ÉVOLUTION DES TACTIQUES ALTERNATIVES CHEZ L’OMBLE DE ...€¦ · Mes premiers remerciements vont spontanément à Julian Dodson, mon directeur, qui m’a offert en 1998 un projet

VÉRONIQUE THÉRIAULT

ÉVOLUTION DES TACTIQUES ALTERNATIVES CHEZ L’OMBLE DE FONTAINE

Patrons de reproduction, héritabilité et pêche sélective

Thèse présentée à la Faculté des études supérieures de l’Université Laval

dans le cadre du programme de doctorat en biologie pour l’obtention du grade de Philosophia Doctor (Ph.D.)

DÉPARTEMENT DE BIOLOGIE FACULTÉ DES SCIENCES

UNIVERSITÉ LAVAL QUÉBEC

OCTOBRE 2007 © Véronique Thériault, 2007

i

Résumé L’objectif principal de cette thèse était de déterminer les bases génétiques des tactiques

alternatives de vie chez l’omble de fontaine, Salvelinus fontinalis. L’anadromie, la

migration en eau salée et le retour vers l’eau douce pour la reproduction, ainsi que la

résidence, la réalisation du cycle de vie entièrement en eau douce, sont deux formes de vie

communes chez les salmonidés souvent retrouvées en sympatrie. Ces formes sont ici

considérées comme des tactiques alternatives au sein d’une stratégie conditionnelle et

étudiées sous le modèle de traits seuils. Tout d’abord, à l’aide de marqueurs moléculaires

et d’analyses d’assignation parentale, la reproduction entre les deux formes, assurée par les

mâles résidents, a été mise en évidence. De plus, le succès reproducteur individuel était lié

à la taille chez les femelles, mais pas chez les mâles, suggérant l’emploi d’une tactique de

reproduction furtive par ces derniers. Ensuite, des méthodes de reconstruction de groupes

d’individus apparentés couplées à un « modèle animal » ont permis d’estimer l’héritabilité

de la tactique (gamme variant entre 0.53 et 0.56) ainsi que la corrélation génétique entre la

taille et la tactique (-0.52 ou -0.61), suggérant une évolution conjointe de ces deux traits.

Finalement, à l’aide d’un modèle éco-génétique, les conséquences de la pêche sportive sur

l’évolution de l’anadromie et la résidence ont été évaluées. Après 100 ans de pression de

pêche, la norme de réaction de migration est déplacée, entrainant une diminution dans la

probabilité de migrer avec une augmentation de l’intensité de pêche. Ce changement est

accompagné par une augmentation dans l’âge à la migration. La proportion de poissons

adoptant la tactique anadrome diminue dans la population à mesure que l’intensité de pêche

augmente, tout comme le nombre absolu de poissons retrouvé en eau salée. Ces

changements se traduisent en de plus bas âges et tailles à maturité. Cette thèse contribue à

notre compréhension du déterminisme des phénotypes alternatifs et se distingue par sa

réalisation complète sous conditions naturelles. En mettant en lumière les bases génétiques

de l’anadromie et la résidence, ce travail suggère qu’une réponse évolutive est possible face

à des pressions de sélection, anthropiques ou naturelles, et une telle réponse est démontrée

grâce à une approche de modélisation innovatrice.

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Abstract The central objective of this thesis was to assess the genetic basis of alternative life-history

tactics in brook charr, Salvelinus fontinalis. Anadromy, defined as migration to sea before

returning to freshwater to spawn, and residency, the completion of the entire life-cycle in

freshwater, are two tactics commonly found in sympatry in salmonids. These two life-

history forms are considered here as alternative tactics within a conditional strategy and are

studied according to the threshold model of quantitative genetics. First, molecular markers

and parentage analysis revealed that reproduction frequently occurred between the two

forms, and was mediated by the resident males. Moreover, individual reproductive success

was linked to body size in females, but not in males, which suggest that smaller males

make use of the alternative sneaker reproductive tactic. Second, sib-reconstruction

methods coupled to an “animal model” allowed the estimation of a significant heritability

for the life-history tactic (between 0.53 and 0.56) and a significant genetic correlation

between body size and tactic (-0.52 and -0.61), suggesting a joint evolution of these two

traits. Finally, the evolutionary consequences of sportfishery on the evolution of anadromy

and residency were assessed with the use of an eco-genetic model. After a hundred years

of fishing-induced selection directed toward anadromous fish, the migration reaction norms

shifted, resulting in a decrease in the probability of migrating with increasing harvest rate.

This change was accompanied by a higher mean age at migration. The proportion of fish

adopting the anadromous tactic decreased in the population as harvest rate increased, as did

the absolute number of fish found in saltwater. These changes resulted in a lower mean age

and size at maturity. This thesis contributes to our understanding of the determinism of

alternative phenotypes and stands out because of its realization under completely natural

conditions. By highlighting the genetic basis of anadromy and residency, this work

suggests that an evolutionary response is expected in face of anthropogenic or natural

selective forces, and such consequences are presented through an innovative modeling

approach.

Avant-propos

« Ce n'est point dans l'objet que réside le sens des choses, mais dans la démarche.»

Antoine de Saint-Exupéry

Remerciements

Ah! L’avant-propos! Quand on est rendu là ça veut dire que la fin est là, pour vrai. À en

croire Saint-Exupéry, ma longue démarche n’aura pas été vaine, et m’aura permis à tout le

moins de trouver un certain sens.

Mes premiers remerciements vont spontanément à Julian Dodson, mon directeur, qui m’a

offert en 1998 un projet de maîtrise sur l’omble de fontaine. Après presque une décennie

de collaboration, je ne peux qu’admirer et louanger toute la liberté qu’il nous donne, à

nous, ses étudiants. J’ai apprécié le scientifique et le chercheur, qui, par son intérêt, ses

conseils et ses encouragements m’ont permis d’avancer. J’ai aussi apprécié l’homme, qui

est d’une grande générosité et sensibilité.

Louis Bernatchez, mon co-directeur, me surprendra toujours par sa capacité de garder le fil.

Sans préambule, il arrivait à « sauter » dans mes résultats, à y relever les forces et les

faiblesses et à soulever d’importantes questions. Son aide me fut inestimable et ses

réflexions et commentaires ont sans contredit enrichi cette thèse. Merci!

Merci aussi à Helga Guderley et Steeve Côté d’avoir suivi mes travaux tout au long de ces

années en tant que membres de mon comité d’encadrement. Un merci particulier à Helga,

qui a accepté, même en sabbatique à l’autre bout du monde, d’être examinatrice de ma

thèse. Ce sont des femmes comme elle qui me donnent le goût de continuer en sciences.

J’ai côtoyé des gens dans mes « deux » labos durant ces années qui ont aidé mes réflexions,

qui sont devenus de bons amis et/ou qui m’ont tout simplement permis de passer du bon

temps : Stéphane Plourde, Nadia Aubin-Horth, Dany Garant, Christian Landry, Fred

Lecomte, Jeff Bourque, Robert St-Laurent, Vincent Castric, Dylan Fraser, Sean Rogers,

iv Guy Perry, Vincent Bourret, Jonatan Blais, Lucie Papillon, Simon Blanchet, David Paez,

Gesche Winkler, Pierre-Philippe Dupont, Marc Ringuette.

J’ai passé les 4 dernières années de ma vie entourée de 6 filles : Dju, Chunky, Chât, Caro,

Isa, Cath, les filles de mon équipe de canot à glace. Sans elles la vie aurait été un peu plus

difficile, et surtout, beaucoup plus ennuyante! Elles m’ont apporté un brin d’équilibre dans

cette longue démarche doctorale, et m’ont fait plus souvent qu’autrement sombrer dans le

vice! Merci pour ces moments de pur délire, et même si vous avez significativement ralenti

la progression de mes travaux (!), je ne vous en tiens pas rigueur et je ferais exactement la

même chose si c’était à recommencer. Je vous adore!

Merci à mon père, Jos, et ma mère, Jacqueline, pour leur admiration et leur support

inconditionnel. Merci à ma sœur et grande amie, Annie-Claude, complice de mes

réflexions scientifiques et existentielles. Manu, ma cousine, toujours là pour me

dévergonder, pourra enfin m’appeler à juste titre « doc virus ». Un clin d’œil à Yan, qui a

fait preuve de compréhension et de patience sans égal durant les 3 derniers mois de ma

rédaction. Je souhaite à chacun d’avoir quelqu’un d’aussi apaisant dans sa vie.

Le CIRSA (Centre Interuniversitaire de Recherche sur le Saumon Atlantique) a changé ma

vie. J’ai passé près de 6 saisons de terrain aux abords de la rivière Sainte-Marguerite au

Saguenay, et je m’y suis sentie tout de suite chez-moi. Plus que des collègues, assistants et

techniciens, j’y ai rencontré des personnes formidables qui ont fait de ce séjour une

expérience humaine inoubliable. Dans le désordre : Albertine Gauthier, André Boivin,

Geneviève Morinville, François Martin, Annie Ménard, Christian Langlois, Mélanie

Carrier, Olivier Higgins, Jean-Guillaume Marquis, Mylène Levasseur, Louis Vincent St-

Hilaire Gravel. Certaines continuent d’agrémenter ma vie, d’autres ne sont plus que

souvenir. Mais elles font toutes désormais partie de ma mémoire, et ont contribué chacune

à leur façon à la personne que je suis aujourd’hui.

v Organisation de la thèse Les chapitres 2, 3 et 4, qui constituent le corps de la thèse, sont présentés sous un format

approprié pour publication scientifique. Mon directeur de thèse, Julian Dodson, ainsi que

mon co-directeur, Louis Bernatchez, sont co-auteurs pour chacun des chapitres publiés et

soumis car ils ont contribué de façon substantielle à l’élaboration et au raffinement de

chacun de ces chapitres par d’innombrables commentaires et suggestions.

Le chapitre 2 est publié sous la référence : Thériault V., Bernatchez L. et Dodson J.J. 2007.

Mating system and individual reproductive success of sympatric anadromous and resident

brook charr, Salvelinus fontinalis, under natural conditions, Behavioural Ecology and

Sociobiology, doi:10.1007/s00265-007-0437-8.

Le chapitre 3 est publié sous la référence: Thériault V., Garant D., Bernatchez L. et Dodson

J.J. 2007. Heritability of life-history tactics and genetic correlation with body size in a

natural population of brook charr (Salvelinus fontinalis). Journal of Evolutionary Biology,

doi:10.1111/j.1420-9101.2007.01417.x.

Le co-auteur Dany Garant (Université de Sherbrooke, Département de biologie, 2500 boul.

de l’Université, Sherbrooke, Qc, J1K 2R1) a contribué à l’analyse statistique et à l’écriture

de ce chapitre par ses commentaires et suggestions.

Le chapitre 4 est soumis à la revue Evolutionary Applications comme contribution pour un

numéro spécial portant sur l’évolution des salmonidés qui sera publié en 2008 : Thériault

V., Dunlop E., Dieckmann U., Bernatchez L. et Dodson J.J. The impact of fishing-induced

mortality on the evolution of alternative life-history tactics in brook charr.

La co-auteure Erin Dunlop (Institute of Marine Research, P. O. Box 1870 Nordnes, N-5817

Bergen, Norway) a développé et adapté le modèle utilisé dans ce chapitre et a contribué

grandement à sa qualité par ses commentaires et suggestions. Le co-auteur Ulf Dieckmann

(International Institute for Applied Systems Analysis, Schlossplatz 1, 2361 Laxenburg,

Austria) a aussi fournit des commentaires lors de la rédaction.

À Louis Vincent 1978-2003

Table des matières Résumé....................................................................................................................................i

Abstract................................................................................................................................. ii

Avant-propos....................................................................................................................... iii

Table des matières ............................................................................................................. vii

Liste des tableaux..................................................................................................................x

Liste des figures.................................................................................................................. xii

Chapitre 1. Introduction générale.......................................................................................1

1.1 Diversité et plasticité : les phénotypes alternatifs.........................................................1 1.1.1 Phénotypes alternatifs comme exemple extrême de plasticité...............................1 1.1.2 Phénotypes alternatifs comme traits seuils ............................................................3

1.2 La migration et la résidence chez les salmonidés .........................................................5 1.3 Héritabilité : son estimation en milieu naturel..............................................................8

1.3.1 Milieu contrôlé versus milieu naturel ....................................................................8 1.3.2 Les marqueurs moléculaires comme outils............................................................9 1.3.3 Les erreurs de génotypage et leurs effets.............................................................12

1.4 Mortalité sélective : effet de la pêche .........................................................................13 1.4.1 Réponse plastique vs. évolutive...........................................................................13 1.4.2 La norme de réaction probabiliste .......................................................................15 1.4.3 Une approche de modélisation.............................................................................18

1.5 Le cas de l’omble de fontaine au Québec, Salvelinus fontinalis ................................19 1.6 Objectifs et contributions............................................................................................22

Chapitre 2. Mating system and individual reproductive success of sympatric

anadromous and resident brook charr, Salvelinus fontinalis, under natural conditions

..............................................................................................................................................25

2.1 Résumé........................................................................................................................26 2.2 Abstract.......................................................................................................................27 2.3 Introduction.................................................................................................................28 2.4 Material and Methods .................................................................................................31

2.4.1 Study site and brook charr reproductive behavior ...............................................31 2.4.2 Sampling ..............................................................................................................31 2.4.3 Microsatellite polymorphism analyses ................................................................33 2.4.4 Statistical analyses ...............................................................................................33

2.5 Results.........................................................................................................................36 2.5.1 Characteristics of fish sampled ............................................................................36 2.5.2 Standard genetic statistics ....................................................................................37 2.5.3 Population genetic structure.................................................................................37 2.5.4 Parentage analysis................................................................................................38 2.5.5 Mating patterns ....................................................................................................39 2.5.6 Individual reproductive success...........................................................................39

viii

2.6 Discussion...................................................................................................................40 2.6.1 Gene flow and mating patterns ............................................................................40 2.6.2 Reproductive success...........................................................................................42 2.6.3 Where have all the parents gone? ........................................................................43 2.6.4 Conclusion ...........................................................................................................44

2.7 Acknowledgments ......................................................................................................46 2.8 Tables..........................................................................................................................47 2.9 Figures ........................................................................................................................53

Chapitre 3. Heritability of life-history tactics and genetic correlation with body size in

a natural population of brook charr (Salvelinus fontinalis)............................................58


3.4.1 Study Site and Sampling......................................................................................64 3.4.2 Pedigree reconstruction........................................................................................65 3.4.3 Quantitative genetic analyses...............................................................................66 3.4.4 Power and sensitivity analysis .............................................................................68

3.5 Results.........................................................................................................................70 3.5.1 Pedigree reconstruction........................................................................................70 3.5.2 Heritability and genetic correlations....................................................................71

3.6 Discussion...................................................................................................................72 3.7 Acknowledgments ......................................................................................................79 3.8 Tables..........................................................................................................................80 3.9 Figures ........................................................................................................................85

Chapitre 4. The impact of fishing-induced mortality on the evolution of alternative

life-history tactics in brook charr......................................................................................87


4.4.1 Migration .............................................................................................................94 4.4.2 Somatic growth ....................................................................................................94 4.4.3 Maturation............................................................................................................95 4.4.4 Reproduction........................................................................................................95 4.4.5 Inheritance and expression...................................................................................96 4.4.6 Natural mortality..................................................................................................97 4.4.7 Fishing-induced mortality....................................................................................97 4.4.8 Initial population structure and parameterization ................................................98

4.5 Results.........................................................................................................................99 4.5.1 Impact of different exploitation rates over 100 years ..........................................99 4.5.2 Impact of different natural mortality rates .........................................................100

ix

4.6 Discussion.................................................................................................................100 4.7 Acknowledgments ....................................................................................................104 4.8 Table .........................................................................................................................105 4.9 Figures ......................................................................................................................107 4.10 Supplemental material ............................................................................................111

4.10.1 Heritability through time .................................................................................111 4.10.2 Comparison of results with growth included as an evolving trait ...................112 4.10.3 The effect of density-dependent growth ..........................................................114

Chapitre 5. Conclusion générale......................................................................................116

5.1 Rappel des principaux résultats ................................................................................116 5.2 Contributions ............................................................................................................118 5.3 La valeur et la signification de l’héritabilité .............................................................119 5.4 Pour ou contre les réponses évolutives ? ..................................................................120 5.5 La perte ou la cachette de l’anadromie? ...................................................................121 5.6 Perspectives ..............................................................................................................125

Bibliographie .....................................................................................................................129

Liste des tableaux Chapitre 2. Mating system and individual reproductive sucess of sympatric


Table 2-1. PCR conditions for the 13 loci amplified. ...........................................................47 Table 2-2. Number of samples (N), number of alleles (A), FIS, observed (HO) and expected

(HE) heterozygosities, and probabilities of conforming to Hardy-Weinberg equilibrium (P(HW), score U test) for each locus and each temporal sample (RES = resident, ANA = anadromous) separately. Bold values are significant at ∝ = 0.0096 following Bonferroni corrections. .................................................................................................48

Table 2-3. Genetic differentiation between anadromous and resident brook charr estimated by θST for each locus. N = 32 anadromous and 98 resident fish in 2000; N = 15 anadromous and 323 resident fish in 2001. ** P < 0.001 following 2,000 permutations with alpha adjusted for multiple testing using Bonferroni correction (∝ = 0.0038 for single-locus comparisons and ∝= 0.0125 for multilocus comparisons). ......................51

Table 2-4. Number of samples (N), mean, variance, and range of individual reproductive success (RS - number of offspring assigned to individuals) for males and females together (overall) and separately according to life-history form. Means and variances of life-history forms are compared with ANOVA and Levene's test respectively. ......52


a natural population of brook charr (Salvelinus fontinalis)

Table 3-1. Number of alleles (N), observed (Ho) and expected (He) heterozygosity at each locus. * indicates significant departure from Hardy-Weinberg equilibrium. SfoB52, SfoC113, SfoC129, SfoC28, SfoC88, SfoC115, SfoD100, SfoD75, T. L. King, US Geological Survey, unpublished; SCO204, SCO216, SCO218 from DeHaan & Ardren (2005); Sfo262Lav, Sfo266Lav from Perry et al. (2005b). ...........................................80

Table 3-2. Sample size (N), trait means with their standard deviation (SD), estimates of residual (VR), additive (VA) and phenotypic (VP) variance components and heritability (h2) with their standard error (SE) for life-history tactic (anadromy/residency: Tactic), body size (fork length: FL) and six morphological traits (body depth: DEP, maximum body width: WID, peduncle depth: PED, caudal fin height: CAUD, pectoral fin length: PECT and pelvic fin length: PELV, all transformed following PCA, see methods) in brook charr. Pedigree 1 is the best one obtained with a weight of 1, Pedigree 2 is the best one obtained with a weight of 5, and Pedigree 3 is the same as Pedigree 1, but where half-sib relationships were added (see methods). h2 of the life-history tactic is given transformed to the liability scale (see methods). P-values are those obtained from likelihood ratio tests to assess the significance of the additive genetic component.......................................................................................................................................81

Table 3-3. Power analysis for a range of simulated heritabilities (h2) for a continuous and a binomial trait. The mean heritability estimate and the mean standard error of 20 simulations are presented. Simulations were ran in order to mimic the actual data.

xi

Heritabilities estimated with a sample size of 349 individuals refer to body size and tactic, while a sample size of 215 relates to morphological traits. The heritability of tactic is given transformed to the liability scale for comparison purposes (see methods). Power is assessed by dividing the number of simulations that gave a significant additive variance estimate over a total number of 20 simulations..............82

Table 3-4. Genetic correlations with their standard errors between life-history tactic (anadromy/residency) and body size (FL) and the six morphological traits for the 3 pedigrees used (as in Table 2). Life-history tactic was coded as 0 for anadromous and 1 for resident. P-values are those obtained from likelihood ratio tests to assess the significance of the covariance genetic component. ......................................................83

Table 3-5 Mean heritability (h2) and genetic correlation (rG) estimates as well as mean standard error (SE) obtained over 20 simulations using a full-sib pedigree along with simulated phenotype data from a half-sib pedigree. Phenotype data were simulated according to h2 and rG similar to those estimated in the present study.........................84


life-history tactics in brook charr

Table 4-1. Model parameters and their values...................................................................105

Liste des figures Chapitre 1. Introduction générale

Figure 1-1. Illustration schématique du modèle de trait seuil. Le graphique du haut représente le cas simple à un locus, où la valeur du trait sous-jacent est déterminée par l’action additive de 2 allèles à un locus. Les barres indiquent la valeur de ce trait sous-jacent (et non sa fréquence dans la population). Les génotypes AA et Aa ont des valeurs qui excèdent le seuil, et se traduisent par la forme 2. Le génotype aa est quant à lui associé à la forme 1. Le graphique du bas représente le modèle polygénique, où plusieurs locus agissent de façon additive pour déterminer la valeur du trait sous-jacent, qui est distribué normalement dans la population. Les parties hachurées et non-hachurées représentent la fréquence dans la population. Les individus qui ont des valeurs de traits sous-jacents qui dépassent le seuil adoptent la forme 2, alors que les autres adoptent la forme 1. D’après Roff 1996. ..............................................................4

Figure 1-2. Interprétation de la norme de réaction pour la taille et l’âge à maturité. Les individus à croissance plus rapide (trajectoire de croissance avec une pente plus élevée) deviennent matures à un âge plus jeune. Plus la croissance est lente (trajectoires de croissance où les pentes sont moins élevées), plus l’âge à maturité augmente. La norme de réaction est définie par la ligne qui joint la taille à maturité à chaque âge. L’interprétation de cette courbe en tant que norme de réaction est basée sur la supposition que les différences dans les taux de croissance sont en grande partie dues aux différences dans les conditions environnementales. D’après Heino et al. 2002. .............................................................................................................................16

Figure 1-3. Distribution de taille à l’âge de 1 an pour les individus résidents (barres noires) et migrants (barres blanches). Parmi les résidents se retrouvent les individus qui migreront à 2 ans et qui sont les plus petits de leur cohorte à l’âge de 1 an (ligne noire). D’après Thériault et Dodson (2003). ................................................................21

Chapitre 2. Mating system and individual reproductive sucess of sympatric


Figure 2-1. Location of study area, sampling traps, and electrofishing sites. .....................53 Figure 2-2. Rate of juvenile allocation obtained with PASOS as a function of cumulative

number of loci, and using a maximum offset tolerance set to zero (MOT 0 – see text). A plateau is starting to appear at the end of the cumulative curve and the 20% rate attained at SfoC88 was used as a first estimate of the proportion of sampled spawners.......................................................................................................................................54

Figure 2-3. (a) Number of fish caught in the upstream migration trap in 2000 (black) and 2001 (grey) and (b) corresponding length distribution.................................................55

Figure 2-4. Reproductive success (number of offspring assigned per individual) (a) and number of mates (b), as a function of body size for female spawners. Open circles are resident life-history fish, while closed circles are anadromous life-history fish. .........56

xiii Figure 2-5. Reproductive success (number of offspring assigned per individual) as a

function of body size for male spawners. Open circles are resident life-history fish, while closed circles anadromous life-history fish. .......................................................57


a natural population of brook charr (Salvelinus fontinalis)

Figure 3-1. Distribution of family size for Pedigree 1 and 3 (black bars) and Pedigree 2 (white bars). These families are those that were kept in the final analyses, i.e. the ones that were deemed significant by the randomization procedures (see methods). ..........85


life-history tactics in brook charr

Figure 4-1. Schematic of the life-cycle of brook charr showing the sequence of events in the eco-genetic model. ......................................................................................................107

Figure 4-2. Empirically derived functions used in the model. (a) Probabilistic migration reaction norms estimated for Morin creek (reproduced from Thériault and Dodson 2003); (b) Probabilistic maturation reaction norms estimated for anadromous and resident individuals showing the 50% (midpoint) 1% and 99% probability curves; (c) Relationship between fecundity and body size for anadromous (open circles) and resident individuals (closed circles) reproduced from Lenormand (2003); (d) Stock-recruitment relationship derived from Elliott (1993); (e) Harvest probabilities curves according to different maximal harvest probabilities increasing from 0.05 to 1 in increments of 0.05.......................................................................................................108

Figure 4-3. Model results after 100 years of fishing-induced mortality, according to different maximum harvest probabilities. The top two panels show the age-specific migration reaction norms (line thickness increases with increasing maximum harvest probabilities between 0 and 1). Results are averaged for 30 independent model runs.....................................................................................................................................109

Figure 4-4. Model results after 100 years of fishing-induced mortality, according to varying survival conditions in freshwater (poor, normal and good, see methods). The maximum harvest probability was 0.5. Results are averaged for 30 independent model runs..............................................................................................................................110

Chapitre 5. Conclusion générale

Figure 5-1. Représentation schématique de l’anadromie et la résidence en tant que trait seuil. (a) Un individu adopte la tactique qui lui procure le plus haut fitness selon la valeur du trait sous-jacent. L’intersection des fonctions de fitness représente le seuil, et la position de celui-ci changera si les fonctions de fitness se déplacent, influençant directement les proportions de chaque morphe dans la population (zone noire pour Anadrome, grise pour Résidents). Les cas où seule la tactique R est exprimée sont présentés en b, c et d. (b) Les conditions présentes (zone grise) font en sorte que le seuil est toujours dépassé. Les différents seuils représentent la variabilité génétique

xiv

individuelle. (c) Les seuils sont déplacés sous l’effet de la sélection. (d) Assimilation génétique, menant à la canalisation du trait, où seule la résidence peut être exprimée, peu importe la valeur du trait sous-jacent. ..................................................................124

Chapitre 1. Introduction générale « Évolution inéluctable qui, parallèlement à ce grand

courant partant du singe pour aboutir à l'homme, part de l'homme pour aboutir à l'imbécile.»

Boris Vian

1.1 Diversité et plasticité : les phénotypes alternatifs Le monde vivant nous fascine de par sa diversité. Que ce soit à une échelle temporelle ou

spatiale, au niveau phénotypique ou génétique, entre les espèces ou à l’intérieur même

d’une population, elle est partout. Des dizaines d’espèces présentes dans un mètre carré de

la forêt amazonienne aux différentes grosseurs de becs chez les pinsons des îles Galápagos

en passant par la variété de couleurs de cichlidés du Lac Victoria, les biologistes n’ont

cessé de s’intéresser à la genèse et la dynamique de la diversité du vivant. Outre une

fascination pour le monde vivant en tant que tel, cet intérêt soutenu pour la biodiversité

découle de Darwin lui-même. Selon la théorie darwinienne de l’évolution, la diversité est à

la base de la sélection naturelle, elle est une condition préalable à son action. La sélection

serait définie en ce sens comme la survie et la reproduction différentielles (i.e. fitness

différent) liées à des différences phénotypiques entre des individus appartenant à une même

entité reproductrice (West-Eberhard 2003). Lorsque ces différences phénotypiques sont

causées par des différences génétiques héritables (additives), transmises de génération en

génération, une réponse à la sélection est attendue, et nous parlons alors d’évolution. Il

n’est donc pas étonnant de voir la biodiversité en premier plan de l’écologie évolutive et

des stratégies de conservation : en la conservant, on s’assure du potentiel évolutif des

espèces, de leur capacité d’adaptation à des changements environnementaux, qu’ils soient

causés ou accélérés de façon anthropique ou naturelle.

1.1.1 Phénotypes alternatifs comme exemple extrême de plasticité Un cas frappant de diversité est la présence de plusieurs formes, ou morphes, au sein d’une

même population, d’où l’appellation « polymorphisme » (ou « polyphenisme », dépendant

des auteurs). Les exemples sont nombreux et couvrent toutes les facettes de l’histoire de

vie : induction ou non de défenses contre un prédateur, utilisation de niches trophiques

différentes, morphologies variées, couleurs différentes, tactiques reproductrices

2 alternatives, migration saisonnière ou résidence, etc. (Roff 1996). Devant tant de diversité,

nous ne pouvons nous empêcher de nous questionner : pourquoi et comment ces formes se

sont-elle créées, quels sont les mécanismes qui les sous-tendent et les maintiennent, que

représentent-elles dans le cours de l’évolution? Ces différents phénotypes sont-ils le

résultat de différents génotypes, le résultat d’influences environnementales différentes, ou

bien une combinaison des deux?

Quelques exemples de polymorphismes génétiques ont été démontrés, où les formes

alternatives seraient caractérisées par un système impliquant un seul locus et deux ou

plusieurs allèles (isopodes, Shuster et Wade 1991; poecilidés, Zimmerer et Kallman 1989;

oiseaux, Lank et al. 1995). Par contre, la plupart des cas de phénotypes alternatifs seraient

en fait le résultat d’une plasticité phénotypique plutôt que d’un déterminisme purement

génétique. La plasticité est cette capacité qu’a un organisme à répondre à des changements

dans l’environnement en altérant sa forme, son état, ses mouvements ou son taux d’activité

(West-Eberhard 2003). Dans le cas des phénotypes alternatifs, cette plasticité serait

adaptative, c’est-à-dire que le phénotype exprimé dans un environnement donné permet de

maximiser le fitness de l’individu dans les conditions où il est exprimé, mais pas dans les

autres situations. Les notions d’hétérogénéité de l’environnement et de compromis sont

centrales à l’origine de la plasticité phénotypique (Moran 1992; Hazel et al. 2004). Des

environnements variables spatialement et/ou temporellement qui provoquent un

renversement des fitness relatifs des phénotypes alternatifs est un prérequis pour l’évolution

de la plasticité adaptative (Moran 1992). Un polymorphisme est favorisé lorsque qu’un seul

phénotype n’est pas « le meilleur » dans tous les environnements. Des compromis sont

donc présents, et ce phénomène est bien illustré dans les cas des polymorphismes de

défense contre les prédateurs : les coûts associés à la production de structures de défenses

(i.e. diminution de croissance) sont contrebalancés par une meilleure survie dans un

environnement où les prédateurs sont présents, mais en absence de prédateurs, les individus

ayant développé ces défenses seraient défavorisés comme ils n’obtiennent plus assez

d’avantages en survie pour pallier leur faible croissance (Roff 1996). L’avantage de la

plasticité réside dans la capacité de produire un meilleur couplage phénotype-

3 environnement à travers plus de conditions différentes qu’il ne serait possible de le faire

avec un seul phénotype dans tous les environnements (DeWitt et al. 1998).

Qui dit plasticité ne dit pas nécessairement influence génétique nulle. Un individu pourrait

avoir une tendance, une « prédisposition » génétique pour l’adoption d’un phénotype plutôt

que de son alternative. Les conditions environnementales viendraient alors ultimement

décider. Un contexte théorique applicable (et appliqué! voir Hazel et al. 1990; Gross 1996;

Roff 1996; Hazel et al. 2004) pour comprendre et étudier les phénotypes alternatifs, dans

lequel l’influence conjointe de l’environnement et de la génétique est prise en compte, est

celui du modèle de traits seuils (threshold trait model of quantitative genetics, aussi

équivalent à la stratégie conditionnelle sensus Gross 1996).

1.1.2 Phénotypes alternatifs comme traits seuils Les traits quantitatifs sont des traits que l’on peut mesurer, qui varient d’une façon

continue, comme la croissance, et qui sont influencés par plusieurs gènes ayant chacun de

petits effets. Les traits qui montrent une variation discontinue seraient aussi dans la plupart

des cas des traits quantitatifs, déterminés par l’effet additif de plusieurs locus (Roff 1994a).

Pour comprendre l’expression et la transmission de ces caractères d’une génération à

l’autre, on fait appel au modèle de traits seuils (Roff 1996). Ce modèle suppose l’existence

d’un caractère continu (ou d’un ensemble de caractères) sous-jacent au trait discontinu, où

un seuil est présent (Falconer et Mackay 1996; Hazel et al. 2004). Lorsque le caractère

sous-jacent est en dessous d’un certain seuil, l’individu développe le phénotype A, tandis

qu’il développe le B si le seuil est dépassé (Figure 1-1). L’appellation stratégie

conditionnelle est souvent employée et fait référence au fait que le phénotype adopté ne soit

pas fixé et ne dépende pas que du génotype : le phénotype est conditionnel à

l’environnement dans lequel l’individu se développe (Gross 1996).

Ce contexte théorique de traits seuils a été appliqué à divers organismes, notamment les

insectes où la littérature abonde (coléoptère, Emlen 1996; cricket Roff et al. 1999), mais

aussi les poissons (saumon, Gross 1996; Hazel et al. 2004; Hutchings et Myers 1994) et les

4 invertébrés (escargot, Ostrowski et al. 2000; limule, Brockmann 2001), de même que les

oiseaux (Berthold 1991). L’influence environnementale sur l’adoption d’un phénotype

alternatif a été mise en évidence de façon convaincante à l’aide d’études en milieu contrôlé.

Roff (1996) dresse d’ailleurs un tableau assez complet où des variations dans les conditions

Figure 1-1. Illustration schématique du modèle de trait seuil. Le graphique du haut représente le cas simple à un locus, où la valeur du trait sous-jacent est déterminée par l’action additive de 2 allèles à un locus. Les barres indiquent la valeur de ce trait sous-jacent (et non sa fréquence dans la population). Les génotypes AA et Aa ont des valeurs qui excèdent le seuil, et se traduisent par la forme 2. Le génotype aa est quant à lui associé à la forme 1. Le graphique du bas représente le modèle polygénique, où plusieurs locus agissent de façon additive pour déterminer la valeur du trait sous-jacent, qui est distribué normalement dans la population. Les parties hachurées et non-hachurées représentent la fréquence dans la population. Les individus qui ont des valeurs de traits sous-jacents qui dépassent le seuil adoptent la forme 2, alors que les autres adoptent la forme 1. D’après Roff 1996.

biotiques ou abiotiques telles la densité des conspécifiques, la présence de prédateurs, les

substances sécrétées, la qualité et quantité de nourriture, la photopériode ou la température

sont autant de facteurs qui peuvent induire l’adoption d’une forme ou l’autre. L’influence

génétique a aussi été démontrée à deux niveaux. Tout d’abord, une héritabilité

5 significative (i.e. la variance phénotypique observée dépend de la variance génétique

additive héritée des parents) a été trouvée à plusieurs reprises pour des traits sous-jacents,

soit 1) en estimant directement l’héritabilité des traits sous-jacents spécifiques soupçonnés,

par exemple la croissance (Garant et al. 2003) ou 2) en estimant l’héritabilité du trait

binomial lui-même, et en normalisant cet estimé pour le ramener sur l’échelle continue

sous-jacente (Ostrowski et al. 2000, voir aussi revue par Roff 1996, pour la transformation

discontinue-continue, se référer à Roff et al. 1997). Deuxièmement, il est aussi postulé que

l’influence génétique résiderait dans la valeur seuil, celle-ci étant génétiquement influencée

et héritable (Hazel et al. 1990; Hutchings et Myers 1994; Hazel et al. 2004; Aubin-Horth et

al. 2005). Cette variation génétique dans la valeur seuil a été mise en évidence chez les

insectes (Emlen 1996; Moczek et Nijhout 2003; Tomkins et Brown 2004).

La question du maintien des tactiques alternatives au sein d’une même population revient

souvent. Contrairement au polymorphisme déterminé génétiquement, les fitness des

tactiques alternatives déterminées par un mode de régulation conditionnel n’ont pas besoin

d’être égaux pour que les deux options se maintiennent dans la population (Gross 1996).

L’élément essentiel est qu’un seul phénotype ne doit pas être toujours avantagé. La

tactique A peut avoir un meilleur fitness, mais seulement dans certaines circonstances: dans

d’autres circonstances, c’est la tactique B qui fait mieux. Tant et aussi longtemps que les

circonstances qui favorisent B reviennent, et que les coûts associés au changement de

phénotype et à l’évaluation des signaux environnementaux qui induisent l’adoption de ce

phénotype ne sont pas trop élevés, la capacité de produire le phénotype B peut être

maintenue (Moran 1992; West-Eberhard 2003).

