Breeding dispersal in Black-headedGull: the value of

familiarity in a contrasted environment

GuillaumePeron*, Jean-Dominique Lebreton andPierre-Andre Crochet

Centre d’Ecologie Evolutive et Fonctionnelle UMR5175, CNRS, 1919Route deMende 34293Montpellier, Cedex 5, France

Summary

1. Some species (e.g. migratory species with high movement ability) are unlikely to experience any

physical cost when dispersing, at least at the landscape scale. In these species dispersal is neverthe-

less behaviourally constrained to avoid non-physical costs such as the loss of familiarity with the

breeding environment, and these constraints can bemaladaptive in a fast-changing environment.

2. We evaluated such constraints using multievent modelling of a 20-year capture–mark–recap-

ture data set from a multisite population of Black-headed Gull (Chroicocephalus ridibundus). The

population undertakes seasonal migrations that are very large compared with the size of the study

area.

3. Distances between colonies appeared as a strong predictor of breeding adults’ dispersal rates,

confirming behavioural constraints on dispersal. In addition, birds that had recruited outside their

colony of birth (natal dispersers) tended to return to their colony of birth later in life (long-term

memory effect).

4. An attraction for larger colonies was also visible in breeding adult dispersal patterns. The fact

that distance and memory still constrained dispersal although the largest colony provided higher

breeding success indicated departures from the ideal-free distribution, probably linked with the

lack of information about distant colonies. Moreover, the regional population apparently func-

tioned as a meta-colony where individuals frequently bred in suboptimal-choice locations before

being able to recruit in their preferred colony.

Key-words: buffer effect, coloniality, emigration, e-surge,Larus

Introduction

Dispersal is defined as the change of location between succes-

sive breeding attempts (breeding dispersal) or between birth

and the first breeding attempt (natal dispersal) (Greenwood

& Harvey 1982). Current hypotheses on the evolution of dis-

persal put forward the role of spatio-temporal changes in

habitat quality, intraspecific competition (density depen-

dence) and the risk of inbreeding (Gandon & Michakalis

2001). Yet in many vertebrate species, dispersal is generally

limited both in its frequency of occurrence and in the dis-

tances involved (Wheelwright & Mauck 1998; Huyvaert &

Anderson 2004; Janmaat et al. 2009; and references therein).

Indeed, site-fidelity is commonplace even in species living in

unreliable (Nager et al. 1996; Robinson & Oring 1997) or

recently degraded habitats (Poirier 1968; Igual et al. 2007),

and this can actually be maladaptive (Kokko & Sutherland

2001). The behavioural determinants of dispersal are there-

fore of increasing importance in a context of rapid and

intense anthropogenic global change (e.g. Massot, Clobert &

Ferriere 2008).

In this study, we use capture–mark–recapture (CMR) data

collected in a multisite population of Black-headed Gull

(Chroicocephalus ridibundus Pons, Hassanin & Crochet 2005)

to study breeding dispersal-measured through the probability

to change site (Lebreton et al. 2009) and to highlight, some

of the behavioural constraints on dispersal in this species.

The different subpopulations in the system correspond to

breeding colonies and are separated by 1–30 km, which is

much lower than the >1000 km travelled during seasonal

migrations in this species (Yesou, Isenmann & Lebreton

2004), and roughly equivalent to the daily distance flown by

foraging individuals (Brandl & Gorke 1988). Any constraint

on dispersal was therefore to be of behavioural nature and

caused by ‘non-physical’ costs of dispersal, such as the loss of

familiarity with the environment (Bukacinski, Bukacinska &

Lubjuhn 2000; Schjorring 2001; Brown, Brown & Brazeal

2008). Familiarity provides useful information on food

resources and predation risk (Isbell, Cheney& Seyfarth 1990;

Jacquot & Solomon 1997; Yoder, Marschall & Swanson*Correspondence author. E-mail: guillaume.peron@cefe.cnrs.fr

Journal of Animal Ecology 2009 doi: 10.1111/j.1365-2656.2009.01635.x

� 2009 TheAuthors. Journal compilation� 2009 British Ecological Society

2004) and also enables to spare time and energy otherwise

devoted to territorial and other social interactions with

unknown conspecifics (Eason & Hannon 1994). Long-term

association with a particular place can also promote kinship

between neighbours (van der Jeugd, van der Veen & Larsson

2002; Temple, Hoffman & Amos 2006), which increases the

benefit of cooperative behaviours such as social foraging

(Brown & Bomberger Brown 1996) and communal defence

against predators (Allaine 1991). In short, non-physical costs

of dispersal were expected to produce departures from the

ideal-free distribution (Fretwell & Lucas 1970) simply

because familiar places provide higher fitness for the above-

mentioned reasons. Moreover, contrary to the assumptions

made by Fretwell & Lucas (1970), information is unlikely to

be freely available (e.g. Citta & Lindberg 2007), further

enhancing the interest of breeding in places on which infor-

mation has already been collected during past experiences.

