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Dispersal mood revealed by shifts from routine to direct fl ightsin the meadow brown butterfl y Maniola jurtina

Thomas Delattre, Fran ç oise Burel, Antoine Humeau, Virginie M. Stevens, Philippe Vernonand Michel Baguette

T. Delattre (thomas.delattre@univ-rennes1.fr), F. Burel and A. Humeau, CNRS – Univ. de Rennes 1, UMR 6553 ‘ ECOBIO ’ / IFR CAREN, Campus de Beaulieu – bat. 14B, CS 74205, FR – 35042 Rennes Cedex, France. – V. M. Stevens and M. Baguette, CNRS – MNHN, UMR 7179 ‘ M é canismes adaptatifs: des organismes aux communaut é s ’ 1, Avenue du Petit Ch â teau, FR – 91800 Brunoy, France. VMS also at: F.R.S.-FNRS and Univ. de Li è ge - Unit é de biologie du comportement, 22 quai van Beneden, BE – 4020 Li è ge, Belgium. MB also at: CNRS USR 2936 ‘ Station d ’ é cologie exp é rimentale du CNRS à Moulis ’ , FR – 09200 Moulis, France. – P. Vernon, CNRS – Univ. de Rennes 1. UMR 6553 ‘ ECOBIO ’ / IFR CAREN, Station Biologique de Paimpont, FR – 35380 Paimpont, France.

Oikos 119: 1900–1908, 2010 doi: 10.1111/j.1600-0706.2010.18615.x

© 2010 Th e Authors. Oikos © 2010 Nordic Society Oikos Subject Editor: Justin Travis. Accepted 12 April 2010

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 – benefi t 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 butterfl y Maniola jurtina . Th ese adopted a direct fl ight strategy, which was topologically diff erent from the previously documented foray search strategy. Th ose individuals that used the direct fl ight 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. Th e direct fl ight 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 off spring, 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.

Shifting from the description of biodiversity patterns to the analysis of the underlying mechanism has become a usual approach throughout the short history of ecology as a science (Levin 1992). Dispersal is a crucial process in the turnover of local populations and hence in species persistence within metacommunities (Hanski 1999, Clobert et al. 2001, Holyoak et al. 2005, Bowler and Benton 2009). Dispersal theory has been successful so far in identifying many diff erent drivers of dispersal ecology and evolution in heterogeneous environ-ments (kin competition avoidance: Perrin and Goudet 2001; density dependence: Travis and Dytham 1999, Poethke and Hovestadt 2002; environmental variance: Poethke et al. 2003; landscape confi guration: Travis and Dytham 1999, Heino and Hanski 2001, Mathias et al. 2001). It also rec-ognized that the persistence of a metapopulation depends on the fraction of dispersing individuals returning to the patch of origin (Hastings and Botsford 2006). Dispersal research has undergone its mechanistic revolution quite recently, however, compared with other key ecological pro-cesses (Bonte et al. 2008, Mueller and Fagan 2008, Clobert et al. 2009). Th is time lag may be explained by the lack of consensus around dispersal, making the concept still incon-sistent. Accordingly, there are multiple diff erent defi nitions and viewpoints about dispersal in the literature that have altogether, and progressively, obscured the issue. Dispersal is probably best defi ned as “ any movement of individuals or

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propagules with potential consequences for gene fl ow across space ” (Ronce 2007).

Mechanistically, dispersal can therefore be realized in dif-ferent ways: as a by-product of routine movements associated with resource exploitation (like foraging or mate-searching), or as special movements adapted to net displacement (Van Dyck and Baguette 2005). When resource patches are scat-tered in the landscape, movements associated with resource exploitation and movements adapted to net displacements may be under uncoupled evolutionary pressures, leading to contrasted resulting dispersal trajectories. We consider here trajectories of a moving individual as the topological results of the application of movement rules that are shaped by selec-tive pressures aiming at optimizing either resource fi nding within patches or resource patch fi nding within landscapes. Th eory predicts (Zollner and Lima 1999 for a model), and observations document (reviewed by Baguette and Van Dyck 2007) that trajectories observed within resource patches will become more and more diff erent from trajectories between resource patches, when distances between those patches increase. Topologically, this most often translates into a pro-gressive shift from movements with a high rate of return within patches to more directed movements between patches. Both movement types are expected to be optimal: tortuous displacements will maximize encounter rate with aggregated resources (Bell 1991), whereas direct displacements will

minimize movement costs (direct: mortality, deferred: loss of time and energy) in heterogeneous environments (Heinz and Strand 2006, Barton et al. 2009).