1.2 La migration et la résidence chez les salmonidés L’anadromie, soit la migration en eau salée et le retour vers l’eau douce pour la

reproduction, est un phénomène commun chez plusieurs espèces de poissons des latitudes

élevées. Pour qu’un comportement migrateur voit le jour, il faut que les bénéfices encourus

à utiliser un second habitat (augmentation des ressources alimentaires, évitement des

conditions environnementales défavorables, augmentation du succès reproducteur), moins

6 les coûts associés au mouvement vers un autre habitat (coût énergétique, augmentation de

la prédation, coût développemental des adaptations requises), surpassent les bénéfices à

n’utiliser qu’un seul habitat (Gross 1987). Deux hypothèses peuvent expliquer l’évolution

de l’anadromie, toutes deux visant ultimement à l’augmentation du fitness. Tout d’abord,

l’anadromie pourrait avoir évolué en vue de l’exploitation de l’eau douce pour la

reproduction, ce dernier habitat procurant de meilleures conditions de survie pour les

jeunes stades de vie (Dodson 1997). Cette hypothèse s’applique à des espèces

ancestralement marines, tells certains membres de la famille des Clupeidae (aloses),

Gadidae (poulamons, lottes), Percichthydae (bars) et Gasterosteidae (épinoches), où les

gamètes sont dispersés et non confinés dans des nids (sauf épinoches, McDowall 1993).

L’anadromie pourrait par contre aussi être adoptée en vue d’une augmentation de la

croissance des stades adultes. Cette hypothèse repose sur l’augmentation des ressources en

eau salée comparativement à celles en eau douce. Une telle augmentation est généralement

observée dans les régions froides et tempérées (Gross 1987). Pour des poissons tels les

salmonidés, où le stade ancestral pourrait être la résidence en eaux douces (voir discussion

par McDowall 2002 qui stipule que l’ancêtre des salmonidés était déjà diadrome) et où le

succès reproducteur dépend beaucoup de la taille tant pour l’accès aux partenaires que pour

la fécondité, l’augmentation de la taille par l’exploitation de l’eau salée serait l’avantage

principal de l’anadromie (Dodson 1997).

Plusieurs espèces de salmonidés comportent à la fois des individus anadromes et des

individus non-anadromes (résidents), cer derniers passant leur vie entière en eau douce

(l’omble de fontaine Salvelinus fontinalis, Castonguay et Fitzgerald 1982, Doyon et al.

1991; l’omble chevalier Salvelinus alpinus, Nordeng 1983, Svenning et al. 1992,

Kristoffersen et al. 1994, Rikardsen et al. 1997; la truite arc-en-ciel Oncorhynchus mykiss,

Pascual et al. 2001; la truite brune Salmo trutta; le saumon sockeye Oncorhynchus nerka,

Jonsson, 1985 et le grand corégone Coregonus clupeaformis, Lambert et Dodson 1990).

Dans certains cas, ces deux formes constituent deux populations distinctes, avec peu

d’échanges génétiques (Foote et al. 1989; Wood et Foote 1990; Wood et Foote 1996).

Dans d’autres, les deux phénotypes font partie de la même population (Hindar et al. 1991;

7 Northcote 1992). Dans ce dernier cas, un mode conditionnel de régulation est alors

l’hypothèse avancée pour expliquer la coexistence de ces deux formes. D’ailleurs, les

phénotypes alternatifs liés à la reproduction (précocité sexuelle versus anadromie) ont déjà

été modélisés dans le passé comme traits seuils (Myers et Hutchings 1986; Hazel et al.

1990; Hutchings et Myers 1994).

La plasticité dans l’adoption de l’anadromie et la résidence a été mise en évidence par

plusieurs études expérimentales qui démontrent que le phénotype adopté change selon les

conditions environnementales, notamment celles qui affectent le taux de croissance

(Saunders et al. 1982; Nordeng 1983; Rowe et Thorpe 1990; Olsson et al. 2006). Aussi,

des différences ont été trouvées dans la quantité de réserves lipidiques, l’efficacité de

croissance, et les coûts métaboliques entre les futurs anadromes et les futurs résidents

(Rowe et al. 1991; Forseth et al. 1999; Bohlin et al. 1994; Morinville et Rasmussen 2003).

Les traits sous-jacents à l’adoption de l’anadromie et la résidence semblent donc être reliés

au budget énergétique.

L’influence génétique dans l’adoption d’une ou l’autre des tactiques alternatives a aussi été

mise de l’avant expérimentalement, où la progéniture des croisements anadrome-anadrome

comportait plus d’individus anadromes, alors que la progéniture des croisements résident-

résident comportait plus de résidents (Nordeng 1983; Glebe et Saunders 1986). Une

héritabilité de la maturité sexuelle précoce, associée à la résidence chez les saumons

atlantique (Salmo salar), chinook (Oncorhynchus tshawytscha) et coho (Oncorynchus

kisutch), a de plus été trouvée à plusieurs reprises, et revêt une importance pratique en

aquaculture (Silverstein et Hershberger 1992; Heath et al. 1994; Wild et al. 1994;

Mousseau et al. 1998). Des traits potentiels sous-jacents à l’adoption d’une tactique

alternative, telle la croissance, ont aussi des héritabilités significatives, et ce, autant en

laboratoire que sous conditions naturelles (Garant et al. 2003; Wilson et al. 2003a; Thrower

et al. 2004). Ces résultats suggèrent une réponse possible des tactiques alternatives à une

pression de sélection. Par contre, aucune étude connue à ce jour n’a estimé l’héritabilité de

8 l’anadromie et la résidence spécifiquement, par opposition à la maturation sexuelle précoce

qui s’exprime chez les mâles seulement et ce, ni en laboratoire, ni en milieu naturel.

1.3 Héritabilité : son estimation en milieu naturel

1.3.1 Milieu contrôlé versus milieu naturel La notion d’héritabilité revient constamment lorsque l’on tente de comprendre l’évolution

des phénotypes alternatifs (et de tout autre trait en fait…). L’héritabilité procure une mesure

du degré avec lequel le phénotype des jeunes est déterminé par le génotype de leurs parents.

Un trait doit être héritable si l’on veut que la sélection change sa valeur de génération en

génération et cela est illustré dans l’équation de l’éleveur, où la réponse à la sélection, R,

est déterminée par le produit de l’héritabilité, h2, et du différentiel de sélection, S (R = h2S).

Plus la variation phénotypique observée, VP, est influencée par la variance génétique

additive, VA (h2 = VA/VP), plus on s’attend à ce que le trait réponde rapidement à la

sélection. L’héritabilité est donc centrale en écologie évolutive : elle aide à comprendre la

nature des variations phénotypiques, et nous éclaire sur la réponse possible d’un phénotype

face à une pression de sélection.

La très grande majorité des études de génétique quantitative et d’héritabilité ont été

effectuées en laboratoire et en milieux contrôlés, tout d’abord parce que les techniques

d’estimation de paramètres quantitatifs ont été développées pour des programmes de

croisements et aussi parce que le milieu naturel est en plusieurs points « incontrôlable », ce

qui pose des contraintes pratiques et théoriques. Il est alors légitime de se demander si les

estimés en laboratoire peuvent être exportés en milieu naturel si on veut prédire (ou

simplement comprendre) l’évolution des traits quantitatifs dans la « vraie vie ». La

tendance générale veut que les estimés en laboratoire surestiment l’héritabilité. Ceci est dû

au fait que la variance environnementale est grandement sous-estimée en laboratoire, où les

conditions sont contrôlées. La variance environnementale est incluse dans la variance

phénotypique totale, donc si elle augmente en nature relativement à la variance additive, VP

augmente et h2 diminuera (h2=VA/VP) (Weigensberg et Roff 1996). Par contre, cette

9 généralisation s’est vue un peu démentie par l’étude de Weigensberg et Roff (1999) qui

démontre en comparant 165 estimés d’héritabilité sur le terrain avec 189 estimés en

laboratoire que ces derniers sont de bons estimés, du moins de la magnitude, des premiers.

Les héritabilités estimées sur le terrain ne seraient donc pas grandement réduites par une

inflation relative de la variance environnementale (Roff 1997). Néanmoins, il reste que

l’héritabilité dépende des conditions particulières d’une population en particulier (Falconer

et Mackay 1996) : son estimation n’est valable que pour la population où elle a été

mesurée, et au moment où elle l’a été. Il va donc sans dire que les extrapolations du

laboratoire au milieu naturel sont à prendre avec précaution, tout autant qu’une

extrapolation d’une population à l’autre, et voir, d’une année à l’autre.

1.3.2 Les marqueurs moléculaires comme outils L’estimation de l’héritabilité repose sur le degré de ressemblance entre individus

apparentés, et c’est là que se trouve le défi à relever en milieu naturel. À moins de pouvoir

déterminer la paternité et la maternité par observations directes, comme c’est le cas chez les

espèces apportant des soins parentaux, les liens de parenté ne sont pas faciles à retracer en

nature. Même dans les cas d’observations directes sur le terrain, souvent, c’est seulement

l’identité d’un des sexes qui peut être déterminée avec certitude. L’avènement de

marqueurs moléculaires performants, de pair avec le raffinement des méthodes

mathématiques au cours de la dernière décennie, a ouvert les portes à une multitude de

possibilités. Les microsatellites, de par leur grande accessibilité et variabilité, sont les

marqueurs moléculaires de choix pour les études d’apparentement (Estoup et Angers 1998).

Il est maintenant possible grâce à ces marqueurs de reconstruire les pedigrees en milieu

naturel, et, en plus de rendre l’estimation de l’héritabilité possible, la structure sociale et les

patrons de reproduction peuvent être définis, le succès reproducteur quantifié, et les

programmes de croisements améliorés (Bernatchez et Duchesne 2000; Neff et al. 2000;

Olsen et al. 2001; van de Castelle et al. 2001).

Il existe plusieurs approches pour estimer des paramètres de génétique quantitative à l’aide

de marqueurs moléculaires (revu par Garant et Kruuk 2005). Mise à part une approche

10 développée par Ritland (1996) qui s’est malheureusement avérée peu fiable en milieu

naturel (Thomas et al. 2002; Coltman 2005), la reconstruction d’un pedigree, d’une façon

ou d’une autre, est essentielle. Une première approche est utilisée lorsque les parents ne

sont pas connus et consiste à reconstruire des groupes d’individus apparentés (revu par

Blouin 2003). Les individus sont donc regroupés ensemble selon la prémisse qu’ils sont

plein-frères ou non-apparentés. Certains algorithmes sont maintenant aussi utilisés pour

reconstruire des groupes d’individus apparentés plus complexe, en incluant plein-frères,

demi-frères ou cousins (Herbinger et al. 2006). Ces méthodes de reconstruction sont en

général basées sur des chaînes Monte Carlo de Markov (MCMC), qui identifient les

groupes d’individus les plus probables selon leur génotype et la fréquence allèlique dans la

population (Thomas et Hill 2000). Différents algorithmes sont disponibles, chacun

performant mieux dans des conditions particulières (Butler et al. 2004). Une fois les

individus regroupés ensemble, ce jeu de données peut être utilisé pour l’estimation de

paramètres de génétique quantitative, soit en utilisant des analyses de variance, plus

traditionnelles, soit à l’aide de « modèles animal », la dernière tendance dans le domaine de

la génétique quantitative en milieu naturel (voir plus bas). Les études ayant comparé les

estimés quantitatifs obtenus avec des pedigrees reconstruits par groupes d’individus

apparentés et ceux obtenus avec des pedigree plus complets, où les parents sont identifiés,

trouvent en général une bonne correspondance (Thomas et al. 2002; Wilson et al. 2003b).

Par contre, Thomas et al. (2002) ont mis en évidence qu’un bon nombre d’individus

apparentés ainsi que beaucoup d’information provenant des marqueurs moléculaires sont

nécessaires pour que ces méthodes soient applicables. Dans la même veine, Wilson et al.

(2003b) ont trouvés une sous-estimation des paramètres quantitatifs en employant des

pedigree reconstruits à partir de groupes d’individus apparentés. Ces auteurs blâment la

structure complexe du vrai pedigree pour expliquer cette sous-estimation (beaucoup de

demi-frères ne seraient pas pris en compte dans le processus de reconstruction).

La façon la plus fiable pour estimer des paramètres quantitatifs est toujours d’avoir le plus

d’information possible sur les liens de parenté. En milieu naturel, quand aucune

information comportementale n’est disponible, c’est l’assignation parentale qui est la

11 méthode la plus performante. Cette approche implique évidemment un échantillonnage des

parents et de leurs jeunes, pour ensuite utiliser l’information moléculaire et retracer les

paternités et maternités, en se basant sur les lois héréditaires de Mendel. Ces approches

utilisent soient des méthodes d’exclusion, ou de maximum de vraisemblance, ou les deux

(revu par Jones et Ardren 2003). Le pedigree obtenu peut ensuite être utilisé pour estimer

les paramètres quantitatifs qui nous intéressent, et c’est alors le modèle animal qui prime.

Le modèle animal n’est pas une approche nouvelle en génétique quantitative : c’est une

méthode statistique utilisée depuis les années 50 dans le domaine de l’élevage (revu dans

Kruuk 2004). Elle a fait son apparition dans les années 90 en milieu naturel (Konigsberg et

Cheverud 1992) et a vraiment pris son essor dans les années 2000, avec plus d’une dizaine

d’études l’employant sur des populations naturelles de moutons et moufflons (Réale et al.

1999; Coltman et al. 2001; Milner et al. 2000; Coltman et al. 2003), d’écureuils (McAdam

et al. 2002; Réale et al. 2003), de mésanges (MacColl et Hatchwell 2003; Charmantier et al.

2004; Garant et al. 2004; McCleery et al. 2004; Garant et al. 2005b), de moineaux

domestiques (Jensen et al. 2003), de saumon Atlantique (Garant et al. 2003) et de cerf

(Kruuk et al. 2000). Le modèle animal est en fait un modèle linéaire mixte, permettant

l’incorporation de plusieurs effets fixes, qui influencent la moyenne d’un trait, et aléatoires,

lesquels influencent la variance d’un trait. Ce modèle permet une utilisation plus efficace

des données provenant de pedigrees complexes, multi-générationnels, parce qu’il exploite

toute la matrice de ressemblance entre les individus, et non seulement l’information entre

les paires, ou entre les groupes plein-frères (Garant et Kruuk 2005). De plus, ce modèle

peut s’appliquer à des jeux de données non-balancés, où des données sont manquantes, ce

qui est très fréquent en milieu naturel. Il peut aussi être utilisé en présence de reproduction

non-aléatoire, de sélection et de consanguinité. Finalement, la grande flexibilité

d’incorporation de divers effets fixes et aléatoires supplémentaires, tel l’effet maternel ou

l’environnement commun, en font un outil très apprécié des écologistes évolutifs sur le

terrain (Kruuk 2004).

12 1.3.3 Les erreurs de génotypage et leurs effets Toutes les méthodes permettant d’élucider les liens de parenté entre individus mentionnées

plus haut, de la régression de Ritland à l’assignation parentale, font appel au génotypage à

de nombreux locus microsatellites. Or, les données de génotypage sont sujettes à des

erreurs qui peuvent avoir des conséquences lors de la reconstruction de groupes apparentés

et de l’assignation parentale. L’amplification de fragments non-spécifiques (stutters), la

dominance d’amplification des petits allèles sur les gros (large allele dropout), les allèles

nuls, la mutation et les erreurs humaines lors du génotypage sont autant de facteurs à

considérer en entreprenant ce genre d’analyse. Wang (2004) démontre que si les erreurs

sont ignorées dans le processus de reconstruction d’individus apparentés, les individus

formant de vraies familles se trouvent séparés. Il est donc suggèré de toujours inclure un

taux d’erreur lors d’analyses d’apparentement pour ainsi augmenter le pourcentage de

familles adéquatement reconstruites (Wang 2004). Butler et al. (2004) ont analysé la

performance de plusieurs algorithmes utilisés pour les analyses d’apparentement et

concluent qu’aucun n’est très robuste aux erreurs de génotypage, aux erreurs humaines et

aux mutations. Par contre, en présence d’allèles nuls, ces algorithmes avaient tendance à

encore regrouper les individus dans les bons groupes limitant donc les conséquences de ce

type d’erreur (Butler et al. 2004). Il semblerait qu’en utilisant l’information associée aux

nombreux autres locus, les génotypes qui sont affectés par un allèle nul sont encore

compatibles avec leurs vrais frères et suivent toujours les lois de transmission de Mendel

(Butler et al. 2004). En ce qui concerne les analyses d’assignation parentale, le danger face

aux erreurs est d’exclure de vrais parents, comme le génotype d’un jeune ne correspond

plus à celui de son vrai parent (Dakin et Avise 2004). En incluant l’erreur dans les

analyses, le succès d’assignation se retrouve donc augmenté, comme certaines

dissimilitudes sont alors acceptées (Marshall et al. 1998). Par contre, un compromis doit

être établi entre succès d’assignation et confiance dans ces assignations, car en étant plus

tolérant sur la possibilité d’erreurs, on permet aussi à de faux parents de se voir attribuer la

paternité/maternité. Les logiciels d’analyses d’apparentement et d’assignation parentale

développés à ce jour permettent pour la plupart d’inclure des erreurs de génotypage

potentielles et ainsi d’être plus près de la réalité. Malheureusement, cela ne règle pas tout,

et la réalité nous rappelle que d’autres sources d’inquiétude existent lors d’analyses

13 parentales, notamment le déséquilibre de liaison entre locus, créant une redondance

d’information, de même que la ressemblance entre géniteurs. Tous deux viennent diminuer

le potentiel discriminatoire de notre jeu de locus et ainsi notre confiance dans les

assignations.

Il n’y a pas encore de méthode simple et éprouvée permettant d’inclure le facteur erreur qui

vient avec les pedigrees reconstruits dans les analyses de génétique quantitative

subséquentes (par exemple dans le modèle animal). Pour l’instant, la façon d’évaluer

l’influence de cette erreur est par simulations, ou encore en comparant les estimés

quantitatifs obtenus avec des pedigrees ayant différents taux de confiance dans les

assignations parentales. En simulant la présence d’allèles nuls sur 10% des locus lors d’une

analyse d’apparentement, Thomas et Hill (2000) ont trouvé une héritabilité plus faible que

lorsque aucune erreur n’était tolérée. Cette diminution dans l’héritabilité a aussi été

observée lors d’assignation parentale en utilisant un pedigree où la confiance dans les

paternités était de 80% comparativement à celui où la confiance était de 95% (Milner et al.

2000).

1.4 Mortalité sélective : effet de la pêche

1.4.1 Réponse plastique vs. évolutive Face à des changements dans le régime de mortalité, le paysage adaptatif change, menant à

différentes solutions optimales (Gasser et al. 2000). Que la pêche représente une force de

sélection capable de changer les traits d’histoire de vie est une idée qui n’est plus remise en

doute (Stokes et Law 2000; Conover 2000). L’évolution par sélection naturelle implique

des pressions qui font en sorte que les individus avec des traits héritables « non-avantagés »

ont une probabilité de survie réduite, alors que ceux avec des caractéristiques plus

« favorables » survivent et se reproduisent mieux, contribuant ainsi davantage à la

prochaine génération (Hutchings 2004b). La pêche peut produire ce genre de pression de

sélection, comme elle cible souvent certains individus d’une population plutôt que d’autres,

par exemple les plus gros et les plus âgés. Par contre, face à un changement phénotypique

14 causé par des pressions naturelles ou anthropiques, il n’est pas toujours clair quelle est la

nature de ce changement : est-ce un changement évolutif (i. e. génétique) ou est-ce une

manifestation de plasticité phénotypique? Comme la pêche influence aussi les conditions

environnantes dans lesquelles les stocks se développent, ces changements

environnementaux sont souvent pointés comme les responsables de la réponse

phénotypique, plutôt que des changements dans la structure génétique de la population.

L’exemple le plus cité et démontré est une diminution dans l’âge à maturité (Law 2000).

Une explication intuitive est que la pêche réduit grandement la biomasse du stock exploité,

diminuant la compétition intraspécifique, laissant plus de nourriture pour les survivants, qui

grandissent alors plus vite. Une croissance rapide est souvent associée à une maturation

rapide, à un plus jeune âge (Stearns 2002). Cette diminution dans l’âge à maturité pourrait

donc être une réponse purement plastique face aux conditions environnementales

changeantes qui augmentent les taux de croissance. Par contre, ce type de réponse

compensatoire n’explique pas tout, et de plus en plus d’évidences laissent croire qu’un

changement génétique est aussi en cause dans bien des pêcheries (Rijnsdorp 1993; Conover

et Munch 2002; Barot et al. 2004; Olsen et al. 2004). Comme pour beaucoup d’espèces, la

pêche chez les salmonidés capture souvent les individus de plus grandes tailles, et agit sur

des traits tels que la croissance et la taille à maturité en plus de l’âge à maturité (Ricker

1995; Haugen et Vollestad 2001). De par sa variation temporelle, la pêche peut aussi

sélectionner les individus basé sur leur moment de migration (run timing, Quinn et al.

2007). La croissance et le moment de migration sont des traits héritables chez les

salmonidés (Garant et al. 2003; Quinn et al. 2007), ce qui fait de la mortalité induite par la

pêche une force sélective capable de créer une réponse évolutive, c’est-à-dire d’occasionner

des changements génétiques.

Que des changements évolutifs aient lieu ne représente pas en soi un problème : l’évolution

par sélection est d’ailleurs vue comme une adaptation favorable à de nouvelles conditions.

Par contre, les mortalités induites par la pêche peuvent représenter des pressions

supplémentaires substantielles sur les populations naturelles, et les conséquences évolutives

à plus ou moins longs termes sont peu connues. Les populations naturelles peuvent-elles

15 s’adapter si vite à de telles perturbations, avant que la mortalité n’excède le potentiel

d’accroissement démographique (Hendry et Kinnison 1999)? De plus, il ne suffit pas de

fermer la pêche pour que la population exploitée retrouve son état original. Des

changements évolutifs peuvent prendre beaucoup plus de temps à renverser que des

réponses plastiques (Law 2000). Les individus qui survivent à une pression de pêche sont

probablement ceux dont les génotypes confèrent un meilleur fitness sous ces conditions de

sélection anthropiques, par exemple les poissons avec de faibles croissances et de bas âges

à maturité. Lorsque cette sélection artificielle n’est plus, les individus restants ne sont plus

optimaux face aux forces de sélection naturelle, ce qui mène à des temps de rétablissement

des stocks très longs (Conover 2000). De plus, un arrêt de la pêche ne produit pas

nécessairement une intensité de sélection égale dans la direction opposée. Rowell (1993) a

démontré qu’en absence de pression de pêche, l’âge à maturité avait très peu d’effet sur la

production totale d’œufs sur toute la durée de vie : le plus grand nombre d’œufs chez les

individus plus âgés compensait pour le fait qu’ils aient retardé la maturation. Par contre, la

pêche favorise un âge à maturité plus faible et peut induire un changement génétique dans

ce trait. Si on ferme la pêche en espérant renverser le processus de sélection, il est peu

probable que la sélection favorisant un âge à maturité élevé soit très forte. Cet exemple

démontre bien l’asymétrie potentielle entre les pressions anthropiques et naturelles.

1.4.2 La norme de réaction probabiliste Récemment, plusieurs études ont adopté une nouvelle méthode pour départager les

réponses plastiques des réponses génétiques dans l’âge et la taille à maturité face à la pêche

(Olsen et al. 2004, 2005; Barot et al. 2004, 2005). L’âge et la taille à maturité sont deux

trait clés de l’histoire de vie souvent étudiés comme covariables, et la relation entre la taille

à maturité et l’âge est habituellement présentée graphiquement comme une norme de

réaction (Figure 1-2). Strictement parlant, une norme de réaction illustre, pour un

génotype, le phénotype adopté sous différentes conditions environnementales (Stearns

1992). La relation entre la taille et l’âge à maturité n’implique pas directement de variable

environnementale, ce n’est donc pas une norme de réaction dans le sens strict du terme. Par

contre, l’emploi du terme « norme de réaction » est justifié car on présume que ce sont des

16 variations dans les taux de croissance, fortement dépendant des conditions

environnementales, qui influencent l’âge et la taille à maturité (Stearns et Koella 1986).

Figure 1-2. Interprétation de la norme de réaction pour la taille et l’âge à maturité. Les individus à croissance plus rapide (trajectoires de croissance avec une pente plus élevée) deviennent matures à un âge plus jeune. Plus la croissance est lente (trajectoires de croissance où les pentes sont moins élevées), plus l’âge à maturité augmente. La norme de réaction est définie par la ligne qui joint la taille à maturité à chaque âge. L’interprétation de cette courbe en tant que norme de réaction est basée sur la supposition que les différences dans les taux de croissance sont en grande partie dues aux différences dans les conditions environnementales. D’après Heino et al. 2002.

Donc, chaque point de la relation taille et âge à maturité correspond à une trajectoire de

croissance caractérisée par un taux de croissance moyen, déterminé par les conditions

environnementales précédentes (Figure 1-2, Barot et al. 2004). En d’autres mots, la norme

de réaction de maturation (MRN – maturation reaction norm) décrit comment les

variations dans la croissance, reflétées dans la taille à l’âge, influencent la maturation (Grift

et al. 2003). Traditionnellement, la MRN implique que la maturation est entièrement

déterminée par l’âge et la taille (TMRN – traditional maturation reaction norm), et qu’elle

a lieu aussitôt qu’une trajectoire de croissance intercepte la norme de réaction. Or, en

nature, il existe une variabilité dans la taille à maturité pour un âge donné, mettant en

évidence la nature stochastique et probabiliste de la maturation. Étant un processus

physiologique complexe, la maturation est influencée par d’autres facteurs tels que la

disponibilité des ressources ou les réserves énergétiques, lesquels, à leur tour, sont

influencées par l’environnement local et l’expérience individuelle (Bernardo 1993; Grift et

al. 2003). Heino et al. (2002) ont donc proposé une nouvelle approche pour prendre en

considération cette variation inexpliquée dans la maturation : la norme de réaction

probabiliste (PMRN – probabilistic maturation reaction norm).

17

La PMRN représente donc la probabilité pour un individu immature qui a survécu et atteint

un certain âge et taille, de devenir mature à cet âge. Elle exprime la tendance à la

maturation comme une probabilité qui est conditionnelle à l’atteinte d’un certain âge et

taille. En ce sens, le processus de maturation en tant que tel est séparé des processus

démographiques (croissance et mortalité) qui déterminent la probabilité d’atteindre un

certain âge et taille : la PMRN est donc indépendante de la croissance et de la mortalité.

C’est cette caractéristique qui la différencie de la TMRN et qui permet à la PMRN d’être

utilisée pour séparer la réponse génétique d’une réponse phénotypique. Un changement

dans la PMRN représenterait donc plus probablement un changement génétique qu’un

changement plastique. En observant des changements dans la PMRN sur des données de

séries temporelles, l’hypothèse d’un changement génétique causé par la pêche a été avancée

pour la morue Atlantique (Gadus morhua, Barot et al. 2004; Olsen et al. 2004, 2005) et la

plie d’Amérique (Hippoglossoides platessoides, Barot et al. 2005). Cette conclusion repose

entre autres sur la présomption que la MRN est un caractère héritable. Des évidences dans

la littérature suggèrent qu’une héritabilité significative est présente pour diverses normes de

réactions (Ostroswki et al. 2000; Brommer et al. 2005; Nussey et al. 2005), et donc qu’une

réponse évolutive est possible.

Le principe de l’approche de la norme de réaction probabiliste peut être appliqué à d’autres

transitions ontogénétiques que la maturation. Une telle transition chez les salmonidés

anadromes, qui a lieu avant la maturation, est la migration d’alimentation en mer. L’âge à la

maturation pourrait être subtilisé par l’âge à la migration, en gardant exactement la même

logique, et l’approche probabiliste utilisée pour le processus de migration. Proposons donc

une PMigRN (probabilistic migration reaction norm). Tout comme pour la taille à

maturité, il existe des variations dans la taille à la migration à un âge donné, parce que

d’autres facteurs, tels la condition ou les taux métaboliques, influencent le processus de

migration (Thorpe 1994). L’approche probabiliste semble donc appropriée et pourrait être

un moyen intéressant d’évaluer si des changements évolutifs ont lieu dans l’âge et la taille à

la migration pour des populations de salmonidés anadromes exposées à la pêche. Il est

18 surprenant de constater que si peu d’études explorant les effets évolutifs de la pêche sur les

salmonidés ne soient disponibles, étant donné leur grande valeur économique, tant

commerciale que récréative (mais voir Ricker 1995; Haugen et Vollestad 2001). Peut-être

est-ce la difficulté d’acquérir les données suffisantes et adéquates pour montrer de tels

changements en milieu naturel qui limite ce genre d’étude.

1.4.3 Une approche de modélisation C’est d’ailleurs en partie pour pallier ce manque de données empiriques qu’une approche

de modélisation est de plus en plus employée pour évaluer les changements induits par la

pêche au sein des populations naturelles. En plus de l’avantage évident à utiliser et créer

des données virtuelles, le pouvoir prédictif des modèles en font d’excellents outils de

gestion. Une approche de modélisation permet d’identifier les pressions de sélection

passées (naturelles ou anthropiques) qui furent responsables d’un changement adaptatif, et

permet aussi de prédire de futurs changements en fonction des pressions de sélection

actuelles (Ernande et al. 2004). Il est par exemple possible d’évaluer, à l’aide de modèle de

dynamique des populations, comment les stratégies de récolte influenceraient l’évolution

d’un trait et par conséquent quelles seraient les stratégies les plus souhaitables pour

maximiser le rendement à long terme (Heino 1998; Ratner et Lande 2001). Des méthodes

ont maintenant vu le jour qui intègrent à la fois des principes de génétique quantitative pour

prédire l’évolution de certains traits héritables et des aspects clés de la dynamique

écologique (par exemple la structure en âge et en taille). Certains incluent explicitement la

plasticité phénotypique en modélisant entre autres les normes de réaction (Ernande et al.

2004; Baskett et al. 2005; Dunlop et al. 2007). Notamment, le modèle récemment

développé par Dunlop et al. (2007) présente plusieurs avancées relativement aux autres

modèles. Tout d’abord, une approche basée sur l’individu (individual-based model, IBM) a

permis d’inclure des effet tels la croissance dépendante de la densité, une caractéristique

importante pour plusieurs populations de poissons, qui influence les prédictions face à des

pressions de sélection. Aussi, contrairement à des modèles plus traditionnels

d’optimisation, où on doit définir les critères de fitness à optimiser (Law 1979), un IBM

laisse le concept de fitness émerger naturellement : des individus avec certains traits seront

plus aptes à survivre, se reproduire, et laisser plus de descendants. Ensuite, la plasticité

19 phénotypique dans l’âge et la taille à maturité fut modélisée au moyen d’une PMRN, ce qui

inclut donc la dépendance de l’âge et la taille à maturité aux conditions environnementales,

de même que la nature probabiliste de la maturation. De plus, les auteurs ont pris en

compte la force sélective engendrée par les soins parentaux, et démontrent ainsi comment

les caractéristiques spécifiques d’une espèce peuvent influencer la réponse évolutive sous

mortalité sélective (Dunlop et al. 2007). L’approche employée par Dunlop et al. (2007)

permet de suivre l’évolution temporelle des traits quantitatifs, et non seulement son résultat

final : on peut ainsi évaluer à quelle vitesse les traits évoluent. En plus de toutes ces

caractéristiques, de telles approches « éco-génétiques » sont alléchantes par le fait qu’en

même temps qu’elles prédisent les changements dans les traits quantitatifs, les

conséquences démographiques sont aussi évaluées (abondance, biomasse).

1.5 Le cas de l’omble de fontaine au Québec, Salvelinus fontinalis L’omble de fontaine est natif du nord-est de l’Amérique du Nord et on le retrouve

communément sous plusieurs formes, en général confiné à l’eau douce en lac (landlocked),

mais aussi résidant en rivière ou encore sous la forme anadrome (Smith et Saunders 1958;

Dutil et Power 1980; Castonguay et Fitzgerald 1982; McCormick et al. 1985; Naiman et al.

1987; Lesueur 1993). L’omble de fontaine aurait colonisé le nord-est de l’Amérique du

Nord du sud au nord, en suivant le retrait des glaciers il y a plus de 10 000 ans. Les

fondateurs des populations nordiques auraient donc été anadromes, leur séjour en eau salée

en dehors de leur rivière d’origine leur permettant de se disperser (Castric et Bernatchez

2003). Ces individus anadromes coexistent maintenant avec des individus résidents dans

plusieurs rivières s’écoulant dans le golfe et le fleuve Saint-Laurent.

Le CIRSA (Centre Interuniversitaire de Recherche sur le Saumon Atlantique) a entrepris il

y a près de 10 ans une étude exhaustive du cycle de vie de l’omble de fontaine de la rivière

Sainte-Marguerite, au Saguenay, où des individus anadromes et résidents vivent en

sympatrie. Malgré la popularité générale de l’omble de fontaine au Québec (pêche

récréative et aquaculture), peu est connu sur son cycle de vie anadrome, de même que sur

20 les différences génétiques et comportementales entre ces formes. Au cours des 10 dernières

années, une multitude de données ont été récoltées et plusieurs hypothèses ont été testées.

Les patrons de migration sont maintenant bien connus (Lenormand et al. 2004). Les jeunes

ombles migrants quittent la rivière pour la première fois en grande majorité à l’âge de 1 ou

2 ans entre la mi-mai et la mi-juin. Après 1, 2 ou 3 saisons en eau salée, avec plusieurs

retours fréquents vers l’eau douce, les ombles remontent en rivière pour une fraie

automnale en octobre. Pendant ce temps, les ombles résidents, eux, n’ont pas bougé.

L’âge médian à la première reproduction est de 3 ans, pour les deux formes, et les multi-

frayeurs sont fréquents. Des croisements en laboratoire et des observations sur le terrain

ont également suggèré que la reproduction est possible entre les formes (obs. personnelles).

Une étude précédente a étudié l’importance de la taille atteinte avant la migration sur la

décision de migrer dans le cadre d’une stratégie conditionnelle (Thériault et Dodson 2003).

Les résultats obtenus ont mis en évidence deux moments de décision : le premier, à un an,

montre que la taille est légèrement plus grande pour les individus qui entreprendront la

migration à cet âge. Cette différence s’explique par le fait qu’à 1 an, les individus qui

restent sont composés de deux groupes : ceux qui migreront l’année suivante, et ceux qui

resteront en eau douce toute leur vie (Figure 1-3). Lorsqu’on retire le groupe des futurs

migrants, qui sont les plus petits, la taille ne diffère plus entre les migrants à 1 an et les

résidents. L’influence de la taille à 1 an sur la décision de migrer n’est donc pas très nette :

les individus de même taille adoptent ultimement une ou l’autre des tactiques. Le

deuxième moment de décision, à 2 ans, est quant à lui relié plus fortement à la taille : les

plus petits individus migrent, alors que les plus gros restent en eau douce pour y compléter

leur cycle vital (Thériault et Dodson 2003).

21

0

10

20

30

40

50 60 70 80 90 100 110 120

Taille (mm)N

ombr

e de

poi

sson

s

Figure 1-3. Distribution de taille à l’âge de 1 an pour les individus résidents (barres noires) et migrants (barres blanches). Parmi les résidents se retrouvent les individus qui migreront à 2 ans et qui sont les plus petits de leur cohorte à l’âge de 1 an (ligne noire). D’après Thériault et Dodson (2003).

Parallèlement à l’étude des taux de croissance, les bases énergétiques de l’anadromie et de

la résidence ont aussi été investiguées (Morinville et Rasmussen 2003). Les résultats

révèlent un taux de consommation plus élevé ainsi que des efficacités de croissance

moindres l’année précédant la migration pour les ombles migrants. Les ombles migrants

ont donc des coûts métaboliques plus élevés que les résidants et ce, avant la migration. De

plus, les ombles qui entreprendront la migration sont retrouvés dans des habitats à courants

plus élevés que les ombles qui adopteront la résidence (Morinville et Rasmussen 2006).

Les différences morphologiques trouvées entre les deux formes dans leur stade de vie

juvéniles vont dans le même sens : les futurs migrants sont plus fusiformes, ce qui

correspond bien à un habitat à plus forte vélocité (Morinville et Rasmussen 2007). Mais

alors, c’est l’œuf ou la poule? Les futurs migrants seraient-ils les individus qui au départ

ont des coûts métaboliques génétiquement plus élevés, ce qui les poussent à utiliser un

habitat où l’apport de nourriture est augmenté (courants rapides), ou bien se retrouvent-ils

dans cet habitat de façon aléatoire en regard de leur génotype, et voient leur coûts

métaboliques augmenter en réponse aux coûts élevés associés à l’activité de nage pour

maintenir une position dans les courants rapides? De façon similaire, ces futurs migrants

auraient-ils au préalable une forme plus allongée, ce qui leur permettrait de tenter leurs

chances dans les courants rapides, étant pré-adaptés, ou bien est-ce le fait de se retrouver

dans un courant rapide qui « moule » leur morphologie?