Under these hypotheses, we predicted that site-fidelity

should be the most widely adopted habitat choice strategy.

When dispersing, the rate of exchange between colonies

should decrease with distance (Citta & Lindberg 2007), in

order tominimize the loss of familiarity with the breeding and

foraging environment. Second, we predicted that, if leaving

the colony of birth (e.g. because of intraspecific competition

forcing natal dispersal, see below), individuals should after-

wards try to reintegrate it (‘memory effect’, detailed below).

High site-fidelity can also derive from habitat-choice

behaviours if favourable habitats are infrequent at the land-

scape scale (Heino & Hanski 2001; see also Post 1994). For

example, the results of Pinto, Rocha & Moreira (2005) sug-

gest that in a habitat-specialist bird, the population can con-

centrate in a single habitat patch due to the conjunction of

habitat quality temporal variation, social attraction and lack

of information about other potential breeding habitat (see

also Forbes & Kaiser 1994). In colonially breeding species,

colony size is expected to correlate with habitat quality and

to have a strong influence on dispersal or settlement proba-

bilities (Forbes & Kaiser 1994; Henaux, Bregnballe & Lebr-

eton 2007). Colony size per se can be a good predictor of not

only intraspecific competition for food and the length of for-

aging travels (Brandl & Gorke 1988; Lewis et al. 2006) but

also competition for the best nesting sites (Grosbois et al.

2003; Kokko, Harris & Wanless 2004). Colony size on the

other hand influences the efficiency of cooperative-like

behaviours (Brown & Bomberger Brown 1996). We thereby

expected that colony size would influence dispersal, just as

density does (Lena et al. 1998; Lambin, Aars & Piertney

2001).

In addition, individual quality, age and social rank are

expected to modulate the effects of intraspecific competition

(Holekamp 1986; Newton 1993; Sutherland 1996; Poston

1997), with young or low-quality individuals sometimes

forced to low-density, low-quality sites, whereas old and

high-quality individuals can stay in or disperse towards high-

density, high-quality sites (Potts, Coulson & Deans 1980;

Lena et al. 1998; Steiner &Gaston 2005;Moore, Loggenberg

& Greeff 2006). As heterogeneity in individual quality is a

common feature (e.g. Hamel et al. 2008), the occurrence of

individual heterogeneity in dispersal rates can be predicted.

Additional individual variation can originate from gender-

dependent dispersal (Greenwood 1980) or relatedness-depen-

dent dispersal (Bollinger, Harper & Barrett 1993; Wheel-

wright & Mauck 1998; Lambin et al. 2001; Szulkin &

Sheldon 2008). Although the biological foundations of indi-

vidual heterogeneity are sometimes hard to elucidate, it is

important to take such heterogeneity into account in demo-

graphic models as it is known to potentially bias the estima-

tion of several demographic parameters (Vaupel & Yashin

1985; Cam et al. 2002; Peron et al. 2009), as well as the out-

come of information-theoretic approaches (Burnham &

Anderson 2002).

Another potential consequence of the exclusion of young ⁄low-quality individuals from optimal sites is delayed first

reproduction where individuals may queue for recruiting

(Komdeur 1992; Ens, Weissing & Drent 1995; Ekman, Bylin

& Tegelstrom 1999; Kokko & Johnstone 1999). However, in

such a situation early reproduction could be obtained on a

low-density site (Ens et al. 1995), and individuals could sub-

sequently return to the colony of birth [contrary to the indi-

viduals in the study of Ens et al. (1995)]. Such a ‘breed-while-

queuing’ strategy would enable individuals to combine the

advantages of (i) reproducing as early as possible (Newton

1989), even if it is with a (slightly) lower breeding success than

in the preferred site; and (ii) breeding in a familiar place after

the second dispersal event. This mechanism implies the abil-

ity to keep long-term memory of the birth location, an ability

that many birds evidently possess, especially migratory spe-

cies (see also Mettke-Hofmann & Gwinner 2003; Davis &

Stamps 2004). The long-term memory of the site of birth in

itself and not through imprinting with some habitat variables

has so far been little evidenced in the context of habitat choice

and intraspecific competition.

In brief, following what we know about the costs and bene-

fits of dispersal in a colonially breeding, long-lived, migratory

bird like the Black-headedGull, and considering the method-

ological and biological implications of individual heterogene-

ity, we focused on the following points:

1. We looked for heterogeneity in individual breeding dis-

persal probabilities and investigated whether it linked to

natal dispersal behaviour, by checking if natal dispersers

(i.e. individuals that first breed outside their colony of

birth) exhibited a different breeding dispersal tendency

fromnatal philopatrics.

2. We tested for a relationship between the distance

between colonies and the dispersal probabilities, expect-

ing to find a decrease in dispersal probability with dis-

tance.

