be addressed in the wild.
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