22

Quoi qu’il en soit, ces études précédentes ouvrent la voie à la question fondamentale de

l’influence relative des facteurs génétiques et environnementaux dans le déterminisme des

tactiques alternatives chez les salmonidés, et dans notre cas particulier, chez l’omble de

fontaine.

1.6 Objectifs et contributions Ce projet de doctorat se veut un pas de plus vers la compréhension de l’évolution des

cycles vitaux et de la diversité phénotypique intraspécifique, en particulier des facteurs qui

déterminent et maintiennent les phénotypes alternatifs au sein d’une population. J’ai choisi

d’étudier l’anadromie et la résidence chez l’omble de fontaine dans une perspective de

stratégie conditionnelle, puisque cette hypothèse est largement appliquée aux phénotypes

alternatifs en général (West-Eberhard 2003) et aux salmonidés en particulier (Gross 1996;

Hazel et al. 1990; Hutchings et Myers 1994). En considérant ce dimorphisme comme un

trait seuil, il devient possible de considérer à la fois les composantes environnementales et

génétiques (Hutchings 2004a).

Le premier objectif de mon projet de doctorat est d’élucider et de décrire les patrons de

reproduction des ombles anadromes et résidents. Les études et observations précédentes

sur le même système supposent et suggèrent que les ombles anadromes et résidents font

partie de la même population, mais cette hypothèse n’a jamais été formellement testée.

Être en présence d’une seule population est une exigence des modèles de stratégie

conditionnelle et de traits seuils. À l’aide de marqueurs moléculaires microsatellites et

d’analyse d’assignation parentale, les patrons de reproduction peuvent être reconstruits et il

devient alors possible de déterminer s’il y a reproduction entre les deux formes. Comme

sous-objectif, je voulais de plus estimer le succès reproducteur individuel et son association

avec la taille. Ceci n’a jamais été réalisé pour les formes anadromes et résidentes où les

deux sexes peuvent adopter une ou l’autre des tactiques.

23 Le second objectif a pour but d’estimer l’héritabilité de l’anadromie et de la résidence, ainsi

que de traits sous-jacents, soient la taille et la forme du corps. De plus, je voulais établir si

les corrélations phénotypiques préalablement observées entre la tactique adoptée et la taille

et la forme du corps sont en partie causées par des corrélations génétiques. Ces estimations

ont été faites en milieu naturel, à l’aide de pedigrees reconstruits basés sur l’information

des marqueurs moléculaires, sans aucune manipulation expérimentale ni croisement

artificiels, ce qui est, à ma connaissance, une première en ce qui concerne l’anadromie et la

résidence.

Le troisième et dernier objectif se voulait un exercice de modélisation pour explorer les

conséquences d’une mortalité sélective engendrée par la pêche sportive. Si l’anadromie et

la résidence sont caractérisées par une variance additive sous-jacente et donc une

héritabilité significative, une réponse évolutive est possible face à des pressions de

sélection anthropiques. Une approche « éco-génétique », incluant des principes de

génétique quantitative et une modélisation des normes de réactions, a été employée dans un

but prédictif, voulant évaluer quelles pourraient être les conséquences évolutives et

démographiques d’une pression de pêche exercée sur les anadromes.

Cette étude revêt une importance fondamentale dans la compréhension de l’évolution des

cycles vitaux, du maintien des stratégies alternatives chez les poissons et de leur réponse à

la sélection. De plus, ce travail représente un pas de plus vers le développement d’outils

moléculaires puissants et de nouvelles méthodes d’assignation parentale et de calcul

d’héritabilité en nature, sujets tout chauds. Cette étude a de plus une importance pratique

pour la gestion et la conservation de l’omble de fontaine au Québec. Depuis la chute de la

plupart des stocks de saumons atlantique il y a plus de 10 ans, l’exploitation de l’omble de

fontaine anadrome s’est intensifiée. Il est évident qu’une bonne compréhension de la

biologie de cette espèce est synonyme d’une bonne gestion. La démonstration qu’ombles

anadromes et résidents font partie de la même population reproductrice viendrait justifier

une gestion conjointe de ces deux formes. De plus, la compréhension du déterminisme

24 génétique et environnemental de ces tactiques alternatives viendrait nous éclairer sur ce qui

influence la proportion d’ombles anadromes disponibles pour les pêcheurs sportifs. De

plus, la quantification de l’héritabilité de l’anadromie et de la résidence peut contribuer à

prédire et comprendre la réponse à la récolte sélective des anadromes potentiellement

exercée par la pêche sportive. Enfin, l’omble de fontaine est le poisson le plus important

pour l’aquaculture au Québec, sa production comptant pour plus de 50% de toute la

production piscicole. Les programmes de croisements sélectifs ont besoin de

connaissances génétiques de bases sur les traits associés à l’anadromie et à la résidence,

connaissances auxquelles ce projet contribue.

Chapitre 2. Mating system and individual reproductive success of sympatric anadromous and resident brook charr, Salvelinus fontinalis, under natural conditions

26

2.1 Résumé Les salmonidés sont bien connus pour leurs deux formes de vie souvent présentes dans une

même rivière, une qui entreprend une migration vers la mer avant la reproduction

(anadrome) et une qui reste toute sa vie en eau douce (résidente). Plusieurs études

génétiques ont suggéré que ces deux formes peuvent appartenir à une seule population

reproductrice, mais les patrons de reproduction sont rarement décrits, particulièrement dans

les populations où les deux sexes sont présents sous les deux formes. En utilisant des

marqueurs microsatellites et des analyses parentales dans une population naturelle d’omble

de fontaine (Salvelinus fontinalis), nous avons mis en évidence l’occurrence de

reproduction entre les deux formes, principalement assurée par les mâles résidents qui se

reproduisent autant avec des femelles anadromes que résidentes. Les déterminants du

succès reproducteur, estimé par le nombre de juvéniles ayant survécu jusqu’à 1 ou 2 ans,

diffèrent entre les sexes. Ainsi, la taille chez les mâles ne semble pas être associée au

succès reproducteur, alors que chez les femelles, les plus grandes ont un meilleur succès.

Le plus haut succès reproducteur individuel des anadromes comparés aux résidents est

principalement expliqué par le plus grand succès des femelles anadromes. Nous suggérons

que les mâles résidents adoptent une tactique de reproduction furtive comme façon

d’augmenter leur succès reproducteur en pouvant féconder les œufs des femelles de toutes

les tailles, dans tous les habitats. La persistance de la tactique résidente chez les femelles

pourrait être associée à leur avantage à accéder à des sites spatialement limités dans de

petits tributaires, non accessibles aux plus grandes femelles.

27

2.2 Abstract Salmonids are known for the occurrence in sympatry of two life-history forms, one that

undergoes migration to sea before returning to freshwater to reproduce (anadromous) and

one that inhabits freshwater without a migratory phase (resident). Whereas one breeding

population is often suggested by population genetic studies, mating patterns have rarely

been directly assessed, especially when both sexes are found within each life-history form.

By using highly polymorphic microsatellite loci and parentage analysis in a natural

population of sympatric anadromous and resident brook charr (Salvelinus fontinalis), we

found that gene flow occurred between the two forms and was mediated by resident males

mating with both resident and anadromous females. Determinants of reproductive success,

estimated by the number of surviving juveniles (ages 1 and 2 years), differed between the

sexes. No strong evidence of the influence of size on individual reproductive success was

found for males, whereas larger females (hence most likely to be anadromous) were more

successful. The higher individual reproductive success of anadromous fish compared to

residents was mainly explained by this higher reproductive success of anadromous females.

We suggest that resident males adopt a “sneaking” reproductive tactic as a way of

increasing their reproductive success by mating with females of all sizes in all habitats.

The persistence of the resident tactic among females may be linked to their advantage in

accessing spatially constrained spawning areas in small tributary streams unavailable to

larger females.

28

2.3 Introduction The study of mating systems provides insights into the reproductive strategies adopted by

both sexes to maximize reproductive success and contributes to our understanding of

selection and local adaptation (Reynolds 1996). The use of highly polymorphic genetic

markers along with parentage assignment analyses has made major contributions to the

field, namely by revealing important discrepancies between behavioral- and genetic-based

definitions of mating systems. Early genetic work on birds and mammals showed that

many species were far more polygamous than previously thought (Westneat 1987; Hughes

1998; Coltman et al. 1999). More recent work on fishes, known for their great diversity of

mating systems and reproductive tactics, has also provided a more complete picture of

mating patterns than that previously described based on behavioral observations alone

(DeWoody and Avise 2001; Avise et al. 2002). In addition to the discovery of

unsuspected elevated levels of polygamy in both sexes (Garant et al. 2001; Feldheim et al.

2004), field studies have provided genetic evidence for cuckoldry, extra-pair paternity,

nest-takeover events, and egg thievery in nest-tending species (Conrad et al. 2001;

DeWoody and Avise 2001; Blomqvist et al. 2002) and have provided more direct measures

of individual reproductive success (Garant et al. 2001; Neff 2001; Blanchfield et al. 2003;

Garant et al. 2005a). This body of work has emphasized the existence of alternative mating

tactics in many taxa and species as a way of achieving substantial mating success (Scott

and Williams 1993; Jones et al. 1998; Coltman et al. 1999; Kempenaers et al. 2001).

Salmonid mating systems have been the focus of many studies (Fleming 1998; Blanchfield

et al. 2003; Dickerson et al. 2004; Seamons et al. 2004b), especially that of Atlantic salmon

(Salmo salar), that involves alternative mating tactics among males (Thomaz et al. 1997;

Garant et al. 2001; Garcia-Vazquez et al. 2001; Jones and Hutchings 2002; Garant et al.

2003). In this species, a proportion of male parr (a term referring to the juvenile

freshwater stages of salmon) mature in freshwater at younger ages and smaller sizes than

anadromous males that migrate to sea before returning to spawn. Whereas anadromous

males fight among themselves to control access to female salmon, mature parr sneak into

29 females’ nests to gain access to mating. However, in many other species of salmonids,

both males and females may adopt residency (maturation without going to sea) and are

often found in sympatry with the anadromous form. Population genetic analyses have

generally failed to demonstrate significant genetic differentiation between sympatric forms

(but see Foote et al. 1989; Wood and Foote 1990; Wood and Foote 1996). Most studies

have revealed greater genetic differentiation between geographical localities than between

coexisting life-history forms within any one locality (brown trout Salmo trutta, Hindar et al.

1991, Schreiber and Diefenbach 2005; brook charr Salvelinus fontinalis, Jones et al. 1997,

Boula et al. 2002, Castric and Bernatchez 2003; rainbow trout Oncorhynchus mykiss

Docker and Heath 2003, Narum et al. 2004). Moreover, experimental crosses and

transplant studies have shown that parr from “pure” anadromous or resident crosses can

either become one form or the other and that transplanted resident fish have given rise to

anadromous stock, or vice versa (Nordeng 1983; Morita et al. 2000; Olsson and Greenberg

2004; Schreiber and Diefenbach 2005). Behavioral observations also provided evidence

for reproduction between anadromous and resident fish (Jonsson 1985; Schreiber and

Diefenbach 2005). Altogether, these studies strongly suggest that in most circumstances,

sympatric resident and anadromous forms of salmonids belong to a single gene pool. Yet,

population genetic analyses and behavioral observations provide little insight into mating

patterns: The actual reproduction is not seen and, even if it was, would not reveal which

fishes were successful in reproducing. No studies have yet documented the mating system

and associated reproductive success of sympatric forms of anadromous and resident

salmonids, other than Atlantic salmon, either in controlled or natural environments.

Adult size in salmonids has often been identified as an important determinant of

reproductive success (Fleming 1996). Size certainly represents a major discrepancy

between anadromous and resident forms. Anadromous individuals benefit from higher

growth rates at sea (Gross 1987; Morita and Takashima 1998), and a bigger size confers a

fecundity advantage to females (Fleming 1996) and a dominance advantage in males

(Blanchfield et al. 2003). Furthermore, because males are able to achieve substantial

reproductive success by adopting alternative reproductive tactics (Hutchings and Myers

30 1988), females often predominate within the anadromous part of the population

(Kristoffersen et al. 1994; Rikardsen et al. 1997; Doucett et al. 1999), and in some

instances, only males adopt the resident tactic (Bohlin et al. 1994). Reproductive success

and its correlation with size have never been compared between sympatric anadromous and

resident individuals where females, and not just males, are adopting both life-history forms.

The brook charr is native of northeast North America and commonly occurs as landlocked,

freshwater-river resident and anadromous forms. Colonization of northeast North America

is believed to have taken place from south to north, after the retreat of glaciers 10,000 years

ago. Founders of extant populations are thus considered to have been anadromous (Castric

and Bernatchez 2003) and now coexist with resident individuals in many populations

occupying tributaries of the Gulf of St. Lawrence and the St. Lawrence R. Little is known

about the life history of sympatric anadromous and resident brook charr. However, it has

been shown that growth rate and growth efficiency differ between future migrants and

future residents and are proximate factors linked to the form adopted (Morinville and

Rasmussen 2003; Thériault and Dodson 2003). This suggests that anadromy and residency

in this species may be under a conditional mode of regulation, where a threshold exists that

must be exceeded to adopt one form or the other (Hazel et al. 1990; Roff 1996).

The objective of this study was to use highly polymorphic microsatellite loci and parentage

analysis to document the mating systems of sympatric resident and anadromous brook charr

in a tributary of the Sainte-Marguerite River, Québec, Canada, under natural conditions.

By means of parentage analysis, we first determined if reproduction occurs between the two

forms and if so, if it is mediated by resident males only. We then estimated individual

reproductive success and its variance for both resident and anadromous fish based on the

number of surviving young (ages 1 and 2 years). We further investigated the mating system

by documenting and comparing the relationship between reproductive success, size, and

number of mates for both sexes and forms.

31 2.4 Material and Methods

2.4.1 Study site and brook charr reproductive behavior The Sainte-Marguerite River system in Quebec, Canada, sustains a large population of

anadromous brook charr that migrates into the Sainte-Marguerite Bay and the Saguenay

River before returning to the freshwater to reproduce (Fig. 2-1). They migrate at 1 or 2+

years of age and to a lesser extent at age 3+, and sex ratio is 1:1 at both downstream and

upstream migrations (Lenormand 2003; Thériault and Dodson 2003). Male and female

resident brook charr also occur in the river and are mainly found in tributaries of the main

river branch. Sampling as well as underwater observations at different sites of the river

showed that anadromous charr use tributaries for reproduction, and thus that both forms are

present on the same spawning grounds (Thériault, personal observation). Reproductive

behavior of brook charr is typical of other river salmonids: Females excavate their nests in

gravel substrates during the fall where they deposit their eggs. Males compete for access to

females and hence for opportunities to fertilize the eggs. Sneaking and satellite behavior by

small males has previously been observed in lacustrine populations of this species

(Blanchfield et al. 2003).

2.4.2 Sampling The study was performed on a small tributary of the Sainte-Marguerite River, Morin Creek

(average 5.6 m wide, 0.3 m deep, Fig. 2-1). An impassable waterfall (75 m high) is located

4 km upstream from the mouth of the tributary. The study was conducted in a 2.5 km

section below this waterfall, accessible to anadromous fish.

An upstream migration trap was installed at 1 km from the mouth of the stream and was

operated from the end of June to the end of October in 2000 and 2001 for intercepting

upstream-migrating anadromous spawners (Fig. 2-1). The trap covered the entire width of

the stream, except for some periods of high flood where fish could pass either over or under

it (see “Results” section). Traps were visited twice daily, fish were measured (fork length)

and marked individually with a T-bar Floy Tag, the adipose fins were taken and preserved

32 in 95% ethanol, and subsequently, fish were released 200 m upstream. Fish caught in the

upstream migration trap were differentiated into anadromous or resident forms based on

length, morphological identification, maturation stage (when available) and/or recapture

information (Thériault and Dodson 2003; Lenormand et al. 2004). Thus, fish bigger than

250 mm were always classified as anadromous as this length approaches the maximum size

of residents observed in this stream. Only three resident fish recorded during 7 years of

survey of this stream exceeded 250 mm (253, 256 and 258 mm fork length respectively)

(Thériault, unpublished data). Fish between 170 and 250 mm were either mature resident

when signs of maturation were present (coloration, body shape, sperm release, oviposition

pore visible) or immature anadromous when no such signs were detected. Although some

mature resident fish were caught in the upstream migration trap, most were captured with

electrofishing gear from June to September 2000 and 2001, in three distinct areas along the

2.5-km section (Fig. 2-1). All fish greater than 120 mm were considered as potential

resident spawners as this was approximately the minimum observed length at sexual

maturity in this stream (114 mm, Lenormand 2003). Fish were measured (with their

adipose fins sampled) and then released not more than 50 m from their capture site. Sex

was noted when external signs of maturation were present.

In 2002, 2003, and 2004, 1+ and 2+ juvenile fish (progeny from the 2000 and 2001

spawners sampled) were collected either by means of a downstream migration trap

intercepting first time migrants in May and June, or by electrofishing from June to October

in the same 2.5-km section as for resident spawners (Fig. 2-1). Fish were classified as

either 1+ or 2+ based on length distribution, previously validated with age determination

based on otoliths from the same system (Thériault and Dodson 2003). All fish were

measured (with their adipose fins sampled) and subsequently released near their site of

capture.

33 2.4.3 Microsatellite polymorphism analyses Total DNA was extracted from the adipose fin tissue using Qiagen® DNeasy™ extraction

kit. Microsatellite polymorphism was analyzed at 13 loci using fluorescent-labeled primers

(SfoB52, SfoC113, SfoC129, SfoC28, SfoC88, SfoC115, SfoD100, and SfoD75, T. L. King,

US Geological Survey, unpublished; SCO204, SCO216, and SCO218; DeHaan and Ardren

2005; Sfo262Lav and Sfo266Lav; Perry et al. 2005b). Five polymerase chain reactions

(PCR) were carried out using either a Perkin-Elmer 9600 thermocycler v.2.01 or a

Biometra® T1 thermocycler (Table 2-1). PCR products 1 and 2 (Table 2-1) were purified

with a PCR96 Cleanup Plate Manu30 from Millipore and were subsequently separated

electrophoretically using a BaseStation™ DNA Fragment Analyzer (MJ Research) (gel 1:

quintuplex; gel 2: triplex). Allelic sizes were scored against the size standard GENESCAN

ROX-500 (Applied Biosystems) using CARTOGRAPHER™ analysis software v.1.2.0.

PCR products 3, 4, and 5 (Table 2-1) were pooled and run together on an ABI™ 3100

automated capillary sequencer (Applied Biosystems). Allelic sizes were scored against the

size standard GENESCAN ROX-500 (Applied Biosystems) using GENESCAN™ analysis

v.3.7 and GENOTYPER™ v.3.7 NT software. Allelic sizes for each locus were

standardized with the software ALLELOGRAM v.1.

2.4.4 Statistical analyses

2.4.4.1 Standard genetic statistics Genetic diversity in the adult population was quantified by the number of alleles per locus

and by observed and expected heterozygosities. Hardy-Weinberg equilibrium (HWE) was

tested separately for each year and form (anadromous and resident), using the score test (U

test), implemented in GENEPOP v.3.4 (Raymond and Rousset 1995). Significance level

was adjusted to account for multiple testing using Bonferroni correction procedure (k = 52

for single-locus comparisons, ∝ = 0.05/k = 0.00096). As we subsequently used a

parentage allocation procedure (see below), several features were investigated that could

affect our analysis, namely the presence of null alleles, linkage disequilibrium, and pairwise

relatedness in the adult population (Pemberton et al. 1995; Dakin and Avise 2004). The

potential occurrence of null alleles was tested by estimating their frequency using the

34 Brookfield (1996) null allele estimator implemented in MICRO-CHECKER (van

Oosterhout et al. 2004). Linkage disequilibrium among loci was examined using the

genotypic linkage disequilibrium option implemented in GENPEOP v.3.4 (Raymond and

Rousset 1995). Finally, pairwise relatedness in the adult population was estimated using

the identity index implemented in IDENTIX (Belkhir et al. 2002) and was compared to its

random expectation under the hypothesis of a panmictic association after 1,000

permutations.

2.4.4.2 Population genetic structure The hypothesis of genic (allelic frequency) differentiation between anadromous and

resident spawners for each year of sampling was tested using a Fisher exact test at

individual loci as well as over multiple loci using GENEPOP v.3.4 (Raymond and Rousset

1995). The extent of genetic differentiation was quantified by FST estimated by θ (Weir

and Cockerham 1984) using GENETIX v.4.02 (Belkhir et al. 2000). Significance level for

single as well as multilocus FST was tested by 2,000 permutations and was adjusted to

account for multiple testing using Bonferroni correction procedure (k = 13 for single-locus

comparisons, ∝ = 0.05/13 = 0.0038; k = 4 for multilocus comparisons, ∝ = 0.05/4 =

0.0125).

2.4.4.3 Parentage analysis Parental allocation was performed using PASOS 1.0, a software package allowing the

allocation of progeny to either one or two parents in an open system, where parents are

potentially missing (Duchesne et al. 2005). Allocation can be performed whether the sex of

putative parents is known. Using a sequential allocation and simulation procedure, PASOS

provides an estimate of the overall allocation correctness rate as well as an estimate of the

proportion of parents that contributed to reproduction but were not collected. Briefly, to

allocate an offspring, PASOS first searches for the most likely pairs among all potential

pairs of collected parents. The likelihoods are computed according to a fixed error model,

wherein the transmission probability from allele X to X equals 0.98 and the remaining 0.02

is evenly distributed over all remaining offspring alleles for any given locus. At least one

most likely pair is always obtained this way. False parents are filtered out by building the

35 most likely transmission scenario and by subsequently computing the distances between

each transmitted parental allele and its presumed offspring counterpart. If the transmission

distance for one putative parent is not within the maximum offset tolerance (MOT – see

below) determined a priori, this parent is rejected (only a single mismatch – one locus – is

needed for rejection). The MOT is a user-defined parameter (set to either 0, 1, or 2) and

refers to the maximum number of offsets between a parental and an offspring allele that

PASOS accepts as possibly due to a scoring error. For example, 254 and 258 are two

offsets apart within a dinucleotide locus, or one offset apart within a tetranucleotide locus.

Allocation with PASOS was performed following two steps. We first allocated the

offspring using the sequence allocation option, starting with the most informative loci, with

MOT set to 0. Adults sampled in 2000 and 2001 were treated as potential parents for all

juveniles, allowing for repeat spawning and incomplete adult sampling. The resulting curve

provided an estimate of the percentage of parents collected among the pool of spawners

needed to produce the juveniles analyzed, which typically corresponds to the point where

the curve reaches a plateau (Fig. 2-2). The second step consists of performing simulations

with this estimate to produce a simulated curve that fits the true allocation curve. This

provides an estimate of the overall correctness rate (confidence). Simulated offspring were

created from the true parental file with a 2% error model and an offset of 2, the

transmission probability being 0.98 for the focal allele, 0.008 at one offset, and 0.002 at

two offsets. The simulated allocation was performed at MOT 0, to better reflect the true

allocation. True and simulated allocation were also performed at MOT 1 and 2, but we

opted for a conservative approach by keeping MOT at 0, as this was the value that provided

the maximal confidence, albeit at the cost of lowering allocation rate (see “Results” and

“Discussion” sections).

For each allocated offspring, we thus obtained the identity of either one or both parents as

well as the number of offspring assigned to each parental pair and, hence, to each

individual. When a single parent fathered or mothered two juveniles or more, those

36 offspring were further partitioned into full-sib families using COLONY v.1.2 (Wang 2004).

COLONY uses a maximum likelihood method to assign individuals sampled into full-sib

families nested within half-sib families based on offspring genotype, allowing for typing

errors. Thus, even if the identity of the mating partners was not known (i.e., in the cases

where only one parent was found), this exercise provided an estimation of the number of

mates involved in a particular mating event.

2.4.4.4 Analyses from the parental allocation results We first used the results of the allocation procedure to assess if reproduction occurred

between anadromous and resident life-history forms. We then performed an analysis of

variance (ANOVA) to detect any significant difference in individual reproductive success

(mean number of juveniles produced per individual) as well as number of mates between

forms. This analysis was performed by considering both each sex separately and both

sexes combined. We used linear regression analysis and ANCOVA to assess the

relationship between reproductive success, length, and form, as well as between number of

mates (estimated from COLONY), size, and form, for each sex separately. Those tests

were done using JMP v.5.0.1a (SAS Institute Software).

2.5 Results

2.5.1 Characteristics of fish sampled Upstream migration of spawners occurred principally in August and to a lesser extent in

September (Fig. 2-3a). Four heavy floods in 2000 interrupted the monitoring of upstream-

migrating fish and probably resulted in the undersampling of the spawning run. In 2000, 55

fishes were classified as anadromous, either mature (N = 31, 255 to 398 mm fork length,

mean = 312.16 mm) or immature (N = 24, 177 to 244 mm fork length, mean = 207.92 mm)

(Fig. 2-3b). In 2001, 30 were anadromous, with 15 being mature (254 to 394 mm fork

length, mean = 310.71) and 15 immature (range 179 to 241 mm fork length, mean= 201.73

mm) (Fig. 2-3b). A total of 153 and 334 potential resident spawners were caught in 2000

and 2001 respectively, mainly by electrofishing but also in the upstream or downstream

traps (2000, 120 to 258 mm fork length, mean = 155.53 mm; 2001, 120 to 256 mm fork

length, mean = 154.94 mm). The significantly higher number of captures in 2001 reflects

37 an increased electrofishing sampling effort in that year. A total of 981 juveniles were

sampled from 2002 to 2004, with 828 aged 1+ (56 to 115 mm fork length, mean = 84.41

mm) and 153 aged 2+ (80 to 140 mm fork length, mean = 121.54 mm).

2.5.2 Standard genetic statistics The 13 loci used showed moderate to high degrees of polymorphism in the adult

population, with 6 to 30 alleles observed per locus and HE ranging from 0.30 (SfoC28) to

0.89 (SCO216) for an overall expected heterozygosity level of 0.76 (Table 2-2). One

temporal sample (RES 2001) displayed significant departures from HWE with a

heterozygote deficiency observed at five loci (Table 2-2). Three of these, SfoC115,

SfoD100 and SfoD75, showed evidence of null alleles with estimated frequencies of 0.045,

0.052, and 0.061 respectively (see parentage analysis results to see how they were dealt

with for parental allocation). Furthermore, the magnitude of the difference between

observed and expected heterozygosities for those five loci was small, suggesting that non-

conformation to HW equilibrium was not of main concern in this sample. Exact test of

genotypic linkage disequilibrium revealed a higher proportion of significant P values than

expected by chance (17 out of 78 observed, 3.9 out of 78 expected by chance at ∝ = 0.05),

again for the temporal sample RES 2001 only. The mean observed pairwise identity

coefficient did not depart significantly from its expected distribution under the hypothesis

of a random association for any of the temporal samples (ANA 2000, P = 0.117; RES 2000,

P = 0.06; ANA 2001, P = 0.998; RES 2001, P = 0.136). Adults were thus not composed of

individuals more related than expected by chance.

2.5.3 Population genetic structure Significant temporal variation in allele frequency was detected among years within the

adult resident sample (exact test of genic differentiation, P < 0.001), although this variation

was mainly due to the effect of two loci out of 13 (SfoC28 and SfoC115). Population

differentiation between anadromous and resident samples was estimated separately for each

year. No evidence for differentiation was found in 2000, with none of the 13 loci showing

significant allele frequency differences among forms (Table 2-3). In 2001, the

differentiation between anadromous and resident samples was significant (FST = 0.012, P =

38 0.003). However, FST values differed greatly among loci (four loci had negative values,

Table 2-3) and the significance of the differentiation was entirely due to a single locus

(SfoD100). Estimating FST and correcting for the presence of null alleles using FreeNA

(Chapuis and Estoup 2007) did not change any of our results (not shown). Overall, these

analyses do not refute the null hypothesis that anadromous and resident adult fish are part

of the same breeding population.

2.5.4 Parentage analysis A total of 494 potential spawners (85 anadromous and 409 resident) and 974 juveniles (1+

and 2+) were used for parentage allocation. A total of 315 juveniles were assigned to a

single parent, whereas 42 were assigned to both parents, leading to a total allocation rate of

21%. These 42 juveniles were either half-sibs or unrelated, suggesting that they were

offspring of 42 different couples. That is, no more than one offspring was assigned to the

same couple. The sequential allocation curve did not reach a true plateau but decreased

more slowly toward the end of the sequence (Fig. 2-2). The allocation rate estimated from

the last loci added was used to estimate the fraction of sampled spawners (20%, see Fig. 2-

2) even though the plateau was not attained because simulation suggested stabilization of

the curve after adding one or two more loci (data not shown). However, parental allocation

was complicated by the occurrence of null alleles, which may cause the false exclusion of a

true parent. Any such bias would be conservative (i.e., excluding true parents rather than

including false parents, Marshall et al. 1998; Dakin and Avise 2004). On the other hand,

this can have an impact on the estimation of the proportion of sampled/missed spawners

and, consequently, on the estimated confidence in our allocations. PASOS is not designed

to account for null alleles as the error model used in the simulation procedure allows error

at a maximum of two offsets apart from the focal allele, whereas the error associated with

null alleles is not necessarily restricted to alleles close to the focal allele. Because removal

of loci with null alleles from our parentage analysis decreased confidence significantly

(results not shown), we chose to retain them in the analysis, making an upward correction

to the estimated proportion of sampled spawners as follows. We estimated the probability

of a false exclusion given by the three loci showing null alleles to be 12% (see formula

developed by Dakin and Avise 2004). This 12% was added to the 20% of sampled parents

39 (estimated by the allocation curve given by PASOS). We thus concluded that a maximum

of 32% of the parents were sampled, and therefore that 68% of the spawners were missing.

This estimate was subsequently used in the simulation procedure, which yielded an

allocation correctness rate of 87%. A total of 72 spawners had two or more offspring

(maximum of 19), and their progeny was divided into full-sib families with COLONY.

Family sizes were small, ranging from one to four individuals (mean = 1.37). That is, no

more than four individuals shared the same unsampled parent. Analysis with COLONY

allowed us to find full-sib individuals in our sample, which could not have been detected

with PASOS because of the high proportion of unsampled spawners.

2.5.5 Mating patterns Out of the 42 couples reconstructed from the parentage allocation analysis, half (21)

involved an anadromous and a resident spawner, clearly showing reproduction and viability

of offspring between the life-history forms. The sex of the adults was known for 13 of those

21 interform crosses and in every case, the male was the resident fish. The remaining

crosses were anadromous-anadromous, producing five offspring, and resident-resident,

producing 16 offspring. The mean number of partners estimated with COLONY did not

differ between life-history form and sex (ANOVA, F1,26 = 0.995, P = 0.33 for form; F1,26 =

0.024, P = 0.88 for sex) and ranged from one to eight (mean = 3.25) for anadromous and

one to seven (mean = 2.52) for resident fish. When anadromous females were found

mating with multiple partners, males were either all resident or they were composed of a

single anadromous fish and many resident fish (three resident males in one mating event,

four in the other). No more than one anadromous male was found mating with the same

female. However, the number of partners must be viewed as conservative as it is limited by

the total number of offspring assigned to each individual.

2.5.6 Individual reproductive success Globally, individual reproductive success of anadromous fish (total number of offspring

assigned to each spawner, 1+ and 2+ combined) was significantly higher than reproductive

success of resident fish (ratio anadromous/resident = 2.9) and the same was true for

variance in individual reproductive success (Table 2-4). This difference was due to

40 anadromous females having a higher reproductive success than resident females. No

difference was observed among males (only four anadromous males were available for this

analysis, Table 2-4).

2.5.6.1 Female determinants of reproductive success Reproductive success was positively related to length for females and explained 46% of the

variation (linear regression, F = 20.75, P = 0.0001, R2 = 0.46, Fig. 2-4a). This relationship

seems to be driven by a few anadromous females that dominated spawning, but a quadratic

regression did not fit the data better than the linear one (F-test, F = 2.19, P = 0.15). An

analysis of covariance revealed that the effect of the life-history form on reproductive

success was not significant when length was included (F1,22 = 4.28, P = 0.05 for length;

F1,22 = 0.07, P = 0.79 for form). The interaction term was not significant and thus the effect

of length on reproductive success was the same within each form (length by form, F1,22 =

1.19, P = 0.25). The number of mates was not related to length in either form (ANCOVA,

F1,12 = 0.13, P = 0.73 for length; F1,12 = 0.02, P = 0.90 for form; F1,12 = 0.09, P = 0.77 for

the interaction term; Fig. 2-4b).

2.5.6.2 Male determinants of reproductive success For males, neither length nor life-history form had a significant effect on reproductive

success (ANCOVA, F1,28 = 1.61, P = 0.21 for length; F1,28 = 1.35, P = 0.26 for form; F1,28 =

1.47, P = 0.24 for the interaction term; Fig. 2-5). However, the low number of anadromous

males (four) in this analysis limits the strenght of our conclusions. Analyses involving

numbers of mates were omitted because mate numbers for anadromous males were

available for two individuals only.

2.6 Discussion

2.6.1 Gene flow and mating patterns Our results showed that anadromous and resident brook charr in this system most likely

belonged to the same breeding population based on both FST and parentage analysis.

Reproduction between the forms occurred principally through anadromous females and

resident males, and confirmed previous behavioral observations in this system and in other

41 species (Wood and Foote 1996; Schreiber and Diefenbach 2005). For instance, Wood and

Foote (1996), despite extensive observations, never observed male sockeye (anadromous,

Oncorhynchus nerka) orienting to female kokanee (resident), but male kokanees were

frequently observed as sneak males to sockeye females, either in the absence or presence of

a sockeye male. Schreiber and Diefenbach (2005) observed anadromous female brown trout

and resident males over the same spawning grounds, and the unequal sex ratio found in

favor of females led them to suggest a frequent interbreeding of anadromous females with

resident males.

Although anadromous males did not appear to mate with resident females in this study,

reproduction between bigger males (normal phenotype) and smaller females (dwarf

phenotype) was suggested in a lacustrine Arctic charr population where normal males

appear to fertilize eggs of normal females first, then those of dwarf females, whose

spawning period was delayed (Jonsson and Hindar 1982). In our study system, the resident

females spawn first- about two weeks before anadromous females- and it is the resident

males that take part in both reproductive events, exhibiting an extended spawning window

overlapping the two spawning periods. It is possible that the predominance of the pairing of

anadromous females with resident males, as well as the few offspring assigned to

anadromous-anadromous mating (only five) can be explained in part by the apparent rarity

of males within the anadromous run. Biased sex ratio in favor of anadromous females is

commonly seen among salmonids, notably in Arctic charr and brown trout (Kristoffersen et

al. 1994; Rikardsen et al. 1997; Doucett et al. 1999; Schreiber and Diefenbach 2005). Sex

was known for 13 anadromous fish, of which only four were males. Indeed, the fact that

sex was most of the time undetermined could argue in favor of a bias in sex ratio favoring

females. Most anadromous males are usually already differentiated in August, having a

more laterally compressed reddish belly and a small kype. Most anadromous fish caught in

the upstream trap exhibited few morphological signs enabling us to clearly identify the sex.

We believe that these fish were most likely females. Moreover, sizes of reproducing

anadromous fish entering the Morin Creek (from 254 mm to 398 mm fork length) were at

the low end and almost outside the size range of anadromous charr in the Sainte-Marguerite

42 River system (measuring from 312 mm to 561 mm fork length, data not shown). Females in

this system are typically smaller than males (females, mean = 421.46 mm fork length;

males, mean = 448.42 mm fork length, t test, t97= -2.5 , P = 0.01). It is noteworthy that

such a possible biased sex ratio toward females occurs in Morin Creek as we know that sex

ratio at downstream migration is 1:1 in this stream (Thériault and Dodson 2003) and that

the sex ratio is also 1:1 during both the downstream and the upstream migration in the main

stem of the river (Lenormand 2003). We hypothesize that availability of adequate

spawning grounds or resting pools is size-limiting for anadromous charr in small tributary

creeks, selecting for smaller anadromous fish and, consequently, mostly females.