Th e scale of movement investigation of widely foraging organisms obviously matters. For moving individuals, the distance from which they can detect suitable habitat (percep-tual range) is the determinant scale at which information is available to make oriented movement decisions (Wiens 1989, Olden et al. 2004). Accordingly, the interaction between indi-vidual movements and landscapes should depend on whether or not the grain of resource patches matches the spatial scale of the perceptual range (Baguette and Van Dyck 2007), which itself may vary according to the evolutionary history of the population. When the landscape grain is smaller than the perceptual range of the individual, there is no real dif-ference (in terms of costs) between movements within and between habitats; dispersal may occur as a by-product of rou-tine, explorative movement. On the contrary, if the grain of resources is larger than the perceptual range of the animal, dispersal bears larger costs for the individual: as searching time for resource patches increased, predation or other mor-tality risks, and deferred costs become higher (Van Dyck and Baguette 2005). In such cases, we expect that specifi c disper-sal rules should evolve. Several evolutionary responses aiming at decreasing this cost were reported: a decrease in the pro-pensity of leaving resource patches and the switch from tortu-ous routine movements to directed dispersal movements; the neuro-sensorial changes like an increase of perceptual range; or even changes in functional morphology associated with displacements (Baguette and Van Dyck 2007, Turlure et al. 2010). Th e adoption of one or the other dispersal strategy is dependent on the grain of resources (context-dependence).

Empirical evidence documenting movement specially adapted to dispersal still remains scarce, however. Non-territo-rial butterfl ies have proved to be excellent models for the study of displacements in widely foraging organisms (Baguette and Van Dyck 2007). Adults are usually easy to follow individually and continuously fl y, weather permitting, searching for well defi ned resources that are often organized in discrete aggregates (i.e. resource patches) in the landscapes. Schtickzelle et al. (2006) performed an integrated study on individual movements along a gradient (four levels) of resource patch fragmentation using the bog fritillary butterfl y Proclossiana eunomia as model spe-cies. Results indicated that (1) mortality costs increased with fragmentation, (2) individuals were more reluctant to leave resource patches in fragmented landscapes and (3) trajectories within and between resource patches were markedly diff erent in fragmented landscapes, individuals switched from explora-tion movements to direct displacements when released into the landscape matrix (Schtickzelle et al. 2006, 2007). Altogether these results suggest the existence of two context-dependent dispersal strategies based on the interaction between individual movements and the grain of resources in the landscape. Butter-fl ies in ‘ dispersal mood ’ adopt a specifi c dispersal strategy (with rapid and direct fl ights) where the grain of resources is coarse, whereas in tight-grained landscapes, dispersal can be realized through routine-like movements.

Besides, a potentially widespread systematic dispersal strat-egy termed foray search has been described in two butterfl y species: Maniola jurtina and Pyronia tithonus (Conradt et al. 2000, 2001, Conradt and Roper 2006). With foray search

fl ights, butterfl ies search systematically for suitable habitat by fl ying in a succession of progressively larger ellipsoidal loops ( “ forays ” ) away from and back to their starting point (Conradt et al. 2003). Such ellipsoidal loops correspond to movements used in a systematic search strategy, either in homing behavior or in within-habitat foraging behavior (Van Dyck and Baguette 2005). Th e use of this strategy when resource patches are distant from each other seems problem-atic, however: it is doubtful whether real animals have both the navigational and the memory skills required to use such complex trajectories at large scales that are relevant to disper-sal. In their release experiments, Conradt et al. (2000, 2001) mentioned that besides foray search, individuals of Maniola jurtina and Pyronia tithonus also used direct fl ights.