3. We tested for a relationship between colony size and dis-

persal probability, expecting a positive one (dispersal

influenced by social attraction and ⁄or concentration on

good quality sites: Veene 1977; Serrano et al. 2004). A

negative correlation would have indicated that dispersal

was mostly influenced by intraspecific competition, and

2 G. Peron et al.

� 2009TheAuthors. Journal compilation� 2009 British Ecological Society, Journal of Animal Ecology

therefore invalidated the hypothesis that breeding dis-

persal, as opposed to natal dispersal, involves good com-

petitors.

4. Finally, we checked whether there was a preference for

the site of birth when emigrating from a colony that is

not the site of birth, as expected if there exists a ‘breed

while queuing’ mechanism for recruiting to the natal site.

Materials andmethods

DATA COLLECTION

The whole population in the area is migratory. Colonies are deserted

in late summer–autumn, with winter records of ringed birds entirely

originating from areas hundreds of kilometres away – from Southern

and Western France to Iberia, where most of the birds seem to be in

winter, and (marginally) North Africa (unpublished data, including

re-sightings of colour-ringed birds). Breeding settlement in spring is

thus entirely an active choice and is not physically constrained by dis-

persal capacities.

Details of the field surveys are available in Prevot-Julliard et al.

(1998b). In brief, the study area is located in the Forez basin, central

France (30 kmNNE of Saint-Etienne, Loire department). Each year,

c. 20 colonies of Black-headed Gull are established in man-made

ponds in a farmland mosaic (Lebreton 1987). This includes a single,

large colony (La Ronze = LR), which has been occupied every year

and whose size varied between 3000 and 5000 pairs during the study

period 1986–2005. The remaining colonies numbered on average 163

pairs (SD: 171) and were not occupied each year. Thus, there was a

clear distinction between a large colony that was possibly over-

crowded, and several smaller colonies, where field observations

clearly indicated a lower density of birds. However, colony size and

density are not necessarily correlated in small colonies where avail-

ability of nest sites is somewhat variable (G.P. pers. obs.). As we have

no information on density per se, we examined the effects of colony

size on dispersal parameters.

Since 1977, we have ringed pre-fledging young birds in several col-

onies with standardmetal rings from the French ringing centre. Some

adult birds have also been caught with cannon-nets at feeding sites

(group 10 inAppendix S2). Ringed adults were re-sighted in the colo-

nies from a floating blind and the codes of their metal rings were read

using a telescope (Lebreton 1987). Re-sighting effort was spread

between the large colony of LR and three other small colonies (Les

Marquants, La Verchere and La Vallon 5, abbreviated as MA, VE

and V5; mean colony size over the study period was 590, 413 and 138

pairs respectively, excluding years when a colony was absent). Small

colonies were searched for ringed birds from 1994 onward whereas

LR was followed since 1977. The distances between colonies are

given in Appendix S1. We also ringed birds in other colonies that

were not subsequently surveyed and were ring-reading did not take

place. On the whole, these colonies averaged 2306 pairs over the

study period and they constituted a fifth compartment of our multi-

site population (see next section).

We analysed the dispersal of ringed adults after their first re-obser-

vation as breeders in the study colonies (2590 individuals). Each indi-

vidual was assigned to an explicit group according to (i) its site of

birth and (ii) its site of first re-observation (Appendix S2). In the fol-

lowing, ‘natal philopatrics’ are birds that were first seen as adults on

their colony of birth, and ‘natal dispersers’ are birds that were first

seen as adults on another colony. These groups constitute proxy for

the real status of a bird, because unless they were seen when they were

2 years old, we did not have any certainty that a bird had not bred

somewhere else before we first detected it.

Thus, the data in the recapture data set consisted of observations

of 2590 adult birds over 20 years (1986–2005). For a given year and

individual, the data were coded as 0 (not observed), 1 (observed in

LR), 2 (observed inMA), 3 (observed in V5), 4 (observed in VE) and

dispatched between groups that coded for birth site and natal dis-

persal status (Appendix S2 and next section).

In addition to ringing and re-sighting, we also monitored the loca-

tion and size of all colonies in the study area each year, independently

of whether these colonies were searched for ringed birds or not. We

thereby obtained an estimate of the number of pairs that were not

monitored each year.

CMR MODELS FOR THE STUDY OF DISPERSAL

We focused on breeding dispersal, which was analysed by modelling

separately the ‘site fidelity probability’ (the probability to remain in

the previous breeding location) and the ‘settlement probability’ (the

probability to settle in colonyAwhen leaving colony B) following the

framework proposed byGrosbois & Tavecchia (2003).

Capture–mark–recapture multistate ‘Arnason–Schwartz’ models

(Arnason 1972, 1973; Schwarz, Schweigert & Arnason 1993) have

been designed to estimate dispersal rates of marked individuals

while coping with the imperfect detection of individuals in natural

populations of animals. They are particularly suited to detect

between-site variations in demographic parameters as well as to test

hypotheses about the evolution of colonial breeding (Brown &

Bomberger Brown 1996). We started from multisite CMR models

disentangling site-fidelity and settlement probabilities as proposed

by Grosbois & Tavecchia (2003). To account for the presence of

non-monitored colonies, we added an unobservable state ‘Alive

Elsewhere’, AE (Burnham 1993). There were thus four study colo-

nies but five sites in the multisite model: LR, MA, V5, VE and AE.