2.6.2 Reproductive success Anadromous fish had a higher individual reproductive success than residents, and this was

due to the fact that anadromous females were bigger and thus producing more juveniles

than resident fish. Size in salmonid females has often been reported as an important

determinant of reproductive success (Fleming and Gross 1994; Fleming et al. 1997),

accounting for up to 80% of the variability in the reproductive success of Atlantic salmon

(Fleming 1996). This positive relationship is often related to higher fecundity and larger

eggs among bigger females (Morita and Takashima 1998; Hendry et al. 2001), to better

access to preferential breeding sites (Foote 1990) and to the digging of deeper nests,

providing increased protection against scouring (Steen and Quinn 1999). A greater number

of mates has also been proposed as a determinant of higher reproductive success for

females through genetic and ecological benefits in unstable environments (see the paper of

Garant et al. 2001 for discussion about Atlantic salmon). In our study, females were found

to have multiple partners (one to eight, mean 3.38), regardless of size and form, and this

range must be viewed as conservative because the number of partners was limited by the

number of offspring assigned to each parent. Analyses linking the number of mates and

reproductive success were omitted due to the probable artifact related to the very small

numbers of offspring sampled for the majority of individuals, inevitably resulting in a

positive relationship.

43 Anadromous and resident males were found to have similar reproductive success, but this

result must be considered with caution as only four anadromous males were available for

this analysis. However, none of the four anadromous males, although bigger, produced a

number of offspring outside the resident male’s range. Therefore, no association of size

with reproductive success was found. Size is expected to be a determinant of reproductive

success in males due to its relation to dominance: Dominant males usually win in

intrasexual competition for access to females (Quinn and Foote 1994; Fleming 1998;

Blanchfield et al. 2003; Dickerson et al. 2005). However, in many salmonid studies, little

or no relationship has been found between male size and reproductive success (Garant et al.

2001; Jones and Hutchings 2002; Blanchfield et al. 2003; Seamons et al. 2004a; Dickerson

et al. 2005). Other factors such as arrival timing, ripeness of available females, numbers of

mates, or operational sex ratio, allowing even small males to mate in years where more

females are available, may influence reproductive success (Seamons et al. 2004a;

Dickerson et al. 2005). In our study system, it is likely that resident males use alternative

tactics to increase their reproductive success, being less selective or more opportunistic, as

illustrated by individual males fertilizing eggs of both resident and anadromous females.

This suggests that they might adopt an alternative behavior (for example, sneaking instead

of fighting) in the presence of bigger anadromous males to gain access to mating.

2.6.3 Where have all the parents gone? Parentage allocation in an entirely wild, open system without partial complementary

behavioral information on mating events, has rarely been attempted (but see the studies of

Seamons et al. 2004 a, b; Dickerson et al. 2005). The parentage allocation procedure used

in PASOS, combined with a correction owing to null alleles, allowed us to estimate that

approximately 68% of the spawners needed to have produced the pool of juveniles

analyzed were missing from the pool of putative parents. This high proportion of missing

spawners limits our allocation success by forcing us to perform conservative allocations

(MOT set to 0 and hence no mismatch tolerated) to achieve an acceptable correctness rate

(87%). First, we may have missed anadromous spawners because of flooding events that

were seen in both years, principally in 2000. Those events probably allowed anadromous

spawners to pass by without being intercepted at the trap, as seen in a similar study with

44 steelhead trout (Seamons et al. 2004b). Second, resident spawners were probably missed

because we electrofished in a single pass in open sections, which is certainly not the most

efficient electrofishing method (Rosenberger and Dunham 2005). Moreover, the deepest

sections had to be omitted. Spawners breeding outside the study stream where their

progeny may have immigrated into the stream during their first year of life could also

explain in part the high proportion of missing spawners. However, the observation that

most of the juveniles successfully allocated were done so to only one parent suggests that

the missing parent must have been reproducing somewhere in the stream, and thus it is not

consistent with the hypothesis of juvenile immigration from outside the study system.

Although an allocation success rate of 21% seems small, the allocated juveniles are

nevertheless representative of the reproductive outcome in the creek. We sampled a large

proportion of the stream (49% by stream length), and the sections omitted were not

preferential habitat of juvenile brook charr. Moreover, half-sib offspring were not clustered

in one or adjacent sampling sections. Qualitative analysis of our data showed that only

members of five half-sib families out of 44 were sampled in the same 300 m sampling

section. All other juveniles sharing one parent were found all along the stream, from

several hundred meters to 3 km apart, suggesting considerable dispersal during the first

and/or second year of life or, at least in some cases, by movement between spawning events

by the shared parent. We thus concluded that we had equal chances of sampling members

of different families.

2.6.4 Conclusion This study directly assessed for the first time the genetic mating system and individual

reproductive success of a population of salmonids composed of both anadromous and

resident forms, under natural conditions, where males and females may adopt either tactic.

Gene flow occurred between the two forms and was mediated by resident males mating

with both resident and anadromous females. Reproduction between anadromous males and

resident females was not seen in this study. Discrepancies were found between the sexes in

terms of determinants of reproductive success. Size in males did not have any influence on

45 individual reproductive success, whereas larger females (and hence most likely to be

anadromous) were more successful. This finding corroborates other studies suggesting that

anadromy would be more beneficial to females than males (Jonsson and Jonsson 1993;

Fleming 1998) and provides evolutionary explanations of why residency is not observed

among females in some populations or species (especially Atlantic salmon, Hutchings and

Jones 1998; and Pacific salmon species as chinook salmon, Unwin et al. 1999; and masu

salmon, Tsiger et al. 1994). However, for females to persist in some populations as

residents, benefits must be provided. One such benefit is the higher survival rate associated

with residency, which can be as low as 10% in saltwater in the first year following

migration and as high as 50% in freshwater for the same cohort that remains in freshwater

(Dodson and Lenormand, unpublished data). However, such an advantage would apply

equally to both sexes. Whereas resident males, by adopting a “sneaking” reproductive

tactic, increased their reproductive success by mating with females of all sizes in all

habitats, females may also adopt different tactics in selecting spawning sites (Holtby and

Healey 1986; Seamons et al. 2004a). We suggest that resident females would enjoy an

advantage in accessing spatially constrained spawning areas in small tributary streams

unavailable to larger females. Structural complexity has recently been shown to influence

the competitive ability of males pursuing alternative reproductive tactics in mites, and thus

it is likely to influence the tactic frequency in different species or populations (Lukasik et

al. 2006). Spatial complexity associated with small and higher-order tributaries could

explain why residency is virtually absent within the main stem of the river and why only

small anadromous fish composed the Morin anadromous run. Larger anadromous females

would probably outcompete and exclude smaller females from larger spawning areas,

typically associated with larger rivers. However, large females would be at a disadvantage

in the more restricted spawning habitats associated with tributaries. Small tributary streams

may thus be viewed as a refuge for residency or, at least, a way of ensuring that the resident

tactic persists within females.

46

2.7 Acknowledgments We acknowledge A. Boivin, S. Bordeleau, M. Foy-Guitard, S.-P. Gingras, Fannie Martin,

François Martin, A. Ménard, G. Morinville, L. Papillon, L. V. St-Hilaire Gravel, and R. St-

Laurent for the field assistance and laboratory work. The authors would like to thank P.

Duchesne for the helpful advice and assistance in the use of the software PASOS and D.

Garant for the helpful comments on a draft version of this manuscript. Funding of this

project was provided to J.J.D. and L.B. by NSERC of Canada (Strategic Grant and

Collaborative Special Projects), the Fondation de la Faune du Québec, the Government of

Québec (FAPAQ), the Government of Canada (Economic development), and the financial

partners of AquaSalmo R&D. This study is a contribution to the program of CIRSA

(Centre interuniversitaire de recherche sur le saumon Atlantique) and Quebec-Ocean. V.T.

was financially supported by funding from NSERC and FQRNT. The experiments

conducted comply with the current Canadian laws.

47

2.8

Tab

les

Tabl

e 2-

1. P

CR

con

ditio

ns fo

r the

13

loci

am

plifi

ed.

PCR

Loci

A

mpl

ifica

tion

stat

e

Rx

volu

me

(µL)

Rx

buff

er1

(µL)

dN

TPs2

(µL)

Ta

q (U

) D

NA

(n

g)

Cyc

le (t

empe

ratu

re in

Cel

cius

deg

res)

1 Sf

oC11

3/Sf

oC28

/Sfo

B52/

SfoC

129

quin

tupl

ex

20

2 0.

8 0.

3 8

5min

at 9

5, 3

5x(4

5s a

t 95,

45s

at 5

6, 4

5s a

t 72)

, 10m

in a

t 72

2 Sf

oC11

5/Sf

oD10

0/Sf

oD75

tri

plex

20

2

0.8

0.3

8 5m

in a

t 95,

35x

(45s

at 9

5, 4

5s a

t 58,

45s

at 7

2), 1

0min

at 7

2 3

SCO

204/

SCO

216/

SCO

218

sim

plex

15

1.

5 0.

3 0.

2 8

3min

at 9

4, 3

8x(3

0s a

t 94,

30s

at 6

0, 3

0s a

t 72)

, 7m

in a

t 72

4 Sf

o262

Lav

sim

plex

10

1

0.3

0.2

8 3m

in a

t 94,

35x

(30s

at 9

4, 3

0s a

t 60,

45s

at 7

2), 7

min

at 7

2 5

Sfo2

66La

v si

mpl

ex

10

1 0.

3 0.

2 8

3min

at 9

4, 3

5x(3

0s a

t 94,

30s

at 5

2, 4

5s a

t 72)

, 7m

in a

t 72

1 co

mpr

ise

10 m

M T

ris-H

CL

[ph

9.0]

, 1.5

mM

MgC

l2, 0

.1%

Trit

onX

-100

, 50m

M K

Cl

2

10 m

M e

ach

dNTP

48

Table 2-2. Number of samples (N), number of alleles (A), FIS, observed (HO) and expected (HE) heterozygosities, and probabilities of conforming to Hardy-Weinberg equilibrium (P(HW), score U test) for each locus and each temporal sample (RES = resident, ANA = anadromous) separately. Bold values are significant at ∝ = 0.0096 following Bonferroni corrections.

2000 2001 Locus A ANA RES ANA RES

SfoB52 12 N 32 95 15 323 A 7 9 7 12 FIS -0.054 0.160 0.048 0.044 HO 0.81 0.65 0.80 0.77 HE 0.76 0.77 0.81 0.81 P(HW) 0.8465 0.0191 0.4848 0.0066 SfoC113 9 N 32 95 15 323 A 6 7 6 9 FIS -0.093 0.013 -0.043 0.005 HO 0.84 0.73 0.80 0.74 HE 0.76 0.73 0.74 0.75 P(HW) 0.7546 0.2372 0.5893 0.0008 SfoC129 7 N 32 95 15 322 A 5 6 5 7 FIS -0.021 0.128 0.000 0.019 HO 0.75 0.62 0.73 0.73 HE 0.72 0.71 0.71 0.74 P(HW) 0.2523 0.0120 0.1192 0.0890 SfoC28 9 N 32 95 15 323 A 6 8 5 8 FIS -0.108 0.020 0.138 0.079 HO 0.59 0.54 0.27 0.51 HE 0.53 0.54 0.30 0.56 P(HW) 0.7300 0.4056 0.3206 0.0918 SfoC88 6 N 32 95 15 322 A 5 6 4 6 FIS 0.026 -0.097 -0.213 0.024 HO 0.63 0.68 0.73 0.64 HE 0.63 0.62 0.59 0.66 P(HW) 0.3889 0.7596 0.9427 0.0230

49 SfoC115 16 N 32 94 15 322 A 7 12 5 15 FIS 0.146 0.063 -0.212 0.115 HO 0.47 0.44 0.60 0.59 HE 0.54 0.46 0.48 0.67 P(HW) 0.2163 0.4483 1.0000 0.0003 SfoD100 10 N 32 93 15 322 A 8 10 6 10 FIS 0.206 0.078 -0.183 0.118 HO 0.59 0.75 0.80 0.72 HE 0.73 0.81 0.66 0.81 P(HW) 0.0791 0.1036 0.9509 < 0.001 SfoD75 13 N 32 94 15 321 A 10 11 8 13 FIS 0.090 0.080 0.058 0.136 HO 0.75 0.79 0.73 0.71 HE 0.81 0.85 0.75 0.83 P(HW) 0.1699 0.0249 0.1482 < 0.001 SCO204 15 N 32 90 15 322 A 7 9 6 15 FIS 0.113 0.062 -0.197 0.002 HO 0.69 0.74 0.87 0.81 HE 0.76 0.79 0.70 0.81 P(HW) 0.2271 0.2531 0.9715 0.2030 SCO216 18 N 32 92 15 322 A 15 13 9 18 FIS 0.091 0.069 -0.057 0.042 HO 0.81 0.82 0.93 0.86 HE 0.89 0.87 0.86 0.89 P(HW) 0.1305 0.0954 0.6490 0.0264 SCO218 14 N 32 90 15 322 A 7 9 6 14 FIS -0.007 0.007 -0.170 -0.023 HO 0.81 0.79 0.87 0.82 HE 0.79 0.79 0.72 0.80 P(HW) 0.6297 0.7035 0.9580 0.3894 Sfo262Lav 19 N 31 87 15 319 A 12 13 7 19 FIS -0.033 -0.074 0.115 0.008 HO 0.87 0.91 0.73 0.84 HE 0.83 0.84 0.80 0.84

50 P(HW) 0.6626 0.9460 0.2865 0.5147 Sfo266Lav 30 N 32 92 15 322 A 13 21 7 29 FIS 0.002 -0.008 0.239 0.048 HO 0.88 0.86 0.60 0.83 HE 0.86 0.85 0.76 0.87 P(HW) 0.0688 0.1244 0.0611 < 0.001 Global N 31-32 87-95 15 319-323 A moy 8.3 10.3 6.3 13.5 A tot 108 134 81 175 HO 0.73 0.72 0.73 0.73 HE 0.74 0.74 0.68 0.77 P(HW) 0.0709 0.0052 0.6102 < 0.001

51

Table 2-3. Genetic differentiation between anadromous and resident brook charr estimated by θST for each locus. N = 32 anadromous and 98 resident fish in 2000; N = 15 anadromous and 323 resident fish in 2001. ** P < 0.001 following 2,000 permutations with alpha adjusted for multiple testing using Bonferroni correction (∝ = 0.0038 for single-locus comparisons and ∝= 0.0125 for multilocus comparisons).

Locus θST 2000 θST 2001

SfoB52 -0.0035 -0.0057 SfoC113 0.0071 -0.0098 SfoC129 -0.0046 0.0146 SfoC28 -0.0007 0.0284 SfoC88 -0.0023 -0.0067 SfoC115 -0.0005 0.0176 SfoD100 0.0006 0.0573 ** SfoD75 0.0027 0.0097 SCO204 -0.0062 0.0227 SCO216 0.0027 0.0116 SCO218 -0.0035 0.0126 Sfo262Lav 0.0147 -0.0105 Sfo266Lav -0.0010 0.0172

Multilocus 0.0007 0.0124 **

52

Tabl

e 2-

4. N

umbe

r of s

ampl

es (N

), m

ean,

var

ianc

e, a

nd ra

nge

of in

divi

dual

repr

oduc

tive

succ

ess (

RS

- num

ber o

f off

sprin

g as

sign

ed to

in

divi

dual

s) fo

r mal

es a

nd fe

mal

es to

geth

er (o

vera

ll) a

nd se

para

tely

acc

ordi

ng to

life

-his

tory

form

. Mea

ns a

nd v

aria

nces

of l

ife-h

isto

ry

form

s are

com

pare

d w

ith A

NO

VA

and

Lev

ene's

test

resp

ectiv

ely.

R

S O

vera

ll

RS

Fem

ales

RS

Mal

es

N

M

ean

Var

ianc

eR

ange

N

M

ean

Var

ianc

e R

ange

N

M

ean

Var

ianc

eR

ange

A

nadr

omou

s 31

4.

48

18.5

21-

19

98.

2235

.94

2-19

4

3.25

4.25

1-5

Res

iden

t 13

8 1.

88

2.15

1-10

17

2.18

3.9

1-9

28

2.39

3.73

1-10

F-Va

lue

(df)

33

.62

(1, 1

67)

39.9

7(1

, 167

)

14

.75

(1, 2

4)17

.96

(1, 2

4)

0.

68(1

, 30)

0.37

(1, 3

0)

P-Va

lue

<0

.000

1 <0

.000

1

0.01

660.

0003

0.41

610.

5466

53

2.9 Figures

Figure 2-1. Location of study area, sampling traps, and electrofishing sites.

54

0

0.2

0.4

0.6

0.8

1

Sfo266

Lav

Sfo262

Lav

Sco21

8

Sco21

6

Sco20

4

SfoC11

5

SfoD10

0

SfoD75

SfoB52

SfoC11

3

SfoC12

9

SfoC28

SfoC88

Loci

Rat

e of

juve

nile

allo

catio

n (%

)

Figure 2-2. Rate of juvenile allocation obtained with PASOS as a function of cumulative number of loci, and using a maximum offset tolerance set to zero (MOT 0 – see text). A plateau is starting to appear at the end of the cumulative curve and the 20% rate attained at SfoC88 was used as a first estimate of the proportion of sampled spawners.

55 (a)

0

4

8

12

16

20

30/6

10/7

20/7

30/7 9/8 19

/829

/8 8/9 18/9

28/9

8/10

18/10

28/10

Date (dd/mm)

Num

ber o

f fis

h

(b)

0

2

4

6

8

10

12

14

120 160 200 240 280 320 360 400Length (mm)

Num

ber o

f fis

h

Figure 2-3. (a) Number of fish caught in the upstream migration trap in 2000 (black) and 2001 (grey) and (b) corresponding length distribution.

56 (a)

0

4

8

12

16

20

100 150 200 250 300 350 400Length (mm)

Num

ber o

f offs

prin

g

(b)

0

1

2

3

4

5

6

7

8

9

100 150 200 250 300 350 400Length (mm)

Num

ber o

f mat

es

Figure 2-4. Reproductive success (number of offspring assigned per individual) (a) and number of mates (b), as a function of body size for female spawners. Open circles are resident life-history fish, while closed circles are anadromous life-history fish.

57

0

2

4

6

8

10

12

100 150 200 250 300 350 400Length (mm)

Num

ber o

f offs

prin

g

Figure 2-5. Reproductive success (number of offspring assigned per individual) as a function of body size for male spawners. Open circles are resident life-history fish, while closed circles anadromous life-history fish.

Chapitre 3. Heritability of life-history tactics and genetic correlation with body size in a natural population of brook charr (Salvelinus fontinalis)

59

3.1 Résumé La présence d’une forme anadrome, qui entreprend une migration vers l’eau salée avant la

reproduction, de pair avec une forme entièrement résidente, qui passe tout sa vie en eau

douce, est un dimorphisme bien connu chez les salmonidés. Quoique ce dimorphisme soit

commun, l’influence génétique et environnementale sur l’adoption d’une tactique de vie en

particulier a rarement été étudiée sous conditions naturelles. Nous avons utilisé des

pedigrees reconstruits à partir de marqueurs microsatellites couplés à un « modèle animal »

pour estimer la variance génétique additive de la tactique adoptée (anadrome vs. résident)

dans une population naturelle d’omble de fontaine, Salvelinus fontinalis. Nous avons de

plus estimé la corrélation génétique entre la tactique adoptée et des traits phénotypiquement

corrélés, la taille et la forme du corps. Une héritabilité significative a été mise en évidence

pour la tactique d’histoire de vie (entre 0.53 et 0.56, tout dépendant du pedigree utilisé)

ainsi que pour la taille (0.44 à 0.50). Il y avait de plus une corrélation génétique

significative entre ces deux traits, où les anadromes étaient génétiquement associés à de

plus grandes tailles à l’âge de 1 an (rG = -0.52 et -0.61). Nos résultats indiquent que la

tactique d’histoire de vie dans cette population a le potentiel de répondre à une sélection qui

agirait soit directement sur la tactique elle-même, soit indirectement sur la taille. Cette

étude est une des seules à avoir utilisé des pedigrees basés sur des relations plein-frères

pour estimer avec succès des paramètres de génétique quantitative sous conditions

naturelles.

60

3.2 Abstract A common dimorphism in life-history tactic in salmonids is the presence of an anadromous

pathway involving a migration to sea followed by a freshwater reproduction, along with an

entirely freshwater resident tactic. Although common, the genetic and environmental

influence on the adoption of a particular life-history tactic has rarely been studied under

natural conditions. Here, we used sibship-reconstruction based on microsatellite data and an

‘animal model’ approach to estimate the additive genetic basis of the life-history tactic

adopted (anadromy vs. residency) in a natural population of brook charr, Salvelinus

fontinalis. We also assess its genetic correlation with phenotypic correlated traits, body size

and body shape. Significant heritability was observed for life-history tactic (varying from

0.52 to 0.56 depending on the pedigree scenario adopted) as well as for body size (from

0.44 to 0.50). There was also a significant genetic correlation between these two traits,

whereby anadromous fish were genetically associated with bigger size at age 1 (rG = -0.52

and -0.61). Our findings thus indicate that life-history tactics in this population have the

potential to evolve in response to selection acting on the tactic itself or indirectly via

selection on body size. This study is one of the very few to have successfully used sibship-

reconstruction to estimate quantitative genetic parameters under wild conditions.

61

3.3 Introduction Organisms that face environmental heterogeneity commonly adjust their phenotype in

response to cues that give information about the current or future state of the environment

(Roff and Bradford 2000). Such phenotypic plasticity is shown in an extreme fashion by

the existence of discrete morphs within a population, such as dimorphism in defensive

structures (horned vs. hornless beetle, Moczek et al. 2002), in feeding specializations

(omnivorous and carnivorous morphs of toad tadpoles, Frankino and Pfennig 2001), in life

cycle (wing dimorphism in insects, Roff 1994b) or in mating tactics (satellite vs. territorial

males in fish, Aubin-Horth and Dodson 2004). Many of those discrete phenotypes

generally involve environmentally cued threshold traits. Threshold traits are thought to be

based on underlying characteristics that vary in a continuous way, called the ‘liability’, with

a threshold of sensitivity (Roff 1996). Individuals lying above the threshold develop into

one morph while individuals below the threshold develop into the alternate morph (Hazel et

al. 1990; Falconer and Mackay 1996; Roff 1996). Characteristics such as the concentration

of juvenile hormone, lipid storage or growth efficiency have been shown to affect the

adoption of alternate morphs, and are hypothesized as potential underlying traits (Roff et al.

1997; Thorpe et al. 1998; Forseth et al. 1999; Emlen and Nijhout 2000). Because it reflects

and/or influences many other factors related to the adoption of alternate morphs, body size

is the most commonly reported liability trait (Moczek et al. 2002; Aubin-Horth and Dodson

2004). The threshold trait framework, associated with the conditional strategy theory,

relies on the basis of fitness trade-offs, where an individual expresses the phenotype that

yields the higher fitness payoffs for its particular condition (i.e. depending on the value of

its liability trait), even though it may have a lower overall average fitness (Gross 1996).

The heritable basis of a given phenotypic trait, and its genetic correlation with other traits,

must be established to predict its response to selection and thus its evolutionary potential

(Falconer and Mackay 1996; Kruuk 2004). Threshold traits are likely to have a polygenic

basis, and most polygenic traits bear significant levels of genetic variation (Roff 1996).

Indeed, many studies have reported a heritable basis for threshold traits, mainly through

62 heritability of their liability traits (reviewed in Roff 1996; see also Mousseau et al. 1998;

Ostrowski et al. 2000; Garant et al. 2003). Thresholds of sensitivity may also harbor

genetic variation themselves, such that threshold values that signal the switch between

alternative phenotypes also differ among genotypes (Hazel et al. 1990; Emlen 1996;

Hutchings and Myers 1994; Hazel et al. 2004). However, most studies that have

documented the quantitative genetics of threshold traits were performed in laboratory or

controlled experiments (but see Garant et al. 2003; Wilson et al. 2003a). Since there is

accumulating evidence that heritability and genetic correlations of traits are influenced by

their environments (reviewed in Charmantier and Garant 2005 and in Sgrò and Hoffmann

2004), direct measures of quantitative genetic parameters in nature are essential and may

improve our understanding of how evolution takes place in the wild.

Following hatching in freshwater, many populations of salmonid fishes (trouts, salmons

and charrs) may either remain in freshwater during their entire lives (residency tactic) or

undertake a feeding migration to sea before returning to freshwater to spawn (anadromy

tactic). The conditional strategy framework and threshold trait hypothesis have been

employed to understand the evolutionary basis of this common dimorphism in salmonids

(Hutchings and Myers 1994; Gross 1996; Thorpe et al. 1998; Aubin-Horth and Dodson

2004). Factors such as body size, growth rate, lipid reserves (Rowe and Thorpe 1990;

Rikardsen et al. 2004), and growth efficiency (Forseth et al. 1999; Morinville and

Rasmussen 2003) have all been suggested as potential underlying traits influencing the

adoption of one form or the other. There may be a critical time when a particular threshold

value that is genetically influenced and variable among individuals must be exceeded in

order for reproduction to occur (Hutchings and Myers 1994; Thorpe et al. 1998). If this

threshold is not exceeded, migration occurs and anadromy is expressed. Some studies have

estimated the heritability of adopting a resident life-history, by documenting the genetic

basis of early sexual maturation, in controlled experiments for aquaculture purposes

(Silverstein and Hershberger 1992; Heath et al. 1994; Wild et al. 1994; Mousseau et al.

1998). To our knowledge, however, no studies have attempted to estimate heritability of

anadromy and residency in the wild.

63

The development of hypervariable genetic markers and analytical tools related to kinship

and parentage, have eased the estimation of quantitative genetic parameters in nature

(Garant and Kruuk 2005). Namely, relationships among wild individuals, which are

essential to build reliable pedigrees and estimate quantitative genetic parameters, can now

be accurately established (Garant and Kruuk 2005). Moreover, the so-called ‘animal

model’ is being increasingly used in natural conditions for estimating quantitative genetic

parameters (reviewed in Kruuk 2004; see also Garant et al. 2005b; Charmantier et al. 2006;

Wilson et al. 2006). However, very few studies have yet combined sibship-reconstruction

based on genetic data and an ‘animal model’ approach to estimate quantitative genetic

parameters in the wild.

Using this framework, our main objective is to elucidate the mechanisms influencing the

expression of a dichotomous life-history in a natural population of brook charr, Salvelinus

fontinalis, which contains both anadromous and resident individuals living in sympatry.

Recent studies have demonstrated frequent mating between anadromous and resident

individuals in this population, mainly through resident males mating with anadromous

females (Thériault et al. 2007a). Also, body size in this population has been shown to be

correlated with the adoption of anadromy and residency (Thériault and Dodson 2003).

Growth efficiencies also differ between anadromous and resident individuals; before

migration, future migrants exhibit lower growth efficiencies than future residents and

higher associated metabolic costs (Morinville and Rasmussen 2003). Also, future migrants

inhabit habitats of faster water currents, and thus it is not clear if their higher metabolic

costs reflect higher standard metabolic rate or higher swimming costs related to the

exploitation of a more energetically costly habitat (Morinville and Rasmussen 2006).

Morphological analyses confirmed previous results on differential habitat use: migrants

have a more streamlined morphology than resident fish, which is what is expected in faster

current velocity habitat because such an elongated morphology incurs lower swimming

costs (Boily and Magnan 2002; Morinville and Rasmussen 2007).

64

Altogether, these results raise the hypothesis that dimorphism in life-history tactics in this

brook charr population represents a threshold trait with potential underlying characters

related to energetic budget. Here, we aimed to estimate the heritability of this threshold

trait (residency/anadromy) by means of pedigree reconstruction assisted by molecular

markers and the ‘animal model’ approach. We also quantified heritability of morphological

traits (body size and shape) and tested whether phenotypic correlations previously observed

among these traits and the life-history tactics (Thériault and Dodson 2003; Morinville and

Rasmussen 2006 and 2007) translate into significant genetic correlations.

3.4 Material and Methods

3.4.1 Study Site and Sampling Fishes were collected from the Morin Creek (average 5.6 m wide, 0.3 m deep, See Figure

3-S1), a tributary of the Sainte-Marguerite River, Quebec, Canada. An impassable

waterfall (75 m high) is located 4 km upstream from the mouth of the tributary. Sampling

was conducted in a 2.5 km section below this waterfall. Previous studies have shown that

anadromous brook charr undergo upstream migration into this tributary for spawning, and

that reproduction between anadromous and resident fish is common (Thériault et al.

2007a).

No obvious external expression of smoltification occurs in migrant brook charr

(McCormick et al. 1985 and V. Thériault, personal observation) making it very difficult to

differentiate a migrant from a resident until the moment of migration. We identified

migrants as fish captured in trap nets during downstream migration; previous mark-

recapture studies on the same system have shown that these fish were true migrants

(Thériault and Dodson 2003). Fish captured in streams following the migration period

were defined as residents. Outstream migration of first-time migrants occurs between mid-

May to mid-June and involves 1 and 2 year old fish in this system (Thériault and Dodson

2003). Two cohorts were sampled: cohort 1 was composed of 1+ fish (designating

65 individuals somewhat older than 1 year of age as they are hatched in early May) sampled in

2002 and 2+ fish in 2003, and cohort 2 was composed of 1+ sampled in 2003 and 2+

sampled in 2004. The trap nets were installed 1 km from the mouth of the stream and were

operated from mid-May to mid-June for the three years of sampling. They were visited

twice daily and the following morphological measures were taken in the field in 2002 and

2003 (see Morinville and Rasmussen, 2007, for detailed methodology): fork length (FL),

standard length (SL), body depth (DEP), maximum body width (WID), peduncle depth

(PED), caudal fin height (CAUD), pectoral fin length (PECT) and pelvic fin length

(PELV). The adipose fin was also clipped and preserved in 95% ethanol for subsequent

genetic analyses, and all fish were released. Resident juveniles were captured using a

backpack electro-fisher following the migration period beginning mid-June for the 3 years

of sampling. Tissue sampling and body measurements of resident fish followed the same

protocols as described for migrant juveniles. Fish were classified as either 1+ or 2+ based

on the frequency distribution of body lengths, previously validated with age determination

using otoliths (Thériault and Dodson 2003).

3.4.2 Pedigree reconstruction Individuals of age 1+ and 2+ were partitioned into groups of putative full siblings using

PEDIGREE 2.2 (Herbinger 2005) based on data from 13 microsatellite loci (see Thériault

et al. 2007a, for methodological details). Six loci showed departure from Hardy-Weinberg

equilibrium (Table 3-1), which could be explained in part by the presence of null alleles at

three loci (Thériault et al. 2007a, see discussion about the consequence of null alleles on

sib-reconstruction). Genotypic linkage disequilibrium was also found between pairs of loci

and we believe that this might lower the power of our dataset to reconstruct pedigrees.

The partitioning of full-sibs was done for each cohort separately since we assumed that

full-sibling relationship between fish of different cohorts is very unlikely. In the complete

absence of parental information, PEDIGREE uses a Markov Chain Monte Carlo (MCMC)

approach to partition sibling by maximizing an overall likelihood score on the basis of

pairwise likelihood ratios of being full siblings or unrelated (Smith et al. 2001; Butler et al.

2004; Herbinger et al. 2006). The algorithm is constrained such that within a group of

putative siblings the genotypes at each locus must be able to be derived from a single

66 parental pair (Herbinger 2005). Multiple runs (from 20 to 60) were performed to find the

“best” sibship configurations, i.e. the one yielding the highest score. This configuration is

then retained for significance testing using genotype randomizations followed by full-sib

reconstruction. Thus, a total of 100 sets of the same number of unrelated individuals as

used for the actual pedigree reconstruction was created, sampled from populations with the

same genotypic frequencies as in our original dataset. The overall significance (P-value) of

the pedigree retained was estimated by the proportion of the 100 randomized trials with a

partition score as high or higher than the observed score. Significance of each full-sib

family was also assessed. A specific full-sib family was deemed significant and kept in the

analysis when its internal cohesion score, the average of the Log of the pairwise likelihood

ratios in that group, was higher than the cohesion scores seen in at least 95 full-sib groups

of the same size out of the 100 produced by the randomization procedure. All other full-sib

groups were discarded from subsequent analyses, as well as all individuals not related to

any other (see also Herbinger et al. 2006).

3.4.3 Quantitative genetic analyses Single cohort analysis did not yield significantly different quantitative genetic estimates

(not shown). Consequently, pedigrees obtained for cohorts 1 and 2 were combined in

subsequent analyses. Traits of interest included life-history tactic, scored as 0 for

anadromous (fish captured as migrants in trap nets) and 1 for resident (fish captured in the

stream by electro-fishing), body size (fork length, FL) and six morphological measures:

body depth (DEP), maximum body width (WID), peduncle depth (PED), caudal fin height

(CAUD), pectoral fin length (PECT) and pelvic fin length (PELV). Principal component

analysis (PCA, SAS system v.8) was performed to remove the size- dependent effect on

these morphological measures. In the presence of a size effect, the PCA grouped all

morphometric measures along one factorial axis, which was largely explained by variation

in size among fish (data not shown). To investigate the variation in body shape

independently of size variation, we removed the size effect by regressing the value of each

variable for each fish on the first factorial axis. The residual values obtained were used to

analyze morphological diversity. A general linear model (GLM, JMP™ 5.0.1a, SAS

Institute inc.) for continuous morphological traits, and a logistic regression for the

67 dichotomous trait (life-history tactic) were conducted to determine which factors needed to

be included as fixed effects in subsequent quantitative genetic analyses. This was done in

order to account for temporal heterogeneity in environmental effects on the phenotype.

Because of the small number of 2+ individuals in our pedigree (N = 41), analyses could not

be calculated separately by age, which was thus fitted as a fixed effect. Other fixed factors

were year of sampling (2002, 2003 and 2004) and day of capture. Age had a significant

influence only on FL (F1,214 = 115.22, P < 0.0001). Year was included as a fixed effect for

every trait except PECT (life-history tactic, c22, N=349 = 14.94, P = 0.001; WID, F1,214 =

7.11, P = 0.008; DEP, F1,214 = 8.36, P = 0.004; PED, F1,214 = 31.84, P < 0.0001; CAUD,

F1,214 = 30.78, P < 0.0001; PELV, F1,214 = 8.53, P = 0.004). Given its effect on FL (F1,214

= 7.45, P = 0.0069), DEP (F1,214 = 16.88, P < 0.0001), PED (F1,214 = 38.39, P < 0.0001),

CAUD (F1,214 = 22.75, P < 0.0001) and PELV (F1,214 = 5.76, P = 0.02), day of capture was

fitted as a fixed effect for these traits.

Heritability of each trait was estimated using a mixed model REML estimation procedure

using the software package ASReml (1.10, VSN International Ltd.). Pedigree information

was used to fit a univariate animal model. The model had the following form:

y = Xb +Za + e

where y is a vector of phenotypic values, b and a are the vector of fixed and random

additive effects, e is the vector of residual values, and X and Z are the corresponding design

matrices which relate the effects to y. Total phenotypic variance (VP) of each trait was

partitioned into additive genetic variance (VA) and residual variance (VR). The narrow-

sense heritability (h2) was estimated as the ratio of the additive genetic variance to the total

phenotypic variance: h2 = VA/VP. Significance of the additive genetic component of each

model was assessed by comparing the full model with a reduced model lacking the additive

genetic component using a likelihood ratio test (following a χ2 distribution, where χ2 = -

2*difference in log likelihood and the change in degrees of freedom between models =1).

Since life-history tactic was scored as a binary trait, the heritability estimate and its

associated standard error were transformed to the underlying liability scale (see Falconer

68 and Mackay 1996; Roff 2001). Heritability of life-history tactic thus refers to the

heritability of the liability of the trait, but for convenience, we refer simply to its

phenotypic manifestation (i.e. h2 of life-history tactic, see Roff et al. 1997).

Genetic correlation between life-history tactic and length, as well as between life-history

tactic and the six morphological traits related to body shape were calculated using pairwise

multivariate animal models. The same fixed and random effects used for heritability

estimation were used in these analyses. Genetic correlations were calculated as

rG = COVAB / VAVB

using the program ASReml. Significance of the genetic covariance was assessed by

comparing the likelihood of the model containing the genetic covariance component with

the reduced model in which the genetic covariance was fixed at 0, again using likelihood

ratio tests.