Here, we investigated the coexistence of these two diff er-ent movement strategies: the direct fl ight (rapid and directed no-return movements) and the foray search (ellipsoidal loops) in the meadow brown butterfl y Maniola jurtina by looking for the use of an alternative dispersal strategy to foray search. If the interaction between individual movements and the grain of resources in the landscape detailed above is somewhat general, we predict that such direct movements adapted to net displace-ments should occur besides the foray search strategy in land-scapes where resource patches are fragmented. We individually followed a large number of non-manipulated butterfl ies that crossed the border of a resource patch in such a fragmented landscape. Th eir topographic positions were recorded and resulting trajectories within the non habitat were analyzed using quantitative methods. Th en we computed the basic parameters of the trajectories resulting from each strategy. We were particu-larly interested in the timing of individual decision and asked if butterfl ies do decide to adopt one or the other strategy directly when crossing the habitat boundary, or to the contrary if they do shift from one to the other when already en route. We also asked wether these diff erences between the two strategies were higher than expected by chance, by comparing observed paths to simulated correlated random walks. Th e answers to these two questions should help distinguishing between well diff er-entiated, alternative dispersal decisions, and a continuum of increasingly linear movements going from explorative loops to direct fl ights: e.g. direct fl ights adopted by butterfl ies ‘ lost ’ during long explorative loops (for instance because they had overpass the distance at which they can perceive their habitat), or loops adopted by individuals that failed to cross the gap between patches (for instance because they had overpass their motivation, or energy reserves). Th is distinction should make a clear diff erence between dispersal as a by-product from rou-tine movements and special dispersal movement that resulted from butterfl ies being in dispersal mood. We also searched for between sex diff erences either in the adoption of one or the other strategy (i.e. the existence of condition-dependent dis-persal strategy) or in trajectory parameters. Indeed, males and females usually display contrasted displacements in butterfl ies (reviewed by Hovestadt and Nieminen 2009).

Material and methods

The species

Th e meadow brown Maniola jurtina is a protandrous but-terfl y having a single generation each year, with adults

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fl ying from mid-June to mid-September with continuous but decreasing adult emergences during this period (Brakefi eld 1982, Bink 1992). Males are generally more active than females (Brakefi eld 1982, Ouin 2000), while females spend more time feeding, and are more aggregated around nectar resources than males (Brakefi eld 1982). Females mate only once (Dowdeswell 1981) and usually within 24 h of emergence (Brakefi eld 1982). Females emerge without egg in their genital tract; egg matura-tion is slow in northwestern Europe (2 – 3 weeks: Bink 1992). Larvae feed on Poa species and on various other herbs (e.g. Agrostis spp., Festuca spp.), whereas the adults use a wide range of nectaring plants (Bink 1992). Females have a rather unselec-tive egg-laying behaviour; they usually oviposit on shorter herbs in the northern part of their distribution range (Bink 1992).

Maniola jurtina is one of the most abundant butterfl y species in the agricultural landscapes of western Europe. How-ever, changes in agricultural practices after world war two have led to the fragmentation of its habitats (open meadows, heath-lands, road verges, glades, hedgerows and forest paths). Th is process is extreme in intensively cultivated landscapes where the species is even becoming rare (Asher et al. 2001). Temporal stochasticity superimposes on this spatial patchiness: current mowing and ploughing practices unpredictably destroy suit-able habitats during adult fl ight season. Accordingly, dispersal is a crucial ingredient for the persistence of the species, particu-larly in highly fragmented, modern agricultural landscapes.

Maniola jurtina shows dispersal rates that are typical of butterfl y metapopulations in fragmented western Euro-pean landscapes (Conradt et al. 2000). Its dispersal behav-ior has been extensively documented (Conradt et al. 2000, 2001, 2003, Schneider et al. 2003, Kindlmann et al. 2004, Conradt and Roper 2006, Aviron et al. 2007, Ö ckinger and Smith 2007, Ouin et al. 2008, Delattre et al. 2010). Con-

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trary to random movements usually implemented in theo-retical models, individuals recognize boundaries between habitat and non habitat and have considerable control over leaving their patch, and over their subsequent trajectories. In particular, this species is known for its non-random, system-atic search strategy (foray search), in which individuals fl y in loops around their departure point (Conradt et al. 2003).

Study site

Th e study site was located in Brittany (south of the Mont Saint-Michel: 48 ° 36’N, 1 ° 32’W), France, in a LTER site (Long-Term Ecosystem Research. See � www.caren.univ-rennes1.fr/pleine-fougeres/ � for this particular study site and � www.lter-europe.net/ � for the European LTER Net-work) which landscape was constituted by a mixture of crops, hedgerows and small grassland patches. Maniola jurtina ’ s habitat (meadows) covers 11% of the total area in this site, with mean distance between patches d � 130 m � 110, and the probability of fi nding neighbour patches with the same habitat – ‘ homogeneity index ’ – h � 0.36 (Ouin 2000).