Temporary emigration (dispersal towards non-monitored colonies

or colonies outside the study area) was modelled as a deterministic

(Markovian) transition to and from the state AE (Fujiwara & Ca-

swell 2002; Schaub et al. 2004). In order for the parameters to be

identifiable separately, we had to make the assumptions that the

return rate from the unobservable state was constant with time and

the survival rate in the state AE the same as in the observed states

(Fujiwara & Caswell 2002).

To reduce the number of parameters in the models, we considered

that survival probability was site-independent and that survival and

dispersal probabilities did not vary between years. These assump-

tions are supported by the results of Prevot-Julliard, Lebreton & Pra-

del (1998a) and Grosbois & Tavecchia (2003) for the same

population. To fit the study design, detection probabilities weremod-

elled as site- and time-dependent, and fixed to zero in years when no

visit was made on a given colony. Importantly, site-fidelity was con-

strained to zero in years when a given colony was not established,

hence modelling that in these cases gulls either changed site or

skipped reproduction waiting for more favourable conditions (Gros-

bois & Tavecchia 2003).

CMR MODELS WITH INDIV IDUAL HETEROGENEITY IN

DISPERSAL

Between-individual variations are not accounted for in the stan-

dard Arnason–Schwartz models. Two methods have been pro-

posed to overcome this issue: random individual effects (Cam

et al. 2002) and mixture models with discrete classes of individuals

Dispersal, familiarity and colony size 3

� 2009 TheAuthors. Journal compilation� 2009 British Ecological Society, Journal of Animal Ecology

(Pledger, Pollock & Norris 2003). We used the latter approach

here in a framework based upon a recent generalization in CMR

multisite models: the multievent models (Pradel 2005). Multievent

models allow a discrete, hidden individual heterogeneity structure

on the parameters of a multisite CMR model (Pradel 2009), thus

making the implementation of Pledger et al. (2003) models

straightforward.

In our case, the underlying state occupied by an individual deter-

mined its current breeding location and its probability to emigrate,

whereas the actual data recorded in the field (‘events’) corresponded

to the current breeding locations only. The point of this mixture

model is to separate histories like ‘10110001’, representing site-faith-

ful individuals, from histories like ‘40130002’, representing non-site-

faithful individuals. These models are hereafter referred to as ‘move-

r ⁄ stayer’ models (Goodman 1961). That is, for each history there are

two possible ‘paths’, one with low and one with high emigration

probability. Each individual has a probability p that it is in the low-

emigration (stayer) path, and 1 ) p that it is in the high-emigration

(mover) path (see Appendix S3). The probability p is estimated like a

demographic parameter by maximizing the overall likelihood of the

data set.

We modelled a repeatable site-fidelity, in the sense that an individ-

ual remained in the same class of site-fidelity for its whole life (transi-

tions were only allowed from a state stayer to another state stayer

and from a state mover to another state mover). Appendix S3 is a

matrix description of this model structure.

All models were fully described by first considering the vector of

probabilities of initial presence in the various states (P-vector), then

linking states at successive sampling occasions by the matrix of sur-

vival ⁄ transition probabilities (F-matrix), exactly like in multistate

models, while the events were linked to states by the matrix of event

probabilities (P-matrix). Following Grosbois et al. (2003), we sepa-

rated F in three steps (S-matrix for survival probabilities, F-matrix

for site-fidelity and E-matrix for settlement probabilities conditional

on emigration; the product of F and E is the usual transition matrix

of multistate CMR models). P-vector was also divided in two steps

(P1-vector for probabilities of being in each colony at first detection

and P2-matrix for the individual heterogeneity). Examples of these

matrices are all presented in Appendix S3.

We used program e-surge 1.1.1 (Choquet, Rouan & Pradel 2009)

to obtain maximum likelihood estimates of the parameters and per-

formmodel selection.

MODEL SELECTION: INDIV IDUAL VARIAT ION AND

MEMORY

Model selection relied on AIC (Aikake Information Criterion: Burn-

ham&Anderson 2002). Amodel was considered to fit the data signif-

icantly better than other concurrent models if it had two AIC-points

less than thesemodels.

We first investigated the presence of individual heterogeneity in

site-fidelity, because it is a source of bias if not accounted for. Then

we examined three hypotheses presented in the introduction, in the

following order of increasing model complexity. At each step, we ten-

tatively added the considered effect to the model selected at the previ-

ous step.

1. Heterogeneity in site-fidelity.

We compared a standard multisite model to the same model with

individual heterogeneity, built as described above.

2. Between-site variations in site-fidelity.

We compared the model preferred at the previous step (i.e. with or

without heterogeneity in site-fidelity) to the same model with a site-

effect on site-fidelity.