3.4.4 Power and sensitivity analysis

3.4.4.1 Power analysis We used the software package PEDANTIX (Morrissey et al. 2007) to assess the power of

the resolved pedigree to detect significant quantitative genetic parameters. This power

analysis wants to determine if enough information is found in our dataset to detect

quantitative genetic parameters, particularly because data availability is limited for

morphological measures (see results).

PEDANTIX uses a given pedigree to simulate phenotypic data for two traits

simultaneously (continuous data, PHENSIM application) according to a user-defined

variance-covariance matrix. Continuous data can be converted afterwards to binomial data

using the application ADVPHESIM. The phenotypic data obtained are then used for

quantitative genetic analyses, following the same procedure as for real data (i.e. animal

69 model implemented in ASReml). We used Pedigree 1 (see below) and simulated

phenotypic data for a continuous trait and a binomial trait, according to different values of

heritability and genetic correlation (from 0.2 to 0.5) and assessed the power of our pedigree

to detect the expected quantitative genetic parameters. Power was expressed by the number

of simulations that gave a significant heritability estimate as a fraction of the total number

of simulations (N = 20).

3.4.4.2 Varying parameters in PEDIGREE PEDIGREE can yield different full-sib arrangements depending on the numbers of runs and

the parameters used by the user, all of which can be equally probable. PEDIGREE does

not provide any strict criterion to choose the reconstruction that represents the most

plausible pedigree. Here, we assessed the consequences of varying one parameter, the

weight, on the quantitative genetic analyses by comparing two different pedigrees

reconstructed using the procedure described above. The weight is an ad hoc parameter in

the range of 1 to 10, 1 being neutral and the default value used in most cases (Smith et al.

2001; Butler et al. 2004; Herbinger et al. 2006). A higher weight promotes the coalescence

of individuals into larger groups, which is useful since PEDIGREE tends to split very large

full-sib families into subgroups (Smith et al. 2001; Butler et al. 2004). Here, we compared

the quantitative genetic parameters estimated using pedigrees reconstructed with a weight

of 1 (Pedigree 1) and a weight of 5 (Pedigree 2).

3.4.4.3 Full-sib assumption We assumed a full-sib structure while using PEDIGREE, but this assumption is likely to be

violated owing to complex mating patterns in our system, where both sexes have many

partners (Thériault et al. 2007a). PEDIGREE allows the reconstruction of kin-groups

(mixtures of full-sibs, half-sibs and sometimes higher degrees of relationship such as

cousins), and to mix kin pedigree with full-sib pedigree in order to reconstruct half-sib

structure, thus potentially resolving a more complete pedigree (Herbinger et al. 2006).

However, this procedure was too complex to be powerful in our system, and we chose to

assess the consequence of using a full-sib constraint on the estimation of quantitative

genetic parameters using two alternative methods. First, we added several half-sib

70 relationships to Pedigree 1 by combining results from parentage assignments previously

obtained with PASOS (Duchesne et al. 2005; Thériault et al. 2007a) with those from

PEDIGREE, such that the identity of one parent was added to a full-sib family when one or

more juveniles in that particular full-sib family had a known parent. This exercise resulted

in 12 full-sib families sharing four different known parents (involving a total of 60 progeny,

Pedigree 3). Second, we used the software package PEDANTIX (Morrissey et al. 2007) to

simulate half-sib structure in Pedigree 1 and to evaluate the consequences on quantitative

genetic parameters. We first added some half-sib relationships to full-sib Pedigree 1 by

assigning a common parent to full-sib families on a pairwise basis. For example, full-sib

families 1 and 2 now shared a common parent, as well as families 3 and 4, and so on. This

half-sib pedigree was then used by PEDANTIX to simulate phenotypic data according to

different scenarios where heritabilities and genetic correlations ranged from 0.2 to 0.5. The

quantitative genetic parameters were then estimated with ASReml using the simulated

phenotypes, along with the actual full-sib pedigree. This allowed assessing the

consequences of using a full-sib pedigree even if our true pedigree had an significant half-

sib structure.

3.5 Results

3.5.1 Pedigree reconstruction A total of 974 age 1+ and 2+ juveniles were available for sib-reconstruction for 2002, 2003

and 2004 combined (anadromous form N = 440, resident form N = 534). The best

pedigrees retained yielded scores that were not reached by any of the 100 randomizations

performed, indicating that we could reject the null hypothesis that the full-sib partitions

could have been seen in sets of unrelated individuals (P < 0.01). From the initial 974

juveniles, we sorted out those not grouping with any other based on the assumption of full-

sibs as well as those clustering into families that were not significant at a 0.05 level. This

left 349 juveniles grouped into 91 full-sib families for the quantitative genetic analyses for

Pedigrees 1 and 3. When using a weight of 5 (Pedigree 2), this same process left 351

juveniles sorted into 89 full-sib families. Family size ranged from two to 12 individuals,

with a mean (± SE) of 3.84 ± 0.17 and 3.94 ± 0.19 individuals per family for Pedigree 1+3

71 and Pedigree 2, respectively (Figure 3-1). Thus, the use of a higher weight did not translate

into the coalescence of individuals into larger families.

3.5.2 Heritability and genetic correlations Significant additive genetic variance and heritability were obtained with the three pedigrees

for the life-history tactic, body size (FL), as well as body depth (DEP), the heritability

values ranging from 0.39 to 0.56 (Table 3-2). Power analysis involving a binomial trait

showed that a moderate to high value of heritability was needed in order to be detected with

our pedigree structure; power dropped from 0.9 to 0.6 when heritability values of 0.5 and

0.4 were simulated, respectively (Table 3-3). The threshold transformation proved to be

reliable, as estimated values following the threshold transformation were generally in good

agreement with expected simulated values on the continuous scale (Table 3-3). This

analysis also revealed that the type of pedigree structure that we used was capable of

detecting a heritability of 0.2 for body size with a power of 0.75, but that heritabilities

below 0.4 were only detected in 60% of the cases for morphological traits (sample size is

smaller for morphological traits, Table 3-2 and 3-3). It thus appear that data availability

was of concern in this system and that the pedigree used for morphological data was not

adequate to detect small to moderate heritabilities. As a result, large standard errors were

associated with all quantitative genetic estimates of traits other than body size. Also,

estimates of heritabilitiy of morphological traits varied slightly depending on the pedigree

used. Namely, marginally significant heritability was detected for PED with Pedigree 2 but

not with the two other pedigrees (Table 3-2). Moreover, Pedigree 1 and 2 led to marginally

significant heritability for PELV, but not Pedigree 3 (Table 3-2).

A negative genetic correlation between life-history tactic and body size was significant for

pedigree 1 and 3, whereby anadromous fish were genetically associated with bigger size at

age (Table 3-4). Pedigree 2 yielded a significant genetic correlation between life-history

tactic and PECT (Table 3-4). None of the other genetic correlations between life-history

tactic and morphological traits were significant, and all the estimates were associated with

large standard errors, showing considerable variation between pedigrees (Table 3-4).

72 Power analysis revealed that genetic correlations were harder to detect than heritabilities.

Assuming a heritability of 0.5 for both continuous and binomial traits, a genetic correlation

of 0.5 could be detected in 65% of the cases between life-history tactic and body size (N =

349, mean estimated rG = 0.52, mean standard error = 0.22) and in 55% of the cases

between tactic and morphological data (N = 215, mean estimated rG = 0.68, mean standard

error = 0.32).

Adding information on half-sib relationships resolved using PASOS to the reconstructed

pedigree did not change any of the estimates of heritability or genetic correlation as these

were not significantly different between Pedigree 1 and 3 for any of the traits (z-scores

from 0.01 to 0.78, P-values from 0.43 to 0.99). The same conclusion was obtained using

PEDANTIX as quantitative genetic parameters estimated using the full-sib pedigree

yielded results that agreed well with the expected values assuming a half-sib structure

(Table 3-5).

3.6 Discussion The main objective of this study was to estimate the heritability of life-history tactics

(residency/anadromy) in brook charr under natural conditions by means of pedigree

reconstruction assisted by molecular markers. Our results demonstrate that the adoption of

either anadromy or residency involves a significant amount of additive genetic variance.

To our knowledge, this is the first study to provide an estimate of heritability for these

tactics under natural conditions.

The heritability value obtained for life-history tactic is within the range of heritability

estimates generally reported for threshold traits (reviewed in Roff 1996), where

approximately one-half of the phenotypic variation can be attributed to additive genetic

variance. It thus suggests that tactics have considerable potential to respond to selection and

evolve, but it also implies a relatively important environmental influence on the adoption of

a tactic. Other studies have provided estimates of heritability of threshold traits linked to

73 anadromy and residency in salmonids under controlled experiments (early maturity, Wild et

al. 1994; precocious maturity, Silverstein and Hershberger 1992; jacking, Heath et al. 1994;

Mousseau et al. 1998; Heath et al. 2002, smolting and maturing, Thrower et al. 2004) and

the values obtained were highly variable (from low and non-significant to high). These

wide differences highlight the fact that it is unwarranted to compare absolute values of

heritability as they are a property of the population under study and the conditions where

they were measured (Stearns 1992; Falconer and Mackay 1996).

We also found significant heritability for body size, our estimates being higher (0.44 to

0.50) than other reported estimates for body size (at age 1+) in salmonids under natural

conditions (e.g. 0.001 ± 0.04, and 0.26 ± 0.12 in brook charr for two populations

respectively, Wilson et al. 2003a; 0.04 ± 0.15, in Atlantic salmon, Salmo salar, Garant et al.

2003). Body size is an important liability trait for early sexual maturity and anadromy in

salmonids, especially in Atlantic salmon where early-maturing males are bigger in early life

stages than anadromous males (Whalen and Parrish 1999; Garant et al. 2002; Aubin-Horth

and Dodson 2004). In a previous study from the same tributary, back-calculated length-at-

age revealed that smaller brook charr at age 1+ delay migration to the following year,

resulting in age 2+ migrants being smaller than age 2+ resident fish (Thériault and Dodson

2003). At age 1+ however, when removing these smaller future migrants from the sample

of resident fish, these authors observed no difference in body size between migrant and

resident fish. Thériault and Dodson (2003) thus proposed that body size was not the only

trait associated with the adoption of the life-history tactic at that age. Physiological traits

related to the energetic budget are more likely to influence tactic choice (Morinville and

Rasmussen 2003 and 2006). Heritability for body size (0.44-0.50) was similar to that of the

liability itself (the life-history tactic, 0.52-0.56) suggesting that body size could be a major

component of the liability, although other components might also be involved.

The covariance analyses suggest a genetic correlation between life-history tactic and body

size, although larger sample sizes would have been needed to yield more accurate

74 estimations of genetic correlation. Another potential concern is the reliability of the

correlation between a binomial trait and a continuous one using the animal model method,

as this has rarely been done (but see Wilson et al. 2003a). However, simulation analysis

using PEDANTIX showed that the estimated genetic correlation between a binomial trait

and a continuous trait corresponded to the expected one assuming two continuously

distributed traits. Our results thus suggest that differences in body size observed previously

between anadromous and resident brook charr (phenotypic correlation of -0.15, P < 0.01;

Thériault and Dodson 2003) are partly due to the genetic correlation between size and life-

history tactic. Since anadromy was coded 0 and residency 1, the negative correlation we

documented implies that bigger fish would be genetically more prone to be anadromous.

This conclusion must be constrained to age 1+ fish and is consistent with the phenotypic

correlation: at age 1+, migrants appear to be bigger because the sample of resident fish

includes small fish, which would ultimately migrate the following year (Thériault and

Dodson 2003). Also, the genetic correlation between these two traits suggests that

selection acting on one of them would likely have an effect on the other. For example,

given continued selection against fish migrating at age 1+ (for instance because of a more

pronounced fishing pressure on anadromous than resident fish), one would predict a

correlated response in body size, 1+ individuals being smaller in subsequent generations. A

similar result was obtained in a breeding experiment with steelhead trout (Oncorhynchus

mykiss), where the proportion maturing at age 2 was negatively genetically correlated with

mass at age 1 (Thrower et al. 2004). Yet, the intermediate values of the correlation found

in the present study (-0.20 to -0.61) give support to the hypothesis stated above that body

size is not the only component of the liability underlying life-history tactic expression. If

so, one would expect body size and the liability trait to reflect more or less the same genetic

character and the genetic correlation obtained to be closer to unity (Falconer and Mackay

1996).

Estimating genetic quantitative parameters in the wild is a difficult task and it is not always

feasible to estimate the variance components that are likely to influence phenotypic

covariance between relatives. In this study, we lacked the information required to estimate

75 maternal or common environmental effects, which, if present, could potentially inflate

heritabilities values (Falconer and Mackay 1996). First, we had no information on the

parental generation of our fish, and thus mother identity was unknown. However, maternal

effects on body size have been shown to be non-significant at 0, 1 and 2 years old in

Atlantic salmon of the Sainte-Marguerite River (Garant et al. 2003). More generally, it has

also been showed that when maternal effects are detected in salmonids, they are more

important at early larval stages and seem to decrease with age (Heath et al. 1999; Perry et

al. 2005a). Because our study focused on later life history stage, we assumed that maternal

effects were negligible. Common environment effects are another concern that cannot be

easily addressed in our system. The sampling location of each resident fish was recorded,

but because the migrants were all sampled in one downstream trap during their

outmigration in spring, their section of origin was unknown. However, animal models with

sampling location as a fixed effect for residents have been fitted for body size, and gave

similar results to those without sampling location (results not shown). Moreover,

qualitative analysis of our results from parentage analyses (see Thériault et al. 2007a)

showed that members of only five half-sib families out of 44 were sampled in the same 300

meter sampling section. All other juveniles sharing one parent were found all along the

stream, from several hundred meters to 3 kilometers apart, suggesting considerable

dispersal during the first and/or second year of life. Similar qualitative analysis of our data

with the full-sib information obtained here with PEDIGREE revealed that only 30% of the

members of a same family were found in the same 300 meters section. There is thus little

evidences suggesting that common environment effects might be inflating our quantitative

genetics parameters.

Estimates of quantitative genetic parameters obtained in nature have mainly been obtained

from long-term studies that used large pedigrees (reviewed in Kruuk 2004). While the

number of recent studies that use highly polymorphic genetic markers to assess pedigree

information is growing (reviewed in Garant and Kruuk 2005), the limitations of such tools

need to be acknowledged. Here, we used a sib-reconstruction method assuming unrelated

full-sib families only, although this assumption is likely to be violated in the study system.

76 Indeed, mating patterns in brook charr involve both sexes mating with many different

partners and thus a more realistic pedigree would necessarily involve an important half-sib

structure (Thériault et al. 2007a). A procedure nesting full-sib families with kin groups has

been used elsewhere to provide a more accurate pedigree reconstruction (see Herbinger et

al. 2006), but the limited numbers of large families in our study prevented us from using

this approach. Moreover, we attempted to use a more complete pedigree (obtained from

parentage analysis), but ended up with a pedigree that did not contain enough related

individuals (see Thériault et al. 2007a). This prevented model convergence when estimating

quantitative genetic parameters. Nevertheless, assuming a full-sib pedigree structure may

have only a limited impact since most of the information used in estimating quantitative

genetic parameters stems from close relatives (Thomas and Hill 2000). This was supported

here by the absence of significant differences in quantitative genetic parameter estimates

between the full-sib pedigree (Pedigree 1) and the pedigree including some half-sib

relationships (Pedigree 3). Furthermore, simulations showed no significant effect when

using phenotypes created from a half-sib pedigree along with our full-sib pedigree to

estimate quantitative genetic parameters. This result also argue in favor of additive genetic

effects not being confounded with non-additive ones owing to the use of full-sibs only

(Falconer and Mackay 1996).

Sib-reconstruction using a MCMC approach is not free of errors. Namely, the algorithm

used by PEDIGREE 2.2 tends to split large full-sib families into subgroups when using

allelic frequencies estimated in the sample instead of true population allelic frequencies

(Smith et al. 2001; Butler et al. 2004). This type of error will have the same consequence

as considering only full-sibs, i.e. the split families are assumed to be unrelated when in fact

they are, which may artificially decrease phenotypic variance between families and thus

produces conservative heritability estimates (Wilson et al. 2003b). However, our use of a

higher weight while reconstructing Pedigree 2 specifically aimed to mitigate this tendency

but did not result in coalescence of large full-sib groups. We thus conclude that splitting

large full-sib families into subgroups was not of concern in this study. Moreover,

quantitative genetic estimates were generally in good agreement between pedigrees using a

77 weight of 1 or 5. Genotyping errors are also likely to influence sib-reconstruction (Butler

et al. 2004) and these errors are not taken into account in subsequent quantitative genetic

analyses under the animal model. Null alleles have been detected in this population

(Thériault et al. 2007a). Such mistyping of heterozygotes as homozygotes is more likely to

cause families to be split rather than incorrect families to be formed, which should cause a

downward bias in quantitative genetic parameter estimates (Thomas and Hill 2000).

Simulation analyses performed by Butler et al. (2004) have shown that the reconstruction

algorithm such as that implemented in PEDIGREE 2.2 is relatively robust to such

problems. It appears that when information from several other loci is available, the

resulting offspring genotypes are still full-sib compatible, and are, in the majority of cases

(75%), consistent with Mendelian rules (Butler et al. 2004).

Two studies have compared estimates of quantitative genetic parameters obtained using a

sib-reconstructed pedigree to ideal values obtained with a « true-pedigree » resolved from

parentage analysis: both concluded that the results were reliable and close to ideal values,

although parameters were generally underestimated (Thomas et al. 2002; Wilson et al.

2003b). In particular, Wilson et al. (2003b) used an aquaculture population of rainbow

trout (Oncorhynchus mykiss) to compare heritability and genetic correlation estimates

between a pedigree obtained by sibship-reconstructions (using the same MCMC approach

as in the present study) and a pedigree built using a parentage analysis based on an

exclusion approach. Their population contained a high number of half-sib relationships due

to factorial crossing in the parental generation, but these relationships were not taken into

account while performing sibship-reconstructions (as in our study). The authors concluded

that the underestimation of quantitative genetic parameters from sib-reconstructed

pedigrees, relative to a “true-pedigree”, is mainly explained by the complex structure of the

true pedigree. The true pedigree consisted of a high number of half-sibling relationships,

which caused an inaccurate partitioning of full-sibships and reduced the recognition of

relatedness between families (see Wilson et al. 2003b). Furthermore, the authors reported

difficulties in obtaining meaningful estimates of quantitative genetic parameters, especially

78 for genetic correlations, when using subsets of their dataset and thus smaller sample sizes

(Wilson et al. 2003b).

Although our analyses suggest no major problems of assuming only full-sibs relationships

(e.g. no underestimation of estimated parameters as observed by Wilson et al. 2003b), the

methods we used to reach such a conclusion may not completely account for the

complexity of the half-sib structure. Furthermore, we do not know the extent of inaccurate

partitioning of full-sibs owing to a high number of half-sibs in our system and to the

presence of null alleles at certain loci. Resolving the half-sib structure in such a system

where the mating pattern is complex and where full-sib family sizes seem small (at least

when using 1+ and 2+ juveniles for sib-reconstruction) would require parental assignment

and thus a sampling of spawners as complete as possible. Because sib-reconstruction was

the only alternative, increasing juvenile sample size would have improved the power of

analyses in our case. Arguably however, such constraints are likely to apply to most

studies performed in similar systems involving natural populations. Finally, as adoption of

a particular life-history tactic can occur at two different ages in our study system, it would

be pertinent in future studies to measure age-specific values of heritability and genetic

correlation. Indeed, age-specific variation in the amount of genetic variance has been

shown to occur under natural conditions in morphological and life-history traits (see Perry

et al. 2004; Charmantier et al. 2006). As such, different age classes are different with

respect to their evolutionary potential or response to selection. Moreover, estimates over

many years would also shed light on the temporal stability of response to selection, as

genetic parameters are expected to change depending on environmental conditions

(Hoffmann and Merilä 1999; Charmantier and Garant 2005).

To conclude, this study represents a contribution towards the acquisition of estimates of

quantitative genetic parameters under wild conditions, and more than being one of the few

(see also Wilson et al. 2003a) to demonstrate the usefulness of sibship-reconstruction in

79 nature in the absence of parental information, it also provides for the first time heritability

estimates of anadromy and residency in salmonids in an entirely natural set-up.

3.7 Acknowledgments We acknowledge A. Boivin, S. Bordeleau, M. Foy-Guitard, S.-P. Gingras, Fannie Martin,

François Martin, A. Ménard, G. Morinville, L. Papillon, L. V. St-Hilaire Gravel, and R.

Saint-Laurent for field assistance and laboratory work. The authors would also like to thank

C. M. Herbinger for assistance with the software PEDIGREE 2.2 and M. B. Morrissey for

assistance with the software PEDANTIX. Funding of this project was provided to J.J.D.

and L.B. by NSERC of Canada (Strategic Grant and Collaborative Special Projects), the

Fondation de la Faune du Québec, the Government of Québec (FAPAQ), the Government

of Canada (Economic development) and the financial partners of AquaSalmo R&D. This

study is a contribution to the program of CIRSA (Centre interuniversitaire de recherche sur

le saumon Atlantique) and Québec-Ocean. V.T. and D.G. were financially supported by

funding from NSERC and FQRNT.

80

3.8 Tables Table 3-1. Number of alleles (N), observed (Ho) and expected (He) heterozygosity at each locus. * indicates significant departure from Hardy-Weinberg equilibrium. SfoB52, SfoC113, SfoC129, SfoC28, SfoC88, SfoC115, SfoD100, SfoD75, T. L. King, US Geological Survey, unpublished; SCO204, SCO216, SCO218 from DeHaan and Ardren (2005); Sfo262Lav, Sfo266Lav from Perry et al. (2005b).

Locus N Ho He SfoB52* 12 0.68 0.74SfoC113 12 0.79 0.75SfoC129 7 0.73 0.71SfoC28 10 0.52 0.54SfoC88 6 0.60 0.61SfoC115* 23 0.55 0.63SfoD100* 10 0.76 0.81SfoD75* 13 0.75 0.80SCO204* 13 0.76 0.80SCO216 18 0.88 0.89SCO218 14 0.81 0.80Sfo262Lav* 19 0.85 0.82Sfo266Lav 30 0.87 0.87

81

Table 3-2. Sample size (N), trait means with their standard deviation (SD), estimates of residual (VR), additive (VA) and phenotypic (VP) variance components and heritability (h2) with their standard error (SE) for life-history tactic (anadromy/residency: Tactic), body size (fork length: FL) and six morphological traits (body depth: DEP, maximum body width: WID, peduncle depth: PED, caudal fin height: CAUD, pectoral fin length: PECT and pelvic fin length: PELV, all transformed following PCA, see methods) in brook charr. Pedigree 1 is the best one obtained with a weight of 1, Pedigree 2 is the best one obtained with a weight of 5, and Pedigree 3 is the same as Pedigree 1, but where half-sib relationships were added (see methods). h2 of the life-history tactic is given transformed to the liability scale (see methods). P-values are those obtained from likelihood ratio tests to assess the significance of the additive genetic component.

Traits N Mean (SD) VR (SE) VA (SE) VP (SE) h2 (SE) P

Pedigree 1 Tactic 349 1.47 (0.50) 0.15 (0.03) 0.08 (0.03) 0.24 (0.02) 0.56 (0.18) 0.0003FL (mm) 349 88.95 (14.55) 42.33 (8.51) 42.73 (12.47) 85.06 (7.18) 0.50 (0.12) < 0.0001DEP 215 -0.15 (0.80) 0.26 (0.06) 0.17 (0.08) 0.43 (0.04) 0.40 (0.16) 0.0069WID 215 0.06 (0.59) 0.26 (0.05) 0.04 (0.05) 0.30 (0.03) 0.13 (0.18) 0.6351PED 215 -0.04 (0.49) 1.52 (0.30) 0.24 (0.26) 1.77 (0.17) 0.14 (0.15) 0.7574CAUD 215 0.56 (1.42) 0.19 (0.04) 0.05 (0.04) 0.24 (0.02) 0.22 (0.15) 0.1024PECT 215 -0.19 (0.57) 0.20 (0.04) 0.01 (0.03) 0.21 (0.02) 0.06 (0.13) 0.7216PELV 215 -0.07 (0.50) 0.23 (0.05) 0.09 (0.05) 0.32 (0.03) 0.28 (0.15) 0.0386

Pedigree 2 Tactic 351 1.48 (0.50) 0.11 (0.02) 0.05 (0.02) 0.16 (0.01) 0.52 (0.19) 0.0002FL (mm) 351 88.99 (14.63) 48.68 (9.65) 38.78 (12.16) 87.48 (7.25) 0.44 (0.12) < 0.0001DEP 216 -0.15 (0.79) 0.20 (0.06) 0.22 (0.08) 0.41 (0.04) 0.53 (0.16) 0.0003WID 216 0.03 (0.58) 0.26 (0.05) 0.03 (0.05) 0.30 (0.03) 0.11 (0.16) 0.5868PED 216 -0.02 (0.50) 1.29 (0.28) 0.55 (0.31) 1.84 (0.19) 0.30 (0.16) 0.0445CAUD 216 0.55 (1.45) 0.22 (0.04) 0.04 (0.04) 0.26 (0.03) 0.15 (0.14) 0.2465PECT 216 -0.06 (0.51) 0.22 (0.04) 0.03 (0.04) 0.25 (0.02) 0.13 (0.14) 0.3126PELV 216 -0.09 (0.55) 0.22 (0.05) 0.08 (0.05) 0.30 (0.02) 0.27 (0.15) 0.0463

Pedigree 3 Tactic 349 1.47 (0.50) 0.15 (0.03) 0.08 (0.03) 0.24 (0.01) 0.55 (0.19) 0.0005FL (mm) 349 88.95 (14.55) 43.21 (9.83) 42.65 (13.00) 85.86 (7.34) 0.50 (0.13) <0.0001DEP 215 -0.146 (0.80) 0.26 (0.07) 0.17 (0.08) 0.43 (0.04) 0.39 (0.16) 0.0105WID 215 0.055 (0.59) 0.28 (0.05) 0.02 (0.05) 0.30 (0.03) 0.06 (0.16) 0.8024PED 215 -0.037 (0.49) 1.55 (0.28) 0.22 (0.25) 1.77 (0.17) 0.12 (0.14) 0.3753CAUD 215 0.560 (1.42) 0.19 (0.04) 0.06 (0.04) 0.24 (0.02) 0.23 (0.15) 0.0797PECT 215 -0.109 (0.57) 0.22 (0.04) 0.03 (0.04) 0.25 (0.02) 0.12 (0.14) 0.3820PELV 215 -0.069 (0.50) 0.26 (0.05) 0.07 (0.05) 0.33 (0.03) 0.22 (0.15) 0.1160

82

Table 3-3. Power analysis for a range of simulated heritabilities (h2) for a continuous and a binomial trait. The mean heritability estimate and the mean standard error of 20 simulations are presented. Simulations were ran in order to mimic the actual data. Heritabilities estimated with a sample size of 349 individuals refer to body size and tactic, while a sample size of 215 relates to morphological traits. The heritability of tactic is given transformed to the liability scale for comparison purposes (see methods). Power is assessed by dividing the number of simulations that gave a significant additive variance estimate over a total number of 20 simulations.

N = 349 individuals N = 215 individuals Binomial trait Continuous trait Continuous trait h2 simulated h2 estimated

mean (SE) Power h2 estimated

mean (SE) Power h2 estimated

mean (SE) Power

0.20 0.28 (0.15) 0.35 0.25 (0.11) 0.75 0.24 (0.14) 0.39 0.30 0.44 (0.14) 0.55 0.32 (0.11) 0.90 0.33 (0.15) 0.60 0.40 0.37 (0.18) 0.60 0.41 (0.11) 0.95 0.44 (0.16) 0.85 0.50 0.47 (0.17) 0.90 0.50 (0.12) 1.00 0.50 (0.16) 0.90

83

Table 3-4. Genetic correlations with their standard errors between life-history tactic (anadromy/residency) and body size (FL) and the six morphological traits for the 3 pedigrees used (as in Table 2). Life-history tactic was coded as 0 for anadromous and 1 for resident. P-values are those obtained from likelihood ratio tests to assess the significance of the covariance genetic component.

Traits Pedigree 1 P Pedigree 2 P Pedigree 3 P FL -0.52 (0.22) 0.0333 -0.20 (0.24) 0.4401 -0.61 (0.23) 0.0188DEP 0.11 (0.32) 0.8149 -0.0007 (0.0002) 1.0000 0.13 (0.33) 0.7876WID 0.55 (0.74) 0.3762 0.37 (0.51) 0.4708 1.09 (2.45) 0.2506PED -0.003 (0.55) 0.6634 0.21 (0.31) 0.5508 -0.06( 0.66) 1.0000CAUD -0.50 (0.54) 0.4393 0.07 (0.47) 1.0000 -0.54 (0.54) 0.3877PECT -0.82 (0.31) 0.0655 -0.70 (0.25) 0.0477 -0.60 (0.32) 0.1526PELV 0.16 (0.35) 1.0000 0.35 (0.30) 0.3192 0.24 (0.37) 0.5565

84

Table 3-5 Mean heritability (h2) and genetic correlation (rG) estimates as well as mean standard error (SE) obtained over 20 simulations using a full-sib pedigree along with simulated phenotype data from a half-sib pedigree. Phenotype data were simulated according to h2 and rG similar to those estimated in the present study.

Simulated Estimated mean (SE)

h2 binomial 0.50 0.48 (0.17) h2 continuous 0.50 0.51 (0.12) rG binomial - continuous 0.50 0.52 (0.23)

85

3.9 Figures

0

10

20

30

40

2 4 6 8 10 12Family size

Num

ber o

f fam

ilies

Figure 3-1. Distribution of family size for Pedigree 1 and 3 (black bars) and Pedigree 2 (white bars). These families are those that were kept in the final analyses, i.e. the ones that were deemed significant by the randomization procedures (see methods).

86

Figure 3-S1. Location of the study area, sampling traps and electro-fishing sites on Morin Creek, a tributary of the Sainte-Marguerite River, Quebec, Canada.

Chapitre 4. The impact of fishing-induced mortality on the evolution of alternative life-history tactics in brook charr

88

4.1 Résumé Bien que des données récentes aient démontré des changements évolutifs dans des traits

d’histoire de vie tels la croissance, l’âge et la taille à maturité pour des population de

poissons exploitées, on ne connaît pas encore l’influence que pourrait avoir la pêche sur

l’évolution des tactiques alternatives de vie chez les espèces migratrices. Nous avons

construit un modèle pour prédire l’effet de la pêche sur l’évolution de l’anadromie et la

résidence chez une population exploitée d’omble de fontaine, Salvelinus fontinalis. Notre

modèle permet à la fois des changements phénotypiques plastiques ainsi que génétiques

(additifs) dans l’âge et la taille à la migration en employant des normes de réaction de

migration. À l’aide de ce modèle, nous prédisons qu’une pêche sportive centrée

uniquement sur les individus anadromes sur une période de 100 ans cause une évolution

dans les normes de réaction de migration, résultant en une diminution de la probabilité de

migrer avec une augmentation du taux d’exploitation. De plus, nous démontrons que des

changements dans les taux de mortalité naturels en eau douce peuvent grandement

influencer l’ampleur et la vitesse des changements évolutifs. Les changements évolutifs

dans le comportement migrateur engendrés par la pêche modifient l’abondance de la

population ainsi que le résultat de la reproduction et devraient être pris en considération si

une gestion efficace et durable des stocks de salmonidés est souhaitée.

89

4.2 Abstract Although contemporary trends indicative of evolutionary change have been detected in the

life-history traits of exploited populations such as growth and maturation schedule, it is not

known to what extent fishing influences the evolution of alternative life-history tactics in

migratory species such as salmonids. Here, we build a model to predict the evolution of

anadromy and residency in an exploited population of brook charr, Salvelinus fontinalis.

Our model allows for both phenotypic plasticity and additive genetic change in the age and

size at migration by including migration reaction norms. Using this model, we predict that

fishing of anadromous individuals over the course of 100 years causes evolution in the

migration reaction norm, resulting in a decrease in average probabilities of migration with

increasing harvest rate. Moreover, we showed that diffrences in natural mortalities in

freshwater can greatly influence the magnitude and rate of evolutionary change. The

fishing-induced changes in migration predicted by our model alter population abundances

and reproductive output and should be accounted for in the sustainable management of

salmonids.

90

4.3 Introduction Fishing is now acknowledged as a potential evolutionary force, described as a “massive

uncontrolled experiment in evolutionary selection” (Stokes and Law 2000). Whenever

individuals with certain characteristics are more likely to survive harvest than others,

fishing can induce evolutionary changes in life-history traits (Law 2000; Haugen and

Vøllestad 2001; Conover and Munch 2002; Barot et al. 2004; Olsen et al. 2004; Reznick

and Ghalambor 2005). That fishing can generate substantial selection differentials on

phenotypic traits that are influenced by additive genetic variation is beyond doubt. Yet, the

rate of these changes and their consequences for stock viability, stability, yield, and

recovery are less clear (Law 2000; Hutchings and Fraser 2008). Survivors of the harvesting

process are likely to be genotypes with traits that confer relatively high fitness under

fishing selection, but may be less than optimal with respect to natural selection (Conover

2000; Carlson et al. 2007). This may lead to slow recovery when fishing mortality is

relaxed. Moreover, because cessation of fishing does not automatically produce equal

selection pressures in the opposite direction, paying off this “Darwinian debt” (Cookson

2004) may take a long time (Conover 2000; Law 2000).

Salmonids are well known for their diversity of life-history forms, with alternative mating

tactics such as early maturing jacks in coho salmon, Oncorhynchus kisutch (Gross 1985),

precocious parr in Atlantic Salmon, Salmo salar (Hutchings and Myers 1988), or various

benthic and pelagic morphs in Artic charr, Salvelinus alpinus and brook charr, Salvelinus

fontinalis (Skúlason et al. 1996; Proulx and Magnan 2004). A common feature of many

systems is the presence of both anadromous (sea-run) and resident males and females found

in sympatry, where resident fish complete their entire life cycle without migrating to sea

(Jonsson and Jonsson 1993). Accumulating evidence suggests that these two forms may

occur as alternative tactics within a single breeding population (Nordeng 1983; Morita et al.

2000; Olsson and Greenberg 2004; Thériault et al. 2007a). Individuals adopt a particular

tactic if a certain threshold is exceeded or not, and various components of the energetic

state of individuals (growth, lipid deposition, and metabolic rate) have been implicated in

91 this process (Thorpe 1986; Bohlin et al. 1990; Thorpe et al. 1998; Hutchings and Myers

1994; Forseth et al. 1999; Morinville and Rasmussen 2003). Although influenced by

environmental conditions (e.g. Olsson et al. 2006), the adoption of alternative tactics in

salmonids involves significant additive genetic variation, which has been demonstrated

both in the laboratory (Silverstein and Hershberger 1992; Heath et al. 1994; Wild et al.

1994) and in the field (Garant et al. 2003; Thériault et al. 2007b). Moreover, whether an

individual migrates or not will have critical consequences for its growth, survival,

maturation, and reproduction. Survival is elevated in freshwater, but growth rates are

reduced and resident individuals attain a smaller size at maturation (Gross 1987). As

reproductive success is linked to body size in females (Fleming 1996; Morita and

Takashima 1998; Thériault et al. 2007a), resident females experience decreased

reproductive success relative to the bigger anadromous females. Reproductive success of

males seems to be less affected by smaller size, as resident males employ alternative

reproductive tactics, such as sneaking, to get access to mating opportunities (Hutchings and

Myers 1988; Fleming 1996).

Owing to its size-selectivity and temporally variable nature (Ricker 1995; Quinn et al.

2007), commercial fishing in salmonids has been shown to impact several life-history traits

such as growth, age and size at maturation, and run timing. However, despite wide

commercial and recreational interests in salmonids, direct evidence of evolutionary change

caused by salmonid fisheries is still mostly circumstantial (Myers et al. 1986; Waples et al.

2007). A fishery that targets only the migrant part of a population will inevitably be

selective with respect to life-history tactics such as anadromy and residency. However, the

consequences of such differential fishery-induced selection on the evolution of alternative

life-history tactics have, to our knowledge, never been rigorously investigated.