We observed butterfl ies at the boundary between a har-vested wheat fi eld ( ‘ non-habitat ’ ), and two patches of mead-ows referred to as ‘ habitat ’ (Fig. 1). Th e non-habitat patch was 330 m long and 220 m wide, which is large enough to study Maniola jurtina ’ s dispersal attempts as the distance to near-est habitat patch was larger than its known perceptual range (40 – 70 m as visually estimated by Conradt et al. 2000).

Th e non-habitat patch was bordered on north and east sides (Fig. 1) by two other non habitat wheat fi elds impracti-cable for experimenters. Th e whole boundary was permeable for individuals starting their moves either from the hedge-rows or directly from the meadows.

Figure 1. Map of the study site in western France, and schematic representation of a foray loop (A) and a direct fl ight (B). Favourable habitat is delineated in dark grey (meadows) and black (hedgerows). Unfavourable habitat is delineated in white (harvested wheat fi eld, where but-terfl ies were tracked) and light grey (cultivated wheat fi elds, impracticable for experimenters). Th e closest suitable habitat patch is located at 220 m from the south patch. Observations consisted in patrolling the habitat boundary from the non habitat side (C). Movement paths (A, B) are approximated by a sequence of straight lines and turning angles. L i : length of the ith move. Θ i : turning angle between moves i and i � 1. Eff ective distance (ED) is the bird ’ s-eye distance between fi rst and last point of the path. Total distance is the sum of the lengths of all moves (L i to L n ) of a given path. Orthogonal distance (OD) is the maximal distance to the nearest habitat patch reached during the fl ight.

Mapping and quantifying movement behavior

Data were collected in July 2008. Altogether, 274 individu-als were individually tracked (68 females, 173 males and 33 not sexed, Table 1). Contrarily to other studies (e.g. homing experiments), we used only observations to avoid interfer-ing with individual behaviour, thus butterfl ies were nor cap-tured and marked. However, large population sizes (Ouin et al. 2000, Conradt et al. 2001) and short residence time of individuals made pseudoreplications unlikely (Conradt et al. 2001). Observations consisted in patrolling the habitat boundary from the non habitat side (Fig. 1, dashed line). Every butterfl y seen less than 2 m from the habitat boundary was tracked until it moved 2 m into the habitat, or it stayed at the boundary for more than 30 s, or it was prematurely lost from sight, or it rested for 5 min, or it left the limits of the study site. When individuals fl ew further than the culti-vated wheat fi eld, they were assumed to have dispersed.

Data on fl ight paths were collected by tracking each indi-vidual from approximately 15 m away, and dropping markers on all stops/turns of its trajectory. Coordinates of the markers were recorded afterwards with a hand-held GPS. As butterfl ies fl ew in almost straight moves with stops and distinct recurrent turnings, fl ight paths were represented as sequences of straight-line moves (between two consecutive turns/stops, as recom-mended by Turchin 1998) and associated turning angles (Fig. 1), which allowed a quantitative analysis of movement param-eters. Using stops and turns instead of sampling at fi xed time intervals is biologically more meaningful, as they likely corre-spond to a decision made by the individual. It prevents prob-lems of over- or undersampling due to the choice of the time interval between two consecutive samplings (Turchin 1998). Th e duration of the fl ight was also recorded; we separated the time that each individual spent either fl ying or resting.

Flight paths parameters

We analyzed individual trajectories (or fl ight paths) using fi ve parameters (Fig. 1): move length (the length of fl ight between two successive stops/turns), total distance (the sum of all move lengths), eff ective distance (net distance between fi rst and last record), orthogonal distance (the maximal distance from the habitat reached during the fl ight), and turning angles between successive moves, that were described by their mean (Mu) and the concentration parameter of their distribution (von Mises K).

In order to test for the existence of diff erences between the supposed two types of fl ight paths (foray search vs direct fl ight), the paths were a priori and qualitatively categorized with respect to whether those individuals that crossed the bor-ders returned to the habitat, or not. Flight paths with return were attributed to foray search (Conradt et al. 2000, 2001,

Conradt and Roper 2006), whereas movements with no return were attributed to direct fl ights. We performed an explorative test for diff erences between these two categories using a dis-criminant analysis on the fi ve movement parameters.