3. Natal dispersal effect.

The presence of heterogeneity indicates the existence of an

unknown source of variation; here we examined whether part of this

variation was explained by the initial dispersal choice. We examined

whether the between-individual variation in site fidelity correlated to

the past history (whether the bird dispersed for its first reproduction

or not). More precisely, we built a model in which the probability to

be a mover or a stayer depended on the natal dispersal status, i.e. the

groups as described in the data collection part and in Appendix S2.

This effect is hereafter referred to as natal dispersal effect. We com-

pared the models with and without natal dispersal effect to conclude

on the maintenance of the initial dispersal choice throughout life. We

further investigated if the pattern was different in the potentially

overcrowded LR colony by comparing a model including the addi-

tional effect of being born in this colony. e-surge syntax is given in

Appendix S2.

4. Memory effect.

Memory was expected to translate into a tendency to return to the

site of birth during breeding dispersal events (referred to as memory

effect). This behaviour was modelled using a combined group- and

site-effect on the probability of settlement (e-surge syntax is given in

Appendix S2).We also considered here that the effect could be stron-

ger for the LR colony.

GOODNESS-OF-F IT

Goodness-of-fit (GOF) of the Arnason–Schwartz four-site model

was estimated with the program u-care (Choquet et al. 2005). The

meanings of the subcomponents of the GOF test are presented in

Pradel, Gimenez & Lebreton (2005). In particular, the component

3G-SR indicates transience (lower probability of subsequent

encounter for first-encountered individuals than already-encoun-

tered ones). As highlighted by Pradel et al. (1997), one of the

effects of transience in CMR studies is to produce an excess of

individuals whose apparent survival is zero after first encounter.

Therefore, if not accounted for, transience induces a lower survival

probability in the first time interval after initial capture, i.e. at age

1 in the sense of CMR models. As recommended by Pradel et al.

(1997), transience can be accounted for by implementing an age-

structure on survival probabilities. For a similar implementation

using a part of the same black-headed gull data, see Prevot-Julliard

et al. (1998a).

POST HOC L INEAR MODELS FOR SETTLEMENT

PROBABIL IT IES: EFFECTS OF DISTANCE AND COLONY

SIZE

The settlement probability from site A to site B was defined as the

probability that the emigrants leaving A settle in B. These probabili-

ties were estimated from the preferred CMR model (see above) and

their variation with between-colony distance and colony size were

used to test the last two hypotheses.

Following Rousset & Gandon (2002), dispersal probabilities are

expected to decrease nonlinearly with distance between colonies.

At the level of resolution available in long-term vertebrate CMR

studies like ours, a model where dispersal probability decreased

4 G. Peron et al.

� 2009TheAuthors. Journal compilation� 2009 British Ecological Society, Journal of Animal Ecology

exponentially with distance was considered a parsimonious represen-

tation of the underlying processes. We employed post hoc linear mod-

els rather than a direct implementation in the CMR framework

because the logarithm link-function required to model the expected

relationship is not available yet in the software e-surge. We built a

generalized linear model, using the distances between colonies, the

log-transformed sizes of the colonies of arrival and their interaction

as explanatory variable, and the estimates of settlement probabilities

as dependent variable. This post hoc model took the correlation

between estimates and their standard error into account via the use of

the variance–covariance matrix provided in e-surge. The presence of

the considered effects was selected or discarded using their 95% con-

fidence intervals.

Results

GOODNESS-OF-F IT

The component 3G-SR of the test was statistically significant

(v2 = 88Æ6, d.f. = 40, P < 0Æ001), indicating transience.

Other tests were not statistically significant. These results

indicate that the Arnason–Schwartz model fitted the data

once transience was accounted for through the age-structure

on survival. Consequently, we did not account for overdis-

persion in the model selection procedure.

MODEL SELECTION: INDIV IDUAL VARIAT ION AND

MEMORY

1. Heterogeneity in site-fidelity.

The model with individual heterogeneity in site-fidelity per-

formed significantly better than the model without it

(Table 1, model 2 vs. 1).

2. Between-site variations in site fidelity.

The model with the site-effect on site-fidelity performed

slightly better than the model without it (Table 1, model 3 vs.

2).

3. Natal dispersal effect.

Themodel with the natal dispersal effect performed signifi-

cantly better than the model without it (Table 1, model 4 vs.

3). Adding an LR-effect improved the fit slightly (Table 1,

model 4bis vs. 4 and 3). The probability to be a mover was

higher, i.e. site-fidelity probabilities were lower for natal dis-

persers than for natal philopatrics (Tables 2 and 3). This

result indicated that part of the individual heterogeneity in

breeding dispersal was explained by the natal dispersal effect.

The birds that dispersed for their first breeding attempt

tended to disperse more often for following attempts. Birds

born in the largest colony of LR exhibited a slight tendency

to disperse more as adults (breeding dispersal) than birds

born elsewhere in the Forez (Table 2).

4. Memory effect.

Adding the memory effect increased markedly the fit

(Table 1, model 5 vs. 4bis). This result indicated that natal

dispersers, when they subsequently engaged in breeding dis-

persal, were more likely to return to their colony of birth than

tomove to any other colony (Table 4).