Here we used a novel modeling approach in order to predict the consequences of fishery-

induced mortality on the evolution of anadromy and residency. The model (hereafter

termed “eco-genetic”) incorporates both ecological and quantitative genetic processes,

92 providing a mechanistically rich framework in which to predict the rate of evolutionary

change on ecological timescales (Dunlop et al. 2007, 2008). In particular, our modeling

approach enables distinguishing between the plastic and evolutionary responses to fishing.

In the wild, salmonids show phenotypic plasticity in the age and size at migration. To

account for such plasticity in the process of migration, we adopted a reaction norm

approach. Reaction norms in the narrow sense describe how a single genotype is translated

into different phenotypes depending on environmental conditions (Stearns 1992), while

empirical estimations of reaction norms must typically rely in a broader definition

operating at the population level (Sarkar and Fuller 2003). Alternative tactics in salmonids

have previously been described by reaction norms, based on the idea that the adoption of a

particular tactic is governed by thresholds in growth rate (Myers and Hutchings 1986;

Thorpe 1986; Bohlin et al. 1990; Hazel et al. 1990). Here we extend this approach and

consider the probability for the adoption of a particular migration tactic (anadromy or

residency) as a function of size-at-age, where size-at-age integrates all environmental

factors affecting growth. Such an approach has previously been used to model the

evolution of maturation reaction norms (Ernande et al. 2004; Dunlop et al. 2007) and to

tease apart phenotypically plastic responses from possible genetic changes in the age and

size at maturation (Heino et al. 2002; Grift et al. 2003; Barot et al. 2004, 2005; Olsen et al.

2004, 2005; Dunlop et al. 2005; Dieckmann and Heino 2007). Our study represents an

extension of the maturation reaction norm approach so as to account for phenotypic

plasticity in another fundamental life-history transition in the study of exploited

populations.

We used data from a well-studied brook charr population in Québec, Canada, to

parameterize our model. Recreational fishermen in the region are increasingly exploiting

the sea-run components of this species as a result of the decline in Atlantic salmon stocks.

Yet, anadromous populations of brook charr are not rigorously managed in many systems.

Here we examine the impact of various exploitation rates on the evolution of migration

93 reaction norms, as well as on ecological and demographic characteristics of the population.

We chose to model dynamics over a 100-year time horizon as this timeframe is commonly

viewed as a manageable window from a conservation standpoint (Frankham et al. 2002).

The main purpose of our study is to address the following two questions (1) Does fishing

induce evolutionary changes in the conditional migration strategy? (2) In a population with

an evolving migration strategy, what are the effects of fishing on fecundity, abundance, and

yield from the fishery? We also explored whether differences in freshwater mortality rates

counteract or exacerbate the impact of fishing in saltwater on the evolution of anadromy

and residency.

4.4 Material and Methods We constructed an individual-based eco-genetic model similar to that developed by Dunlop

et al. (2007, 2008) to evaluate the effects of selective fishing mortality on the evolution of

anadromy and residency within a conditional strategy framework. The model was built to

reflect the life history of a sympatric population of brook charr in which anadromous and

resident migration tactics coexist (Figure 4-1) inhabiting a small tributary of the Ste-

Marguerite River (Québec, Canada), named Morin Creek. The behaviour and life history of

brook charr in this system are well studied (Morinville and Rasmussen 2003, 2006, 2007;

Thériault and Dodson 2003; Lenormand et al. 2004; Thériault et al. 2007a and b) and ample

data from the years 1998-2004 were available to parameterize the model (Figure 4-2, Table

4-1). The model follows evolution of the migration reaction norm, a quantitative trait that

is passed on at the individual-level from parents to offspring. We assumed a closed

population such that no new genetic variance was introduced by immigration. Model

simulations were run for a total duration of 100 years in discrete, one-year time steps. Each

year, individuals may experience the processes of migration to and from saltwater, growth,

maturation, reproduction, and mortality (Figure 4-1).

94 4.4.1 Migration The migration reaction norm was represented by a logistic function, describing the

probability p of migrating as a function of age a and size L,

0 1 2 3logit( )p c c L c a c La= + + + , (1)

where logit( ) log [ (1 )]ep p p= − . This form was chosen because it fits the empirical

relationship and allows the probability of migrating as a function of size to change its slope

with age (Figure 4-2a). Each individual is thus characterized by the four evolving

parameters c0, c1, c2, and c3 describing its probabilistic migration reaction norm (PMigRN),

which, together with its age and length, determines its probability of migrating in a given

year. An individual may migrate at either age 1 or 2 years only: if a fish did not migrate by

age 2, we assumed that it would be a freshwater resident for all its life. This understanding

is corroborated by field observations on this system (Thériault and Dodson 2003).

4.4.2 Somatic growth Individuals grow according to the growth model introduced by Lester et al. (2004).

Newborns in the model are given a random size at emergence, in accordance with the

empirical mean and standard deviation estimated from back-calculations of the 1998, 1999,

and 2000 year classes of fish captured in Morin creek (Thériault 2001; Thériault and

Dodson 2003). Prior to maturation, individuals grow the annual phenotypic growth

increment ig determined by the environment in which they reside during that year

(freshwater, i f= , or saltwater, i s= ). The maximal growth capacity is expressed in

saltwater, whereas individuals living in freshwater grow slower due to the poorer growing

environment they experience. The environment-specific growth rates fg and sg were

empirically derived from immature individuals of the Ste-Marguerite River system and

Morin Creek (Lenormand 2003; Thériault and Dodson 2003, Table 4-1).

Immediately following maturation, a proportion of energy is devoted to reproductive

tissues, so that the length L at age a+1 is given by

95

13 ( )

3a aL L gGSI+ = +

+,

(4)

where GSI is the gonado-somatic index (gonad mass divided by somatic mass) estimated

for anadromous females. The gonado-somatic index is parsimoniously assumed to be

similar and constant for all mature individuals in the population. Growth rates were

assumed to be density-independent, both in saltwater and in freshwater, to keep predictions

simple and motivated by the following two reasons. First, in view of the high productivity

of marine habitats and the small population sizes modeled here, the density dependence of

growth rates in the sea must be expected to be weak. Second, results gathered from a creek

adjacent and similar to Morin Creek failed to detect any density-dependence in freshwater

growth for brook charr of age 0 and older (Centre Interuniversitaire de Recherche sur le

Saumon Atlantique, CIRSA, unpublished data). When we tested the effects of our model

assumption and added density-dependent freshwater growth, there was little impact on the

probability to migrate at age 1, but the probability to migrate at age 2 did evolve to be

higher when the strength of the density-dependence was increased (Supplementary

Information).

4.4.3 Maturation In any given year, an immature individual has a probability to mature during the upcoming

year that is based on its environment (freshwater or saltwater) and on its size and age. This

probability is given by a probabilistic maturation reaction norm (PMRN, Figure 4-2b,

Heino et al. 2002; Dieckmann and Heino 2007). To keep the model simple and to focus on

the evolution of migration, maturation tendency was not considered as an evolving trait in

our model.

4.4.4 Reproduction There is no sex-structure in our model and reproduction occurs annually in freshwater

between random pairs of mature individuals. The largest individual in the reproductive pair

is chosen to be the mother, so as to account for frequently observed mating between

anadromous females (bigger) and resident males (smaller) and the apparent absence of the

reverse (that is, big anadromous males with small resident females, Thériault et al. 2007a).

96 The number of eggs produced by a reproductive pair is estimated from the body length L of

the mother in the pair according to an empirically derived relationship between fecundity

and body size (Figure 4-2c),

F = (H1L)H2 , (5)

with constants H1 and H2. The number of new individuals recruiting to the population at

age 1 is determined from a Ricker-type stock-recruitment function (Figure 4-2d),

R = rSe−bS , (6)

where S is the number of adults, and r and b are constants. As the necessary data to derive

such stock-recruitment functions specifically for our system were not available, they were

instead obtained from corresponding constants estimated for brown trout (Elliott 1993), a

species with life-history characteristics very similar to brook charr. We adjusted these

constants so as to obtain realistic estimates of recruitment and spawner abundance in our

system (Table 4-1).

4.4.5 Inheritance and expression Genotype determination. Inheritance of the PMigRN was described by the infinitesimal

model of quantitative genetics (Cavalli-Sforza and Feldman 1976). We assumed that

phenotypic plasticity for migration is heritable by modeling genetically based reaction

norms that are passed from parents to offspring (e.g. Brommer et al. 2005; Nussey et al.

2005; Dunlop et al. 2007, 2008). The four parameters that describe the PMigRN were thus

considered as evolving traits. The genetic trait value of an offspring was drawn at random

from a normal distribution with a mean given by the mid-parental genetic trait value and a

variance that equaled half the genetic variance in the initial population. Modeling offspring

variance in this way assumes equal variances of maternal and paternal traits and that the

segregation and recombination of genes during reproduction introduce a constant amount of

variation to the population (Roughgarden 1979).

97 Phenotype determination. The phenotypically expressed values of an individual’s four

PMigRN traits were drawn randomly in each year from a normal distribution with a mean

given by the individual’s genetic trait value and a variance that equaled the assumed

environmental variance. The latter was calculated based on an assumed heritability h2 (see

section on initial population structure below) for the PMigRN traits and on an assumed

genetic coefficient of variation. Based on the definition of heritability, h2 = VA/VP with VP

= VA + VE (VA = additive genetic variance; VP = phenotypic variance; VE = environmental

variance), it is possible to calculate VE from h2 and VA. While the environmental variance

for each trait was kept constant in the model, the corresponding values of VA, and thus of

h2, were free to evolve.

4.4.6 Natural mortality Default natural mortalities. Age-specific annual mortality probabilities were estimated

from Morin Creek data for resident individuals, and from a larger mark-recapture

experiment in the whole Ste-Marguerite River system for anadromous individuals

(Lenormand 2003). Immature (mimm) and mature (mmat) mortality probabilities were applied

annually to resident and anadromous individuals (Table 4-1). For anadromous fish, the

mortality probability of an immature individual varied depending on whether it was the first

or second year the individual spent in saltwater (mimm 1st ana and mimm 2nd ana respectively,

Table 4-1).

Alternative natural mortalities. In addition to the default values representing “normal”

freshwater mortality probabilities, we simulated “poor” freshwater survival conditions and

“good” freshwater survival conditions (Table 4-1), while keeping natural saltwater

mortalities unchanged.

4.4.7 Fishing-induced mortality We applied fishing mortality to anadromous individuals only, as they are the only targets of

the recreational fishery. Annual harvest probabilities for these fish were derived based on

the observed sizes of fish caught and on data quantifying overall annual exploitation rates

98 (Lenormand 2003 and CIRSA, unpublished data, Figure 4-2e). Medium-sized anadromous

fish (with lengths between 200 mm and 350 mm) are most likely to be caught, because they

are abundant and, during the upstream migration of immature anadromous brook charr in

early fall (Lenormand et al. 2004), concentrated in the river’s estuary, where their

exploitation is little regulated. Smaller brook charr (with lengths between 110 mm and 200

mm) are not attractive to fishermen, whereas the bigger, mostly mature charr (with lengths

larger than 350 mm) are under spatial and temporal regulations that prevent high fishing

pressures on these larger fish. Size-selective fishing mortality is applied to individuals

regardless of their maturation status. We varied the maximal harvest probabilities in the

selectivity curves of anadromous fish between 0 and 1 in increments of 0.05.

4.4.8 Initial population structure and parameterization The initial population in the model consisted of 5000 age-1 individuals with initial lengths

following a normal distribution with mean and standard deviation estimated for the 1998-

1999-2000 year classes of fish captured in Morin creek (Thériault and Dodson 2003). A

logistic regression was applied to age-specific length distributions of immature and mature

fish to estimate the population’s PMRN (Heino et al. 2002; Dieckmann and Heino 2007).

For anadromous fish, we used data gathered from the whole Ste-Marguerite River system

(pooled from 1998 to 2001), whereas for resident fish, we used data gathered from Morin

creek (pooled from 1998 to 2002). A linear regression of lengths at ages 2 and 3 (the two

age classes for which sufficient data were available) at which the probability to mature in

the next year was 50% was used to estimate the slope and intercept of a linear PMRN

(Figure 4-2a). We then used the 1% and 99% maturation probability percentiles of 3-year-

old individuals to determine the PMRN width.

The initial population-level PMigRN was estimated using data on size and age at migration

from Morin Creek. Data on fish of ages 1 and 2 were analyzed for the years 1998-1999-

2000, as migration occurs almost exclusively at these two ages (Thériault and Dodson

2003). All individuals from the initial population were assigned genetic values for the four

evolving traits c0, c1, c2, and c3 following a normal distribution with means given by the

99 trait values implied by the population-level PMigRN (Figure 4-2b) and standard deviations

given by the assumed genetic coefficient of variation.

The initial heritability of each trait describing the probabilistic migration reaction norm was

assumed as 0.5. We do not know the actual value of heritability of plasticity for anadromy

and residency in this system, but genetic variation and heritability have been demonstrated

for plasticity in general (Scheiner 1993; Nussey et al. 2005) and have been assumed for

migration in salmonids in particular (Hazel et al. 1990; Hutchings and Myers 1994; see also

the review by Hutchings 2004a). After initialization, heritabilities, genetic variances, and

genetic covariances were free to evolve, and can thus be regarded as emerging properties of

the model. Even though heritabilities directly scale the speed of evolution, so that we must

expect slower or faster changes in reaction norms if we assume lower or higher

heritabilities, the nature of predicted evolutionary changes remains unchanged as

heritabilities are jointly increased or decreased (see, e.g., Dunlop et al. 2007).

4.5 Results

4.5.1 Impact of different exploitation rates over 100 years Increasing harvest probability causes a shift in the migration reaction norms for both age 1+

and age 2+ individuals where, for an individual of the same size, the probability of

migration is lowered as harvest probability increases (Figure 4-3). This translates into an

overall probability of migration that is decreasing with increasing harvest probability

(Figure 4-3). The absolute number of fish that migrate decreases as harvest probability

increases, and this trend is more pronounced for age 1 individuals than for age 2 (Figure 4-

3). Mean age at migration increases with harvest probability (Figure 4-3) primarily

reflecting the fact that the proportion of fish migrating at 2 years of age goes up as harvest

probability increases. Mean age at maturation did not change for residents, but decreased

for anadromous individuals (Figure 4-3). Mean individual fecundity, highly dependent on

size, decreased with maximum harvest probability for anadromous fish, but showed no

variation for resident fish (Figure 4-3). Overall abundance of the population shows little

100 change with increasing maximum harvest probability, because the number of fish in

freshwater increased while the number in saltwater decreased to almost zero (Figure 4-3).

Heritability found in the migration reaction norm varied though time, and did not show a

significant increase or decrease, either at low or high harvest probabilities (Figure S1).

4.5.2 Impact of different natural mortality rates Survival conditions in freshwater influenced the evolution of the migration reaction norm.

After 100 years of fishing, low survival in freshwater associated with poor conditions lead

to a migration reaction norm associated with a higher probability of migrating for a given

size than under normal freshwater survival. In contrast, good survival conditions in

freshwater lead to a lower probability of migrating for a given size than seen under normal

conditions (Figure 4-4). Poor survival in freshwater thus offsets the effect of fishing by

increasing the probability of migrating and the number of migrants, while good survival in

freshwater had the opposite effect (Figure 4-4). Population abundance in function of

maximum harvest probability is higher, and relatively constant, in poor than normal

freshwater survival conditions, while under good conditions important variations are seen

(Figure 4-4). The cumulative catch shows similar dome-shaped relationships for the three

survival conditions in freshwater, but peaked at higher values and harvest rates as survival

conditions worsened in freshwater (Figure 4-4).

4.6 Discussion By using a modeling approach, we explored the impact of recreational fishing on the

evolution of anadromy and residency of a small population of brook charr. Following a

hundred years of fishing of anadromous individuals, we predicted evolution in the

migration reaction norm, which translated into a decrease in average probabilities of

migration with increasing harvest rate. This change was accompanied by an increase in the

proportion of fish migrating at age 2, resulting in a higher mean age at migration. These

findings suggest that selective harvesting of anadromous fish would result in an increased

tendency for residency as well as an increased advantage of staying longer in freshwater

and delayed migration. Shifts in the maturation reaction norm towards younger age and

smaller size at maturation in commercially important marine species have been strongly

101 suggested to result from heavy fishing pressure that selected against genotypes

predisposing fish to mature later and larger (American plaice Hippoglossoides platessoides,

Barot et al. 2005; North Sea plaice Pleuronectes platessa, Grift et al. 2003; Atlantic cod

Gadus morhua Barot et al. 2004; Olsen et al. 2004, 2005). Here we show that shifts in the

reaction norm of another ontogenetic process, i.e. migration, an important life-history

characteristic in salmonids, are also expected under fishing-induced mortality.

By acting on heritable traits, selective harvesting by humans can unintentionally select

against those which they desire the most: bigger individuals and increase in harvestable

biomass (Coltman 2008; Hutchings and Fraser 2008). For instance, trophy hunting of

bighorn sheep over a period of 30 years has generated an undesired evolutionary response

in weight and horn length, both of these traits having decreased in association with a

decline in their breeding values (Coltman et al. 2003). Here we show that high harvest

rates on anadromous fish reduce the probability of migration, and thus ultimately lead to a

reduced number of fish in saltwater and thus less fish available to the recreational fishery.

Changes are also seen in age at maturation for the anadromous part of the population but

must not be interpreted as genetic changes as the maturation tendency was not allowed to

evolve in the model. These changes rather reflect the fact that at high harvest rates, only

the smallest, youngest anadromous fish are escaping the harvest process (according to the

harvest probability curves, Figure 4-2e). The removal of large fish by the recreational

fishery also causes a decline in the mean individual fecundity of anadromous fish at high

harvest probabilities.

Genetic changes induced by fisheries, as with any other selective force, are potentially

reversible, given that sufficient heritable genetic variation remains and that selection

differentials in the opposite direction are generated once fishing is relaxed or stopped (Law

2000). According to the body of work on commercially exploited marine species, it

appears that reversibility is a difficult and slow process (Barot et al. 2004; Reznick and

Ghalambor 2005; Swain et al. 2007). Although we have not explored the extent of trait

102 reversal following the cessation of fishing, our results suggest that heritable additive

genetic variance in the migration reaction norm is preserved even at high harvest rates. It

has been theoretically demonstrated elsewhere that a large fraction of the genetic variation

underlying threshold traits is maintained even under strong directional selection, because

variation remains “hidden” by virtue of the threshold nature of the trait (Roff 1994). It

follows from the preservation of genetic variation that threshold traits may be quasi-

immune to extinction, and that giving the return of favorable conditions, a lost alternative

tactic could be restored provided that the mechanisms for producing it have not degenerated

during a period of disuse (West-Eberhard 2003). In fact, cases of non-anadromous

salmonid fish stocks that have kept their capacity to migrate or that have given rise to

anadromous ones have been documented (Staurnes et al. 1992; Pascual et al. 2001;

Thrower et al. 2004).

Our study also aimed at assessing how varying natural survival conditions in freshwater

could influence evolution of migration. The unpredictability of evolution has been

demonstrated on the scale of decades in Darwin’s finches, where selection on body size and

beak shape was changing direction in time (Grant and Grant 2002). Fluctuating selection on

body size has been hypothesized as a factor favoring threshold variation and thus ultimately

maintaining alternative male life-cycles in Atlantic salmon (Aubin-Horth et al. 2005). The

results obtained here emphasize the idea that natural variation in the environment can act to

maintain phenotypic and genetic variability (see also Thrower et al. 2004). Shifts in

migration reaction norms owing to selective harvesting were either impeded or exacerbated

depending on if survival in freshwater was low or high, respectively. In the face of high

temporal variability, such as that occurring in northern temperate salmonid rivers,

predictions about rates and magnitude of life-history evolution caused by fishing would

certainly become difficult over the long-term (e.g. Grant and Grant 2002).

We wanted to focus on fishing-induced changes in the migration reaction norm, which has

received little, if any, attention in the published literature, and in order to keep predictions

103 simple, we did not allow for the evolution of other life-history traits, such as growth, the

maturation reaction norm, or reproductive investment. These traits are most likely to evolve

but usually only maturation age or size, or the maturation reaction norm have been allowed

to evolve in other models (Ernande et al. 2004; Dunlop et al. 2007). However, adding

growth as an evolving trait did not significantly alter the predictions about migration

(Figure S2). The inclusion of the PMigRN as an evolving trait generates a substantial level

of complexity; adding additional variables would unduly complicate the model, at least at

this stage of investigation. Future extensions of the model could include other such

additional evolving traits. The effect of correlated response to selection would also merit

further investigation. Fishing-induced selection on one trait could generate a response in

other genetically correlated traits: this could impede or increase the rate of evolutionary

change, depending on the sign and magnitude of the correlation (Lynch 1999; Walsh et al.

2006; Hutchings and Fraser 2008). Smolting, maturation and growth have been shown to

be genetically correlated to varying degrees in rainbow trout (Oncorhynchus mykiss) and

the dynamic interactions of these traits with season-specific growth rates have been

hypothesized to be a key factor maintaining genetic variation in smolting, despite complete

selection against the phenotypic expression of migration (Thrower et al. 2004). Genes

associated with smolting are thus conserved in the population, through selection for, or

against, other genetically correlated traits. Here migrating at age 1 was positively

genetically correlated with size at age 1 (Thériault et al. 2007b). One could expect that

such a correlation would exacerbate the effect of fishing: selecting against anadromous

individuals migrating at age 1 might select for smaller size at age 1, associated with a

higher probability of staying resident. However, a smaller size at age 1 could also translate

into a smaller size at age 2, which is in turn associated with a higher probability of

migrating. The effect of genetic correlation among traits related to the life-history form

adopted in the face of fishing-induced selection remains to be rigorously explored.

Despite their commercial and recreational interests, the effects of fishing on salmonids

(beyond the immediate consequences for abundance) have rarely been demonstrated.

Genetic responses resulting from the effect of commercial fisheries have been proposed to

104 explain a decrease in size of Pacific salmon (Ricker 1995), as well as change in age and

size at maturation in the European grayling (Thymallus thymallus) (Haugen and Vøllestad

2001), lake whitefish Coregonus clupeaformis (Handford et al. 1977) and Atlantic salmon

(Bielak and Power 1986). However, most of the arguments presented in these previous

studies were largely circumstantial. By illustrating the impact of a sport-fishery on the

evolution of life-history tactics in salmonids, along with its associated ecological and

demographic consequences, this study contributes to the emerging view that evolution can

be rapid enough to be an integral part of ecological interactions (Hendry and Kinnison

1999; Reznick and Ghalambor 2005). The high harvest probabilities that were associated

with the most significant demographic and evolutionary changes in this study are more

often associated with commercial salmonid fisheries (e.g. Atlantic salmon, Dempson et al.

2001) than with recreational fisheries (e.g. this system, mean harvest probability = 0.3,

CIRSA, unpublished data,); however, the latter has still the potential to contribute to

fisheries declines (Cooke and Cowx 2006). It is our hope that modeling approaches such as

the one used in this study will be increasingly integrated by managers and policy-makers as

a complement to traditional fisheries management approaches based on population

dynamics alone.

4.7 Acknowledgments We thank the CIRSA (Centre Interuniversitaire de Recherche sur la Saumon Atlantique)

where data on the Ste-Marguerite River system were collected. The authors would also like

to thank C. Jørgensen and J.A. Hutchings for helpful comments on earlier drafts of this

manuscript. Funding of this project was provided to J.J.D. and L.B. by NSERC of Canada

(Strategic Grant and Collaborative Special Projects), the Fondation de la Faune du Québec,

the Government of Québec (FAPAQ), the Government of Canada (Economic development)

and the financial partners of AquaSalmo R&D. This study is a contribution to the program

of CIRSA and Québec-Océan. V.T. was financially supported by funding from the Natural

Sciences and Engineering Research Council of Canada (NSERC) and the Fonds québécois

de recherches sur la nature et les technologies (FQRNT). E.D. gratefully acknowledges

financial support provided by the Research Council of Norway.

105

4.8 Table Table 4-1. Model parameters and their values. Symbol Description Equation Source Value

__ Initial mean body size (mm) __ 1 82.98

__ Initial standard deviation of body size (mm) __ 1 13.68

__ Mean PMRN slope of resident morph (mm/year) __ 2 -32.41

__ Mean PMRN intercept of resident morph (mm) __ 2 259.72

__ PMRN width of resident morph (mm) __ 2 114.53

__ Mean PMRN slope of anadromous morph (mm/year)

__ 2 -177.58

__ Mean PMRN intercept of anadromous morph (mm)

__ 2 843.38

__ PMRN width of anadromous morph (mm) __ 2 532.9

__ Mean emergence size (mm) __ 1 31.71

__ Standard deviation of emergence size (mm) __ 1 5.52

h2 Initial heritability of evolving PMigRN traits __ __ 0.5

CV Coefficient of variation for all traits __ __ 0.08

c0 Evolving PMigRN trait 1 1 -12.36

c1 Evolving PMigRN trait 1 1 0.11

c2 Evolving PMigRN trait 1 1 9.69

c3 Evolving PMigRN trait 1 1 -0.08

gs Mean growth rate in saltwater (mm/year) 3 2 95.53

gf Mean growth rate in freshwater (mm/year) 3 1 35.35

GSI Mean gonado-somatic index 4 2 0.147

H1 Constant in fecundity function 5 2 0.04

H2 Constant in fecundity function 5 2 2.86

r Constant in stock-recruitment function 6 3 25.0

b Constant in stock-recruitment function 6 3 0.0027

mimm res Immature natural mortality probability for resident morph under default conditions

__ 2 0.60

mmat res Mature natural mortality probability for resident morph under default conditions

__ 2 0.88

mimm 1st ana Immature 1st year natural mortality probability for anadromous morph under default conditions

__ 2 0.80

mimm 2nd ana Immature 2nd year mortality probability for anadromous morph under default conditions

__ 2 0.60

106 mmat ana Mature natural mortality probability for

anadromous morph under default conditions __ 2 0.55

mimm res poor Immature natural mortality probability for resident morph under poor conditions

__ 2 0.80

mmat res poor Mature natural mortality probability for resident morph under poor conditions

__ 2 0.95

mimm res good Immature natural mortality probability for resident morph under good conditions

__ 2 0.20

mmat res good Mature natural mortality probability for resident morph under good conditions

__ 2 0.70

PMRN = probabilistic maturation reaction norm; PMigRN= probabilistic migration reaction norm. Sources : (1) Morin Creek data reproduced from Thériault (2001) and Thériault and Dodson (2003), (2) Ste-Marguerite River data for anadromous fish and Morin Creek data for resident fish reproduced from Lenormand (2003), (3) modified from Elliott (1993).

107

4.9 Figures

Figure 4-1. Schematic of the life-cycle of brook charr showing the sequence of events in the eco-genetic model.

108

Figure 4-2. Empirically derived functions used in the model. (a) Probabilistic migration reaction norms estimated for Morin creek (reproduced from Thériault and Dodson 2003); (b) Probabilistic maturation reaction norms estimated for anadromous and resident individuals showing the 50% (midpoint) 1% and 99% probability curves; (c) Relationship between fecundity and body size for anadromous (open circles) and resident individuals (closed circles) reproduced from Lenormand (2003); (d) Stock-recruitment relationship derived from Elliott (1993); (e) Harvest probabilities curves according to different maximal harvest probabilities increasing from 0.05 to 1 in increments of 0.05.

109

0 100 200 300 400Body size (mm)

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Figure 4-3. Model results after 100 years of fishing-induced mortality, according to different maximum harvest probabilities. The top two panels show the age-specific migration reaction norms (line thickness increases with increasing maximum harvest probabilities between 0 and 1). Results are averaged for 30 independent model runs.

110

0 100 200 300 400Body size (mm)

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Figure 4-4. Model results after 100 years of fishing-induced mortality, according to varying survival conditions in freshwater (poor, normal and good, see methods). The maximum harvest probability was 0.5. Results are averaged for 30 independent model runs.

111 4.10 Supplemental material

4.10.1 Heritability through time

0 20 40 60 80 100Time (years)

0.485

0.49

0.495

0.5

0.505

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itabi

lity

in c

1

Max harv prob = 0.1Max harv prob = 0.8

0 20 40 60 80 100Time (years)

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0 20 40 60 80 100Time (years)

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erita

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c3

0 20 40 60 80 100Time (years)

0.485

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in c

2

Figure S1. Heritability through time according to different maximum harvest probability

values for the different evolving coefficients describing the probabilistic migration reaction

norm (co, c1, c2, c3 – see mtehods). All results represent averages over 30 independent

model runs.

.

112

4.10.2 Comparison of results with growth included as an evolving trait The genetic growth rate was the intrinsic capacity for growth or the fastest an individual

could possibly grow, and was based on the mean growth rate in saltwater (95.53 mm/year)

with an assumed heritabiliy value of 0.5. Individuals living in freshwater grow slower due

to the poorer growing environment that they experienced, and therefore, the phenotypic

growth rate for these individuals, g, was defined as

g = (Gg + VE ) − Rf (Gg + VE )[ ] (S1)

where Gg is the genetic growth rate, VE the environmental variance and Rf the proportional

reduction in freshwater,

Rf =(gs − gf )

gs

(S2)

where gs and gf are the mean growth rate in salt and freshwater respectively, empirically

derived from immature individuals of the Ste-Marguerite River system and Morin Creek

(Table 1).

We included a trade-off between growth capacity and survival. Without such a cost, the

model would always favor higher growth capacities, and thus growth rate would evolve

indefinitely and be unrealistically high. With this trade-off, the probability of mortality Mg

increased with increasing growth capacity Gg,

max

gg

GM

g=

(S3)

where gmax is the maximum growth rate at which the probability of survival drops to 0

(gmax = 140 mm/year). Owing to this additional mortality, we adjusted the natural mortality

probabilities accordingly so that the total natural mortality probability was the same as the

simulations without evolving growth.

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0 100 200 300 400Body size (mm)

0

0.2

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0.6

0.8

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roba

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y of

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igra

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at a

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0 100 200 300 400Body size (mm)

0

0.2

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1

Pro

babi

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of

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age

2


0

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0.8

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of m

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0

400

800

1200

1600

Num

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ting

Figure S2. Sensitivity of migration results to allowing growth capacity to evolve. Top

panels give the probability of migrating when growth capacity is an evolving trait. Bottom

panels show the probability and numbers migrating for age 1 when growth is an evolving

trait (triangles), for age 2 when growth is an evolving trait (plus signs), for age 1 when

growth is not an evolving trait (solid lines with no symbols), and for age 2 when growth is

not an evolving trait (dashed lines with no symbols).

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4.10.3 The effect of density-dependent growth We tested the effect of including density-dependent growth in freshwater on model results.

To implement density-dependent growth, we assumed a reduction in somatic growth as

biomass increased, owing to density-dependent resource limitation:

1P

d D

ggBb

=+

where gd is the density-dependent growth rate in freshwater, gP is the phenotypic growth

rate in freshwater (i.e., the growth rate in freshwater before density-dependent growth is

taken into account), b is the freshwater population biomass, and B and D are constants

(Dunlop et al. 2007).

As we increase the strength of density-dependence (by increasing B or D), there is little

effect on the probability to migrate at age 1. However, the probability to migrate at age 2

increases as the strength of density-dependence increases. Therefore, severe density-

dependence in growth is expected to offset the fishing-induced tendency to become a

resident, but most notably for age 2 individuals.

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Figure S3. The effect of density-dependent growth in freshwater on the probability to

migrate to saltwater. As B or D is increased, the severity of density-dependent growth is

increased. Fishing occurred for 100 years at a maximum harvest probability of 0.5.

Results are averaged over 30 independent model runs.

Chapitre 5. Conclusion générale « Pour tirer le meilleur parti des connaissances

acquises, pour en extraire toute la richesse, il importe de ne pas s'y habituer trop vite, de se laisser le temps

de la surprise et de l'étonnement.» Hubert Reeves

5.1 Rappel des principaux résultats Cette étude voulait apporter un peu plus de lumière sur le déterminisme génétique de

l’anadromie et la résidence chez l’omble de fontaine et s’inscrit dans un contexte général

plus large qui vise la compréhension de l’évolution des tactiques alternatives de vie. Les

résultats de cette étude répondent sans contredit à cet objectif. Tout d’abord, nous avons

mis en évidence qu’une reproduction est fréquente entre anadromes et résidents dans notre

système, et que le mélange semble être assuré par les mâles résidents qui, en adoptant

vraisemblablement une tactique de reproduction furtive en présence de plus grosses

femelles, fécondent autant les œufs de femelles anadromes que de femelles résidentes. Un

examen plus poussé du système de reproduction nous a aussi permis de conclure en un plus

grand succès reproducteur pour les femelles anadromes, lié en partie à leur plus grande

taille. Par contre, la plus grande taille des mâles anadromes ne semble pas se refléter dans

un meilleur succès reproducteur : les mâles résidents obtiennent autant de paternités que les

plus gros mâles anadromes. Cette analyse détaillée du système de reproduction a aussi

révélé que tout type de croisement, qu’il soit entre résidents, anadromes, ou bien entre

résident et anadrome, peut produire des jeunes des deux formes. Ces résultats sont les

premiers à examiner en milieu naturel le système de reproduction entre anadromes et

résidents où des mâles et femelles sont retrouvés sous les deux formes. Ils appuient

l’hypothèse d’un certain déterminisme environnemental dans l’adoption d’une forme ou

l’autre. De plus, ces résultats viennent réfuter certaines croyances populaires, qui veulent

qu’anadromes et résidents fassent partie de deux populations distinctes, justifiant une

gestion différente et séparée. Du moins, le ruisseau Morin au Saguenay ne fait plus partie

de cette croyance…

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Un des principaux résultats de cette thèse consiste en la démonstration d’une d’héritabilité

significative pour une tactique alternative en milieu naturel. Avec le raffinement des

méthodes de reconstruction de pedigree et des modèles statistiques employés en génétique

quantitative, nous avons pu estimer l’héritabilité de l’anadromie et la résidence, de même

que de la taille, ainsi que la corrélation génétique entre ces deux traits. Dans le contexte où

la tactique adoptée est un trait-seuil, les valeurs ici estimées (0.52-0.56) représentent

l’héritabilité du ou des traits sous-jacents (« liability trait »). La valeur de ce trait sous-

jacent, conjointement avec la position du seuil, va déterminer quelle forme sera adoptée.

Nos résultats démontrent que la valeur du trait sous-jacent se transmet de génération en

génération et donc soulignent l’influence des facteurs génétiques dans l’adoption de

l’anadromie et la résidence. Dans le ruisseau Morin, sous les conditions où notre étude a

été menée, il y a toutefois la moitié de la variation phénotypique dans la tactique qui n’est

pas expliquée par la variation génétique, ce qui laisse place aux conditions

environnementales. Nos résultats suggèrent de plus que la corrélation phénotypique entre

la taille et la tactique préalablement observée (Thériault et Dodson 2003) est en partie

déterminée par une corrélation génétique significative. L’évolution de la tactique et de la

taille se ferait donc conjointement : une sélection sur un ou l’autre de ces traits aura

vraisemblablement un effet sur l’autre.

Finalement, grâce à un exercice de modélisation, nous avons démontré quels pourraient être

les effets génétiques et démographiques potentiels de la pêche sportive sur l’anadromie et la

résidence. La plasticité dans l’adoption d’une tactique ou l’autre est incluse dans le modèle

à travers une approche de norme de réaction, où la probabilité de migrer en fonction de

l’âge et la taille a une base héritable (i.e. nous assumons qu’il existe une variation génétique

dans les normes de réaction). Une pêche sportive ciblant les anadromes sur une période de

100 ans a comme effet de déplacer les normes de réaction, de sorte que pour une même

taille, les individus ont en moyenne une moins grande probabilité de migrer à mesure que

l’intensité de la pêche augmente. La résidence est donc favorisée et la proportion

d’anadromes dans la population diminue. À de fortes intensités de pêche, le nombre de

poissons anadromes disponibles pour les pêcheurs sportifs diminue également. Ces

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changements s’accompagnent d’une légère baisse dans l’âge et la taille à maturité. Par

contre, il semble qu’un taux maximal de récolte autour de 30% soit une cible intéressante

d’un point de vue de gestion, lequel, tout en maximisant le nombre de poissons pêchés, a

peu de conséquences sur la probabilité de migrer.