Flight paths analyses

Parameters were pooled for all individuals by category (i.e. foray search and direct fl ights) and by sex, and were analyzed by statistical methods appropriate for linear and circular data (see tables for the description of the tests). Firstly, we assessed the goodness of fi t to a specifi c distribution: lognormal for linear variables and von Mises for turning angles (i.e. the circular normal distribution).

Secondly, we tested for equality of distribution moments between groups: mean μ and variance ς 2 of linear variables, mean Mu and concentration K of turning angles. Concentra-tion K is the inverse of variance for linear distributions: with higher K, angles are more concentrated around the mean. Th e linearity of the path was evaluated by concentration K and the ratio between eff ective distance and total distance.

Next, we investigated the timing of the behavioural choice between these two movement categories by searching for the threshold at which the diff erences between categories (foray searches vs direct fl ights) was detectable. We tested the diff er-ences in three movement parameters (move length, eff ective distance and turning angles), along fl ight paths of increas-ing length. We investigated diff erences in move length and eff ective distance through one-way Anovas, and diff erences in turning angles using modifi ed χ ² to test for diff erences in K. We repeated these analyses for fl ight paths with number of moves from 1 to 5, and for whole fl ight paths (in that case the mean value for each parameter was used).

Goodness of fi t to correlated random walks

We tested for the signifi cance of this dichotomy in fl ight behav-ior by asking if the real fl ights signifi cantly diff ered from cor-related random walks (CRW) with the same fl ight parameters for all simulated paths. We compared simulated vs observed foray searches and simulated vs observed direct fl ights for move length, concentration K i of the turning angles and proportion of all fl ights. CRW were simulated in a virtual landscape with the same size and shape than our study site (Fig. 1), and with the same set of starting points than observed fl ights. Step length and turning angles were defi ned following the distribution of all observed paths, pooled without consideration of return to the home patch. Th en, all CRW were a priori classifi ed with respect to whether the path returned to the habitat, or not (respectively, simulated foray search and direct fl ights). We ran a large number of simulations (i.e. 1000 per starting point) so that exact means of fl ight parameters could be compared to observed values.

Table 1. Sex ratio of Maniola jurtina using foray search and direct fl ights outside their habitat.

Proportion of males Proportion of females Proportion of unsexed individuals n

Population valuesa 0.79 0.21 0 210Direct fl ights 0.45 0.39 0.16 33Foray search 0.68 0.21 0.11 223Paths not assigned 0.39 0.44 0.17 18All movements 0.64 0.26 0.12 274

adata from Ouin 2000 (intra-patch behavior recording: not the total population size estimate).

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Results

We recorded 274 fl ight paths of individuals crossing the habitat boundary (1745 positions), 68 of which were females (388 positions) and 173 were males (1042 positions), 33 indi-viduals were not sexed (Table 1). Altogether, 33 paths were a priori categorized as ‘ direct fl ights ’ (12%) and 223 as ‘ foray search ’ (81%) on the basis of the visual inspection of the but-terfl y trajectory. 7% of fl ight paths were discarded because they were too short to be assigned unambiguously to one or the other category. A discriminant analysis on the fi ve move-ment parameters validated that the two movement categories were signifi cantly diff erent (Fig. 2, F � 12.70, p � 0.0001).

Th e frequency of observed direct fl ights (12%) was higher than expected by chance (2.09%, Fig. 3a, Supplementary material Appendix 4). Th e dichotomy between observed direct fl ights and foray searches was clearer in observed fl ights than in the simulated dataset. Move length of direct fl ights was higher in observed than simulated ones, while moves of observed foray searches were shorter than that of simulated ones (Fig. 3b, Supplementary material Appendix 4). Th e concentration of turning angles was more important for both observed direct fl ights and foray searches than for simulated paths (Fig. 3c, Supplementary material Appendix 4) (however, concentration parameters of the whole datasets are similar: K crw � 1.63 vs K real � 1.49).

Paths of both movement categories fi tted a lognor-mal distribution with frequent short moves and rare long moves between successive turns or stops (Fig. 4, Supplemen-tary material Appendix 1). Distributions of turning angles between successive moves fi tted a symmetrical around zero distribution, but were diff erent from a von Mises distribu-tion (Fig. 4, Supplementary material Appendix 1). Individu-als did not show preferential orientation of turns (i.e. their mean turning angle was zero) and small turns were more frequent than large turns.