The final, preferred model (model 5 in Table 1) thus

included individual heterogeneity, natal dispersal effect, site-

effects on site-fidelity, and memory effect. Natal dispersers

were more often movers than natal philopatrics (meaning

that the initial dispersal decision was more often reproduced

than not; Table 2). Being born in LR induced a slightly

higher probability to be a mover (Table 2). Heterogeneity in

site-fidelity was very significant as indicated by confidence

intervals (Table 3). Site-fidelity also varied between colonies

Table 1. Model selection

Step np Deviance AIC AICc

1. Basic model 89 11 327Æ03 11 505Æ03 11 511Æ442. Model with individual heterogeneity 92 11 282Æ97 11 466Æ97 11 473Æ823. Adding site-effect on fidelity 96 11 274Æ00 11 466Æ00 11 473Æ474. Adding natal dispersal effect 93 11 273Æ91 11 459Æ91 11 466Æ914bis. Natal dispersal effect acting differently in LR 94 11 270Æ86 11 458Æ86 11 466Æ025. Addingmemory effect 99 11 247Æ10 11 445Æ10 11 453Æ05

The different models and the effects included are described inmethods. Given are the number of parameters in the model (np), the deviance, the

AIC and theAICc (AIC corrected for sample size).

Table 2. Proportions ofmovers: variation with site of birth and past history

Site of birth LR not LR

%Movers among natal dispersers 0Æ76 (0Æ51, 0Æ91) 0Æ71 (0Æ45, 0Æ88)%Movers among natal philopatrics 0Æ48 (0Æ27, 0Æ70) 0Æ41 (0Æ20, 0Æ66)

Estimates (95% confidence intervals) are from the preferredmodel 5 in Table 1.

LR, LaRonze is the largest colony in the system (seemethods).

Dispersal, familiarity and colony size 5

� 2009 TheAuthors. Journal compilation� 2009 British Ecological Society, Journal of Animal Ecology

with no obvious effect of colony size, being the smallest on

V5 and the largest on VE (Table 3). During a breeding dis-

persal event, gulls had a higher probability to resettle in their

site of birth than to move to an ‘unknown’ colony (i.e. differ-

ent from their previous breeding colony and from their col-

ony of birth; Table 4).

POST HOC L INEAR MODELS FOR SETTLEMENT

PROBABIL IT IES: EFFECTS OF DISTANCE AND COLONY

SIZES

Here we modelled the settlement probabilities estimated by

the CMR model (model 5 in Table 1), as presented in Fig. 1.

The term for the interaction between distance and colony size

was statistically non-significant (95% confidence interval

encompassed zero). Emigrants settled more often in a colony

close to their previous breeding site (distance effect ± SE:

)0Æ15 ± 0Æ010; Fig. 1a). This effect was additive to and thus

not confounded by the fact that settlers preferentially chose

large colonies (colony size effect ± SE: +0Æ21 ± 0Æ015;Fig. 1b).

Discussion

INDIV IDUAL HETEROGENEITY

There were clear differences between individuals in the pro-

pensity to disperse, as in, e.g. the study of Serrano et al.

(2001). Importantly, this result was obtained without exclud-

ing birds that were not seen on a given year or site.Moreover,

the tendency to disperse was maintained from the natal dis-

persal choice onwards (natal dispersal effect); we detected

this effect in spite of the noise on the data created by the fact

that the natal dispersal status was imprecisely defined (first

observation of a bird did not necessarily occur at its first

breeding attempt, hence on the site it first used to breed).

There are a number of hypotheses to explain such hetero-

geneity. First, we did not specifically account for gender dif-

ferences in the probability to change site because Black-

headed Gulls show little sexual dimorphism and courtship

behaviours were rarely observed during the chick-raising per-

iod when most of the re-sightings occurred. Yet gender is a

well-known cause of individual variation in the propensity to

disperse (Greenwood 1980). Second, the between-individual

variation in dispersal propensity might be due to heterogene-

ity in individual phenotypic quality and ⁄or the conditions

experienced during early life or previous reproduction

attempts (Switzer 1997; Clobert et al. 2009). Last, and per-

hapsmore speculatively, heterogeneity in dispersal behaviour

can result from genetically determined differences in ‘person-

alities’ or other behavioural syndromes, possibly resulting

from frequency-dependent selection (see, e.g. Cote & Clobert

2007; Clobert et al. 2009).