5.2 Contributions Cette thèse contribue à l’avancement des connaissances à trois niveaux. Tout d’abord, au

niveau théorique, ce travail approfondit nos connaissances sur les comportements de

reproduction et les déterminants du succès reproducteur, sur l’évolution des cycles vitaux

et sur la genèse et la dynamique de la diversité phénotypique. Ensuite, au niveau

méthodologique. Tout au long de cette thèse, de nouvelles approches et de nouveaux

outils ont été mis à profit. La réassignation parentale en milieu ouvert, naturel, représente

un défi de taille et cette étude est un excellent exemple des limites et des possibilités d’une

telle entreprise. L’estimation de l’héritabilité en nature fait ses preuves depuis les dernières

années, mais cette thèse fait un pas de plus en estimant des paramètres de génétique

quantitative basés sur des pedigrees obtenus grâce à des marqueurs moléculaires, en ne

considérant qu’une génération, avec seul les liens plein-frères (voir aussi Wilson et al.

2003a). L’approche « éco-génétique » de modélisation ici développée est le dernier cri en

ce qui concerne l’inclusion des facteurs génétiques, environnementaux et démographiques

lorsque l’on s’intéresse à l’effet de la mortalité sélective (Dunlop et al. 2007). Cette thèse

sert donc de bases méthodologiques solides et stimulera (ou du moins ne découragera pas!),

je l’espère, les études de génétique quantitative en milieu naturel. Elles représentent un

défi, certe, mais les bénéfices de pouvoir appliquer ces résultats à ce qui se passe vraiment

dehors, loin de nos bassins, cages et éprouvettes, en valent sans contredit le coup!

Finalement, au niveau pratique. L’omble de fontaine est une espèce d’intérêt sportif

grandissant au Québec, surtout pour l’exploitation des dites « truites de mer ». Avant que

le CIRSA n’entreprenne son programme de recherche, peu était connu sur l’omble

anadrome. Cette thèse apporte des nouvelles connaissances et pourrait éclairer les

différents acteurs de la gestion des salmonidés au Québec, et pourquoi pas, ailleurs en

Amérique. De plus, les conclusions de cette thèse peuvent être mises à contribution dans

le domaine de l’aquaculture où l’héritabilité est un paramètre important des programmes de

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croisements. En étudiant l’écologie et l’évolution d’une espèce exploitée, ce travail tente

de comprendre dans le but de pouvoir prédire. Prédire comment les perturbations

anthropogéniques, biologiques et physiques de l’environnement vont influencer l’histoire

de vie, les taux d’accroissement et la persistance des populations. Cette capacité de

prédiction représente en quelque sorte le but pratique de l’écologie et de l’évolution, et

cette thèse contribue à l’atteinte de cet objectif. Un ensemble de données empiriques a été

exploité ici, créant un cadre réaliste permettant d’émettre des prédictions quant au devenir

d’une population de salmonidés exploitée par la pêche sportive. Cette approche est une

façon élégante de jumeler théorie et apllication, et d’utiliser toute l’information disponible

sur le cycle de vie d’une espèce, des paramètres écologiques et démographiques à

l’architecture génétique.

5.3 La valeur et la signification de l’héritabilité En cherchant à comprendre les bases génétiques et environnementales de l’anadromie et la

résidence, on tente en fait de répondre à l’objectif central de la biologie évolutive :

expliquer la diversité. Les différents phénotypes peuvent être le produit de génotypes

différents, le résultat de différents environnements dans lesquels les individus se

développent, et, bien entendu, une combinaison de ces deux facteurs (Kruuk 2004). La

motivation derrière l’estimation des bases génétiques d’un trait repose en fait sur le désir de

vouloir prédire si un changement phénotypique permanent peut être causé par l’effet de la

sélection. Si certains phénotypes contribuent davantage à la génération suivante que

d’autres, et que ces différences phénotypiques sont associées à des différences génétiques

additives, une réponse évolutive est attendue. Un trait doit donc être héritable pour évoluer

sous l’effet de la sélection, dans le sens génétique du terme. La génétique quantitative pose

donc la question du « comment » (comment le phénotype est-il déterminé?), qui est

associée à la question du « pourquoi » (pourquoi observe-t-on tel ou tel phénotype?), posée

par l’étude de l’adaptation et de l’évolution (Lynch et Walsh 1998; Kruuk 2004).

La compréhension du potentiel adaptatif des espèces prend tout son sens dans le contexte

environnemental actuel. Réchauffement climatique et conservation de la biodiversité sont

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sur toutes les lèvres. Les humains sont d’ailleurs maintenant considérés comme la plus

grande force évolutive sur la planète (Palumbi 2001). Face aux perturbations anthropiques,

qui prennent la forme de dégradation et fragmentation de l’habitat, de surexploitation,

d’introduction d’espèces exotiques ou de modification du climat, les espèces doivent

répondre aux forces sélectives occasionnées par ces changements, sinon c’est l’extinction

qui les attend (Ashley et al. 2003; Pulido et Berthold 2004). Les populations s’adaptent

aux changements contemporains dans leur environnement de deux façons : soit par un

changement plastique (plasticité phénotypique), soit par des changements génétiques

(microévolution). La plasticité phénotypique est vue comme une façon de surmonter des

changements à plus court terme. Les réponses plastiques sont limitées par la gamme

d’environnements dans lesquels les réponses phénotypiques sont adaptatives : en dehors de

cette gamme, l’ajustement du phénotype peut être insuffisant (Pulido et Berthold 2004).

C’est pourquoi dans un environnement continuellement en mutation, les adaptations par

plasticité phénotypique seront tôt ou tard incapables de garder le rythme. Les réponses

évolutives sont associées à des changements à plus long terme et sont en principe la façon

dont les populations répondent à des changements continuels dans leur environnement, en

supposant la présence de variation génétique additive. La question est alors de savoir si les

réponses évolutives se feront assez rapidement, dans un monde où les changements causés

par les humains surgissent à une intensité et un taux sans précédent, pour assurer la

persistance des espèces (Hendry et Kinnison 1999; Berteaux et al. 2004).

5.4 Pour ou contre les réponses évolutives ? Une contradiction voit le jour lorsque l’on parle du potentiel évolutif adaptatif des espèces.

Une réponse évolutive rapide face aux perturbations anthropiques est parfois souhaitée,

alors qu’elle est parfois indésirée. Dans un contexte de conservation, nous souhaitons que

les espèces puissent s’adapter pour échapper à l’extinction, et alors nous voyons d’un bon

œil les réponses évolutives. Par exemple, l’ajustement de date de ponte vers une ponte

hâtive est souvent vu comme une réponse aux températures qui augmentent, de sorte que la

naissance des petits puisse coïncider avec les meilleures conditions de croissance (e.g. plus

de nourriture disponible). Alors que chez les oiseaux les évidences suggèrent que la ponte

hâtive est une réponse plastique au réchauffement climatique (Sheldon et al. 2003; Pulido

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et Berthold 2004; mais voir Nussey et al. 2005), une étude a démontré que l’avancement de

la date de mise-bas chez les écureuils rouges était en partie due à un changement génétique

(Réale et al. 2003). En à peine 10 ans, l’augmentation de température, traduite par une

augmentation de nourriture, a causé une réponse évolutive, menant à une meilleure

association phénotype-environnement. De telles réponses sont bénéfiques et apportent un

peu d’optimiste quant à la persistance des espèces face à d’importants changements

environnementaux.

Par contre, dans d’autres cas de telles réponses ne sont pas souhaitées. Nous ne désirons

pas voir des espèces nuisibles (du point de vue de l’homme bien entendu) s’adapter

rapidement aux antibiotiques et aux pesticides, comme l’histoire l’a démontré pour les

maladies bactériennes et les insectes ravageurs (Palumbi 2001). De même, nous ne

souhaitons pas que le rendement de nos récoltes diminue, ce qui est souvent le cas parce

que plusieurs exploitations, en choisissant les gros individus, favorisent les plus petits. Il

en résulte alors un changement génétique dans la population qui se traduit en une

diminution de la biomasse récoltable, changement qui peut prendre beaucoup plus de temps

à renverser qu’un changement plastique. Nous nous retrouvons donc à défavoriser ce que

nous désirons le plus : les plus gros individus, les meilleures récoltes (Conover et Munch

2002; Coltman et al. 2003; Hutchings 2004b; Hutchings et Fraser 2008). Les adaptations

aux nouveaux environnements sont donc toujours bénéfiques du point de vue des espèces,

leur permettant de survivre et de se reproduire, mais parfois néfastes du côté de l’homme.

5.5 La perte ou la cachette de l’anadromie? Dans le contexte d’un phénotype alternatif tel l’anadromie et la résidence, la question de la

fixation phénotypique revient toujours. Dans une population où seulement une des

tactiques est présente, on se demande si cela signifie la perte de la capacité d’exprimer

l’autre tactique, et donc, en d’autres mots, la perte de la plasticité. Dans le cas de l’omble

de fontaine, cette question est particulièrement intéressante : suite à la colonisation du Sud

vers le Nord dans l’Est de l’Amérique du Nord à partir d’un refuge glaciaire il y a plus de

10 000 ans (où les fondateurs auraient vraisemblablement été anadromes), on note que la

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forme migratrice a pratiquement disparu de l’aire de distribution Sud de l’espèce (Castric et

Bernatchez 2003). Plusieurs facteurs peuvent expliquer la fixation d’un phénotype

alternatif dans un contexte de trait seuil et nous éclairer sur la situation actuelle de l’omble

de fontaine.

Premièrement, une seule tactique peut être exprimée dans une population simplement à

travers une réponse plastique, parce que les conditions qui favorisent l’induction de cette

tactique sont toujours présentes. Donc, les conditions environnementales font en sorte que

le seuil est dépassé pour tous les individus. Dans ce cas particulier la norme de réaction ne

change pas, le phénotype observé n’est que le résultat du déplacement le long de cette

norme de réaction, et des changements génétiques ne sont donc pas impliqués (Fig. 5-1b).

Ceci s’illustre facilement lorsque les facteurs inducteurs sont évidents : par exemple, dans

un environnement sec, les feuilles de boutons d’or (Ranunculus sp.) n’exprimeront que la

forme terrestre (par opposition à la forme aquatique), comme cette forme est une réponse

facultative aux conditions d’humidité (Cook et Johnson 1968 dans West-Eberhard 2004).

Combien de temps un phénotype alternatif peut-il rester intact et être ré-exprimé au retour

des conditions favorables est encore peu investigué.

Ensuite, une fixation phénotypique peut être le résultat d’une réponse évolutive, qui

implique alors des changements génétiques. Face à une sélection directionnelle, favorisant

toujours le même phénotype, la fréquence de ce dernier augmentera dans la population, car

le seuil pour sa production changera. Ce changement est illustré graphiquement par le

déplacement des normes de réaction (Fig. 5-1c). La fixation du phénotype a lieu lorsque le

seuil est poussé si loin que malgré toute la gamme des variations environnementales

présentes, le même phénotype est toujours exprimé. Fait intéressant, la fixation du

phénotype peut se faire sans la fixation du génotype : une bonne portion de la variance

additive est alors conservée. À mesure que la fréquence d’une forme augmente dans la

population, l’intensité de la sélection diminue, car la variance phénotypique sur laquelle la

sélection peut agir diminue (i.e. la population approche de la fixation). La sélection

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directionnelle n’érode donc pas toute la variance génétique qui se cache parmi les individus

qui expriment le même phénotype avantagé (Roff 1994a). Par la nature même du trait seuil,

la variance additive associée au seuil et aux traits sous-jacents qui influencent l’adoption

d’une tactique se trouve non-exposée à la sélection, et peu être donc conservée. Pulido

(2007) stipule que ce bassin de « variation cryptique », protégé de l’action de la sélection

naturelle et donc difficilement éliminable, permet l’expression récurrente de la migration

chez la plupart des populations d’oiseaux qui semblent entièrement résidentes. De plus, la

conservation de la variance génétique pour des phénotypes alternatifs tels que la migration

et la résidence résiderait aussi dans le fait que ces phénotypes sont des traits complexes,

polygéniques, sujet à des interactions pléiotropiques antagonistes (Roff 1996). Certaines

contraintes imposées par des pressions de sélection de direction opposée sur des traits

génétiquement corrélés contribuent vraisemblablement à la quasi-immunité des phénotypes

alternatifs face à l’extinction (Staurnes et al. 1992; Pulido 2007). Ce scénario signifie donc

que des populations qui n’expriment qu’un phénotype et qui apparaissent donc « fixées »

ont le potentiel d’exprimer le phénotype alternatif si une sélection vers celui-ci se produit.

C’est peut-être ce qui explique l’apparition des formes anadromes suite à l’introduction de

souche résidente dans des rivières où elles étaient préalablement inexistantes (Pascual et al.

2001). Et c’est peut-être le cas pour l’omble de fontaine, où les populations du Sud

auraient conservé cette plasticité, mais n’exprimeraient qu’une seule tactique suite à une

sélection directionnelle favorisant les résidents. Les causes de cet avantage lié à la

résidence dans l’aire de distribution Sud de l’espèce ne sont pas claires. Qu’il y a-t-il de

différent dans le paysage adaptatif de ces populations : Meilleures conditions en eau douce?

Moins bonnes conditions en eau salée? Surexploitation des formes anadromes? Destruction

de l’habitat? Qui sait?...

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a

b

c

d

Figure 5-1. Représentation schématique de l’anadromie et la résidence en tant que trait seuil. (a) Un individu adopte la tactique qui lui procure le plus haut fitness selon la valeur du trait sous-jacent. L’intersection des fonctions de fitness représente le seuil, et la position de celui-ci changera si les fonctions de fitness se déplacent, influençant directement les proportions de chaque morphe dans la population (zone noire pour Anadrome, grise pour Résidents). Les cas où seule la tactique R est exprimée sont présentés en b, c et d. (b) Les conditions présentes (zone grise) font en sorte que le seuil est toujours dépassé. Les différents seuils représentent la variabilité génétique individuelle. (c) Les seuils sont déplacés sous l’effet de la sélection. (d) Assimilation génétique, menant à la canalisation du trait, où seule la résidence peut être exprimée, peu importe la valeur du trait sous-jacent.

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Finalement, malgré qu’une perte totale de la plasticité semble difficile, les changements

génétiques occasionnés par une sélection directionnelle poussés à l’extrême peuvent mener

ultimement à la canalisation d’un trait. C’est le phénomène d’assimilation génétique

(Pigliucci et Murren 2003; Pigliucci et al. 2006). L’assimilation génétique est le processus

par lequel un phénotype ne change plus de forme en réponse à un signal environnemental,

il est assimilé, canalisé. L’induction du phénotype alternatif n’est plus possible, la

plasticité est perdue. L’assimilation génétique entraîne une norme de réaction plate, où la

variance génétique est nulle (Fig. 5-1d). Parce que le même phénotype est continuellement

avantagé et que la plasticité a un coût (van Kleunen et Fischer 2005), elle sera

éventuellement perdue. Certains exemples, où l’induction d’un phénotype alternatif n’est

plus possible, suggère une assimilation génétique (plantes, Cook et Johnson 1968;

papillons, Shapiro 1976; oiseaux Pulido 2007). Certains auteurs (West-Eberhard 2003;

Pigliucci et al. 2006) prétendent que l’assimilation génétique a le potentiel d’expliquer

plusieurs processus évolutifs écologiques. Selon cette théorie, la plasticité phénotypique

serait en grande partie un processus développemental, inhérent, et permettrait l’apparition

de nouveaux traits quand une population fait face à un nouvel environnement. Ce nouveau

trait subit alors l’effet de la sélection et, lorsqu’il se trouve toujours avantagé, peut

éventuellement se traduire en une assimilation génétique (Price et al. 2003; Pigliucci et al.

2006). Serait-on en présence d’un exemple d’assimilation génétique « en cours » de la

forme résidente, suivant le gradient Sud-Nord de la colonisation des rivières par l’omble de

fontaine anadrome?

5.6 Perspectives «Quand on ne peut revenir en arrière, on ne doit se

préoccuper que de la meilleure façon d'aller de l'avant.»

Paulo Coehlo

Une thèse de doctorat soulève souvent plus de questions qu’elle ne trouve de réponses, et

c’est bien ainsi, car c’est le questionnement qui fait avancer nos connaissances. On dit

qu’estimer correctement son ignorance est une étape saine et nécessaire. Ce travail apporte

des éléments importants à notre compréhension de l’évolution des phénotypes alternatifs,

mais laisse la porte ouverte (encore grande) à de futures recherches.

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Une piste intéressante à explorer réside dans la nature conditionnelle de l’anadromie et la

résidence. L’hypothèse veut qu’un individu adopte la tactique qui lui procure le plus haut

fitness, par rapport à son statut individuel (ex. taille, Gross 1996, Fig. 5-1a). Il y a donc peu

d’intérêt à comparer le fitness entre deux tactiques, car ce que nous observons est déjà le

résultat de ce qui est en théorie plus profitable au niveau de l’individu. Pour établir la

nature conditionnelle de la stratégie, la vraie question est alors de savoir quel aurait été le

fitness d’un individu qui adopte la tactique A s’il avait opté pour l’autre tactique. Il serait

alors intéressant d’évaluer, pour un même individu (i.e. un même génotype), les

conséquences d’adopter chacune des tactiques. Cet objectif n’est peut-être par contre pas

réalisable, car comment « forcer » un individu à adopter une tactique particulière, alors que

son mode de régulation est adapté pour exprimer l’autre tactique? La façon la plus

convaincante de mettre en évidence la nature condition-dépendante de la sélection dans le

contexte de la stratégie conditionnelle reste alors de démontrer que les fonctions de fitness

(fitness en fonction du statut de l’individu au moment de la « décision »), ne sont pas

linéaires (voir par exemple Hunt et Simmons 2001). La démonstration que les pentes

changent et que ce changement corresponde à un changement de phénotype viendrait

fortement suggérer que les fonctions de fitness se croisent, telle que stipulé par le modèle

de stratégie conditionnelle (Gross 1996). Dans un cas comme l’anadromie et la résidence,

la mise en relation du fitness avec le statut (ou la valeur du trait sous-jacent) n’a jamais été

réalisée, à ma connaissance. Cet objectif en est par contre un d’envergure, car il implique

de connaître à la fois la valeur du trait qui influence l’adoption d’une tactique pour chaque

individu, et le fitness du même individu, deux données qui sont difficilement mesurables, et

qui ne sont pas mesurées au même moment du stade de vie.

Il serait ensuite pertinent d’estimer la variance génétique additive (et par le fait même

l’héritabilité) présente dans le seuil, et non seulement à travers les traits sous-jacents

comme réalisé ici. Nous avons supposé que cette variance génétique dans le seuil était

présente pour les besoins du chapitre 4 basé sur des exemples existants dans la littérature,

surtout chez les insectes (Emlen 1996; Moczek et Nijhout 2003; Tomkins et Brown 2004).

127

La présence d’une telle variance est aussi suggérée chez les salmonidés (Hutchings et

Myers 1994; Aubin-Horth et al. 2005), mais, à ma connaissance, n’a jamais été

empiriquement démontrée. Une telle entreprise est possible en laboratoire et est

envisageable même en milieu naturel en comparant l’incidence des deux tactiques entre des

familles qui ont la même distribution du trait sous-jacent. En connaissant la valeur du seuil

(par exemple la taille où l’adoption d’une tactique se fait), on peut aussi estimer

directement l’héritabilité de cette valeur. Ce genre d’étude est présentement en cours dans

le laboratoire de J.J. Dodson. La démonstration d’une variance génétique importante

viendrait renforcer le bien-fondé de nos prédictions quant à l’évolution de l’anadromie et de

la résidence en tant que trait seuil.

Cette étude se voulait au départ une étude comparative entre plusieurs rivières où l’on

retrouve des individus anadromes et résidents en sympatrie. Est-ce que la dynamique

anadromes-résidents est la même entre les systèmes (ex. reproduction entre les formes) et si

non, quelles pourraient être les causes de ces différences? L’héritabilité de la tactique

diffèrent-t-elle entre systèmes? La notion d’héritabilité variable selon les conditions

environnementales, bonnes ou mauvaises, a été soulevée récemment (Hoffman et Merilä

1999; Charmantier et Garant 2005). Une comparaison spatiale des estimés d’héritabilité,

de même que temporelle, aurait contribué à l’avancement des connaissances dans ce champ

de recherche, ainsi qu’approfondi nos connaissances sur les réponses possibles des

populations de salmonidés face à des changements dans leur environnement, causés par des

facteurs anthropiques ou non. Il s’est avéré que ce projet de doctorat, dans son état actuel,

représentait un défi de taille au niveau pratique et méthodologique, et que son extension à

d’autres systèmes, et sur plusieurs années, était tout simplement impossible dans le seul

cadre de cette étude. Mais la voie reste ouverte…

Finalement, des extensions au modèle présenté dans le chapitre 4 ont le potentiel d’explorer

d’importantes et intéressantes questions. Premièrement, la question de mortalités variables

en eau douce, adjacente au concept de sélection fluctuante, pourrait jouer un rôle dans le

128

maintien de la variation phénotypique et génétique (Merilä et al. 2001; Grant et Grant 2002;

Aubin-Horth et al. 2005). Ensuite, ce modèle pourrait être utilisé pour prédire les

conséquences évolutives et démographiques des perturbations tel un barrage ou un ponceau

qui bloquent complètement l’accès à la montaison. Ces prédictions (ex. taille et âge à

maturité, fécondité) pourraient être comparées avec des observations faites sur des

populations naturelles qui ont subi de telles perturbations, ce qui validerait le modèle.

Enfin, avec un peu de gymnastique, peut-être serions-nous capable d’utiliser le même genre

de modèle pour prédire l’impact d’un réchauffement climatique? Une hypothèse, en partie

supportée par des données empiriques chez les oiseaux migrateurs, propose une

augmentation de la résidence en réponse à un réchauffement du climat (Pulido et Berthold

2004; Pulido 2007). Des augmentations dans le nombre de résidents, des diminutions dans

la distance de migration, des dates de départ du lieu de naissance repoussées, des dates

d’arrivée devancées ainsi que des changements dans la direction de la migration ont tous

été reliés au réchauffement climatique chez les oiseaux, réchauffement qui se traduirait en

des meilleures survies aux sites de reproduction (Fiedler 2003). Ces réponses reflètent en

partie la plasticité dans l’ajustement du comportement, mais seraient aussi le résultat de

changements évolutifs (i.e génétiques; Pulido et Berthold 2004). La résidence est-elle le

sort que nous réservons aux salmonidés qui expriment encore l’anadromie?

Bibliographie

Ashley MV, Willsonb MF, Pergamsa ORW, et al. (2003) Evolutionarily enlightened

management. Biological Conservation 111, 115-123.

Aubin-Horth N, Dodson JJ (2004) Influence of individual body size and variable thresholds

on the incidence of a sneaker male reproductive tactic in Atlantic salmon. Evolution

58, 136 - 144.

Aubin-Horth N, Ryan DAJ, Good SP, Dodson JJ (2005) Balancing selection on size:

effects on the incidence of an alternative reproductive tactic. Evolutionary Ecology

Research 7, 1171-1182.

Avise JC, Jones AG, Walker D, DeWoody JA (2002) Genetic mating system and

reproductive natural histories of fishes: lessons for ecology and evolution. Annual

Reviews of Genetics 36,19-45.

Barot S, Heino M, Morgan MJ, Dieckmann U (2005) Maturation of Newfoundland

American plaice (Hippoglossoides platessoides): long-term trends in maturation

reaction norms despite low fishing mortality? ICES Journal of Marine Science 62,

52-64.

Barot S, Heino M, O'Brien L, Dieckmann U (2004) Long-term trend in the maturation

reaction norm of two cod stocks. Ecological Applications 14, 1257-1271.

Baskett ML, Levin SA, Gaines SD, Dushoff J (2005) Marine reserve design and the

evolution of size at maturation in harvested fish. Ecological Applications 15, 882-

901.

Belkhir K, Borsa P, Chikhi L, Raufaste N, Bonhomme F (2000) GENETIX 4.02, Logiciel

sous Windows TM pour la génétique des populations. Laboratoire Génome,

Populations, Interactions, CNRS UMR 5000, Université de Montpellier II,

Montpellier, France.

Belkhir K, Castric V, Bonhomme F (2002) IDENTIX, a software to test for relatedness in a

population using permutation methods. Molecular Ecolology Notes 2, 611 – 614.

Bernardo J (1993) Determinants of maturation in animals. Trends in Ecology & Evolution

8, 166-173.

130

Bernatchez L, Duchesne P (2000) Individual-based genotypes analysis in studies of

parentage and population assignment: how many loci, haw many alleles? Canadian

Journal of Fisheries and Aquatic Sciences 57, 1-12.

Berteaux D, Réale D, McAdam AG, Boutin S (2004) Keeping pace with fast climate

change: can artic life count on evolution? Integrative and Comparative Biology 44,

140-151.

Berthold P (1991) Genetic control of migratory behaviour in birds. Trends in Ecology &

Evolution 6, 254-257.

Bielak AT, Power G (1986) Changes in mean weight, sea-age composition, and catch-per-

unit-effort of Atlantic salmon (Salmo salar) angled in the Godbout River, Quebec,

1859-1983. Canadian Journal of Fisheries and Aquatic Sciences 43, 281-287.

Blanchfield PJ, Ridgway MS, Wilson CC (2003) Breeding success of male brook trout

(Salvelinus fontinalis) in the wild. Molecular Ecology 12, 2417-2428.

Blomqvist D, Andersson M, Kupper C, Cuthill IC, Kis J, Lanctot RB, Sandercock BK,

Szekely T, Wallander J, Kempenaers B (2002) Genetic similarity between mates

and extra-pair parentage in three species of shorebirds. Nature 419, 613 – 615.

Blouin MS (2003) DNA-based methods for pedigree reconstruction in kinship analysis in

natural populations. Trends in Ecology & Evolution 18, 503-511.

Bohlin T, Dellefors C, Faremo U (1990) Large or small at maturity-theories on the choice

of alternative male strategies in anadromous salmonids. Annales Zoologici Fennici

27, 139-147.

Bohlin T, Dellefors C, Faremo U (1994) Probability of first sexual maturation of male parr

in wild sea-run brown trout (Salmo trutta) depends on condition factor 1 yr in

advance. Canadian Journal of Fishery and Aquatic Sciences 51, 1920-1926.

Boily P, Magnan P (2002) Relationship between individual variation in morphological

characters and swimming costs in brook charr (Salvelinus fontinalis) and yellow

perch (Perca flavescens). Journal of Experimental Biology 205, 1031-1036.

Boula D, Castric V, Bernatchez L, Audet C (2002) Physiological, endocrine, and genetic

bases of anadromy in the brook charr, Salvelinus fontinalis, of the Laval River

(Quebec, Canada). Environmental Biology of Fishes 64, 229 – 242.

131

Brockmann HJ (2001) An experimental approach to altering mating tactics in male

horsehoes crabs (Limulus polyphemus). Behavioral Ecology 13, 232-238.

Brommer JE, Merilä J, Sheldon BC, Gustafsson L (2005) Natural selection and genetic

variation for reproductive reaction norms in a wild bird population. Evolution 59,

1362-1371.

Brookfield JFY (1996) A simple new method for estimating null allele frequency from

heterozygote deficiency. Molecular Ecolology 5, 453-455.

Butler K, Field C, Herbinger CM, Smith B (2004) Accuracy, efficiency and robustness of

four algorithms allowing full sibship reconstruction from DNA marker data.

Molecular Ecolology 13, 1589 - 1600.

Carlson SM, Edeline E, L. VA, et al. (2007) Four decades of opposing natural and human-

induced artificial selection acting on Windermere pike (Esox lucius). Ecology

Letters 10, 512-521.

Castonguay M, Fitzgerald GJ (1982) Life history movements of anadromous brook charr,

Salvelinus fontinalis, in the St-Jean River, Gaspé, Québec. Canadian Journal of

Zoology 60, 3084-3091.

Castric V, Bernatchez L (2003) The rise and fall of isolation by distance in the anadromous

brook charr (Salvelinus fontinalis Mitchill). Genetics 163, 983-996.

Cavalli-Sforza LL, Feldman MW (1976) Evolution of continuous variation: direct approach

through joint distribution of genotypes. Proceedings of the National Academy of

Sciences of the United States of America 73, 1689-1692.

Chapuis MP, Estoup A (2007) Microsatellite null alleles and estimation of population

differentiation. Molecular Biology and Evolution 24, 621-631.

Charmantier A, Garant D (2005) Environmental quality and evolutionary potential: lessons

from wild populations. Proceedings of the Royal Society of London B Biological

Sicences 272, 1415-1425.

Charmantier A, Kruuk LEB, Blondel J, Lambrechts MM (2004) Testing for microevolution

in body size in three blue tit populations. Journal of Evolutionary Biology 17, 732-

743.

132

Charmantier A, Perrins CM, McCleery RH, Sheldon BC (2006) Age-dependent genetic

variance in a life-history trait in the mute swan. Proceedings of the Royal Society of

London B Biological Sicences 273, 225-232.

Coltman DW (2005) Testing marker-based estimates of heritability in the wild. Molecular

Ecology 14, 2593 - 2599.

Coltman DW, Bancroft DR, Robertson A, Smith J, Clutton-Brock TH, Pemberton JM

(1999) Male reproductive success in a promiscuous mammal: behavioural estimates

compared with genetic paternity. Molecular Ecolology 8,1199-1209.

Coltman DW, O'Donoghue P, Jorgenson JT, et al. (2003) Undesirable evolutionary

consequences of trophy hunting. Nature 426, 655-658.

Coltman DW, Pilkington JG, Kruuk LEB, Wilson K, Pemberton JM (2001) Positive

genetic correlation between parasite resistance and body size in a free-living

ungulate population. Evolution 55, 2116-2125.

Coltman DW (2008) Molecular ecological approaches to studying the evolutionary impact

of selective harvesting in wildlife. Molecular Ecology 17, in press.

Conover DO (2000) Darwinian fishery science. Marine Ecology Progress Series 208, 303-

306.

Conover DO, Munch SB (2002) Sustaining fisheries yields over evolutionary time scales.

Science 297, 94-96.

Conrad KF, Johnston PV, Crossman C, Kempenaers B, Robertson RJ, Wheelwright NT,

Boag T (2001) High levels of extra-pair paternity in an isolated, low-density, island

population of tree swallows (Tachycineta bicolor). Molecular Ecology 10,1301-

1308.

Cook SA, Johnson MP (1968) Adaptation to heterogeneous environements. I. Variation in

heterophylly in Ranunculus flammula L. Evolution 22, 496-516.

Cooke SJ and Cowx IG (2006) Contrasting recreational and commercial fishing: Searching

for common issues to promote unified conservation of fisheries resources and

aquatic environments. Biological Conservation 128, 93-108.

Cookson C (2004) Over-harvesting leads to a Darwinian debt as only the smaller cod

survive. The Financial Times 28 August 2004: 1. Available online a

http://www.iiasa.ac.at/docs/HOTP/Sep04/article.pdf.

133

Dakin EE, Avise JC (2004) Microsatellite null alleles in parentage analysis. Heredity 93,

504-509.

DeHaan PW, Ardren WR (2005) Characterization of 20 highly variable tetranucleotide

microsatellite for bull trout (Salvelinus confluentus) and cross amplification in other

Salvelinus species. Molecular Ecology Notes 5, 582-585.

Dempson JB, Schwarz CJ, Reddin DG et al (2001) Estimation of marine exploitation rates

on Atlantic salmon (Salmo salar L.) stocks in Newfoundland, Canada. ICES

Journal of Marine Science 58, 331-341.

Dewitt TJ, Sih A, Wilson DS (1998) Costs and limits of phenotypic plasticity. Trends in

Ecology & Evolution 13, 77-81.

DeWoody JA, Avise JC (2001) Genetic perspectives on the natural history of fish mating

systems. Journal of Heredity 92,167-172.

Dickerson BR, Brinck KW, Willson MF, Bentzen P, Quinn TP (2005) Relative importance

of salmon body size and arrival time at breeding grounds to reproductive success.

Ecology 86, 347-352.

Dickerson BR, Willson MF, Bentzel P, Quinn TP (2004) Size-assortative mating in

salmonids: negative evidence for pink salmon in natural conditions. Animal

Behaviour 68, 381-385.

Dieckmann U. and Heino M. (2007) Probabilistic maturation reaction norms: Their history,

strengths, and limitations. Marine Ecology Progress Series 335, 253-269.

Docker MF, Heath DD (2003) Genetic comparison between sympatric anadromous

steelhead and freshwater resident rainbow trout in British Columbia, Canada.

Conservation Genetics 4, 227-231.

Dodson JJ (1997) Fish migration: an evolutionary perspective. In: Behavioural Ecology of

teleost fishes (ed. Godin J-GJ), pp. 10-36. Oxford university press, Oxford.

Doucett RR, Power M, Power G, Caron F, Reist JD (1999) Evidence for anadromy in a

southern relict population of Arctic charr from North America. Journal of Fish

Biology 55, 84-93.

Doyon J-F, Hudon C, Morin R, Whoriskey FG (1991) Bénéfices à court terme des

mouvements anadromes saisonniers pour une population d'omble de fontaine

134

(Salvelinus fontinalis) du Nouveau Québec. Canadian Journal of Fisheries and

Aquatic Sciences 48, 2212-2222.

Duchesne P, Castric T, Bernatchez L (2005) PASOS (parental allocation of singles in open

systems): a computer program for individual parental allocation with missing

parents. Molecular Ecology Notes 5, 701-704.

Dunlop ES, Shuter BJ, Dieckmann U (2007) The demographic and evolutionary

consequences of selective mortality: predictions from an eco-genetic model of the

smallmouth bass. Transactions of the American Fisheries Society 136, 749-765.

Dunlop ES, Shuter BJ, Ridgway MS (2005) Isolating the influence of growth rate on

maturation patterns in the smallmouth bass (Micropterus dolomieu). Canadian


Dunlop ES, Heino M and Dieckmann U (2008) Modeling contemporary life-history

evolution: introducing the eco-genetic approach, with an application to harvest-

induced adaptive change. Submitted.

Dutil JD, Power G (1980) Coastal populations of brook trout, Salvelinus fontinalis, in Lac

Guillaume-Delisle (Richmond Gulf) Québec. Canadian Journal of Zoology 58,

1828-1835.

Elliott JM (1993) A 25-year study of production of juvenile sea-trout, Salmo trutta, in an

English Lake District stream. Canadian Special Publication of Fisheries and


Emlen DJ (1996) Artificial selection on horn length-body size allometry in the horned

beetle Onthophagus acuminatus (coleoptera: scarabaeidae). Evolution 50, 1219-

1230.

Emlen DJ, Nijhout HF (2000) The development and evolution of exaggerated

morphologies in insects. Annual Review of Entomology 45, 661-708.

Ernande B, Dieckmann U, Heino M (2004) Adaptive changes in harvested populations:

plasticity and evolution of age and size at maturation. Proceedings of the Royal

Society of London B Biological Sicences 271, 415-423.

Estoup A, Angers B (1998) Microsatellite and minisatellites for molecular ecology:

theoretical and experimental considerations. In: Advances in molecular ecology, p.

313. IOS Press.

135

Falconer D, Mackay TFC (1996) Introduction to quantitative genetics, Fourth edn. Pearson

Education Limited, Harlow.

Feldheim KA, Gruber SH, Ashley MV (2004) Reconstruction of parental microsatellite

genotypes reveals female polyandry and philopatry in the lemon shark, Negaprion

brevirostris. Evolution 58, 2332-2342.

Fiedler W (2003) Recent changes in migratory behaviour of birds: A compilation of field

observations and ringing data. In: Avian migration (eds. Berthold P, Gwinner E,

Sonnenschein E), pp. 21-38. Springer, Berlin.

Fleming IA (1996) Reproductive strategies of Atlantic salmon: ecology and evolution.

Reviews in Fish Biology and Fisheries 6, 379-416.

Fleming IA (1998) Pattern and variability in the breeding system of Atlantic salmon (Salmo

salar), with comparisons to other salmonids. Canadian Journal of Fisheries and


Fleming IA, Gross MR (1994) Breeding competition in a Pacific salmon (Coho,

Oncorhynchus kisutch) - Measures of natural and sexual selection. Evolution 48,

637-657.