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Direct fl ights were approximately four times longer than foray search in total distance, and their length was more vari-able (Table 2, 3). Eff ective distance covered by individuals in direct fl ights was from four to fi ve times longer than in foray search. Orthogonal distance, i.e. maximal distance from the nearest habitat border reached during the whole fl ight, was four times greater in direct fl ights than in foray search. Th e mean orthogonal distance in foray search was well below the mean grain of the study site (14.3 m vs 130 m). Th ere were no diff erences in fl ight speed between the two types of move-ments (Table 2), but time spent fl ying and time spent in non-habitat during the path were both three times greater in direct fl ights than in foray search. Th e concentration param-eter (von Mises K) of turning angles was on average twice as large in direct fl ights as in foray search (Table 3, Fig. 4), which was a cue for a higher path linearity.

Diff erences in fl ight path parameters between direct fl ights and foray searches were observed from the very begin-ning of movements as shown by the comparison of the fi rst pairs of steps between foray search and direct fl ights. Foray searches had consistently smaller move lengths, smaller eff ec-tive distances and were more tortuous (smaller K) than direct fl ights (Fig. 5, Supplementary material Appendix 2).

Th e sex ratio of individuals using foray search was highly skewed to males (with only 24% of females among the but-terfl ies sexed), which was not signifi cantly diff erent from the sex-ratio observed in CMR studies in the same area ( χ 1 ² � 0.59, p � 0.44; Table 1). It was largely less skewed to males for individuals in direct fl ights ( χ 1 ² � 10.31, p � 0.01; Table 1), where at least 46% of sexed butterfl ies were females (15% were unsexed). In other words, propor-tionally much more females were observed in direct fl ights than in foray searches (46% vs 24%). Move lengths of females using direct fl ights were longer than those of males in direct fl ights, whereas males spent more time resting in the matrix than females (Supplementary material Appendix 3). Beside

Figure 2. Factorial discriminant analysis between foray search and direct fl ights performed on eff ective distance, move length, total distance, orthogonal distance, and variance of turning angles in fl ight paths of Maniola jurtina butterfl ies. Mean turning angle was not kept in the fi nal model because no signifi cant eff ect was detected.

these two parameters, foray search and direct fl ights were similar in both sexes.

Discussion

We showed that (1) direct fl ights adapted to net displace-ments were used by individuals moving in non-habitat

alternatively to foray search, (2) butterfl ies adopted this dispersal strategy immediately after crossing their habitat boundary; and (3) direct fl ights were used more frequently by females, which at the end of the adult fl ight season might have considerable consequences for gene fl ow in this particular species.

Th eory predicts that the adoption of a fast, rectilinear tra-jectory is the best inter-patch search strategy when mortality risks and deferred costs – i.e. lost of time and energy with subsequent fi tness consequences – are high (Zollner and Lima 1999). Th is occur in the context of our study system, where the distance between neighboring habitat patches is larger than the individual ’ s perceptual range: direct fl ights were observed more frequently than expected by chance. Th e most exciting point is that we detected here an alternative trajectory to foray search that was indeed perfectly adapted to rapid, oriented displacements: moves were longer and straighter, without the return phase observed in foray search. Th is strategy was also more rectilinear – and more diff erent from foray loops – than CRW predicts, stenghtening the sug-gestion that it has been selected for its effi ciency. Moreover, these diff erences were observed from the beginning of each fl ight, which means that individuals using the direct fl ight strategy were already in a ‘ dispersal mood ’ when they crossed the border between habitat and non habitat. Th is deduction is far from anecdotal: the optimality paradigm (Baguette and Van Dyck 2007, Clobert et al. 2009) presupposes that indi-vidual dispersal decisions are conditioned to a cost–benefi t analysis, with fi tness as currency, that depends both on the internal condition of the individual and the external con-text of its current environment. According to this paradigm, dispersal decisions should be taken in the habitat prior to border crossing, which corresponds to what we observed in butterfl ies using the direct fl ight dispersal strategy. Th e fact that both real foray loops and direct fl ights showed angles that were more concentrated around the mean than their simulated equivalent also suggests that both kind of fl ight in hostile habitat have been selected for optimality.