LONG-DISTANCE DISPERSAL

Our study, as most studies on dispersal in birds, focused on a

landscape scale (0–100 km) and therefore on what can be

called short-distance dispersal. Long-distance dispersal can

retrospectively be considered as rare because distance already

limits dispersal at the scale investigated here. Moreover,

long-distance dispersal is associated to permanent emigration

Table 3. Site fidelity: variation with class of individual heterogeneity and current breeding location

Colony LR MA VE V5

Colony size 3750 590 413 138

Fidelity of movers 0Æ27 (0Æ11, 0Æ52) 0Æ23 (0Æ07, 0Æ54) 0Æ74 (0Æ57, 0Æ86) 0Æ14 (0Æ04, 0Æ42)Fidelity of stayers 0Æ84 (0Æ63;0Æ95) 0Æ81 (0Æ60;0Æ93) 0Æ98 (0Æ93;0Æ99) 0Æ71 (0Æ40;0Æ90)

Estimates (95% confidence intervals) are from the preferredmodel 5 in Table 1. Colony size is the average number of pairs over the study

period.

MA, LesMarquants; VE, LaVerchere; V5, La Vallon 5.

Table 4. Settlement probabilities: variation with sites of departure and arrival, and effect of the memory of the site of birth

From\to LR MA V5 VE AE

N 3750 590 138 413 2306

LR 3750 0Æ03 (0Æ08) 0Æ01 (0Æ03) 0Æ02 (0Æ05) 0Æ94*MA 590 0Æ05 (0Æ24) 0Æ07 (0Æ22) 0Æ40 (0Æ74) 0Æ48*V5 138 0Æ03 (0Æ15) 0Æ07 (0Æ20) 0Æ13 (0Æ34) 0Æ78*VE 413 0Æ09 (0Æ59) 0Æ35 (0Æ86) 0Æ06 (0Æ26) 0Æ50*AE 2306 0Æ85 (0Æ98) 0Æ01 (0Æ12) 0Æ01 (0Æ10) 0Æ13*

Values are for individuals not born (born) in the site of settlement. LaRonze (LR), LesMarquants (MA), La Verchere (VE) and LaVallon 5

(V5) are the four study colonies and Alive Elsewhere (AE) is the unobservable state. Colony sizeN is the average number of pairs over the study

period.

*Probabilities that were computed as 1 – the other estimates on the same line (seeMaterials andmethods).

6 G. Peron et al.

� 2009TheAuthors. Journal compilation� 2009 British Ecological Society, Journal of Animal Ecology

and is well-known to bias the estimate of survival down-

wards. Yet, the survival estimate in our study is in the high

part of the range reported for the species (data not shown).

The scarcity of reports of Forez-ringed adults from colonies

outside the study area (only 20 records) also suggests the rare

occurrence of long-distance dispersal, although the low

recapture effort of ringed gulls outside of the Forez renders

this latter assertion speculative.

COSTS AND BENEFITS OF SHORT-DISTANCE DISPERSAL

Distance- and memory-effects as evidence for non-physi-

cal costs of dispersal

The memory effect implies that after a first dispersal event,

individuals keep trying to return to their site of birth. This

result strongly suggests that philopatry is the best strategy in

the study population. This is in line with the fact that breed-

ing dispersal is clearly constrained by distance. Therefore,

dispersal must have non-physical costs (physical costs being

unlikely in the considered species at the considered geograph-

ical scale).We suggest that dispersal in the Black-headedGull

is mainly constrained by the costs of settling in an unfamiliar

environment. Familiarity with the environment could allow

gulls to gain knowledge of local predators’ habits, or could

bring foraging benefits, such as efficient match of the forag-

ing strategy to the local resource phenology, and detailed

knowledge of the most productive areas. It could also allow

individuals to interact with already-known conspecifics,

thereby sparing time otherwise invested in establishing a hier-

archy with new neighbours (Eason & Hannon 1994). Alter-

natively, high site-fidelity could create or be promoted by kin

clusters in a colony (Bukacinski et al. 2000; Schjorring 2001;

van der Jeugd et al. 2002), thus enhancing the advantages of

cooperative behaviours such as social foraging (Brown &

Bomberger Brown 1996) and communal defence of the col-

ony (Allaine 1991). Such small-scale structure of the popula-

tion, however, remains to be observed.

Breeding dispersal as a mean to recruit in large colonies

after acquiring experience in smaller colonies?

Previous results have shown a later age at first reproduction

in the large LR colony than in small colonies, and a higher

rate of natal dispersal for individuals born in LR colony than

for individuals born in small colonies (Grosbois et al. 2003;

G. Peron, unpublished). Breeding in the large LR colony

therefore seems costly for young inexperienced individuals. It

is thus unlikely that LR offers more available places than

small colonies. On the contrary, recruiting in LR apparently

entails more competition than recruiting in small colonies.

These considerations are congruent with results from at least

another bird species in which dense colonies export first-time

breeders (Henaux et al. 2007). More generally, high levels of

intraspecific and ⁄or kin competition are known to trigger

natal dispersal in several species (e.g. Lena et al. 1998;Moore

et al. 2006).

Yet in our study, the way emigrants distributes themselves

into the available colonies supports the existence of a positive

effect of colony size on colony attractiveness (Fig. 1a). The

attraction for larger colonies could stem from direct benefits

of colony size (Brown & Bomberger Brown 1996) or indicate

that large colonies are situated in high-quality habitats (dis-

cussed in Forbes & Kaiser 1994). Whether this effect would

have beenmaintained if removing the largest LR colony from

the system remains unknown.

