Changes of movement patterns from early dispersal to settlement

Abstract

Moving and spatial learning are two intertwined processes: (a) changes in movement behavior determine the learning of the spatial environment, and (b) information plays a crucial role in several animal decision-making processes like movement decisions. A useful way to explore the interactions between movement decisions and learning of the spatial environment is by comparing individual behaviors during the different phases of natal dispersal (when individuals move across more or less unknown habitats) with movements and choices of breeders (who repeatedly move within fixed home ranges), that is, by comparing behaviors between individuals who are still acquiring information vs. individuals with a more complete knowledge of their surroundings. When analyzing movement patterns of eagle owls, Bubo bubo, belonging to three status classes (floaters wandering across unknown environments, floaters already settled in temporary settlement areas, and territory owners with a well-established home range), we found that: (1) wandering individuals move faster than when established in a more stable or fixed settlement area, traveling larger and straighter paths with longer move steps; and (2) when floaters settle in a permanent area, then they show movement behavior similar to territory owners. Thus, movement patterns show a transition from exploratory strategies, when animals have incomplete environmental information, to a more familiar way to exploit their activity areas as they get to know the environment better.

Shared space, individually used: spatial behaviour of non-breeding ravens (Corvus corax) close to a permanent anthropogenic food source

“…During such a stop phase, movement patterns seem to be more similar to those of settled breeders with defined home ranges than to those of vagrant nonbreeders, which has also been shown for other species (Smith 1978;Arcese 1989;Delgado et al 2009). In particular, the small size of the core areas-which were all concentrated around the main food source-suggests that ravens may easily learn about the local environment and thereby probably improve their foraging efficiency.…”

“…Indeed, the costs of dispersal when travelling through unknown areas (e.g. Pärt 1995;Stamps et al 2005) can be reduced by becoming familiar with an area (Delgado et al 2009). However, it is likely that there is a trade-off between familiarity with an area of high foraging potential and a high number of competitors for food and territories as well as the costs of possible agonistic interactions.…”

“…Waser et al 1994;Alberts and Altmann 1995), but efficiency can increase as spatial memory improves and as the individual learns about its environment (Saarenmaa et al 1988;Vuilleumier and Perrin 2006). When an animal temporarily settles in an area during dispersal, it may reflect the transition from exploratory strategies with incomplete environmental information to a more specific use of spatial resources by increasing the value of familiar space (Delgado et al 2009). …”

Using risk prediction models and species sensitivity maps for large-scale identification of infrastructure-related wildlife protection areas: The case of bird electrocution

“…The nesting area value was applied only to the 1 km × 1 km grid sections where the nest was located. The home range radius sizes were assigned according to annual home range studies carried out close to our study area as follows: golden eagle, 5 km (Fraguas et al, 2001); Bonelli's eagle, 4 km (Sanz et al, 2005;Pérez-García et al, 2013); and Eurasian eagle owl, 2 km (Delgado et al, 2009;Campioni et al, 2013). For griffon vulture, we considered only a protection area of 1 km around colonies because of the vast home range associated with this species (> 4000 km 2 , García-Ripollés et al, 2011, Zuberogoitia et al, 2012.…”

The straight and narrow path: the evolution of straight-line dispersal at a cane toad invasion front

“…B 281: 20141385 compass direction), each leg of movement is given equal weight, irrespective of the actual distance travelled during that leg. Fractal dimension (hereafter fractal D) is another measure of straightness that has been applied to study animal paths [27][28][29][30]. Fractal D-values are bounded between 1 and 2 and can be viewed as a measure of a linear path's ability to fill a plane.…”