Th e use of the direct fl ight strategy should be somewhat general, as testifi ed by the existence of ‘ type 1 fl ight ’ that cor-responded to direct fl ights adopted by butterfl ies in other studies (Conradt et al. 2000, Conradt and Roper 2006). In the only study directly comparable to the present one because butterfl ies were not manipulated before observation, the fre-quency of direct fl ights was about 2% (3 out of 145 fl ight paths recorded between two good patches of diff erent habitat quality), while we observed a frequency of 12%. We suspect that the frequency of use of this dispersal strategy could diff er according to the context in which populations evolved. Par-ticularly, dispersal strategies adapted to net displacements are expected to evolve when the functional grain of the landscape is larger than the perceptual ranges of the individuals (Baguette and Van Dyck 2007), that is in coarse-grained landscapes. Our study system should be considered coarse-grained from a butterfl y viewpoint since the mean inter-patch distances (130 m) is far larger than the perceptual range reported for this species (40 – 70 m, Conradt et al. 2000). Although we can-not test it, we may hypothesize that this coarse grain of our study landscape could explain why direct fl ights were observed so often in our study relative to the other. Another hypothesis could be that individual experience and particularly spatial

Figure 3. Comparison of foray search and direct fl ights parameters between fi eld data (triangles � IC 95% ) and correlated random walk simulations (circles � IC 95% ). Signifi cance is given by no overlap between confi dence intervals. (A) proportion of all fl ights classifi ed as foray search or direct fl ight, (B) move length, (C) concentration Ki of turning angles. See Supplementary material Appendix 4 for precise values.

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learning could cause changes in movement patterns through time. Indeed, we tracked butterfl ies at the end of the fl ight season, which means that old butterfl ies might have the opportunity to accumulate some spatial knowledge through learning. Individuals having experienced diffi culties to move between patches (i.e. long fl ights with low patch-fi nding suc-cess) should tend to limit their dispersal attempts and, when they fi nally decide to disperse, tend to limit its costs by choos-ing the more effi cient fl ight strategy.

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Several lines of evidence support that in Maniola jurtina , dispersing individuals disperse rather freely in the landscape. Firstly, diff erent CMR studies on M. jurtina everywhere in Europe reported frequent dispersal events (Schneider et al. 2003, Kindlmann et al. 2004, Aviron et al. 2007, Ö ckinger and Smith 2007, Ouin et al. 2008). Secondly, the amount of dispersal movement between two habitat patches depended primarily on the size of populations and on the distance between patches, and is rather insensitive to the composition

Figure 4. Distributions of move lengths and turning angles for foray search and direct fl ights in Maniola jurtina butterfl ies. (A, B) distribu-tions of move lengths. Grey bars: observed. Black lines: fi tted lognormal distribution with mean μ and variance ς 2 . Direct fl ights are longer and straighter than foray search movements. (C, D) distributions of turning angles. Gray dashed lines: fi tted von Mises distribution with mean m and concentration K. Continuous line: observed distribution. Direct fl ights are straighter than foray search movements: turning angles are smaller and more concentrated around 0.

Table 2. Tests for equality of means in fl ight path parametersfor Maniola jurtina butterfl ies in direct fl ights or foray search fl ights.

Parameter Test name Test statistic p

Move lengths one-way ANOVA F � 267.84 �0.001Effective distance one-way ANOVA F � 145.61 �0.001Total distance one-way ANOVA F � 102.17 �0.001Orthogonal distance one-way ANOVA F � 125.20 �0.001Total distance/

effective distanceWilcoxon W � 6919 �0.001

Flying timea one-way ANOVA F � 100.80 �0.001Time spent in bad

habitataone-way ANOVA F � 43.43 �0.001

Flight speed one-way ANOVA F � 0.35 0.55

afl ying time is the time actually spent in fl ight when dispersing. Time spent in bad habitat is the total duration of the move, including time spent in fl ight and time spent resting.All data with the exception of K (the concentration of turning angles distribution) and the ratio of total distance to effective distance were log-transformed prior to analysis.

Table 3. Tests for equality of variances in fl ight paths parameters of Maniola jurtina butterfl ies in direct fl ights or in foray search fl ights.