Fleming IA, Lamberg A, Jonsson B (1997) Effects of early experience on the reproductive

performance of Atlantic salmon. Behavioural Ecology 8, 470-480.

Foote CJ (1990) An experimental comparison of male and female spawning territoriality in

a Pacific salmon. Behaviour 115, 283-314.

Foote CJ, Wood CC, Withler RE (1989) Biochemical genetic comparision of sockeye

salmon and kokanee, the anadromous and nonanadromous forms of Oncorhynchus

nerka. Canadian Journal of Fisheries and Aquatic Sciences 46, 149-158.

Forseth T, Nasje TF, Jonsson B, Harsaker K (1999) Juvenile migration in brown trout: a

consequence of energetic state. Journal of Animal Ecology 68, 783-793.

Frankham R, Ballou JD and Briscoe DA (2002) Introduction to Conservation Genetics.

Cambridge University Press, New York.

Frankino AW, Pfennig DW (2001) Condition-dependent expression of trophic

polyphenism: effects of individual size and competitive ability. Evolutionary

Ecology Research 3, 939-951.

136

Garant D, Dodson JJ, Bernatchez L (2001) A genetic evaluation of mating system and

determinants of individual reproductive success in Atlantic salmon (Salmo salar L.).

Journal of Heredity 92, 137-145.

Garant D, Dodson JJ, Bernatchez L (2003) Differential reproductive success and

heritability of alternative reproductive tactics in wild Atlantic Salmon (Salmo salar

L.). Evolution 57, 1133-1141.

Garant D, Dodson JJ, Bernatchez L (2005) Offspring genetic diversity increases fitness of

female Atlantic salmon (Salmo salar). Behavioural Ecology and Sociobiology 57,

240-244.

Garant D, Fontaine P-M, Good SP, Dodson JJ, Bernatchez L (2002) The influence of male

parental identity on growth and survival of offspring in Atlantic salmon (Salmo

salar). Evolutionary Ecology Research 4, 537-549.

Garant D, Kruuk LEB (2005) How to use molecular marker data to measure evolutionary

parameters in wild populations. Molecular Ecology 14, 1843-1859.

Garant D, Kruuk LEB, McCleery R, Sheldon BC (2004) Evolution in a changing

environment: a case study with great tit fledging mass. American Naturalist 164,

E115-E129.

Garant D, Kruuk LEB, Wilkin TA, McCleery RH, Sheldon BC (2005) Evolution driven by

differential dispersal within a wild bird population. Nature 433, 60-65.

Garcia-Vazquez E, Moran P, Martinez JL, Perez J, de Gaudemar B, Beall E (2001)

Alternative mating strategies in Atlantic salmon and brown trout. Journal of

Heredity 92,146-149.

Gasser M, Kaiser M, Berrigan D, Stearns SC (2000) Life-history correlates of evolution

under high and low adult mortality. Evolution 54, 1260-1272.

Glebe BD, Saunders RL (1986) Genetic factors in sexual maturity of cultured Atlantic

salmon (Salmo salar) parr and adults reared in sea cages. Canadian Special

Publication of Fisheries and Aquatic Sciences 89, 24-29.

Grant PR, Grant BR (2002) Unpredictable evolution in a 30-years study of Darwin's

finches. Science 296, 707-711.

137

Grift RE, Rijnsdorp AD, Barot S, Heino M, Dieckmann U (2003) Fisheries-induced trends

in reaction norms for maturation in North Sea plaice. Marine Ecology Progress

Series 257, 247-257.

Gross MR (1985) Disruptive selection for alternative life histories in salmon. Nature 313,

47-48.

Gross MR (1987) Evolution of diadromy in fishes. American Fisheries Society Symposium

1, 14-25.

Gross MR (1996) Alternative reproductive strategies and tactics: diversity within sexes.

Trends in Ecology &. Evolution 11, 92-98.

Handford P, Bell G, Reimchen TE (1977) A gillnet fishery considered as an experiment in

artificial selection. Journal of the Fisheries Research Board of Canada 34, 954-961.

Haugen T, Vollestad LA (2001) A century of life-history evolution in grayling. Genetica

112-113, 475-491.

Haugen TO, Vollestad LA (2000) Population differences in early life-history traits in

grayling. Journal of Evolutionary Biology 13, 897-905.

Hazel W, Smock R, Johnsson MD (1990) A polygenic model for the evolution and

maintenance of conditional strategies. Proceedings of the Royal Society of London B

Biological Sicences 242, 181-187.

Hazel W, Smock R, Lively C (2004) The ecological genetics of conditional strategies.

American Naturalist 163, 888 - 900.

Heath DD, Devlin B, Heath JW, Iwana GK (1994) Genetic, environmental and interaction

effects on the incidence of jacking in Oncorhynchus tshawytacha (chinook salmon).

Heredity 72, 146-154.

Heath DD, Fox CW, Heath JW (1999) Maternal effects on offspring size: variation through

early development of Chinook salmon. Evolution 53, 1605-1611.

Heath DD, Rankin L, Bryden CA, Heath JW, Shrimpton JM (2002) Heritability and Y-

chromosome influence in the jack male life history of chinook salmon

(Oncorhynchus tshawytscha). Heredity 89, 311 - 317.

Heino M (1998) Management of evolving fish stocks. Canadian Journal of Fisheries and


138

Heino M, Dieckmann U, Godø OR (2002) Measuring probabilistic reaction norms for age

and size at maturation. Evolution 56, 669-678.

Hendry AP, Castric V, Kinnison MT, Quinn TP (2004) The evolution of philopatry and

dispersal: homing versus straying in salmonids. In: Evolution illuminated: salmon

and their relatives (eds. Hendry AP, Stearns SC), pp. 52-91. Oxford University

Press, New York.

Hendry AP, Day T, Taylor EB (2001) Optimal size and number of propagules: allowance

for discrete stages and effects of maternal size on reproductive output and offspring

fitness. American Naturalist 157, 387-407.

Hendry AP, Kinnison MT (1999) The pace of modern life: measuring the rates of

contemporary microevolution. Evolution 53, 1637-1653.

Herbinger CM, O'Reilly PT, Verspoor E (2006) Unravelling first-generation pedigrees in

wild endangered salmon populations using molecular genetic markers. Molecular

Ecology 15, 2261-2275.

Herbinger, C.M. 2005. PEDIGREE Help Manual, see

http://herbinger.biology.dal.ca:5080/Pedigree/.

Hindar K, Jonsson K, Rymon N, Stahl S (1991) Genetic relationships among landlocked,

resident, and anadromous brown trout, Salmo trutta L. Heredity 66, 83-91.

Hoffmann AA, Merilä J (1999) Heritable variation and evolution under favourable and

unfavourable conditions. Trends in Ecology & Evolution 14, 96-101.

Holtby LB, Healey MC (1986) Selection for adult size in female coho salmon

(Oncorhynchus kisutch). Canadian Journal of Fisheries and Aquatic Sciences 43,

1946-1959.

Hughes CR (1998) Integrating molecular techniques with field methods in studies of social

behavior: a revolution results. Ecology 79, 383-399.

Hunt J, Simmons LW (2001) Status-dependent selection in the dimorphic beetle

Onthophagus taurus. Proceedings of the Royal Society of London B Biological

Sicences 268, 2409-2414.

Hutchings JA (1993) Adaptive life histories effected by age-specific survival and growth

rate. Ecology 74, 673-684.

139

Hutchings JA (1996) Adaptive phenotypic plasticity in brook trout, Salvelinus fontinalis,

life histories. Ecoscience 3, 25-32.

Hutchings JA (2000) Collapse and recovery of marine fishes. Nature 406, 883-885.

Hutchings JA (2004a) Norms of reaction and phenotypic plasticity in salmonids life

histories. In: Evolution illuminated: salmon and their relatives (eds. Hendry AP,

Stearns SC), pp. 154-174. Oxford University Press, New York.

Hutchings JA (2004b) The cod that got away. Nature 428, 899-900.

Hutchings JA, Jones MEB (1998) Life history variation and growth rate thresholds for

maturity in Atlantic salmon, Salmo salar. Canadian Journal of Fisheries and


Hutchings JA, Myers RA (1988) Mating success of alternative maturation phenotypes in

male Atlantic salmon, Salmo salar. Oecologia 75, 169-174.

Hutchings JA, Myers RA (1994) The evolution of alternative mating strategies in variable

environments. Evolutionary Ecology 8, 256-268.

Hutchings JA and Fraser DJ (2008) The nature of fisheries- and farming-induced evolution.

Molecular Ecology 17, in press.

Jensen H, Saether B-E, Ringsby TH, et al. (2003) Sexual variation in heritability and

genetic correlations of morphological traits in house sparrow (Passer domesticus).

Journal of Evolutionary Biology 16, 1296-1307.

Jones AG, Ardren WR (2003) Methods of parentage analysis in natural populations.

Molecular Ecology 12, 2511-2523.

Jones AG, Östlund-Nilsson S, Avise JC (1998) A microsatellite assessment of sneaked

fertilizations and egg thievery in the fifteenspine stickleback. Evolution 52, 848-

858.

Jones MW, Danzman RG, Clay D (1997) Genetic relationship among populations of wild

resident, and wild and hatchery anadromous brook charr. Journal of Fish Biology

51, 29-40.

Jones MW, Hutchings JA (2002) Individual variation in Atlantic salmon fertilization

success: implications for effective population size. Ecological Applications 12, 184-

193

140

Jonsson B (1985) Life history patterns of freshwater resident and sea-run migrant brown

trout in Norway. Transactions of the American Fishery Society 114, 182-194.

Jonsson B, Hindar K (1982) Reproductive strategy of dwarf and normal Artic charr

(Salvelinus alpinus) from Vangsvatnet Lake, Western Norway. Canadian Journal of

Fishery and Aquatic Sciences 39, 1404-1413.

Jonsson B, Jonsson N (1993) Partial migration: niche shift versus sexual maturation in

fishes. Reviews in Fish Biology and Fisheries 3, 348-365.

Kempenaers B, Everding S, Bishop C, Boag P, Robertson RJ (2001) Extra-pair paternity

and the reproductive role of male floaters in the tree swallow (Tachycineta bicolor).

Behavioural Ecology and Sociobiology 49, 251-259.

Konigsberg LW, Cheverud JM (1992) Uncertain paternity in primate quantitative genetic

studies. American Journal of Primatology 27, 133-143.

Kristoffersen K, Halvorsen M, Jorgensen L (1994) Influence of parr growth, lake

morphology and freshwater parasites on the degree of anadromy in different

populations of Artic charr (Salvelinus alpinus) in northern Norway. Canadian

Journal of Fishery and Aquatic Sciences 51, 1229-1246.

Kruuk LEB (2004) Estimating genetic parameters in natural populations using the 'animal

model'. Philosophical Transactions of the Royal Society 359, 873 - 890.

Kruuk LEB, Clutton-Brock TH, Slate J, et al. (2000) Heritability of fitness in a wild

mammal population. Proceedings of the National Academy of Sciences of the

United States of America 97, 698-703.

Lambert Y, Dodson JJ (1990) Influence of freshwater migration on the reproductive

patterns of anadromous populations of Cisco (Coregonus artedii) and lake

Whitefish (C. clupeaformis). Canadian Journal of Fisheries and Aquatic Sciences

47, 335-345.

Lank DB, Smith CM, Hanotte O, Burke T, Cooke F (1995) Genetic polymorphism for

alternative mating behaviour in lekking male ruff Philomachus pugnax. Nature 378,

59-62.

Law R (1979) Optimal life histories under age-specific predation. American Naturalist 114,

399-417.

141

Law R (2000) Fishing, selection, and phenotypic evolution. ICES Journal of Marine

Science 57, 659-668.

Lenormand S (2003) Évolution de l'anadromie et stratégie de reproduction chez l'omble de

fontaine, (Salvelinus fontinalis). Thèse de doctorat. Biologie. Université Laval,

Québec, Canada pp 122.

Lenormand S, Dodson JJ, Ménard A (2004) Seasonal and ontogenetic patterns in the

migration of anadromous brook charr (Salvelinus fontinalis). Canadian Journal of

Fisheries and Aquatic Sciences 61, 54-67.

Lester NP, Shuter BJ, Abrams PA (2004) Interpreting the von Bertalanffy model of somatic

growth in fishes: the cost of reproduction. Proceedings of the Royal Society of

London B Biological Sicences 271, 1625-1631.

Lesueur C (1993) Détermination des caractéristiques biologiques de la population de truite

de mer (Salvelinus fontinalis) de la rivière Éternité (Saguenay), Master thesis,

Université du Québec à Chicoutimi.

Lukasik P, Radwan J, Tomkins JL (2006) Structural complexity of the environment affects

the survival of alternative male reproductive tactics. Evolution 60, 399-403

Lynch M (1999) Estimating genetic correlations in natural populations. Genetical Research

74, 255-264.

Lynch M, Walsh B (1998) Genetics and analysis of quantitative traits. Sunderland, MA:

Sinauer. Sinauer, Massachusset.

MacColl ADC, Hatchwell BJ (2003) Heritability of parental effort in a passerine bird.

Evolution 57, 2191-2195.

Marshall TC, Slate J, Kruuk LEB, Pemberton JM (1998) Statistical confidence for

likelihood-based paternity inference in natural populations. Molecular Ecology 7,

639-655.

Martinez-Garmendia J (1998) Simulation analysis of evolutionary response of fish

populations to size-selective harvesting with the use of an individual-based model.

Ecological Modeling 111, 37-60.

McAdam AG, Boutin S, Réale D, Berteaux D (2002) Maternal effects and the potential for

evolution in a natural population of animals. Evolution 56, 846 - 851.

142

McCleery RH, Pettifor RA, Armbruster P, et al. (2004) Components of variance underlying

fitness in a natural population of the great tit Parus major. American Naturalist 164,

E62-E72.

McCormick SD, Naiman RJ, Montgomery ET (1985) Physiological smolt characteristics of

anadromous and non-anadromous brook trout (Salvelinus fontinalis) and Atlantic

Salmon (Salmo salar). Canadian Journal of Fisheries and Aquatic Sciences 42,

529-538.

McDowall RM (1993) A recent marine ancestry for diadromous fishes? Sometimes yes, but

mostly no! Environmental Biology of Fishes 37, 329-335.

McDowall RM (2002) The origin of the salmonid fishes: marine, freshwater....or neither?

Reviews in Fish Biology and Fisheries 11, 171-179.

Merilä J, Kruuk LEB, Sheldon BC (2001) Natural selection on the genetical component of

variance in body condition in a wild bird population. Journal of Evolutionary

Biology 14, 918 - 929.

Milner JM, Pemberton JM, Brotherstone S, Albon SD (2000) Estimating variance

components and heritabilities in the wild: a case study using the 'animal model'

approach. Journal of Evolutionary Biology 13, 804 - 813.

Moczek A, Nijhout H (2003) Rapid evolution of a polyphenic threshold. Evolution and

Development 5, 259-268.

Moczek AP, Hunt J, Emlen D, Simmons LW (2002) Threshold evolution in exotic

populations of a polyphenic beetle. Evolutionary Ecology Research 4, 587-601.

Moran NA (1992) The evolutionary maintenance of alternative phenotypes. American

Naturalist 139, 971-989.

Morinville GR, Rasmussen JB (2003) Early juvenile bioenergetic differences between

anadromous and resident brook trout (Salvelinus fontinalis). Canadian Journal of

Fisheries and Aquatic Sciences 60, 401-410.

Morinville GR, Rasmussen JB (2006) Does life-history variability in salmonids affect

habitat use by juveniles? A comparison among streams open and closed to

anadromy. Journal of Animal Ecology 75, 693-704.

143

Morinville GR, Rasmussen JB (2007) Distinguishing between juvenile anadromous and

resident brook trout (Salvelinus fontinalis) using morphology. Environmental

Biology of Fishes, doi 10.1007/s10641-007-9186-9.

Morita K, Takashima Y (1998) Effect of female size on fecundity and egg size in white-

spotted charr: comparison between sea-run and resident forms. Journal of Fish

Biology 53, 1140-1142.

Morita K, Yamamoto S, Hoshino N (2000) Extreme life history change of white-spotted

charr (Salvelinus leucomaenis) after damming. Canadian Journal of Fisheries and

Aquatic Sciences 57, 1300 - 1306.

Morrissey MB, Wilson AJ, Pemberton JM, Ferguson MM (2007) A framework for power

and sensitivity analyses for studies of the quantitative genetics of natural

populations, and case studies in Soay sheep (Ovis aries). Journal of Evoutionary

Biology, in press.

Mousseau TA, Ritland K, Heath DD (1998) A novel method for estimating heritability

using molecular markers. Heredity 80, 218-224.

Myers RA (2001) Stock and recruitment: generalizations about maximum reproductive

rate, density dependence, and variability using meta-analytic approaches. ICES

Journal of Marine Science 58, 937-951.

Myers RA, Hutchings JA, Gibson RJ (1986) Variation in male parr maturation within and

among populations of Atlantic salmon, Salmo salar. Canadian Journal of Fisheries

and Aquatic Sciences 43, 1242-1248.

Myers RA, Hutchings JA (1986) Selection against parr maturation in Atlantic salmon.

Aquaculture 53, 313-320.

Naiman RJ, McCormick SD, Montgomery LW, Morin F (1987) Anadromous brook charr,

Salvelinus fontinalis: Opportunities and constraints for population enhancement.

Marine Fisheries Review 49, 1-13.

Narum SR, Control C, Talbot A, Powee MS (2004) Genetic divergence of sympatric

resident and anadromous forms of Oncorhynchus mykiss in the Walla Walla River,

U.S.A. Journal of Fish Biology 65, 471-488.

Neff BD (2001) Genetic paternity analysis and breeding success in bluegill sunfish

(Lepomis macrochiros). Journal of Heredity 92, 111-119.

144

Neff BD, Repka J, Gross MR (2000) Parentage analysis with incomplete sampling of

candidate parents and offspring. Molecular Ecology 9, 515-528.

Nordeng H (1983) Solution to the 'Char Problem' based on Arctic char (Salvelinus alpinus)

in Norway. Canadian Journal of Fisheries and Aquatic Sciences 40, 1372-1387.

Northcote TG (1992) Migration and residency in streams salmonids-some ecological

considerations and evolutionary consequences. Nordic Journal of Freshwater

Research 67, 5-17.

Nussey DH, Postman E, Gienapp P, Visser ME (2005) Selection on heritable phenotypic

plasticity in a wild bird population. Science 310, 304-306.

Olsen EM, Heino M, Lilly GR, et al. (2004) Maturation trends indicative of rapid evolution

preceded the collapse of northern cod. Nature 428, 932-935.

Olsen EM, Lilly GR, Heino M, et al. (2005) Assessing changes in age and size at

maturation in collapsing populations of Atlantic cod (Gadus morhua). Canadian


Olsen JB, Busack C, Britt J, Bentzen P (2001) The aunt and uncle effect: An empirical

evaluation of the confounding influence of full sibs of parents on pedigree

reconstruction. Journal of Heredity 92, 243 - 247.

Olsson IC, Greenberg LA (2004) Partial migration in a landlocked brown trout population.

Journal of Fish Biology 65, 106-121.

Olsson IC, Greenberg LA, Bergman E, Wysujack K (2006) Environmentally induced

migration: the importance of food. Ecology Letters 9, 645-651.

Ostrowski M-F, Jarne P, David P (2000) Quantitative genetics of sexual plasticity: the

environmental threshold model and genotyped-by-environment interaction for

phallus development in the snail Bulinus Truncatus. Evolution 54, 1614-1625.

Palumbi SR (2001) Humans as the World's Greatest Evolutionary Force. Science 293,

1786-1790.

Pascual M, Bentzen P, Rossi CR, et al. (2001) First documented case of anadromy in a

population of introduced rainbow trout in Patagonia, Argentina. Transactions of the

American Fisheries Society 130, 53 - 67.

145

Pemberton JM, Slate J, Bancroft DR, Barrett A (1995) Nonamplifying alleles at

microsatellite loci: a caution for parentage and population studies. Molecular

Ecology 4, 249-252.

Perry GML, Audet C, Bernatchez L (2005a) Maternal genetic effects on adaptive

divergence between anadromous and resident brook charr during early life history.

Journal of Evolutionary Biology 18, 1348 - 1361.

Perry GML, Bernatchez L, Laplatte B, Audet C (2004) Shifting patterns in genetic control

at the embryo-alevin boundary in brook charr. Evolution 58, 2002-2012.

Perry GML, King T, Valcourt M, St-Cyr J, Bernatchez L (2005b) Isolation and cross

amplification of forty-three microsatellites for the brook charr (Salvelinus

fontinalis). Molecular Ecology Notes 5, 346-351.

Pigliucci M, Murren CJ (2003) Genetic assimilation and a possible evolutionary paradox:

can macroevolution sometimes be so fast as to pass us by? Evolution 58, 1455-1464.

Pigliucci M, Murren CJ, Schlichting CD (2006) Phenotypic plasticity and evolution by

genetic assimilation. Journal of Experimental Biology 209, 2362-2367.

Proulx R, Magnan P (2004) Contribution of phenotypic plasticity and heredity to the

trophic polymorphism of lacustrine brook charr (Salvelinus fontinalis M.).

Evolutionary Ecology Research 6, 503 - 522.

Pulido F (2007) The genetics and evolution of avian migration. Bioscience 57, 165-174.

Pulido F, Berthold P (2004) Microevolutionary response to climate changes. Advances in

Ecological Research 35, 151-183.

Quinn TP, Foote CJ (1994) The effect of body size and sexual dimorphism on the

reproductive behaviour of sokeye salmon, Oncorhynchus nerka. Animal Behaviour

48, 751-761.

Quinn TP, Hodgson S, Flynn L, Hilborn R, Rogers DE (2007) Directional selection by

fisheries and the timing of sockeye salmon (Oncorhynchus nerka) migrations.

Ecological Applications 17, 731-739.

Ratner S, Lande R (2001) Demographic and evolutionary responses to selective harvesting

in populations with discrete generations. Ecology 82, 3093-3104.

Raymond M, Rousset F (1995) GENEPOP (Version 1.2): Population genetics software for

exact tests and ecumenicism. Journal of Heredity 86, 248-249.

146

Réale D, Berteaux D, McAdam AG, Boutin S (2003) Lifetime selection on heritable life-

history traits in a natural population of red squirrels. Evolution 57, 2416 - 2423.

Réale D, Festa-Bianchet M, Jorgenson JT (1999) Heritability of body mass varies with age

and season in wild bighorn sheep. Heredity 83, 526-532.

Reynolds JD (1996) Animal breeding systems. Trends in Ecology & Evolution 11, 68-72.

Reznick DN, Ghalambor CK (2005) Can commercial fishing cause evolution? Answers

from guppies (Poecilia reticulata). Canadian Journal of Fisheries and Aquatic

Sciences 62, 791-801.

Ricker W (1995) Trends in the average size of Pacific salmon in Canadian catches. In:

Climate change and northern fish population (ed. Beamish RJ), pp. 593-602.

Canadian Special Publication of Fisheries and Aquatic Sciences.

Rijnsdorp AD (1993) Selection differentials in male and female North Sea plaice and

changes in maturation and fecundity. In: The exploitation of evolving ressources

(eds. Stokes TK, McGlade J, Law R), pp. 19-36. Springer-Verlag, Berlin.

Rikardsen AH, Svenning M-A, Klemetsen A (1997) The relationship between anadromy,

sex ratio and parr growth of Arctic charr in a lake in north Norway. Journal of Fish

Biology 51, 447-461

Rikardsen AH, Thorpe JE, Dempson JB (2004) Modelling the life-history variation of

Arctic charr. Ecology of Freshwater Fish 13, 305-311.

Ritland K (1996) A marker-based method for inferences about quantitative inheritance in

natural population. Evolution 50, 1062-1073.

Roff DA (1994a) Evolution of dimorphic traits: effect of directional selection on

heritability. Heredity 72, 36-41.

Roff DA (1994b) Habitat persistence and the evolution of wing dimorphism in insects.

American Naturalist 144, 772-798.

Roff DA (1996) The evolution of threshold traits in animals. Quarterly Review of Biology

71, 3-35.

Roff DA (1997) Evolutionary quantitative genetics, Chapman & Hall, New York.

Roff DA (1998) Evolution of threshold traits: the balance between directional selection,

drift and mutation. Heredity 80, 25-32.

147

Roff DA (2001) The threshold model as a general purpose normalizing transformation.

Heredity 86, 404-411.

Roff DA, Bradford MJ (2000) A quantitative genetic analysis of phenotypic plasticity of

diapause induction in the cricket Allonemobius socius. Heredity 84, 193-200.

Roff DA, Stirling G, Fairbairn DJ (1997) The evolution of threshold traits: A quantitative

genetic analysis of the physiological and life-history correlates of wing dimorphism

in the sand cricket. Evolution 51, 1910-1919.

Roff DA, Tucker J, Stirling G, Fairbairn DJ (1999) The evolution of threshold traits:

Effects of selection on fecundity and correlated response in wing dimorphism in the

sand cricket. Journal of Evolutionary Biology 12, 535-546.

Rosenberger AE, Dunham JB (2005) Validation of abundance estimates from mark–

recapture and removal techniques for rainbow trout captured by electrofishing in

small streams. North American Journal of Fisheries Management 25, 1396-1410.

Roughgarden J (1979) Theory of population genetics and evolutionary ecology: An

introduction Macmillan publishing Co. Inc., New York.

Rowe DK, Thorpe JE (1990) Differences in growth between maturing and non-maturing

male Atlantic Salmon, Salmo salar L., parr. Journal of Fish Biology 36, 643-658.

Rowe DK, Thorpe JE, Shanks AM (1991) Role of fat stores in the maturation of male

Atlantic salmon (Salmo salar) parr. Canadian Journal of Fisheries and Aquatic

Sciences 48, 405-413.

Rowell CA (1993) The effects of fishing on the timing of maturity in North Sea cod (Gadus

morhua L.). In: The exploitation of evolving ressources (eds. Stokes TK, McGlade

J, Law R), pp. 44-61. Springer-Verlag, Berlin.

Sarkar S and Fuller T (2003) Generalized reaction norms for ecological developmental

biology. Evolution and Development 5, 106-115.

Saunders RL, Henderson EB, Glebe BD (1982) Precocious sexual maturation and

smoltification in male Atlantic salmon and subsequent survival and growth in sea

cages. Aquaculture 45, 55-66.

Schaffer WM (1974) Selection for optimal life histories: the effects of age structure.

Ecology 55, 291-303.

148

Scheiner SM (1993) Genetics and evolution of phenotypic plasticity. Annual Review of

Ecological Systematics 24, 35-68.

Schreiber A, Diefenbach G (2005) Population genetics of the European trout (Salmo trutta

L.) migration system in the river Rhine: recolonisation by sea trout. Ecology of

Freshwater Fish 14, 1-13.

Scott MP, Williams SM (1993) Comparative reproductive success of communally breeding

burying beetles as assessed by PCR with randomly amplified polymorphic DNA.

Proceedings of the National Academy of Sciences of the United States of America

90, 2242-2245.

Seamons TR, Bentzel P, Quinn TP (2004a) The effects of adult length and arrival date on

individual reproductive success in wild steelhead trout (Oncorhyncus mykiss).

Canadian Journal of Fishery and Aquatic Sciences 61, 193-204.

Seamons TR, Bentzen P, Quinn TP (2004b) The mating system of steelhead, Oncorhynchus

mykiss, inferred by molecular analysis of parents and progeny. Environmental

Biology of Fishes 69, 333-344.

Sgrò CM, Hoffmann AA (2004) Genetic correlations, tradeoffs and environmental

variation. Heredity 93, 241-248.

Shapiro AM (1976) Seasonal polyphenism. Evolutionary Biology 9, 259-333.

Shapiro AM (1980) Physiological and developmental responses to photoperiod and

temperature as data in phylogenetic and biogeographic inference. Systematic

Zoology 29, 335-341.

Sheldon BC, Kruuk LEB, Merilä J (2003) Natural selection and inheritance of breeding

time and clutch size in the collared flycatcher. Evolution 57, 406-420.

Shuster SM, Wade MJ (1991) Equal mating succes among male reproductive strategies in a

marine isopod. Nature 350, 608-610.

Silverstein JT, Hershberger WK (1992) Precocious maturation in coho salmon

(Oncorhynchus kisutch): estimation of heritability. Bulletin of the Aquaculture

Association of Canada 92, 34-36.

Skulason S, Snorrason SS, Noakes DLG, Ferguson MM (1996) Genetic basis of like

history variation among sympatric morphs of arctic char, Salvelinus alpinus.

Canadian Journal of Fisheries and Aquatic Sciences 53, 1807-1813.

149

Smith BR, Herbinger CM, Merry HR (2001) Accurate partition of individuals into full-sib

families from genetic data without parental information. Genetics 158, 1329-1338.

Smith MW, Saunders JW (1958) Movements of brook trout, Salvelinus fontinalis

(Mitchill), between and within fresh and salt water. Journal of Fisheries Research

Board of Canada 15, 1403-1449.

Staurnes M, Lysfjord G, Berg OK (1992) Parr-smolt transformation of a nonanadromous

population of Atlantic salmon (Salmo salar) in Norway. Canadian Journal of

Zoology 70, 197-199.

Stearns SC (1992) The Evolution of life histories Oxford University Press, New York.

Stearns SC, Koella JC (1986) The evolution of phenotypic plasticity in life-history traits:

predictions of reaction norms for age and size at maturity. Evolution 40, 893-913.

Steen RP, Quinn TP (1999) Egg burial depth by sockeye salmon (Oncorhynchus nerka):

implications for survival of embryos and natural selection on female body size.

Canadian Journal of Zoology 77, 836-841.

Stokes K, Law R (2000) Fishing as an evolutionary force. Marine Ecology Progress Series

208, 307-309.

Svenning MA, Smith-Nilsen A, Jobling M (1992) Sea water migration of Arctic charr

(Salvelinus alpinus L.)-Correlation between freshwater growth and seaward

migration, based on back-calculation from otoliths. Nordic Journal of Freshwater

Research 67, 18-26.

Swain DP, Sinclair AF and Hanson MJ (2007) Evolutionary response to size-selective

mortality in an exploited fish population. Proceedings of the Royal Society

Biological Sciences Series B 274, 1015-1022.

Thériault V, Bernatchez L, Dodson JJ (2007a) Mating system and individual reproductive

success of sympatric anadromous and resident brook charr, Salvelinus fontinalis,

under natural conditions. Behavioral Ecology and Sociobiology, 62, 51-65.

Thériault V, Dodson JJ (2003) Body size and the adoption of a migratory tactic in brook

charr. Journal of Fish Biology 63, 1144-1159.

Thériault V, Garant D, Bernatchez L, Dodson JJ (2007b) Heritability of life history tactics

and genetic correlation with body size in natural population of brook charr

150

(Salvelinus fontinalis). Journal of Evolutionary Biology, doi:10.1111/j.1420-

9101.2007.01417.x.

Thériault, V (2001) Anadromie et résidence chez l’omble de fontaine (Salvelinus

fontinalis): présence d’une stratégie conditionnelle basée sur la croissance? Thèse

de maitrise, Université Laval, Québec, Canada.

Thomas SC, Coltman DW, Pemberton JM (2002) The use of marker-based relationship

information to estimate the heritability of body weight in a natural population: a

cautionary tale. Journal of Evolutionary Biology 15, 92 - 99.

Thomas SC, Hill WG (2000) Estimating quantitative genetic parameters using sibships

reconstructed from marker data. Genetics 155, 1961-1972.

Thomaz D, Beall E, Burke T (1997) Alternative reproductive tactics in Atlantic

salmon:factors affecting mature parr success. Proceedings of the Royal Society of

London B Biological Sciences 264, 219-226.

Thorpe JE (1986) Age at first maturity in Atlantic salmon, Salmo salar: freshwater period

influences and conflicts with smolting. Canadian Special Publication of Fisheries

and Aquatic Sciences 89, 7-14.

Thorpe JE (1994) Performance threshold and life-history variability in salmonids.

Conservation Biology 8, 877-879.

Thorpe JE, Mangel M, Metcalfe NB, Huntingford FA (1998) Modeling the proximate basis

of salmonid life-history variation, with application to Atlantic salmon, Salmo salar

L. Evolutionary Ecology 12, 581-599.

Thrower FP, Hard J, Joyce JE (2004) Genetic architecture of growth and early life-history

transitions in anadromous and derived freshwater populations of steelhead. Journal

of Fish Biology 65, 286-307.

Tomkins JL, Brown GS (2004) Population density drives the local evolution of a threshold

dimorphism. Nature 431, 1099-1103.

Tsiger VV, Skirin VI, Krupyanko NI, Kashkin KA, Semenchenko AY (1994) Life history

forms of male masu salmon (Oncorhynchus masou) in South Primore, Russia.

Canadian Journal of Fishery and Aquatic Sciences 51,197-208.

151

Unwin MJ, Kinnison MT, Quinn TP (1999) Exceptions to semelparity: postmaturation

survival, morphology, and energetics of male chinook salmon (Oncorhynchus

tshawytscha). Canadian Journal of Fishery and Aquatic Sciences 56,1172-1181.

van De Castelle T, Galbusera P, Matthysen E (2001) A comparison of microsatellite-based

pairwise relatedness estimator. Molecular Ecology 10, 1539-1549.

van Kleunen M, Fischer M (2005) Constraints on the evolution of adaptive phenotypic

plasticity in plants. New Phytologist 166, 49-60.

van Oosterhout C, Hutchinson WF, Wills DPM, Shipley P (2004) MICRO-CHECKER:

software for identifying and correcting genotyping errors in microsatellite data.

Molecular Ecology Notes 4, 535-538.

Walsh MR, Munch SB, Shiba S and Conover DO (2006) Maladaptive changes in multiple

traits caused by fishing: impediments to population recovery. Ecology Letters 9,

142-148.

Wang J (2004) Sibship reconstruction from genetic data with typing errors. Genetics 166,

1963-1979.

Waples R, Hard J, Huey R, Travis J (2007) Evolutionary changes and salmon:

Consequences of anthropogenic changes for the long-term viability of Pacific

salmon and steelhead, Report of the symposium/workshop, 7-9 December 2006,

Seattle, Washington, USA.

Weigensberg I, Roff DA (1996) Natural heritabilities:can they be reliably estimated in the

laboratory? Evolution 50, 2149-2157.

Weir BS, Cockerham CC (1984) Estimating F-statistics for the analysis of population

structure. Evolution 38, 1358-1370.

West-Eberhard MJ (2003) Developmental plasticity and evolution Oxford University,

Oxford, New York.

Westneat DF (1987) Extra-pair fertilizations in a predominantly monogamous bird: genetic

evidence. Animal Behaviour 35, 877-886.

Whalen KG, Parrish DL (1999) Effect of maturation on parr growth and smolt recruitment

of Atlantic salmon. Canadian Journal of Fisheries and Aquatic Sciences 56, 79-86.

152

Wild V, Simianer H, Gjoeen HM, Gjerde B (1994) Genetic parameters and genotype x

environment interaction for early sexual maturity in Atlantic salmon (Salmo salar).

Aquaculture 128, 51-65.

Wilson AJ, Hutchings JA, Ferguson MM (2003a) Selective and genetic constraints on the

evolution of body size in a stream-dwelling salmonid fish. Journal of Evolutionary

Biology 16, 584 - 594.

Wilson AJ, McDonald G, Moghadam HK, Herbinger CM, Ferguson MM (2003b) Marker-

assisted estimation of quantitative genetic parameters in rainbow trout,

Oncorhynchus mykiss. Genetical Research 81, 145-156.

Wilson AJ, Pemberton JM, Pilkington JG, et al. (2006) Environmental coupling of

selection and heritability limits evolution. PLoS Biol 4, e216.

Wood CC, Foote CJ (1990) Genetic differences in the early development and growth of

sympatric sockeye salmon and kokanee (Oncorhynchus nerka), and their hybrids.

Canadian Journal of Fishery and Aquatic Sciences 47, 2250-2260.

Wood CC, Foote CJ (1996) Evidence for sympatric genetic divergence of anadromous and

nonanadromous morphs of Sockeye salmon (Oncorhynchus nerka). Evolution 50,

1265-1279.

Zimmerer EJ, Kallman KD (1989) Genetic basis for alternative reproductive tactics in the

Pygmy swordail, Xiphophorus nigrensis. Evolution 43, 1298-1307

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