Set

tlem

ent p

roba

bilit

ies

2

1

0

–1

–2

–3

–4

2

1

0

–1

–2

–3

–4

5·0 6·0 7·0 8·0

Set

tlem

ent p

roba

bilit

ies

Number of pairs at destination(log-transformed)

5 10 15 20 25 30Distance between colonies (km)

(a)

(b)

Fig. 1. Relationship between settlement probabilities (the probability

for an emigrant from colonyA to settle in colony B) and (a) distances

between the colonies and (b) size of the colony of settlement (aver-

aged over years). Settlement probabilities are log-transformed and

corrected for the effect of colony size in (a) and distance in (b). There

are four study colonies, plus the state Alive Elsewhere (AE) corre-

sponding to non-monitored colonies. The measure of distance that

we used for state AE was the average distance over the colonies com-

posing it. Each symbol represents an independently estimated proba-

bility frommodel 5 in Table 1.

Dispersal, familiarity and colony size 7

� 2009 TheAuthors. Journal compilation� 2009 British Ecological Society, Journal of Animal Ecology

We suggest that breeding dispersal is a mean to settle in

better-choice colonies, whereas the initial, natal dispersal

event is directed towards the colonies that are easiest to

recruit in.

Departures from the ideal-free distribution

Natal dispersal seems to correspond to a ‘‘breed-while-queu-

ing’’ strategy. As weak competitors, first-time breeders are

indeed unlikely to reach breeding status early if queuing for

LR, and they disperse to more easily accessible colonies.

First-time breeders would thus follow an ideal-free distribu-

tion (Fretwell & Lucas 1970), the ‘resource’ being the breed-

ing success as a function of the level of competition and

individuals’ competitive ability. If experienced breeders,

which are supposedly better competitor than first-time breed-

ers, followed this distribution, they should consistently prefer

the larger LR colony, which offers both higher breeding pros-

pects and reliability G. Peron, unpublished, and in which, as

better competitors, they should have priority. As discussed in

the previous section, it is not the case, breeding dispersal

being shown to be constrained by the by distance- and mem-

ory-effects. Indeed, our study shows that experienced breed-

ers give preference to familiar places when dispersing. This

result implies that, contrary to the assumption of the ideal-

free distribution theory, information is not freely available

and that individuals rely on their personal experience of

potential breeding sites to make habitat choice decisions. A

role for public information use (Boulinier & Danchin 1997)

is, however, possible, considering that such public informa-

tion would only be collected in the colonies near the currently

used colony, thereby producing the observed distance-effect.

BLACK-HEADED GULLS: METAPOPULATION OR

META-COLONY?

Our study system comprises a limited set of available patches

(ponds where the gull colonies can settle), exhibits a non-neg-

ligible rate of exchange between patches, and to some extent

a dynamic of extinction ⁄ colonization (J.-D.L., P.-A.C., G.P.,

unpublished data). It is in that aspect analogous to a meta-

population. But, contrary to plants and mostly short-lived,

semelparous species that are usually illustrating works on

metapopulation ecology, as migratory birds Black-headed

Gulls are not believed to experience dispersal-induced mor-

tality or any other ‘physical’ cost of dispersal (but see Brown

et al. 2008 in a small passerine). Moreover, long-lived species

can capitalize on future as well as current breeding attempts

(Kokko& Johnstone 1999). They can therefore be selected to

expressmore complex behaviours, such as queuing (Ens et al.

1995) and keeping amemory of their site of birth when breed-

ing elsewhere (our study). Indeed, Black-headed Gulls often

use two to four sites during their lives (results not shown).

The term ‘meta-colony’ appears more adequate than meta-

population to describe this situation where ‘satellite colonies’

are used as temporary breeding locations by individuals wait-

ing to be competitive enough, just as the outskirts of large

colonies are used by inexperienced breeders in other systems

(Potts et al. 1980; Steiner &Gaston 2005). This mechanism is

relatively similar to the ‘buffer effect’ observed in the bird Li-

mosa limosa (Gill et al. 2001), in which low-quality sites are

used when the density on the best sites induces costs that are

higher than the costs of using poorer sites.

Acknowledgements

Thanks are due to all researchers, students and volunteers who con-

tributed to the field work. We are grateful to land owners who gave

access to their properties. We thank three reviewers for their insight-

ful comments on previous drafts of this article.

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Received 7May 2009; accepted 12October 2009

Handling Editor: JeanClobert

Supporting Information

Additional Supporting Information may be found in the online ver-

sion of this article.

Appendix S1. Distances (in km) between colonies where re-sightings

of ringed birds took place.

Appendix S2. Explicit groups for coding the effects of ‘Natal Dis-

persal’ and ‘Memory’ in e-surge.

Appendix S3. Matrix description of the multievent model with two-

class heterogeneity in site-fidelity.

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thanmissing files) should be addressed to the authors.

10 G. Peron et al.

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