Foray Search: An Effective Systematic Dispersal Strategy in Fragmented Landscapes

Conradt, Larissa; Zollner, Patrick A.; Roper, T. J.; Frank, Karin; Thomas, Chris D.

doi:10.1086/375298

Cited by 101 publications

(109 citation statements)

References 44 publications

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“…Future work may relate the results of this study to density-dependent emigration or immigration rates (e.g., Andreassen and Ims 2001), as well as movement orientation (Zollner and Lima 1997, 1999a, 1999b) and more systematic movement strategies (e.g., Conradt et al 2003, Russell et al 2003. Some species may also change boundary-crossing behavior throughout the year (Bommarco and Fargan 2002), depending on habitat quality Batzli 2001, 2004) or through interactions with other species (Fagan et al 1999).…”

Section: Discussionmentioning

confidence: 92%

Mechanisms Affecting Population Density in Fragmented Habitat

Tischendorf¹,

Grez²,

Zaviezo³

et al. 2005

E&S

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ABSTRACT. We conducted a factorial simulation experiment to analyze the relative importance of movement pattern, boundary-crossing probability, and mortality in habitat and matrix on population density, and its dependency on habitat fragmentation, as well as inter-patch distance. We also examined how the initial response of a species to a fragmentation event may affect our observations of population density in post-fragmentation experiments. We found that the boundary-crossing probability from habitat to matrix, which partly determines the emigration rate, is the most important determinant for population density within habitat patches. The probability of crossing a boundary from matrix to habitat had a weaker, but positive, effect on population density. Movement behavior in habitat had a stronger effect on population density than movement behavior in matrix. Habitat fragmentation and inter-patch distance may have a positive or negative effect on population density. The direction of both effects depends on two factors. First, when the boundary-crossing probability from habitat to matrix is high, population density may decline with increasing habitat fragmentation. Conversely, for species with a high matrix-to-habitat boundary-crossing probability, population density may increase with increasing habitat fragmentation. Second, the initial distribution of individuals across the landscape: we found that habitat fragmentation and inter-patch distance were positively correlated with population density when individuals were distributed across matrix and habitat at the beginning of our simulation experiments. The direction of these relationships changed to negative when individuals were initially distributed across habitat only. Our findings imply that the speed of the initial response of organisms to habitat fragmentation events may determine the direction of observed relationships between habitat fragmentation and population density. The time scale of post-fragmentation studies must, therefore, be adjusted to match the pace of post-fragmentation movement responses.

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Section: Discussionmentioning

confidence: 92%

Mechanisms Affecting Population Density in Fragmented Habitat

Tischendorf¹,

Grez²,

Zaviezo³

et al. 2005

E&S

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“…Non-random systematic search strategies, deviating from a correlated random walk, have been documented in the meadow brown butterfly, Maniola jurtina (Conradt et al, 2000) and the gatekeeper butterfly Pyronia tithonus (Conradt et al, 2001). When released at large distances from their habitat, both species flew around in petal-like loops back to their starting point each time ; this strategy was termed 'foray search ' (Conradt et al, 2003). This may allow them to explore the surrounding habitat but to return back if a suitable patch is not found, which may be adaptive if the chance of finding a new suitable patch is low (Conradt et al, 2000).…”

Section: ( D ) Sex Ratiomentioning

confidence: 99%

“…This may allow them to explore the surrounding habitat but to return back if a suitable patch is not found, which may be adaptive if the chance of finding a new suitable patch is low (Conradt et al, 2000). Modelling work has revealed these non-random search strategies often to achieve a greater dispersal success than random strategies (Zollner & Lima, 1999 ;Conradt et al, 2003).…”

Section: ( D ) Sex Ratiomentioning

confidence: 99%

Causes and consequences of animal dispersal strategies: relating individual behaviour to spatial dynamics

2005

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Knowledge of the ecological and evolutionary causes of dispersal can be crucial in understanding the behaviour of spatially structured populations, and predicting how species respond to environmental change. Despite the focus of much theoretical research, simplistic assumptions regarding the dispersal process are still made. Dispersal is usually regarded as an unconditional process although in many cases fitness gains of dispersal are dependent on environmental factors and individual state. Condition-dependent dispersal strategies will often be superior to unconditional, fixed strategies. In addition, dispersal is often collapsed into a single parameter, despite it being a process composed of three interdependent stages : emigration, inter-patch movement and immigration, each of which may display different condition dependencies. Empirical studies have investigated correlates of these stages, emigration in particular, providing evidence for the prevalence of conditional dispersal strategies. Ill-defined use of the term ' dispersal', for movement across many different spatial scales, further hinders making general conclusions and relating movement correlates to consequences at the population level. Logistical difficulties preclude a detailed study of dispersal for many species, however incorporating unrealistic dispersal assumptions in spatial population models may yield inaccurate and costly predictions. Further studies are necessary to explore the importance of incorporating specific condition-dependent dispersal strategies for evolutionary and population dynamic predictions.

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“…In other words, looping is an egocentric mechanism of exploration in which the explorer travels in a circular path that closes at the path origin. This mode of exploration has previously been observed in animals subjected to unfamiliar environments, especially under conditions of poor visibility (Avni et al, 2006;Bengtsson et al, 2004;Conradt et al, 2000;Conradt et al, 2003;Zadicario et al, 2005). For example, the diurnal fat sand rat (Psammomys obesus) explored a dark arena first by looping and then by wall-following .…”

Section: Behaviors Involved In the Construction Of Spatial Representamentioning

confidence: 64%

The dynamic process of cognitive mapping in the absence of visual cues:human data compared with animal studies

Yaski

Portugali

Eilam

2009

Journal of Experimental Biology

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SUMMARYThe present study aimed to investigate the behavior involved in constructing spatial representation in humans. For this, blindfolded adult human subjects were introduced into an unfamiliar environment, where they were requested to move incessantly for 10 min. Analysis of the locomotor activity of the participants revealed the following exploratory behaviors: (1) 'looping'; (2) 'wall-following'; (3) 'step-counting'; (4) 'cross-cutting'; and (5) 'free traveling'. Looping is a typical exploratory mode of sightless explorers, based on returning to a recently traveled place. Wall-following is common in enclosed spaces, whereby explorers follow the perimeter of the environment. Both looping and wall-following are based on an egocentric frame of reference by which explorers obtain information about the shape, size and landmarks in the environment. Blindfolded explorers displayed step-counting in order to scale the environment and the relationships in it. Altogether, exploration by looping, wall-following and step-counting resulted in an allocentric spatial representation. The acquisition of spatial representation was manifested by crosscutting and free travel, with subjects walking in a relatively fast and decisive manner. In light of the above modes of activity, we suggest that exploration of an unfamiliar environment is a synergetic self-organized process (synergetic inter-representation networks, SIRN model); an interplay between external and internal representations. According to this model, the interplay gives rise to an order parameter, such as the environment's dimensions or geometry, enabling progression to a subsequent exploratory behavior. This dynamic and sequential interplay reaches a steady state when a spatial representation (i.e. 'cognitive map') is established. Supplementary material available online at

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Foray Search: An Effective Systematic Dispersal Strategy in Fragmented Landscapes

Cited by 101 publications

References 44 publications

Mechanisms Affecting Population Density in Fragmented Habitat

Mechanisms Affecting Population Density in Fragmented Habitat

Causes and consequences of animal dispersal strategies: relating individual behaviour to spatial dynamics

The dynamic process of cognitive mapping in the absence of visual cues:human data compared with animal studies

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