Parameter Test name Test statistic p

Move length Levene's test F � 2.97 0.08Effective distance Levene's test F � 15.38 � 0.001Total distance Levene's test F � 3.57 0.06Orthogonal distance Levene's test F � 0.26 0.61Concentration Ki of

turning anglesModifi ed χi² a χ1² � 77.37 � 0.001

Total distance effective distance

Levene's test

Flying timeb Levene's test 5.87 � 0.05Time spent in bad habitatb Levene's test 4.12 � 0.05

aJammalamadaka and Sengupta 2001.bfl ying time is the time actually spent in fl ight when dispersing. Time spent in bad habitat is the total duration of the move, including time spent in fl ight and time spent resting.All data with the exception of K (the concentration of turning angles distribution) and the ratio of total distance to effective distance were log-transformed prior to analysis.

of the landscape matrix (Ouin et al. 2008). Th irdly, older individuals were more often found in linear grassy elements between habitat patches than younger ones ( Ö ckinger and Smith 2007). Finally, investigations of population genetic structure using allozymes showed little diff erentiation at large spatial scale ( � 40 km), besides the existence of two loci under selective pressures (Goulson 1993).

Given the large diversity of study systems in which disper-sal has been investigated – including highly fragmented land-scapes (Kindlmann et al. 2004, Ouin et al. 2008) and large scale studies ( Ö ckinger and Smith 2007) – it seems therefore unlikely that routine movements associated with foray search would be the only dispersal strategy of M. jurtina that could explain such a dispersal pattern. Th e use of this strategy when resource patches are distant from each other seems indeed problematic, as it is doubtful whether real animals have both the navigational and the memory skills required to use such complex trajectories at large scales that are relevant to disper-sal. Th e use of the direct fl ight strategy should be somewhat general; however, the relative frequencies of this dispersal mood and foray search could diff er according to the grain of the landscape, or to other parameters, like for instance the experience of individuals. Th ere is a crucial need to investigate

the relationship between individual movements and dispersal rates among local populations in butterfl ies (Stevens et al. in press). M. jurtina is an excellent model species to achieve this challenge, as exemplifi ed by recent attempts in this direction (Kindlmann et al. 2004). However, our study warns against the risk of over-simplifying movement rules by considering only a part of the behavioral register of the target organism.

Despite mobility up to six times higher in males than in females in this species (Brakefi eld 1982, Ouin 2000), the fre-quency of direct fl ights strategy was here signifi cantly skewed to females: ca 20% of females were observed in direct fl ights, vs less than 10% of males. Moreover, females engaged in direct fl ights seemed more motivated than males (longer move length, less frequent stops). We suggest that this pattern is related to the life-history of the species. Females indeed emerge from their pupa without egg in their genital tract and are quickly mated after emergence; they are then constantly harassed by courting males, either during egg maturation or between egg-laying events. Such male harassments have direct fi tness cost in butterfl ies by decreasing off spring quality (Gibbs et al. 2005, Turlure and Van Dyck 2009); it is therefore not surprising that too much male encounters lead females to escape chasing males (Odendaal et al. 1989, Baguette et al. 1996). Accord-ingly, dispersal decision would be shaped by individual internal state and experience (Tibbetts 2007). Another, non exclusive, explanation might be spatial bet-hedging: female fi tness would be increased by laying eggs in diff erent resource patches, which could decrease the risks of either kin competition or inbreeding, or provide an insurance against environmental stochasticity. Th is latter point is of tremendous importance for a species like M. jurtina , whose habitat is spatially and temporally unpre-dictable in current man-shaped agricultural landscapes. All these advantages have obviously to be traded off against dis-persal costs. Anyway, females were more resolute than males about to move to other resource patches, which should have strong consequences on both population genetics (gene fl ow) and demography (colonization, reinforcement).

Acknowledgements – We thank Yannick Delettre (UMR CNRS 6553 ECOBIO) for his helpful comments on statistical analysis and Camille Turlure for critical reading. Yann Fournis took part in data collection. Th is manuscript was greatly improved by comments from Justin Travis. Financial support was given to TD by a grant of the French Ministry in charge of Higher Learning and Research, and the research grant no. 07-000025 “Diva-Corridor” of the French Ministry in charge of Environment. MB was partly funded by the EU FP7 SCALES project (“Securing the conservations of biodiversity across Administrative levels and spatial, temporal and Ecological Scales”; project no. 226852).

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Supplementary material (available online as Appendix O18615 at <www.oikos.ekol.lu.se/appendix>.). Appendix 1–4