Dispersal mood revealed by shifts from routine to direct flights in the meadow brown butterfly Maniola jurtina

Abstract

A comprehensive mechanistic approach to dispersal requires the translation of the whole mobility register of the target organism into movement rules that could subsequently be used to model its displacements. According to the optimality paradigm, this procedure implies a cost–benefit analysis of mobility patterns taking into account not only movements, but also their external context and the internal state of the moving individuals. Using this framework, we detected a ‘dispersal mood’ in some individuals of the meadow brown butterfly Maniola jurtina. These adopted a direct flight strategy, which was topologically different from the previously documented foray search strategy. Those individuals that used the direct flight strategy moved straighter as soon as they left the habitat and avoided heading back to their patch of origin, which is the best inter‐patch search strategy when dispersal risks and costs are high. The direct flight strategy was conditional to sex: females used it twice as much as males. We suggest that this sex bias was due to female investment in offspring, which is maximized by male avoidance and spatial bet hedging. Inter‐patch dispersal of gravid females is crucial for the persistence of M. jurtina populations in spatially and temporally unpredictable environments.

Do all inter-patch movements represent dispersal? A mixed kernel study of butterfly mobility in fragmented landscapes

“…This result is in good agreement with those of other butterfly studies, and it conforms to the value predicted for the immigration probability proportional to patch diameter (Englund & Hamback 2007). Diameter scaling of immigration can be expected when butterflies moving though the matrix would either fly more or less linearly (Dusenbery 1989); rather straight inter‐patch movement of butterflies has, for example, been reported by Delattre et al. (2010).…”

Interactive effects of landscape and weather on dispersal

“…Contrary to random movements usually implemented in theoretical models, individuals recognize boundaries between habitat and non habitat and have considerable control over leaving habitat patch, and over their subsequent trajectories. In particular, this species is known for a dispersal behaviour constituting two distinct, non‐random movement strategies: a systematic search strategy (short‐distance ‘foray search’) (Conradt et al 2003), and a ‘direct flights’ strategy adapted to long distance dispersal in a hostile matrix (Delattre et al 2010a, b). The two strategies can be unambiguously categorized by the topology of the butterfly trajectory, following Delattre et al (2010a).…”

“…Four study landscapes (Fig. 1, and see Delattre et al 2010a for a detailed description of a typical study landscape) were chosen along a gradient of habitat fragmentation driven by agricultural intensification (Burel et al 1998) (Supplementary material Appendix A1 ESM 1 for values of landscape metrics). This gradient will be hereafter considered as a proxy for the temporal process of fragmentation (historical data on this LTER site validate this assumption, Burel et al 1998).…”

“…This species is particularly known for displaying two contrasted dispersal strategies: a systematic search strategy (‘foray search’), in which individuals fly in loops to explore the immediate vicinity of their departure patch, and a ‘direct flight’ strategy with straight movements allowing long distance dispersal (Conradt et al 2003, Delattre et al 2010a). The topology of the movements associated with each of these strategies was markedly different: short flight bouts with a high frequency of correlated turns for the foray search strategy, and longer and straighter bouts for the direct flight strategy (Delattre et al 2010a). We hypothesised that the shift from one dispersal strategy to the other depends on the landscape context (Delattre et al 2010a).…”

Individual dispersal, landscape connectivity and ecological networks

“…Dispersing individuals have to travel longer distances across unsuitable parts of the landscape (the matrix), which requires time and energy and increases the risk of unsuccessful dispersal (Bonte et al, 2012). Schtickzelle et al, 2007;Delattre et al, 2010;Turlure et al, 2011). This would eventually reduce dispersal costs either through a reduced search time or through the selection of relatively safe dispersal routes (e.g.…”